The Interactive Fly

Genes involved in tissue and organ development

Interneurons: Development, connectivity and neural processing

Aggression and Courtship
Antenna, Antennal lobe, and Sound
Clock and Photoperiod
Gustatory processing, pharynx, subesophageal zone, proboscis extension, taste, and feeding
Mushroom Body, circuits, and learning
Olfactory system
Somatosensory, PNS, nociceptive, proprioceptive, and mechanosensory neurons
Ventral Cord: walking, flying and neurohormone systems
Vision1: Eye and Optic lobe
Vision2: Optic glomeruli, central complex
Miscellaneous circuits

Aggression and Courtship
More information is to be found at the following Interactive Fly sites: Courtship and Aggression

Hormonal control of motivational circuitry orchestrates the transition to sexuality in Drosophila
Zhang, S. X., Glantz, E. H., Miner, L. E., Rogulja, D. and Crickmore, M. A. (2021). Sci Adv 7(25). PubMed ID: 34134981

Newborns and hatchlings can perform incredibly sophisticated behaviors, but many animals abstain from sexual activity at the beginning of life. Hormonal changes have long been known to drive both physical and behavioral changes during adolescence, leading to the largely untested assumption that sexuality emerges from organizational changes to neuronal circuitry. This study shows that the transition to sexuality in male Drosophila is controlled by hormonal changes, but this regulation is functional rather than structural. In very young males, a broadly acting hormone directly inhibits the activity of three courtship-motivating circuit elements, ensuring the complete suppression of sexual motivation and behavior. Blocking or overriding these inhibitory mechanisms evokes immediate and robust sexual behavior from very young and otherwise asexual males. Similarities to mammalian adolescence suggest a general principle in which hormonal changes gate the transition to sexuality not by constructing new circuitry but by permitting activity in otherwise latent motivational circuit elements (Zhang, 2021).

The identification and evaluation of a potential mating partner require multisensory integration, but, in the experimental paradigm used in this study, the decision to court is ultimately triggered by a male tapping a female with his pheromone receptor-bearing leg. The tap delivers parallel excitatory and inhibitory inputs to the male's P1 courtship command neurons, which initiate and maintain courtship when sufficiently stimulated. The sensitivity of P1 neurons to the inhibitory input from a tap is decreased by a local dopamine signal, which, in mature males, is tuned to reflect recent mating history. If a male has not mated for several days, the dopamine tone is high, increasing the probability that a tap will lead to courtship. Once courtship has commenced, the same dopamine signal maintains courtship bouts for the tens of seconds to several minutes required before mating starts. This motivating dopaminergic activity is maintained for days in the absence of females, is decremented by each mating, and slowly recovers over 3 to 4 days (Zhang, 2021).

Matings promote satiety by activating a set of copulation reporting neurons (CRNs). These neurons, as a population, project dendrites to the external genitalia and send axons to the brain, where they reduce the activity of fruitless-positive neuropeptide F (NPF) producing neurons. This decrease is relayed through the NPF receptor to the motivation-promoting dopamine neurons, reducing their activity. After a few matings, substantial satiety is induced, and reproductive motivation remains low for several days. Mating drive has an intrinsic tendency to recover because of recurrent excitation: NPF neurons excite and are excited by Doublesex-positive pCd neurons, forming a loop that holds and gradually accumulates activity during periods of abstinence. Loop activity is prevented from immediately rebounding by the activity-dependent transcription factor CREB2, which, during the period of high motivation that precedes mating, transcribes inhibitory genes (e.g., potassium channels) that will sustain the decremented activity state, forcing recovery to proceed on a biochemical, rather than electrical, time scale (Zhang, 2021).

This circuit architecture suggests several hypotheses for the prevention of courtship in newly eclosed males. For example, a juvenile male might not recognize or tap females; the CRNs may be constantly active, inducing overwhelming satiety; or, as in the organizational hypothesis, some or all of the courtship circuitry may not be fully developed. This study presents evidence refuting all these hypotheses. Instead, this study found that a spike in juvenile hormone levels at eclosion directly and selectively imposes long-lasting activity suppression on all known motivation-promoting circuit elements: both populations of loop neurons and the downstream dopaminergic neurons. Overriding any of these repressive mechanisms evokes robust courtship from extremely young males, providing clear evidence that much of the reproductive circuitry is developed and functional but lays dormant in juveniles. The multitiered suppression of motivational circuitry appears to be the key difference between the complete inactivation of mating drive in early life and the fluctuations experienced in adulthood (Zhang, 2021).

The story of Eden indicates that the diverse behavioral changes coinciding with reproductive maturity had been fascinating and frustrating humans thousands of years before they were known to involve the brain. The hormonal signaling pathways that trigger these changes in mammals are now understood, but little is known about their mechanistic impact on behavioral and motivational circuitry. Teleological explanations for delays in the onset of sexual behavior likely vary across species, but the pervasiveness of this phenomenon suggests the possibility of a core mechanistic conservation that transcends idiosyncrasies of duration, purpose, and even the molecular nature of the hormonal trigger. The system described in this paper for analyzing the transition to sexuality allows rapid insight, with principles that suggest molecular and circuit hypotheses in other animals and other late-emerging brain functions (Zhang. 2021).

One obvious but likely superficial difference in the control of behavioral maturation between Drosophila and mammals is the sign of the regulation by circulating hormones. Although some gonadal hormones can suppress mating drive, in juvenile male rodents, experimental elevation of testosterone causes precocious mating behavior, whereas this study found that juvenile hormone suppresses mating behavior. This discordance is reconciled early in signal transduction, as loss of the Met receptor for juvenile hormone decreases sexual behavior, similar to the effects of androgen (testosterone) receptor antagonists in humans. The receptors for testosterone, estrogen, and progesterone are all transcription factors, as are the Met and Gce receptors for juvenile hormone. Unlike ablating the source of juvenile hormone or overriding its action at the level of neuronal activity or CREB activation, removing the suppressive receptor, Gce, does not cause substantial juvenile courtship. This points to the likely existence of yet another juvenile hormone receptor, the identification of which will provide a deeper understanding of the suppressive mechanisms used to completely, selectively, and transiently inactivate this fundamental drive (Zhang. 2021).

In mature animals, the recurrent loop that drives the male to court also primes itself for satiety through activity-induced, CREB-mediated production of suppressive TASK7-containing potassium channel complexes. This motivation-suppressing module is also used in juveniles, with hormonal signaling causing CREB2 activation. Although additional suppressive effectors have not yet been identified in juveniles, evidence is seen of fast-acting suppression by juvenile hormone and direct suppression of the dopaminergic neurons, neither of which can be accounted for by CREB activity in the pCd/NPF loop. Parallel fast and slow responses have also been found in the response to mammalian gonadal hormones. Multiple repressive mechanisms are likely necessary to completely inactivate mating drive, since individually removing or overriding individual suppressive effectors allows juvenile courtship. This is again similar to findings in mammals, where administering testosterone to either the preoptic area of the hypothalamus or to the medial amygdala suffices to restore mating behaviors in castrated males (Zhang. 2021).

A second clear difference between Drosophila and vertebrate juvenile stages is the time scale. The fly system requires suppression of sexual behavior for days, not months or years [even 150 years as suggested in Greenland sharks]. However, several nonneuronal structures are still maturing in juvenile flies, such as the abdominal musculature, the cuticle, and the ejaculatory bulb, indicating that the neuronal circuitry that will eventually animate these features may require structural development as well. Although the kind of detailed anatomical analysis required to argue for or against fine-scale structural rearrangements, courtship circuitry appears grossly normal in juveniles, and the stimulation of several circuit elements (P1, dopaminergic, NPF, and pCd) can rapidly drive coherent courtship. While it is not yet known whether the courtship performed by juvenile males is identical to that of mature males (e.g., in song production),the current findings serve as strong evidence against a strict developmental ontogeny for the posteclosion emergence of reproductive motivation and behavior (Zhang. 2021).

A recent report found structural changes in a key hypothalamic population during estrus and showed that these neurons could not drive sexual behaviors when activated in ovariectomized mice. It is noted that it was not possible to restore sexual behavior in male flies if subpopulations of individually necessary dopaminergic neurons are stimulated, a consideration that leaves open the possibility that the motivational and behavioral circuitry may be at least partially functional, but suppressed, in nonestrus female mice. The most parsimonious explanation may be that both structural and activational changes take place between asexual and sexual periods of life. Increased connectivity in motivational circuitry could be a result, rather than a cause, of increased activity, as has been reported in a growing number of systems. No reports were found of neuronal stimulation eliciting juvenile sexual behavior in the mammalian literature, but stimulation of hypothalamic neurons can produce coherent and robust parenting behaviors from otherwise nonparental mice, demonstrating latent but functional circuitry for these late-emerging behaviors (Zhang. 2021).

Recently, new functions for pCd and NPF neurons have been reported in male-specific behaviors. In the Anderson laboratory, pCd neurons were found to sustain sexual and aggressive behaviors after P1 activation. This sustained excitation is remarkably similar to the role of pCd in the accrual and maintenance of sexual motivation in mature male flies. Since P1 activity is constantly required to sustain courtship, it is suggested that subsets of the eight pCd neurons may be specialized for maintaining recurrent activity over minutes (together with P1 neurons in sustaining courtship and aggression) and over days (together with NPF neurons in sustaining reproductive motivation). In work from the Montell laboratory, male-specific NPF neurons were reported to decrease sexual motivation generally and to prevent male-male courtship in particular. These conclusions appear to be in direct contrast with the courtship-promoting roles for these same NPF neurons described in earlier work. The results obtained across these studies are derived from a variety of assays and genetic manipulations, complicating direct comparisons, although they clearly point to multiple roles for NPF in courtship target selection and motivation. While several experiments have argued for various forms of hypersexuality resulting from decreased NPF signaling, the lone NPF neuronal stimulation experiment to yield a reduction in courtship behavior assessed courtship toward decapitated females and the effect was modest. The robust effects seen in this study make the authors confident that increasing the output of NPF neurons promotes a net increase in sexual motivation in otherwise asexual juveniles and in satiated males recovering from ad libitum access to virgin females (Zhang. 2021).

These results provide an alternative explanation for what has been the strongest evidence in favor of the organizational hypothesis for the maturation of reproductive behaviors in mammals: the delay between hormonal changes and the behaviors they induce. In the fly, the long-lasting, CREB-imposed effects of an earlier suppressive hormonal state must decay away to allow loop activity to ramp up and promote sexual behavior. Enduring and distributed suppressive effects may explain why the awakening of sexuality triggered by hormonal changes is gradual and halting in both flies and mammals (Zhang. 2021).

A sexually dimorphic olfactory neuron mediates fixed action transition during courtship ritual in Drosophila melanogaster
Tanaka, N. K., Hirao, T., Chida, H. and Ejima, A. (2021). J Neurosci. PubMed ID: 34649953

Animals perform a series of actions in a fixed order during ritualistic innate behaviors. Although command neurons and sensory pathways responding to external stimuli that trigger these behaviors have been identified, how each action is induced in a fixed order in response to multimodal sensory stimuli remains unclear. In this study, the sexually dimorphic lateral antennal lobe tract projection neuron 4 (lPN4) in male Drosophila melanogaster mediates the expression of a fixed behavioral action pattern at the beginning of the courtship ritual, in which a male taps a female body and then extends a wing unilaterally to produce a courtship song. Blocking the synaptic output of lPN4 caused an increase in the ratio of male flies that extended a wing unilaterally without tapping the female body, whereas excitation of lPN4 suppressed the transition from the tapping phase to the unilateral wing extension phase. Real-time calcium imaging showed that lPN4 is activated by a volatile pheromone, palmitoleic acid, whose responses were inhibited by simultaneous gustatory stimulation with female cuticular hydrocarbons, showing the existence of an "AND-gate" for multimodal sensory inputs during male courtship behaviors. These results suggest that the function of lPN4 is to suppress unilateral wing extension while responding to a female smell, which is released by appropriate contact chemosensory inputs received when tapping a female. As the female smell also promotes male courtship behaviors, the olfactory system is ready to simultaneously promote and suppress the progress of courtship actions while responding to a female smell (Tanaka, 2021).

Neural circuit mechanisms of sexual receptivity in Drosophila females
Wang, K., Wang, F., Forknall, N., Yang, T., Patrick, C., Parekh, R. and Dickson, B. J. (2020). Neural circuit mechanisms of sexual receptivity in Drosophila females. Nature. PubMed ID: 33239786

Choosing a mate is one of the most consequential decisions a female will make during her lifetime. A female fly signals her willingness to mate by opening her vaginal plates, allowing a courting male to copulate. Vaginal plate opening (VPO) occurs in response to the male courtship song and is dependent on the mating status of the female. How these exteroceptive (song) and interoceptive (mating status) inputs are integrated to regulate VPO remains unknown. This study characterize the neural circuitry that implements mating decisions in the brain of female Drosophila melanogaster. VPO was shown to be controlled by a pair of female-specific descending neurons (vpoDNs). The vpoDNs receive excitatory input from auditory neurons (vpoENs), which are tuned to specific features of the D. melanogaster song, and from pC1 neurons, which encode the mating status of the female. The song responses of vpoDNs, but not vpoENs, are attenuated upon mating, accounting for the reduced receptivity of mated females. This modulation is mediated by pC1 neurons. The vpoDNs thus directly integrate the external and internal signals that control the mating decisions of Drosophila females (Wang, 2020).

Drosophila males woo potential mates by vibrating their wings to produce a species-specific courtship song. The male song induces deflections of the female aristae, thereby activating auditory sensory neurons that project to the central brain. Several types of song-responsive neurons have been identified in the female brain, but it is unknown whether and how these neurons regulate sexual receptivity. How a female responds to the song of a male is highly dependent on whether or not she has previously mated. Once mated, females store sperm for days to weeks, and during this time are reluctant to mate again. A male seminal fluid peptide (Sex peptide) binds to sperm and signals the presence of sperm in the female reproductive tract through an ascending pathway from the sex peptide sensory neurons (SPSNs) in the uterus via the sex peptide abdominal ganglion (SAG) neurons in the ventral nerve cord to the pC1 neurons in the brain. Sex peptide attenuates neuronal activity in the SPSN, SAG and pC1 neurons, thereby reducing sexual receptivity after mating. This study sought to investigate how these distinct external and internal signals are integrated in the female brain to control VPO, the motor output that signals the willingness of the female to mate (Wang, 2020).

Female receptivity is impaired by blocking the activity of the approximately 2,000 neurons that express either of the two sex-determination genes, fruitless (fru) or doublesex (dsx). This class of neurons includes the fru+ dsx+ SPSNs, the dsx+ SAGs13 and the dsx+ pC1 cells3. To search for other fru+ or dsx+ neurons that contribute to female receptivity, a collection of 234 sparse driver lines specific for various fru+ or dsx+ cell types were screened. These driver lines were used to genetically silence each of these cell types, and virgin females were assayed for their frequency of copulation within 10 min of being individually paired with naive wild-type males. Of the seven lines with the strongest reduction in receptivity, two labelled the SPSNs, one labelled the SAGs and one labelled the pC1 cells. The other three lines targeted a pair of female-specific descending neurons, which were named vpoDNs. These neurons are dsx+, fru- and cholinergic. Their dendrites arborize primarily in the lateral protocerebrum and their axons project to multiple regions of the ventral nerve cord, including the abdominal ganglion (Wang, 2020).

Acute optogenetic silencing or genetic ablation of the vpoDNs rendered virgin females unreceptive, markedly reducing the frequency of VPO but not the intensity of male courtship. Conversely, photoactivation of vpoDNs reliably triggered VPO in isolated virgin females. No peripheral expression was detected that was driven by the vpoDN lines, and by severing the abdominal nerve, it was confirmed that the VPO response is indeed due to activation of central neurons (Wang, 2020).

Mated females are less receptive than virgins, which was found to correlate with a lack of VPO. To assess whether the failure to perform VPO accounts for the low receptivity of mated females, the vpoDNs were photoactivated in mated females as they were being courted by wild-type males. Whereas control females never copulated during a 1-h assay, approximately 30-50% of the vpoDN-activated females did remate. A similar remating frequency was observed upon vpoDN activation in mated females paired with wingless males, which court but cannot sing. Thus, direct activation of vpoDNs bypasses the need for both the internal state (virginity) and the external cue (song) that normally combine to elicit VPO (Wang, 2020).

Wing extension was found to be the most frequent male action just before female VPO, and both VPO and copulation rates were found to be reduced if males are muted by removing their wings or females deafened by removing their aristae. These results suggested that the vpoDNs might be activated by male song. Indeed, in two-photon calcium-imaging experiments, a robust increase of calcium levels was detected in the neurites of vpoDNs in virgin females upon playback of male courtship song, but not in response to white noise. The response to courtship song was lost when the aristae were immobilized to deafen the female. Song responses have also been reported for the pMN2 neurons, which are morphologically similar to vpoDNs and also dsx+, although their reported functions differ (Wang, 2020).

The vpoDN dendrites lie mostly in the superior lateral protocerebrum, with no obvious arborizations within the antennal mechanosensory centre (AMMC), the primary auditory neuropil, or in the wedge region, a secondary auditory neuropil known to include song-responsive neuron. Therefore attempts were made to trace potential pathways from these auditory centres to the vpoDNs within the electron microscopy volume of a full adult female brain (FAFB). A single vpoDN was detected in each hemisphere and the vpoDN was extensively traced in the right hemisphere as well as its presynaptic partners, identifying a total of 45 neurons with at least 10 synapses impinging onto vpoDN (Wang, 2020).

None of the vpoDN input neurons innervate the AMMC, but at least two cell types have extensive arborizations within the wedge. Multiple split-GAL4 driver lines specific for these two cell types WERE obtained. Fluorescence in situ hybridization predicted, and whole-cell recording confirmed, that one of these cell types is excitatory and the other is inhibitory. Accordingly, these two cell types were named the vpoENs and vpoINs, respectively. Within FAFB there are two vpoEN cells and 14 vpoIN cells in each hemisphere (Wang, 2020).

Optogenetic silencing and activation experiments were performed to examine the roles of vpoENs and vpoINs in VPO and receptivity. Acute inhibition of the vpoENs significantly reduced the frequency of copulation and VPO when virgin females were paired with males. Conversely, strong optogenetic activation of vpoENs elicited VPO in isolated females, mimicking activation of vpoDNs. In virgin females paired with males, activating vpoINs suppressed mating and VPO, whereas silencing vpoINs had no effect. Thus, vpoENs and vpoINs promote and suppress, respectively, both VPO and receptivity (Wang, 2020).

Using two-photon calcium imaging, it was found that both vpoENs and vpoINs, as with vpoDNs, responded to playback of male courtship songs. The courtship song varies considerably between different Drosophila species and is the primary cue the female uses for species recognition. To test whether the vpoDNs, vpoENs and vpoINs are specifically tuned to the D. melanogaster courtship song, natural courtship songs were presented from seven other Drosophila species, selecting two representative audio clips from each species. The vpoDNs showed little or no response to any of these songs, the vpoENs responded to one or two clips from five species, and the vpoINs responded to all but one clip from one species (Wang, 2020).

Artificial pulse songs were generated for each of the other species, again systematically altering the IPI from 10 ms to 300 ms. Notably, the vpoDNs responded to the pulse songs of five other species once their IPI was shifted to match that of the D. melanogaster song. Together, these data establish that the vpoDNs are finely tuned to the D. melanogaster pulse song, owing to their selectivity for an IPI of about 35 ms. This narrow tuning may arise through a combination of strong excitation from highly selective vpoENs and weak inhibition from broadly responsive vpoINs (Wang, 2020).

Having determined how auditory input controls VPO and sexual receptivity, how this response is modulated by the mating status of the female was examined. VPO may be attenuated after mating either because the vpoENs and vpoDNs are less potent at eliciting VPO, or because they are less excited by song. In optogenetic activation and calcium-imaging experiments, it was found that vpoDNs are equally potent in mated and virgin females, whereas both the basal calcium levels and the response to courtship song were lower in mated females than in virgins. By contrast, the vpoENs were significantly less potent at eliciting VPO in mated than in virgin females. Although basal fluorescence of vpoENs was slightly higher in mated females than in virgins, their song responses were indistinguishable. Calcium levels were imaged in vpoINs, and it was found that the basal fluorescence and song responses of these cells were similar in mated and virgin females. Thus, these data show that vpoENs have a similar response to song in mated females as they do in virgins, but they are less able to excite vpoDNs in mated females (Wang, 2020).

It is concluded that the decision of the female fly to mate or not to mate is largely determined by how the vpoDNs integrate signals from two direct synaptic inputs: the vpoENs, which are selectively tuned to the conspecific male courtship song, and the pC1 cells, which encode the mating status of the female. When the male sings, female vpoENs are activated; whether or not this leads to vpoDN activation and hence VPO depends on the level of pC1 activity, which is higher in virgins than in mated females. The neural computation that underlies this state-dependent sensorimotor transformation remains to be determined; this will require methods for simultaneously manipulating and recording from all three cell types. One possibility is that the pC1 inputs gate the vpoEN inputs in a nonlinear fashion. No obvious spatial segregation of vpoEN and pC1 synapses onto the vpoDN dendrites was noted, as might be expected if these inputs are indeed processed hierarchically. Alternatively, vpoDNs might simply use a sum-to-threshold mechanism, in which the combined input from vpoENs and pC1s must exceed a certain level to elicit action potentials in vpoDNs. In this scenario, the lower pC1 activity after mating would necessitate a stronger vpoEN input to activate the vpoDNs. This model may account for the observation that wild-caught females are often multiply mated, consistent with the prediction from evolutionary theory that a mated female would increase her reproductive fitness by remating when she is courted by a male of higher quality than her first partner (Wang, 2020).

The many other, as yet uncharacterized, inputs to pC1, vpoEN and vpoDN cells may convey additional signals that modulate female receptivity. For example, pC1 cells are reported to respond to a male pheromone, which may serve to enhance the receptivity of both virgin and mated females. The persistent enhancement of vpoDN song responses upon transient activation of pC1 cells resembles the persistent state of courtship arousal induced in males by transient activation of the male pC1 counterparts. The female pC1 cells may therefore encode both mating status and, as with their male counterparts, a lasting state of mating arousal induced by sensory cues from potential mates. The ensuing interaction between the two sexes involves a coordinated sequence of signals and responses, as exemplified by the male singing to elicit female VPO. In both sexes, these sensorimotor transformations may not be directly mediated by pC1 cells, as commonly thought, but rather modulated by the arousal states they encode. The neural architecture reported in this study for the control of Drosophila female sexual receptivity may thus also serve as a paradigm for understanding male sexual behaviour, and perhaps more generally for the state-dependent signal processing that underlies behavioural decisions across a range of species (Wang, 2020).

Regulation of Drosophila Long-Term Courtship Memory by Ecdysis Triggering Hormone
Lee, S. S. and Adams, M. E. (2021). Front Neurosci 15: 670322. PubMed ID: 33967686

Endocrine state is an important determinant of learning and memory in animals. In Drosophila, rejection of male courtship overtures by mated females leads to an aversive response manifested as courtship memory. This study reports that ecdysis triggering hormone (ETH) is an obligatory enabler of long-term courtship memory (LTM). ETH deficiency suppresses LTM, whereas augmented ETH release reduces the minimum training period required for LTM induction. ETH receptor knockdown either in the mushroom body (MB) γ lobe or in octopaminergic dorsal-anterior-lateral (DAL) neurons impairs memory performance, indicating its direct action in these brain areas. Consistent with these findings, brain exposure to ETH mobilizes calcium in MB γ lobe neuropils and DAL neurons. ETH receptor (ETHR) knockdown in the corpus allatum (CA) to create juvenile hormone (JH) deficiency also suppresses LTM, as does knockdown of the JH receptor Met in the MB γ lobe, indicating a convergence of ETH and JH signaling in this region of the brain. These findings identify endocrine-enabled neural circuit components in the brain that are critical for persistent behavioral changes resulting from aversive social experience (Lee, 2021).

Neurons that function within an integrator to promote a persistent behavioral state in Drosophila
Jung, Y., Kennedy, A., Chiu, H., Mohammad, F., Claridge-Chang, A. and Anderson, D. J. (2020). Neuron 105(2):322-333. PubMed ID: 31810837

Innate behaviors involve both reflexive motor programs and enduring internal states, but how these responses are coordinated by the brain is not clear. In Drosophila, male-specific P1 interneurons promote courtship song, as well as a persistent internal state that prolongs courtship and enhances aggressiveness. However, P1 neurons themselves are not persistently active. This study identified pCd neurons as persistently active, indirect P1 targets that are required for P1-evoked persistent courtship and aggression. Acute activation of pCd neurons alone is inefficacious but enhances and prolongs courtship or aggression promoted by female cues. Brief female exposure induces a persistent increase in male aggressiveness, an effect abrogated by interruption of pCd activity. pCd activity is not sufficient but necessary for persistent physiological activity, implying an essential role in a persistence network. Thus, P1 neurons coordinate both command-like control of courtship song and a persistent internal state of social arousal mediated by pCd neurons (Jung, 2020).

Octopamine neuron dependent aggression requires dVGLUT from dual-transmitting neurons
Sherer, L. M., Catudio Garrett, E., Morgan, H. R., Brewer, E. D., Sirrs, L. A., Shearin, H. K., Williams, J. L., McCabe, B. D., Stowers, R. S. and Certel, S. J. (2020). PLoS Genet 16(2): e1008609. PubMed ID: 32097408

Neuromodulators such as monoamines are often expressed in neurons that also release at least one fast-acting neurotransmitter. The release of a combination of transmitters provides both "classical" and "modulatory" signals that could produce diverse and/or complementary effects in associated circuits. This study establish that the majority of Drosophila octopamine (OA) neurons are also glutamatergic and identify the individual contributions of each neurotransmitter on sex-specific behaviors. Males without OA display low levels of aggression and high levels of inter-male courtship. Males deficient for dVGLUT solely in OA-glutamate neurons (OGNs) also exhibit a reduction in aggression, but without a concurrent increase in inter-male courtship. Within OGNs, a portion of VMAT and dVGLUT puncta differ in localization suggesting spatial differences in OA signaling. These findings establish a previously undetermined role for dVGLUT in OA neurons and suggests that glutamate uncouples aggression from OA-dependent courtship-related behavior. These results indicate that dual neurotransmission can increase the efficacy of individual neurotransmitters while maintaining unique functions within a multi-functional social behavior neuronal network (Sherer, 2020).

Addressing the functional complexities of 'one neuron, multiple transmitters' is critical to understanding how neuron communication, circuit computation, and behavior can be regulated by a single neuron. Over many decades, significant progress has been made elucidating the functional properties of neurons co-expressing neuropeptides and small molecule neurotransmitters, where the neuropeptide acts as a co-transmitter and modulates the action of the neurotransmitter. Only recently have studies begun to examine the functional significance of co-transmission by a fast-acting neurotransmitter and a slow-acting monoamine (Sherer, 2020).

This study has demonstrated that OA neurons express dVGLUT and has utilized a new genetic tool to remove dVGLUT in OA-glutamate neurons. Quantifying changes in the complex social behaviors of aggression and courtship revealed that dVGLUT in brain OGNs is required to promote aggressive behavior and a specific behavioral pattern, the lunge. In contrast, males deficient for dVGLUT function do not exhibit an increase in inter-male courtship. These results establish a previously undetermined role for dVGLUT in OA neurons located in the adult brain and reveal glutamate uncouples aggression from inter-male courtship. It has been suggested that classical neurotransmitters and monoamines present in the same neuron modulate each other's packaging into synaptic vesicles or after release via autoreceptors. For example, a reduction of dVGLUT in DA-glutamate neurons resulted in decreased AMPH-stimulated hyperlocomotion in Drosophila and mice suggesting a key function of dVGLUT is the mediation of vesicular DA content. In this study, the independent behavioral changes suggests enhancing the packaging of OA into vesicles is not the sole function of dVGLUT co-expression and suggests differences in signaling by OA from OGNs on courtship-related circuitry (Sherer, 2020).

Co-transmission can generate distinct circuit-level effects via multiple mechanisms. One mechanism includes spatial segregation; the release of two neurotransmitters or a neurotransmitter and monoamine from a single neuron occurring at different axon terminals or presynaptic zones. Recent studies examining this possible mechanism have described; (i) the release of GLU and DA from different synaptic vesicles in midbrain dopamine neurons and (ii) the presence of VMAT and VGLUT microdomains in a subset of rodent mesoaccumbens DA neurons. This study expressed a new conditionally expressed epitope-tagged version of VMAT in OGNs and visualized endogenous dVGLUT via antibody labeling. Within OGNs, the colocalization of VMAT and dVGLUT puncta was not complete suggesting the observed behavioral phenotype differences may be due to spatial differences in OA signaling (Sherer, 2020).

A second mechanism by which co-transmission may generate unique functional properties relies on activating distinct postsynaptic receptors. In Drosophila, recent work has identified a small population of male-specific neurons that express the alpha-like adrenergic receptor, OAMB, as aggression-promoting circuit-level neuronal targets of OA modulation independent of any effect on arousal and separately knockdown of the Rdl GABAa receptor in a specific doublesex+ population stimulated male aggression. Future experiments identifying downstream targets that express both glutamate and octopamine receptors would be informative, as well as using additional split-Gal4 lines to determine if segregation of transporters is a hallmark of the majority of OGNs. Finally, a third possible mechanism is Glu may be co-released from OGNs and act on autoreceptors to regulate presynaptic OA release (Sherer, 2020).

Deciphering the signaling complexity that allows neural networks to integrate external stimuli with internal states to generate context-appropriate social behavior is a challenging endeavor. Neuromodulators including monoamines are released to signal changes in an animal's environment and positively or negatively reinforce network output. In invertebrates, a role for OA in responding to external chemosensory cues as well as promoting aggression has been well-established. In terms of identifying specific aggression circuit-components that utilize OA, previous results determined OA neurons directly receive male-specific pheromone information and the aSP2 neurons serve as a hub through which OA can bias output from a multi-functional social behavior network towards aggression. The ability of OA to bias behavioral decisions based on positive and negative reinforcement was also recently described for food odors. In vertebrates, it has been proposed that DA-GLU cotransmission in the NAc medial shell might facilitate behavioral switching. The finding that the majority of OA neurons are glutamatergic, suggests that the complex social behavior of aggression may rely on small subsets of neurons that both signal the rapid temporal coding of critical external stimuli as well as the frequency coding of such stimuli resulting in the enhancement of this behavioral network. One implication of the finding regarding the separable OA-dependent inhibition of inter-male courtship is the possibility of identifying specific synapses or axon terminals that when activated gate two different behavioral outcomes. A second implication is that aggressive behavior in other systems may be modified by targeting GLU function in monoamine neurons (Sherer, 2020).

Finally, monoamine-expressing neurons play key roles in human behavior including aggression and illnesses that have an aggressive component such as depression, addiction, anxiety, and Alzheimer's. While progress is being made in addressing the functional complexities of dual transmission, the possible pathological implications of glutamate co-release by monoamine neurons remains virtually unknown. Analyzing the synaptic vesicle and release properties of monoamine-glutamate neurons could offer new possibilities for therapeutic interventions aimed at controlling out-of-context aggression (Sherer, 2020).

A Circuit Node that Integrates Convergent Input from Neuromodulatory and Social Behavior-Promoting Neurons to Control Aggression in Drosophila
Watanabe, K., Chiu, H., Pfeiffer, B. D., Wong, A. M., Hoopfer, E. D., Rubin, G. M. and Anderson, D. J. (2017). Neuron 95(5): 1112-1128 e1117. PubMed ID: 28858617

Diffuse neuromodulatory systems such as norepinephrine (NE) control brain-wide states such as arousal, but whether they control complex social behaviors more specifically is not clear. Octopamine (OA), the insect homolog of NE, is known to promote both arousal and aggression. A systematic, unbiased screen identified OA receptor-expressing neurons (OARNs) that control aggression in Drosophila. The results uncover a tiny population of male-specific aSP2 neurons that mediate a specific influence of OA on aggression, independent of any effect on arousal. Unexpectedly, these neurons receive convergent input from OA neurons and P1 neurons, a population of FruM(+) neurons that promotes male courtship behavior. Behavioral epistasis experiments suggest that aSP2 neurons may constitute an integration node at which OAergic neuromodulation can bias the output of P1 neurons to favor aggression over inter-male courtship. These results have potential implications for thinking about the role of related neuromodulatory systems in mammals (Watanabe, 2017).

A rich behavioral literature has implicated OA in the control of invertebrate aggression, although the direction of its effects differs between species. Classic studies in lobsters have shown that injection of OA into the hemolymph promotes a subordinate-like posture, while injection of serotonin (5HT) produces a dominant-like posture. In contrast, hemolymph injections of OA in crickets restore aggressiveness to subordinated animals, mimicking the arousing effects of episodes of free flight. OA has also been suggested to play a role in aggressive motivation restored to defeated crickets by residency in a shelter. In Drosophila, null mutations of TβH strongly suppressed aggressiveness, suggesting a positive-acting role for OA in flies as in crickets. Interestingly, intra-hypothalamic infusion of NE in mammals can also enhance aggression. However, little is known about the neurons on which these amines act directly to influence aggression, in any organism (Watanabe, 2017).

This study applied a novel, unbiased approach to identify OARNs relevant to aggression in Drosophila. Importantly this screen was based not on mutations in OAR genes, but rather upon genetic silencing of neurons that express GAL4 under the control of different OAR gene cis-regulatory modules (CRMs). This screen was agnostic with respect to which OAR gene is involved, or in which neurons that OAR is expressed. It yielded a small population of male-specific, FruM+ OA-sensitive neurons, called aSP2, the activity of which isrequired for normal levels of aggressiveness. No significant change in UWEs (male-male courtship) was observed when these neurons were activated or silenced. Nevertheless, neuronal silencing in the parental R47A04-GAL4 line increased male-male courtship, perhaps reflecting an inhibitory role for non-aSP2 neurons in that line. Therefore, while it is not possible to completely exclude a role for aSP2 neurons to suppress male-male courtship, the evidence does not strongly support it (Watanabe, 2017).

Multiple lines of evidence suggest that R47A04aSP2 neurons are indeed OA responsive, likely via OAMB. First, these neurons are labeled by a CRM from the Oamb gene. Second, RNAi-mediated knockdown of Oamb in R47A04 neurons reduced aggression, phenocopying the effects of an Oamb null allele. (However, knockdown using the split-GAL4 R47A04aSP2driver only yielded a trend to reduced aggression that did not reach significance, perhaps reflecting a floor effect in this assay.) Third, overexpression of Oamb cDNAs in these neurons using R47A04-GAL4 rescued the Oamb null mutant and enhanced the effect of OA feeding to promote aggression. Fourth,R47A04aSP2 neurons were activated by bath-applied OA in brain explants, and this effect was also blocked by RNAi-mediated knockdown of Oamb. Taken together, these data strongly suggest that aSP2 neurons respond directly to OA to mediate its effects on aggression, although they do not exclude a role for other OA-responsive non-aSP2 neurons in line R47A04. While it was not possible to definitively establish which of the 27 different classes of OANs in Drosophila provide functional OA input to aSP2 cells, some candidate OA neurons labeled in retrograde PA-GFP experiments (VUM and VPM) have previously been implicated in aggression (Watanabe, 2017).

In Drosophila OA, like NE in vertebrates, is thought to promote arousal. Consistent with such a function, OAergic fibers are broadly distributed across the entire Drosophila CNS, as are NE fibers in vertebrates. Thus OARNs could enhance aggression by increasing arousal, and there is evidence for such a function in crickets. However, manipulations of R47A04aSP2neurons that increased or decreased aggression did not affect locomotion, circadian activity, or sleep. This suggests that these neurons influence aggression directly and specifically, rather than by increasing generalized arousal. Other classes of OARNs not investigated in this study have been implicated in sleep-wake arousal (Watanabe, 2017).

Does OA promote aggression in a permissive or instructive manner? While it is clear that OA synthesis and release are required for aggression in Drosophila, whether increasing OA suffices to promote aggression is less clear. It was reported that NaChBac-mediated activation of Tdc2-GAL4 neurons enhanced aggression, but the current study neither this manipulation, nor activation of Tdc2 neurons using dTrpA1 or Chrimson, yielded consistent effects. Thus, while OA is essential for normal levels of aggression, it is not clear whether it plays an instructive role to promote this behavior (Watanabe, 2017).

In principle, OA RNs could act directly in command-like neurons that mediate aggression, or rather in cells that play a modulatory role. It was found that aggression was increased by tonically enhancing the excitability of R47A04aSP2 neurons using NaChBac, but not by phasically activating them optogenetically, arguing against a command-like function. Furthermore, the influence of TK FruM neurons, which do promote aggression when phasically activated, was not dependent on the activity of R47A04aSP2 neurons, indicating that the latter are not functionally downstream of the former. Together, these data argue against a role for R47A04aSP2 cells as command-like neurons, or as direct outputs of command neurons, for aggression. Rather, these cells exert a modulatory influence on agonistic behavior (Watanabe, 2017).

In searching for neurons that may interact with R47A04aSP2 cells in their modulatory capacity, P1 neurons, a FruM+ population of 20 neurons/hemibrain was identified that controls male courtship, but which can also promote aggression when activated. It has been argued that this aggression-promoting effect is due to a subset of FruM neurons in the GAL4 line used in these studies, R71G01-GAL4. However, this study shows that conditional expression of FLP-ON Chrimson in a subset of neurons within the R71G01-GAL4 population using Fru-FLP. Nevertheless, these data do not exclude that the aggression-promoting neurons in the P1 cluster expressed Fru-FLP only transiently during development, nor do they exclude the possibility that different subpopulations of neurons within line R71G01 control courtship versus aggression; further studies will be required to resolve these issues (Watanabe, 2017).

The P1 cluster is known to project to downstream cells that are specific for courtship . The present study provides the first evidence that cells in this cluster also functionally activate (and physically contact) aggression-specific neurons. However, due to limitations of the genetic reagents employed, it is not certain that the behavioral, physiological, and anatomical interactions with aSP2 cells demonstrated in this study are all mediated by the same subset of neurons in the P1 cluster. With this caveat in mind, these data suggest that aSP2 neurons are functionally downstream of both a subset(s) of P1 neurons, as well as of OA neurons (Watanabe, 2017).

Feeding flies OA potentiated the activation of R47A04aSP2 neurons by P1 neuron stimulation, in brain explants. Furthermore, activation of aggression by P1 stimulation was enhanced and suppressed by pharmacologically increasing or decreasing OA signaling, respectively. While some off-target effects of the drugs, or an action on non-aSP2 neurons expressing OARs, cannot be excluded these pharmacologic effects were overridden by opposite-direction genetic manipulations of R47A04aSP2neuronal activity. Whether P1 neurons and OANs normally activate aSP2 neurons in vivo, simultaneously or sequentially, is not yet clear. Nevertheless it is striking that P1 and Tdc2 putative inputs occupy adjacent regions of aSP2 dendrites. Taken together, these findings suggest that aSP2 cells may serve as a node through which OA can bias output from a multifunctional social behavior network involving P1 neurons, in a manner that favors aggression. However, aSP2 neurons themselves do not appearto control directly the choice between mating and fighting (Watanabe, 2017).

Male-specific cuticular hydrocarbons such as 7-tricosene (7-T) are known to be required for aggression. Interestingly, it has recently been shown that gustatory neurons expressing Gr32a, which encodes a putative 7-T receptor, innervate OANs in the SEZ; these OANs are activated by 7-T in a Gr32a-dependent manner. SEZ-innervating OANs include the VPM/VUM subsets seen in PA-GFP retrograde labeling experiments. These data raise the possibility that R47A04aSP2 neurons might be targets of VPM/VUM OANs activated by 7-T. If so, then they could provide a potential link between the influence of male-specific pheromones, OA, and central aggression circuitry. Studies of NE neurons in vertebrates have led to a prevailing view that this neuromodulator is released in a diffuse, 'sprinkler system'-like manner to control brain-wide states like arousal. Recent studies in Drosophila indicate that the broad, brain-wide distribution of OAergic fibers reflects the superposition of close to 30 anatomically distinct subclasses of OANs). The data presented in this study reveal a high level of circuit specificity for OARNs that mediate the effects of OA on aggression, mirroring the anatomical and functional specificity of OANs reported to control this behavior. If this anatomical logic is conserved, then such circuit specificity may underlie the actions of NE in mammals to a greater extent than is generally assumed (Watanabe, 2017).

P1 interneurons promote a persistent internal state that enhances inter-male aggression in Drosophila
Hoopfer, E.D., Jung, Y., Inagaki, H.K., Rubin, G.M. and Anderson, D.J. (2015). Elife 4:e11346. PubMed ID: 26714106

How brains are hardwired to produce aggressive behavior, and how aggression circuits are related to those that mediate courtship, is not well understood. This large-scale screen for aggression-promoting neurons in Drosophila identifies several independent hits that enhance both inter-male aggression and courtship. Genetic intersections reveal that P1 interneurons, previously thought to exclusively control male courtship, are responsible for both phenotypes. The aggression phenotype is fly-intrinsic, and requires male-specific chemosensory cues on the opponent. Optogenetic experiments indicate that P1 activation promotes aggression vs. wing extension at low vs. high thresholds, respectively. High frequency photostimulation promotes wing extension and aggression in an inverse manner, during light ON and OFF, respectively. P1 activation enhances aggression by promoting a persistent internal state, which could endure for minutes prior to social contact. Thus P1 neurons promote an internal state that facilitates both aggression and courtship, and can control these social behaviors in a threshold-dependent manner (Hoopfer, 2015).

This study describes the first large-scale neuronal activation screen for aggression neurons in Drosophila. Using the thermosensitive ion channel dTrpA1, a collection of over 3,000 GAL4 lines was screened for flies that exhibited increased fighting following thermogenetic neuronal activation. Among ~20 hits obtained, three exhibited both increased aggression and male-male courtship behavior. Intersectional refinement of expression patterns using split-GAL4 indicated that both social behaviors are controlled, in all three hits, by a subpopulation of ~8-10 P1 neurons per hemibrain. P1 cells are male-specific, FruM+ interneurons that integrate pheromonal and visual cues to promote male courtship behavior. The results indicate, surprisingly, that at least a subset of P1 neurons, previously thought to control exclusively courtship, can promote male aggression as well. Moreover, it was shown that they exert this influence by inducing a persistent fly-intrinsic state, lasting for minutes, that enhances these behaviors. These data define a sexually dimorphic neural circuit node that may link internal states to the control of mating and fighting, and identify a potentially conserved circuit 'motif' for the control of social behaviors (Hoopfer, 2015).

Sound: Antenna, Antennal lobe and the Central Brain

Auditory activity is diverse and widespread throughout the central brain of Drosophila
Chodankar, A., Sadanandappa, M. K., VijayRaghavan, K. and Ramaswami, M. (2020). Pacheco, D. A., Thiberge, S. Y., Pnevmatikakis, E. and Murthy, M. (2021). Nat Neurosci 24(1): 93-104. PubMed ID: 33230320

Sensory pathways are typically studied by starting at receptor neurons and following postsynaptic neurons into the brain. However, this leads to a bias in analyses of activity toward the earliest layers of processing. This paper presents new methods for volumetric neural imaging with precise across-brain registration to characterize auditory activity throughout the entire central brain of Drosophila and make comparisons across trials, individuals and sexes. It was discovered that auditory activity is present in most central brain regions and in neurons responsive to other modalities. Auditory responses are temporally diverse, but the majority of activity is tuned to courtship song features. Auditory responses are stereotyped across trials and animals in early mechanosensory regions, becoming more variable at higher layers of the putative pathway, and this variability is largely independent of ongoing movements. This study highlights the power of using an unbiased, brain-wide approach for mapping the functional organization of sensory activity (Pacheco, 2021).

Flies detect sound using a feathery appendage of the antenna, the arista, which vibrates in response to near-field sounds. Antennal displacements activate mechanosensory Johnston's organ neurons (JONs) housed within the antenna. Three major populations of JONs (A, B and D) respond to vibratory stimuli at frequencies found in natural courtship song. These neurons project to distinct areas of the antennal mechanosensory and motor center (AMMC) in the central brain. Recent studies suggest that the auditory pathway continues from the AMMC to the wedge (WED), then to the ventrolateral protocerebrum (VLP) and to the lateral protocerebral complex (LPC). However, knowledge of the fly auditory pathway remains incomplete, and the functional organization of regions downstream of the AMMC and WED are largely unexplored. Moreover, nearly all studies of auditory coding in Drosophila have been performed using female brains, even though both males and females process courtship song information (Pacheco, 2021).

To address these issues, methods were developed to investigate the representation of behaviorally relevant auditory signals throughout the central brain of Drosophila and to make comparisons across animals. Two-photon microscopy was used to sequentially target the entirety of the Drosophila central brain in vivo, combined with fully automated segmentation of regions of interest (ROIs). In contrast to recent brain-wide imaging studies of Drosophila, temporal speed for was traded off for enhanced spatial resolution. Imaging at high spatial resolution facilitates automated ROI segmentation, with each ROI covering subneuropil structures, including cell bodies and neurites. ROIs were accurately registered into an in vivo template brain to compare activity across trials, individuals and sexes, and to build comprehensive maps of auditory activity throughout the central brain. The results reveal that the representation of auditory signals is broadly distributed throughout 33 out of 36 major brain regions, including in regions known to process other sensory modalities, such as all levels of the olfactory pathway, or to drive various motor behaviors, such as the central complex. The representation of auditory stimuli is diverse across brain regions, but focused on conspecific features of courtship song. Auditory activity is more stereotyped (across trials and individuals) at early stages of the putative mechanosensory pathway, becoming more variable and more selective for particular aspects of the courtship song at higher stages. This variability cannot be explained by simultaneous measurements of ongoing fly behavior. Meanwhile, auditory maps are largely similar between male and female brains, despite extensive sexual dimorphisms in neuronal number and morphology. These findings provide the first brain-wide description of sensory processing and feature tuning in Drosophila (Pacheco, 2021).

Sensory systems are typically studied starting from the periphery and continuing to downstream partners guided by anatomy. This has limited the understanding of sensory processing to early stages of a given sensory pathway. This study used a brain-wide imaging method to unbiasedly screen for auditory responses beyond the periphery and, via precise registration of recorded activity, to compare auditory representations across brain regions, individuals and sexes. Auditory activity was found to be widespread, extending well beyond the canonical mechanosensory pathway, and is present in brain regions and tracts known to process other sensory modalities (that is, olfaction and vision) or to drive motor behaviors. The representation of auditory stimuli diversified, in terms of both temporal responses to stimuli and tuning for stimulus features, from the AMMC to later stages of the putative pathway, becoming more selective for particular aspects of courtship song (that is, sine or pulse song, and their characteristic spectrotemporal patterns). Auditory representations were more stereotypic across trials and individuals in early stages of mechanosensory processing, and more variable at later stages. By recording neural activity in behaving flies, this study found that fly movements accounted for only a small fraction of the variance in neural activity, which suggests that across-trial auditory response variability stems from other sources. These results have important implications for how the brain processes auditory information to extract salient features and guide behavior (Pacheco, 2021).

Understanding of the Drosophila auditory circuit thus far has been built up from targeted studies of neural cell types that innervate particular brain regions close to the auditory periphery. Altogether, these studies have delineated a pathway that starts in the Johnston's organ and extends from the AMMC to the WED, the VLP and the LPC. By imaging pan-neuronally, widespread auditory responses that spanned brain regions beyond the canonical pathway, which suggests that auditory processing was found to be more distributed. However, for neuropil signals, it was challenging to determine the number of neurons that contribute to the described ROI responses. Although the diverse set of temporal and tuning types sampled per neuropil suggests that many neurons per neuropil, restricting GCaMP to spatially restricted genetic enhancer lines will assist with linking broad functional maps with the cell types constituting them (Pacheco, 2021).

Findings of widespread auditory activity are likely not unique to audition. So far, in adult Drosophila, only taste processing has been broadly surveyed. While that study did not map activity onto neuropils and tracts, nor did it make comparisons across individuals, it suggested that taste processing was distributed throughout the brain. Similarly, in vertebrates, widespread responses to visual and nociceptive stimuli have been observed throughout the brain. The findings are consistent with anatomical studies that found connections from the AMMC and the WED to several other brain regions, and with the analysis of the hemibrain connectome. While it is not yet known what role this widespread auditory activity plays in behavior, this study shows that ROIs that respond to auditory stimuli do so with mostly excitatory (depolarizing) responses and that activity throughout the brain is predominantly tuned to features of the courtship song. During courtship, flies evaluate multiple sensory cues (olfactory, auditory, gustatory and visual) to inform mating decisions and to modulate their mating drive. Although integration of multiple sensory modalities has been described in higher-order brain regions, the results suggest that song representations are integrated with olfactory and visual information at earlier stages. In addition, song information may modulate the processing of non-courtship stimuli. Song representations in the MB may be useful for learning associations between song and general olfactory, gustatory or visual cues, while diverse auditory activity throughout all regions of the LH may indicate an interaction between song processing and innate olfactory behaviors. Finally, auditory activity was found in brain regions involved in locomotion and navigation (the central and lateral complex, and the superior and ventromedial neuropils). Auditory activity in these regions is diverse, which suggests that pre-motor circuits receive information about courtship song patterns and could therefore underlie stimulus-specific locomotor responses (Pacheco, 2021).

D. melanogaster songs are composed of pulses and sines that differ in their spectral and temporal properties; however, it is unclear how and where selectivity for the different song modes arises in the brain. Since neurons in the LPC are tuned for pulse song across all time scales that define that mode of song, neurons upstream must carry the relevant information to generate such tuning. This study found many ROIs that are selective for either sine or pulse stimuli throughout the entire central brain. A more detailed systematic examination of tuning in the neuropils that carry the most auditory activity (the AMMC, the SAD, the WED, the AVLP and PVLP, the PLP and the LH) revealed that most ROIs are tuned to either pulse or sine features, with few ROIs possessing intermediate tuning. This suggests that sine and pulse information splits early in the pathway. It was also found that sine-selective responses dominate throughout the brain. Although some of this selectivity may simply reflect preference for continuous versus pulsatile stimuli, this investigation of feature tuning revealed that many of these ROIs preferred frequencies that are specifically present in courtship songs. Previous studies indicated that pulse song is more important for mating decisions, with sine song purported to play a role in only priming females. However the results, in combination with the fact that males spend a greater proportion of time in courtship singing sine versus pulse song, suggest a need for reevaluation of the importance and role of sine song in mating decisions. This study therefore lays the foundation for exploring how song selectivity arises in the brain (Pacheco, 2021).

The results also revealed that early mechanosensory brain areas contain ROIs with less variable auditory activity across trials and animals. The results for across-animal variability have parallels to the Drosophila olfactory pathway, whereby third-order MB neurons are not stereotyped, while presynaptic neurons in the AL, the PNs, are. Similarly, a lack of stereotypy beyond early mechanosensory brain areas may reflect stochasticity in synaptic wiring. The amount of variation observed in some brain areas was large, and follow-up experiments with sparser driver lines will be needed to validate whether what is reported here applies to variation across individual identifiable neurons (Pacheco, 2021).

A wide range of across-trial variability was observed throughout neuropils with auditory activity. Imaging from a subset of brain regions in behaving flies revealed that trial-to-trial variance in auditory responses is not explained by spontaneous movements, which suggests that variance is driven by internal dynamics. This result differs from recent findings in the mouse brain, which showed that a large fraction of activity in sensory cortices corresponds to non-task-related or spontaneous movements. This may indicate an important difference between invertebrate and vertebrate brains and the degree to which ongoing movements shape activity across different brains. However, it should be pointed out that while motor activity is known to affect sensory activity in flies, this modulation is tied to movements that are informative for either optomotor responses or steering. In these experiments, although flies walked abundantly, they did not produce reliable responses to auditory stimuli, although playback of the same auditory stimuli can reliably change walking speed in freely behaving flies. Adjusting the paradigm to drive such responses might uncover behavioral modulation of auditory activity. Alternatively, behavioral modulation of auditory responses may occur primarily in motor areas, such as the central complex, or areas containing projections of descending neurons. Further dissection of the sources of this variability would require the simultaneous capture of more brain activity in behaving animals while not significantly compromising spatial resolution (Pacheco, 2021).

This paper provides tools for characterizing sensory activity registered in common atlas coordinates for comparisons across trials, individuals and sexes. By producing maps for additional modalities and stimulus combinations and by combining these maps with information on connectivity between and within brain regions, the logic of how the brain represents the myriad stimuli and their combinations present in the world should emerge (Pacheco, 2021).

Glomerulus-selective regulation of a critical period for interneuron plasticity in the Drosophila antennal lobe
Chodankar, A., Sadanandappa, M. K., VijayRaghavan, K. and Ramaswami, M. (2020). J Neurosci. PubMed ID: 32532889

Several features of the adult nervous systems develop in a "critical period," (CP) during which high levels of plasticity allow neural circuits to be tuned for optimal performance. Through an analysis of long-term olfactory habituation (LTH) in female Drosophila, this study provides new insight into mechanisms by which CPs are regulated in vivo LTH manifests as a persistently reduced behavioural response to an odorant encountered for four continuous days and occurs together with the growth of specific, odorant-responsive glomeruli in the antennal lobe. The CP for behavioral and structural plasticity induced by ethyl butyrate (EB) or carbon dioxide (CO(2)) closes within 48 hours after eclosion. The elaboration of excitatory projection neuron (PN) processes likely contribute to glomerular volume increases: both occur together and similarly require cAMP signalling in the antennal lobe inhibitory local interneurons (iLNs). Further, the CP for structural plasticity could be extended beyond 48 hours if EB- or CO(2)-responsive olfactory sensory neurons (OSNs) are silenced after eclosion; thus, OSN activity is required for closing the CP. Strikingly, silencing of glomerulus-selective OSNs extends the CP for structural plasticity only in respective target glomeruli. This indicates existence of a local, short-range mechanism for regulating CP closure (Chodankar, 2020).

GABAergic local interneurons shape female fruit fly response to mating songs
Yamada, D., Ishimoto, H., Li, X., Kohashi, T., Ishikawa, Y. and Kamikouchi, A. (2018). J Neurosci 38(18): 4329-4347. PubMed ID: 29691331

Many animals use acoustic signals to attract a potential mating partner. In fruit flies (Drosophila melanogaster), the courtship pulse song has a species-specific interpulse interval (IPI) that activates mating. Although a series of auditory neurons in the fly brain exhibit different tuning patterns to IPIs, it is unclear how the response of each neuron is tuned. This study examined the neural circuitry regulating the activity of antennal mechanosensory and motor center (AMMC)-B1 neurons, key secondary auditory neurons in the excitatory neural pathway that relay song information. By performing Ca(2+) imaging in female flies, it as found that the IPI selectivity observed in AMMC-B1 neurons differs from that of upstream auditory sensory neurons [Johnston's organ (JO)-B]. Selective knock-down of a GABAA receptor subunit in AMMC-B1 neurons increased their response to short IPIs, suggesting that GABA suppresses AMMC-B1 activity at these IPIs. Connection mapping identified two GABAergic local interneurons that synapse with AMMC-B1 and JO-B. Ca(2+) imaging combined with neuronal silencing revealed that these local interneurons, AMMC-LN and AMMC-B2, shape the response pattern of AMMC-B1 neurons at a 15 ms IPI. Neuronal silencing studies further suggested that both GABAergic local interneurons suppress the behavioral response to artificial pulse songs in flies, particularly those with a 15 ms IPI. Altogether, this study identified a circuit containing two GABAergic local interneurons that affects the temporal tuning of AMMC-B1 neurons in the song relay pathway and the behavioral response to the courtship song. These findings suggest that feedforward inhibitory pathways adjust the behavioral response to courtship pulse songs in female flies (Yamada, 2018).

The organization of projection neurons and local neurons of the primary auditory center in the fruit fly Drosophila melanogaster
Matsuo, E., Seki, H., Asai, T., Morimoto, T., Miyakawa, H., Ito, K. and Kamikouchi, A. (2016). J Comp Neurol 524(6):1099-164. PubMed ID: 26762251

Acoustic communication between insects serves as an excellent model system for analyzing the neuronal mechanisms underlying auditory information processing. To understand the central auditory pathways a large-scale analysis was performed of the interneurons associated with the primary Drosophila auditory center. By screening expression driver strains and performing single-cell labeling of these strains, 44 types of interneurons were identified innervating the primary auditory center - 5 types were local interneurons whereas the other 39 types were projection interneurons connecting the primary auditory center with other brain regions. The projection neurons comprised three frequency-selective pathways and two frequency-embracive pathways. Mapping of their connection targets revealed that five neuropils in the brain - the wedge, anterior ventrolateral protocerebrum, posterior ventrolateral protocerebrum (PVLP), saddle (SAD), and gnathal ganglia (GNG) - were intensively connected with the primary auditory center. In addition, several other neuropils, including visual and olfactory centers in the brain, were directly connected to the primary auditory center. The distribution patterns of the spines and boutons of the identified neurons suggest that auditory information is sent mainly from the primary auditory center to the PVLP, WED, SAD, GNG, and the thoracico-abdominal ganglia. Based on these findings, this study has established the first comprehensive map of secondary auditory interneurons, which indicates the downstream information flow to parallel ascending pathways, multimodal pathways, and descending pathways (Matsuo, 2016).

A neural command circuit for grooming movement control
Hampel, S., Franconville, R., Simpson, J.H. and Seeds, A.M. (2015). Elife 4:e08758.. PubMed ID: 26344548

Animals perform many stereotyped movements, but how nervous systems are organized for controlling specific movements remains unclear. This study used anatomical, optogenetic, behavioral, and physiological techniques to identify a circuit in Drosophila melanogaster that can elicit stereotyped leg movements that groom the antennae. Mechanosensory chordotonal neurons detect displacements of the antennae and excite three different classes of functionally connected interneurons, which include two classes of brain interneurons and different parallel descending neurons. This multilayered circuit is organized such that neurons within each layer are sufficient to specifically elicit antennal grooming. However, differences were found in the durations of antennal grooming elicited by neurons in the different layers, suggesting that the circuit is organized to both command antennal grooming and control its duration. As similar features underlie stimulus-induced movements in other animals, there is a possibility of a common circuit organization for movement control that can be dissected in Drosophila (Hampel, 2015).

Clock and photoperiod
The lateral posterior clock neurons of Drosophila melanogaster express three neuropeptides and have multiple connections within the circadian clock network and beyond
Reinhard, N., Bertolini, E., Saito, A., Sekiguchi, M., Yoshii, T., Rieger, D. and Helfrich-Forster, C. (2021). J Comp Neurol. PubMed ID: 34961936

Drosophila's lateral posterior neurons (LPNs) belong to a small group of circadian clock neurons that is so far not characterized in detail. Thanks to a new highly specific split-Gal4 line, this study describes LPNs' morphology in fine detail, their synaptic connections, daily bimodal expression of neuropeptides, and a putative role of this cluster in controlling daily activity and sleep patterns is proposed. The three LPNs were found to be heterogeneous. Two of the neurons with similar morphology arborize in the superior medial and lateral protocerebrum and most likely promote sleep. One unique, possibly wakefulness-promoting, neuron with wider arborizations extends from the superior lateral protocerebrum toward the anterior optic tubercle. Both LPN types exhibit manifold connections with the other circadian clock neurons, especially with those that control the flies' morning and evening activity (M- and E-neurons, respectively). In addition, they form synaptic connections with neurons of the mushroom bodies, the fan-shaped body, and with many additional still unidentified neurons. Both LPN types rhythmically express three neuropeptides, Allostatin A, Allostatin C, and Diuretic Hormone 31 with maxima in the morning and the evening. The three LPN neuropeptides may, furthermore, signal to the insect hormonal center in the pars intercerebralis and contribute to rhythmic modulation of metabolism, feeding, and reproduction. These findings are discussed in the light of anatomical details gained by the recently published hemibrain of a single female fly on the electron microscopic level and of previous functional studies concerning the LPN.

Neuron-specific knockouts indicate the importance of network communication to Drosophila rhythmicity
Schlichting, M., Diaz, M. M., Xin, J. and Rosbash, M. (2019). Elife 8: e48301. PubMed ID: 31613223

Animal circadian rhythms persist in constant darkness and are driven by intracellular transcription-translation feedback loops. Although these cellular oscillators communicate, isolated mammalian cellular clocks continue to tick away in darkness without intercellular communication. To investigate these issues in Drosophila, behavior as well as molecular rhythms were assayed within individual brain clock neurons while blocking communication within the ca. 150 neuron clock network. CRISPR-mediated neuron-specific circadian clock knockouts were also generated. The results point to two key clock neuron groups: loss of the clock within both regions but neither one alone has a strong behavioral phenotype in darkness; communication between these regions also contributes to circadian period determination. Under these dark conditions, the clock within one region persists without network communication. The clock within the famous PDF-expressing s-LNv neurons however was strongly dependent on network communication, likely because clock gene expression within these vulnerable sLNvs depends on neuronal firing or light (Schlichting, 2019).

Neuronal networks make myriad contributions to behavior and physiology. By definition, individual neurons within a network interact, and different networks also interact to coordinate specialized functions. For example, the visual cortex and motor output centers must coordinate to react properly to environmental changes. In a less immediate fashion, sleep centers and circadian clocks are intertwined to properly orchestrate animal physiology. The brain clock is of special interest: it not only times and coordinates physiology within neuronal tissues but also sends signals to the body to keep the entire organism in sync with the cycling external environment (Schlichting, 2019).

The small, circumscribed Drosophila clock network is ideal to address circadian communication issues. The comparable region in mammals, the suprachiasmatic nucleus, is composed of thousands of cells depending on the species. There are in contrast only 75 clock neurons per hemisphere in Drosophila. These different clock neurons can be divided into several subgroups according to their location within the fly brain. There are 4 lateral and three dorsal neuron clusters, which have different functions in controlling fly physiology (Schlichting, 2019).

The four small ventro-lateral neurons (sLNvs) are arguably the most important of the 75 clock neurons. This is because ablating or silencing these neurons abolishes rhythms in constant darkness (DD). They reside in the accessory medulla region of the fly brain, an important pacemaker center in many insects, and express the neuropeptide PDF. In addition, they are essential for predicting dawn. A very recent study suggests that the sLNvs are also able to modulate the timing of the evening (E) peak of behavior via PDF. The other ventral-lateral group, the four large-ventro-lateral neurons (lLNvs), also express PDF and send projections to the medulla, the visual center of the fly brain; they are important arousal neurons. Consistent with the ablation experiments mentioned above, the absence of pdf function or reducing PDF levels via RNAi causes substantial arrhythmic behavior in DD (Schlichting, 2019).

Other important clock neurons include the dorso-lateral neurons (LNds), which are essential for the timing of the E peak and adjustment to long photoperiods. Two other clock neuron groups, the lateral-posterior neurons (LPN and a subset of the dorsal neurons (DN1s), were recently shown to connect the clock network to sleep centers in the fly central complex. The DN2 neurons are essential for temperature preference rhythms, whereas no function has so far been assigned to the DN3s (Schlichting, 2019).

Despite these distinct functions, individual clock neuron groups are well-connected to each other. At the anatomical level, all lateral neuron clusters and even DN1 dorsal neurons send some of their projections into the accessory medulla, where they can interact. A second area of common interaction is the dorsal brain; only the lLNvs do not project there (Schlichting, 2019).

Several studies have investigated interactions between different clock neurons. Artificially expressing kinases within specific clock neurons causes their clocks to run fast or slow and also changes the overall free-running period of the fly, indicating that network signaling adjusts behavior. Similarly, speeding up or slowing down individual neurons is able to differentially affect behavioral timing in standard light-dark (LD) cycles. A high level of neuronal plasticity within the network also exists: axons of individual cells undergo daily oscillations in their morphology, and neurons change their targets depending on the environmental condition (Schlichting, 2019).

How neuronal communication influences the fly core feedback loop is not well understood. The latter consists of several interlocked transcriptional-translational feedback loops, which probably underlie rhythms in behavior and physiology. A simplified version of the core feedback loop consists of the transcriptional activators Clock (CLK) and Cycle (CYC) and the transcriptional repressors Period (PER) and Timeless (TIM). CLK and CYC bind to E-boxes within the period (per) and timeless (tim) genes (among other clock-controlled genes) and activate their transcription. After PER and TIM synthesis in the cytoplasm, they form a heterodimer and enter the nucleus toward the end of the night. There they interact with CLK and CYC, release them from their E-box targets and thereby inhibit their own transcription. All 75 pairs of clock neurons contain this canonical circadian machinery, which undergoes daily oscillations in level. Indeed, the immunohistochemical cycling of PER and TIM within these neurons is a classic assay to visualize these molecular oscillations (Schlichting, 2019).

Silencing PDF neurons stops their PER cycling, indicating an important role of neuronal firing in maintaining circadian oscillations. However, only two time points were measured, and the results were possibly confounded by developmental effects. PDF neuron silencing also phase advances PER cycling in downstream neurons, suggesting that PDF normally serves to delay cycling in target neurons. This is consistent with experiments showing that PDF signaling stabilizes PER. In addition, neuronal activation is able to mimic a light pulse and phase shift the clock due to firing-mediated TIM degradation (Schlichting, 2019).

To investigate more general features of clock neuron interactions on the circadian machinery, the majority of the fly brain clock neurons were silenced, and behavior and clock protein cycling within the circadian network was examined in a standard light-dark cycle (LD) as well as in constant darkness (DD). Silencing abolished rhythmic behavior but had no effect on clock protein cycling in LD, indicating that the silencing affects circadian output but not oscillator function in a cycling light environment. Silencing similarly abolished rhythmic behavior in DD but with very different effects on clock protein cycling. Although protein cycling in the LNds was not affected by neuronal silencing in DD, the sLNvs dampened almost immediately. Interestingly, this differential effect is under transcriptional control, suggesting that some Drosophila clock neurons experience activity-regulated clock gene transcription. Cell-specific CRISPR/Cas9 knockouts of the core clock protein Per further suggests that network properties are critical to maintain wild-type activity-rest rhythms. The data taken together show that clock neuron communication and firing-mediated clock gene transcription are essential for high amplitude and synchronized molecular rhythms as well as rhythmic physiology (Schlichting, 2019).

The central clock of animals is essential for dictating the myriad diurnal changes in physiology and behavior. Knocking out core clock components such as period or Clock severely disrupts circadian behavior as well as molecular clock properties in flies and mammals. This study show that similar behavioral effects occur when the central clock neurons are silenced and thereby abolish communication within this network and with downstream targets, that is fly behavior becomes arrhythmic in LD as well as DD conditions and resembles the phenotypes of core clock mutant strains (Schlichting, 2019).

Despite the loss of all rhythmic behavior, silencing did not impact the molecular machinery in LD conditions: PER and PDP1 protein cycling was normal. These findings suggest that (1) rhythmic behavior requires clock neuron output, which is uncoupled from the circadian molecular machinery by network silencing, and (2) synchronized molecular rhythms of clock neurons do not require neuronal activity. These findings are in agreement with previous work showing that silencing the PDF neurons had no effect on Per cycling within these neurons. The results presumably reflect the strong effect of the external light-dark cycle on these oscillators (Schlichting, 2019).

In DD however, the individual neurons change dramatically: the different neurons desynchronize, and their protein cycling damps to different extents. Interestingly, sLNv cycling relies most strongly on neuronal communication: these neurons cycle robustly in controls but apparently not at all in the silenced state. sLNvs were previously shown to be essential for DD rhythms. Unfortunately, the sensitivity of immunohistochemistry precludes determining whether the molecular clock has actually stopped or whether silencing has only (dramatically) reduced cycling amplitude. However, a simple interpretation of the adult-specific silencing experiment favors a stopped clock: decreasing the temperature to 18 degrees after a week at high temperature failed to rescue rhythmic behavior. A similar experiment in mammals gave rise to the opposite result, suggesting an effect of firing on circadian amplitude in that case. However, different explanations cannot be excluded, for example chronic effects of neuronal silencing or a too large phase difference between the different neuronal subgroups to reverse after a week without communication (Schlichting, 2019).

In either case, a stopped clock or an effect on clock protein oscillation amplitude, these results make another link to the mammalian literature: modeling of the clock network suggests that different neurons resynchronize more easily if the most highly-connected cells are intrinsically weak oscillators. The sLNvs are essential for DD rhythms, known to communicate with other clock neurons and are situated in the accessory medulla; this is an area of extensive neuronal interactions in many insects. These considerations rationalize weak sLNv oscillators (Schlichting, 2019).

An important role of interneuron communication in DD is in agreement with previous work showing that altering the speed of individual neuron groups can change the phase of downstream target neurons. An important signaling molecule is the neuropeptide PDF: its absence changes the phase of downstream target neurons, and silencing PDF neurons causes an essentially identical phenotype to the lack of PDF. However, the effects reported in this study are much stronger and show different levels of autonomy than PDF ablation, suggesting that other signaling molecules and/or the neuronal activity of additional clock neurons are essential to maintain proper rhythmic clock protein expression (Schlichting, 2019).

To address these possibilities, this study took two approaches. First, clock gene RNA levels were investigated after silencing. The goal was to assess whether the damping of silenced neurons is under gene expression control, likely transcriptional control. Indeed, tim mRNA profiles nicely reproduced the protein cycling profiles: robust cycling of all (assayed) clock neurons was maintained in LD even with silencing, but tim-mRNA levels in the sLNvs stopped cycling in DD; in contrast, robust cycling was maintained in the LNds. This suggests that the changes in protein cycling amplitude and also possibly phase are under transcriptional control. Importantly, the tim signal in the sLNvs disappeared upon silencing, suggesting that neuronal activity promotes clock gene transcription at least in this subset of neurons. This recapitulates for the first time in Drosophila the robust positive relationship between neuronal firing and clock gene transcription in mammals. To date, Drosophila neuronal firing had only been connected to post-transcriptional clock protein regulation, namely TIM degradation. Conceivably, these two effects are connected: TIM degradation might be required to relieve transcriptional repression and maintain cycling (Schlichting, 2019).

The second approach was a cell-specific knockout strategy, applied to the clock neuron network. Three guides were generated targeting the CDS of per and also CAS9 was expressed in a cell-specific manner. The guides caused double strand breaks in the per gene, which in turn led to cell-specific per mutations. This adult brain knockout strategy worked reliably and specifically, in glial cells as well as neurons, with high efficiency and with no apparent background effects. This strategy was successfully used to knock out most if not all Drosophila GPCRs and it is believed to be superior to RNAi for most purposes. Importantly, expression of the guides with the clk856-GAL4 driver phenocopied per01 behavior. To focus on individual clock neurons, cell-specific knockouts were generated in different clock neurons. PERKO in the PDF cells did not increase the level of arrhythmicity, only a PERKO in most lateral neurons, E cells as well as PDF cells, generated high levels of arrhythmic behavior (Schlichting, 2019).

Morning and evening circadian pacemakers independently drive premotor centers via a specific dopamine relay
Liang, X., Ho, M. C. W., Zhang, Y., Li, Y., Wu, M. N., Holy, T. E. and Taghert, P. H. (2019). Neuron. PubMed ID: 30981533

Many animals exhibit morning and evening peaks of locomotor behavior. In Drosophila, two corresponding circadian neural oscillators-M (morning) cells and E (evening) cells-exhibit a corresponding morning or evening neural activity peak. Yet little is known of the neural circuitry by which distinct circadian oscillators produce specific outputs to precisely control behavioral episodes. This study shows that ring neurons of the ellipsoid body (EB-RNs) display spontaneous morning and evening neural activity peaks in vivo: these peaks coincide with the bouts of locomotor activity and result from independent activation by M and E pacemakers. Further, M and E cells regulate EB-RNs via identified PPM3 dopaminergic neurons, which project to the EB and are normally co-active with EB-RNs. These in vivo findings establish the fundamental elements of a circadian neuronal output pathway: distinct circadian oscillators independently drive a common pre-motor center through the agency of specific dopaminergic interneurons (Liang, 2019).

Recurrent circuitry for balancing sleep need and sleep
Donlea, J. M., Pimentel, D., Talbot, C. B., Kempf, A., Omoto, J. J., Hartenstein, V. and Miesenbock, G. (2018). Neuron 97(2): 378-389. PubMed ID: 29307711 Sleep-promoting neurons in the dorsal fan-shaped body (dFB) of Drosophila are integral to sleep homeostasis, but how these cells impose sleep on the organism is unknown. This study reports that dFB neurons communicate via inhibitory transmitters, including allatostatin-A (AstA), with interneurons connecting the superior arch with the ellipsoid body of the central complex. These "helicon cells" express the galanin receptor homolog AstA-R1, respond to visual input, gate locomotion, and are inhibited by AstA, suggesting that dFB neurons promote rest by suppressing visually guided movement. Sleep changes caused by enhanced or diminished allatostatinergic transmission from dFB neurons and by inhibition or optogenetic stimulation of helicon cells support this notion. Helicon cells provide excitation to R2 neurons of the ellipsoid body, whose activity-dependent plasticity signals rising sleep pressure to the dFB. By virtue of this autoregulatory loop, dFB-mediated inhibition interrupts processes that incur a sleep debt, allowing restorative sleep to rebalance the books (Donlea, 2018).

Communication Among Photoreceptors and the Central Clock Affects Sleep Profile
Damulewicz, M., Ispizua, J. I., Ceriani, M. F. and Pyza, E. M. (2020). Front Physiol 11: 993. PubMed ID: 32848895

Light is one of the most important factors regulating rhythmical behavior of Drosophila melanogaster. It is received by different photoreceptors and entrains the circadian clock, which controls sleep. The retina is known to be essential for light perception, as it is composed of specialized light-sensitive cells which transmit signal to deeper parts of the brain. This study examined the role of specific photoreceptor types and peripheral oscillators located in these cells in the regulation of sleep pattern. Sleep was shown to be controlled by the visual system in a very complex way. Photoreceptors expressing Rh1, Rh3 are involved in night-time sleep regulation, while cells expressing Rh5 and Rh6 affect sleep both during the day and night. Moreover, Hofbauer-Buchner (HB) eyelets which can directly contact with s-LN (v) s and l-LN (v) s play a wake-promoting function during the day. In addition, this study showed that L2 interneurons, which receive signal from R1-6, form direct synaptic contacts with l-LN (v) s, which provides new light input to the clock network (Damulewicz, 2020).

CRY-dependent plasticity of tetrad presynaptic sites in the visual system of Drosophila at the morning peak of activity and sleep
Damulewicz, M., Woznicka, O., Jasinska, M. and Pyza, E. (2020). Sci Rep 10(1): 18161. PubMed ID: 33097794

Tetrad synapses are formed between the retina photoreceptor terminals and postsynaptic cells in the first optic neuropil (lamina) of Drosophila. They are remodelled in the course of the day and show distinct functional changes during activity and sleep. These changes result from fast degradation of the presynaptic scaffolding protein Bruchpilot (BRP) by Cryptochrome (CRY) in the morning and depend on BRP-170, one of two BRP isoforms. This process also affects the number of synaptic vesicles, both clear and dense-core, delivered to the presynaptic elements. In cry01 mutants lacking CRY and in brpΔ170, the number of synaptic vesicles is lower in the morning peak of activity than during night-sleep while in wild-type flies the number of synaptic vesicles is similar at these two time points. CRY may also set phase of the circadian rhythm in plasticity of synapses. The process of synapse remodelling stimulates the formation of clear synaptic vesicles in the morning. They carry histamine, a neurotransmitter in tetrad synapses and seem to be formed from glial capitate projections inside the photoreceptor terminals. In turn dense-core vesicles probably carry synaptic proteins building the tetrad presynaptic element (Damulewicz, 2020).

The results confirmed earlier studies that the presynaptic element (T-bar) of tetrad synapses is remodelled during the day and night and this rhythm is regulated by light and circadian clock. In the present study, it was found additionally that cyclic changes occur in the T-bar ultrastructure and its volume. Ultrastructural changes in T-bars and synaptic vesicles were possible because of using high resolution electron microscope tomography (EMT). In the present study it was also found that the number of synaptic vesicles cycles during the day, but this rhythm is masked by light. This result indicates that in the case of tetrad synapses, which are sites of fast neurotransmission between photoreceptors and the first order interneurons, intense neurotransmission occurs during the morning peak of locomotor activity, when more synaptic vesicles are attached to the T-bar platform than during sleep (ZT16) and are transported from capitate projections located next to the T-bars. At ZT16, tetrad synapses are ready for neurotransmission, since the total number of synaptic vesicles near tetrad synapses is similar at ZT1 and ZT16, but it is in a standby mode with lower frequency of synapses and vesicles, which are not attached to the T-bar platform and are not delivered from glial cells, respectively. However, transmission can be activated and is efficient because synapses during sleep have larger volume, and synaptic vesicles can be transported to the T-bar platform, if necessary, in response to an unexpected light pulse. Cyclic remodelling of tetrad presynaptic sites depends on BRP, which must be delivered to T-bars and degraded after light exposure after binding to CRY. This fast remodelling of synapses affects the number of vesicles transported to the presynaptic element (Damulewicz, 2020).

The present study was carried out only in light/dark (LD 12:12) conditions because in earlier studies it was found that the rhythm of the changes in BRP abundance in tetrad synapses of D. melanogaster is circadian. The rhythm is maintained in constant darkness (DD) and abolished in the per01 clock null mutant. On the basis of these results, it is assumed that rhythmic changes during the 24 h cycle reported is this paper are also circadian; however, in DD, the morning peak in BRP is not present because it depends on light (Damulewicz, 2020).

Electron microscope tomography (EMT) used in this study showed that synaptic vesicles are attached to the platform of the T-bar with filamentous proteins that are reduced in brpΔ170 and brpΔ190 mutants, which have fewer synaptic vesicles compared with wild-type flies. Two types of vesicles, clear and dense-core were detected. Dense-core synaptic vesicles were less numerous than clear ones. It is known that synaptic vesicles of tetrad synapses contain histamine, while the content of dense-core vesicles is unknown. It is possible that they carry presynaptic proteins to the T-bar. The comparison of ultrastructure of tetrad synapses in the morning peak of activity (ZT1) and during sleep (ZT16) indicates that more vesicles are attached to the T-bar platform and to capitate projections at ZT1, but this pattern is not present in brpΔ170, brpΔ190 and cry01 . This result confirmed an earlier study that both high motor activity in the morning and light exposure increase activity of the visual system. In the morning, there is intense transport of synaptic vesicles to T-bars and delivery of histamine in clear vesicles from the epithelial glial cells through capitate projections. The evidence for a role of capitate projections in neurotransmitter recycling has already been reported and now this study showed, using EMT, that vesicles are produced from capitate projections and directly delivered to T-bars. This intense transport is damaged in all mutants studied, suggesting that both BRP isoforms and CRY are needed for this process. In addition, in the brpΔ190 mutant lacking BRP-190, the T-bar structure is less dense than in the other strains studied. In a previous study, it was found that there are approximately 50% fewer synapses in brpΔ190 than in Canton S and brpΔ170. Another study reported that BRP isoforms are important for the formation of T-bars in neuromuscular junctions, and in brp mutants T-bars are smaller than in controls. T-bar height was reduced in brpΔ190, whereas the widths of pedestal and platform were reduced in both mutants. They also decrease transmission since the active zone was smaller in both mutants and the number of synaptic vesicles was reduced. These ultrastructural changes are correlated with cell physiology since the amplitude of evoked excitatory junctional current was decreased in both mutants with a stronger effect in brpΔ190 (Damulewicz, 2020).

The obtained reconstructions of tetrad T-bars from TEM serial sections of the lamina showed that although there were fewer synapses during the night (ZT16), the volume of the T-bar was larger at that time than in the morning (ZT1), while the total number of synaptic vesicles was similar. In contrast, a day/night difference (ZT1 vs. ZT16) in the number of vesicles was observed in brpΔ170 and cry01 . This suggests that the CRY protein and BRP-170 are responsible for an increase in the number of synaptic vesicles during the morning peak of activity. Since CRY co-localizes with BRP and is involved in BRP degradation in the morning, CRY is probably also involved in the degradation of other proteins of synaptic vesicle organization in the morning since the number of vesicles in cry01 was low in the morning but high at night (ZT16). It seems that in cry01, synaptic vesicles are not delivered to the photoreceptor terminals from capitate projections and tethered to the cytomatrix in the morning. It is also interesting that the daily rhythm in the number of vesicles is not maintained in BRP mutants, which confirms an earlier study, and the BRP N-terminus, which lacks brpΔ190, is necessary to maintain daily remodelling of the T-bar structure. Although both isoforms participate in building the cytomatrix their functions seem to be different in the course of the day. It is also possible that CRY is not only responsible for degradation of synaptic proteins but also as a protein, what is known, affecting the clock. In another cell types, in clock neurons l-LNvs, CRY, except interaction with TIM, is responsible for blue light response and firing of the l-LNvs. In the lamina it was found that in cry01 mutant the daily rhythm in synapse number and their remodelling was delayed in phase and the day/night difference in Canton S increased when peaks in the number of synapses were shift to ZT4 and ZT16. In result the difference between ZT1 and ZT16 was increased in cry01 (Damulewicz, 2020).

BRP is also responsible for rapid remodelling of the presynaptic active zone (AZ), and as reported in Drosophila NMJ, presynaptic homeostatic potentiation increases the number of BRP molecules and other AZ proteins, Unc13A and RBP, within minutes (Damulewicz, 2020).

When synaptic vesicles were counted at two different distances from the T-bar, to 200 nm and above 200 nm, there were differences between clear vesicles containing histamine and dense-core ones located in both areas. More clear vesicles were located near the T-bar and fewer above 200 nm. In the case of dense-core vesicles, their number was similar in both areas. This difference was not so striking in mutants in the case of vesicles located next to the platform, but in brpΔ170 and cry01, there were more dense-core vesicles at ZT16 in the distance above 200 nm than closer to the T-bar. This result indicates that BRP-170 and CRY are important for the distribution of clear synaptic vesicles next to the T-bar as well as dense-core vesicles located above 200 nm from the presynaptic element. It is possible that dense-core vesicles contain T-bar proteins, probably BRP. When transport along the actin cytoskeleton is disrupted, the number of tetrad synapses decreases, and rapid AZ remodelling also fails (Damulewicz, 2020).

The above mentioned ultrastructural changes depend on the level of the presynaptic scaffolding protein BRP, which changes in abundance during the day and night. These changes are controlled by the daily expression of CRY, which seems to have many functions in photoreceptors in addition to being the circadian clock photoreceptor. In an earlier study, it was found that CRY interacts with BRP but only during light exposure and leads to the degradation of BRP during the day/light phase of the 24 h cycle. This seems to be responsible for the decrease in BRP level in the middle of the day after its peak at the beginning of the day. The lack of CRY in cry01 mutants changes the pattern of the tetrad presynaptic profile frequency during the day and the size of the T-bar. However, the rhythm is not completely abolished, which indicates that other proteins are also involved in the daily remodelling of tetrad synapses. Since CRY plays several functions in photoreceptors, changes in the number of tetrad synapse and T-bar size in cry01 may result from different processes and lack of interactions of CRY with TIM and BRP. CRY is a component of the molecular clock and interacts with TIM, and this may affect daily changes in the number and size of T-bars. In addition, light-activated CRY binds BRP and targets it to degradation. Previous work showed that flies with constitutively active CRY have low BRP level. In turn, cry01 mutants show changes in the pattern of BRP expression, with higher BRP level during the day (ZT4), at the time when wild-type flies have minimum of BRP expression. The pattern of BRP expression is similar to the pattern of daily changes in tetrad synapse number, so it is possible that the number of synapses or T-bar size is directly dependent on the amount of BRP which oscillates during the day. However, CRY in the retina photoreceptors binds also actin and is involved in the organization of phototransduction cascade of proteins in rhabdomeres38. This may be also involved in the regulation of T-bar structure. The differences in T-bar size of cry01 are shown at time when in Canton S CRY is active (during the day) or its level increases (ZT16). At the beginning of the night the level of CRY is very low, so there was no effect on T-bar structure and no difference between CS and cry01 was observed (Damulewicz, 2020).

The epithelial glial cells are important for many processes during phototransduction and in recycling neurotransmitters and other compounds during the night. Glia take up histamine and metabolize it to carcinin, which is next delivered to the photoreceptor terminals, and capitate projections are involved in this process. Activity of glial cells is also controlled by the circadian clock. During the night, glial cells seem to be more active than neurons to recycle neurotransmitters, and many proteins, including proteins of ion pumps, are found at higher concentrations at that time. The high number of synaptic vesicles near the tetrad T-bar during the morning peak of activity in Drosophila seems to depend on capitate projections invaginating from the epithelial glia to the photoreceptor terminals in the lamina of Drosophila (Damulewicz, 2020).

Although the presynaptic cytomatrix can be rapidly remodelled with transmission strength, it is also affected by motor and visual system activity, external factors, such as light in the case of the visual system, and the circadian clock, showing plasticity and correlation to changes in behaviour during the day/night cycle. As was shown in the present study synaptic plasticity and synapse remodelling during the day is a complex process which involves presynaptic proteins of the T-bar as well as two types of synaptic vesicles, clear and dense-core, and glial cells. It was also found that fast degradation of proteins involved in transmission is as important as pre- and postsynaptic protein synthesis (Damulewicz, 2020).

Protocerebral Bridge Neurons That Regulate Sleep in Drosophila melanogaster
Tomita, J., Ban, G., Kato, Y. S. and Kume, K. (2021). Front Neurosci 15: 647117. PubMed ID: 34720844

The central complex is one of the major brain regions that control sleep in Drosophila. However, the circuitry details of sleep regulation have not been elucidated yet. This study shows a novel sleep-regulating neuronal circuit in the protocerebral bridge (PB) of the central complex. Activation of the PB interneurons labeled by the R59E08-Gal4 and the PB columnar neurons with R52B10-Gal4 promoted sleep and wakefulness, respectively. A targeted GFP reconstitution across synaptic partners (t-GRASP) analysis demonstrated synaptic contact between these two groups of sleep-regulating PB neurons. Furthermore, it was found that activation of a pair of dopaminergic (DA) neurons projecting to the PB (T1 DA neurons) decreased sleep. The wake-promoting T1 DA neurons and the sleep-promoting PB interneurons formed close associations. Dopamine 2-like receptor (Dop2R) knockdown in the sleep-promoting PB interneurons increased sleep. These results indicated that the neuronal circuit in the PB, regulated by dopamine signaling, mediates sleep-wakefulness (Tomita, 2021).

Gustatory processing, pharynx, subesophageal zone, proboscis extension, and feeding extension

A neural circuit integrates pharyngeal sensation to control feeding
Yang, T., Yuan, Z., Liu, C., Liu, T. and Zhang, W. (2021). Cell Rep 37(6): 109983. PubMed ID: 34758309

Swallowing is an essential step of eating and drinking. However, how the quality of a food bolus is sensed by pharyngeal neurons is largely unknown. This study finds that mechanical receptors along the Drosophila pharynx are required for control of meal size, especially for food of high viscosity. The mechanical force exerted by the bolus passing across the pharynx is detected by neurons expressing the mechanotransduction channel NOMPC (no mechanoreceptor potential C) and is relayed, together with gustatory information, to IN1 neurons in the subesophageal zone (SEZ) of the brain. IN1 (ingestion neurons) neurons act directly upstream of a group of peptidergic neurons that encode satiety. Prolonged activation of IN1 neurons suppresses feeding. IN1 neurons receive inhibition from DSOG1 (descending subesophageal neurons) neurons, a group of GABAergic neurons that non-selectively suppress feeding. These results reveal the function of pharyngeal mechanoreceptors and their downstream neural circuits in the control of food ingestion (Yang, 2021).

Overconsumption is harmful for animals. Although the drive to ingest can be overwhelming for a hungry animal in the initial stage of a meal, inhibition becomes more dominant with the processes of food intake. This study found that food flowing across the pharynx accumulates the satiety state in the brain, demonstrating that multiple strategies are used by the nervous systems to avoid overeating. These pharyngeal sensory neurons are sensitive to sugar and mechanical force, serving as a flow meter that monitors food quality and amount so that the brain knows how much food is ingested even before the food reaches the intestine. This circuit may coordinate with other satiety signals, such as those conveyed by mechanical feedback from the intestine, to control feeding (Yang, 2021).

Gustatory and mechanosensory neurons are well separated on the fly labellum before their axons reach the SEZ, where they interact with each other to regulate the perception of food quality. In contrast, the sensory neurons in the pharynx seem to adapt a different coding mechanism. Some of the pharyngeal neurons are polymodal because they respond to chemical and mechanical stimuli, with PM neurons being an example. A 'generalist' versus 'specialist strategy has been found in other sensory organs too. Being able to evaluate multiple properties of a bolus in the pharynx allow the animals to effectively control the feeding amount. There are sensory neurons in the pharynx that may be tuned to gustatory or mechanosensory cues. For example, the R41E11-GAL4 and nompC-QF labeled approximately 10 pairs of neurons in LSOs along the pharynx, similar to the number observed for mechanosensory neurons. Most of those neurons are likely 'generalist' and are tuned to mechanical stimuli only. It would be valuable to determine the full repertoire of these sensory neurons to understand how the swallowing maneuver is initiated, sustained, and terminated (Yang, 2021).

It has been proposed that IN1 neurons may function as a key node of the feeding control circuits to govern rapid feeding decisions. Previous studies have revealed that IN1 neurons are directly downstream of pharyngeal GRNs and that activation of IN1 neurons to sugar stimulation is correlated with a fly's motivation to feed. Because activation of IN1 neurons triggers proboscis extension to food, they are likely upstream of the motor circuit that controls feeding. IN1 neurons thus appear to function as a hub that integrates sensory information to initiate food ingestion. This study found that IN1 neurons' activity is under control of the fly's feeding states. IN1 neurons are directly downstream of DSOG1 neurons that non-selectively suppress ingestion. In fed flies, DSOG1 neurons impart inhibition on IN1 neurons, resulting in a transient and moderate response to a sugar sip that triggers a robust and sustained calcium response in fasted flies (Yang, 2021).

It has been proposed that DSOG1 neurons impart constant inhibition on the neuronal circuits that initiate food ingestion. However, the upstream circuit of DSOG1 neurons has not been identified. A cohort of neuropeptide receptor genes has been screened, but none of them seemed to function on DSOG1 neurons in feeding control. This study found that interrupting signaling of the neuropeptide MIP phenocopied overfeeding in flies with silenced DSOG1 neurons. It is tantalizing to hypothesize that MIP neurons are upstream of the DSOG1 circuit, either directly or indirectly. Because the receptors of MIP have not yet been identified, further experiments are need to differentiate between the two possibilities (Yang, 2021).

Besides PM neurons, there are many NOMPC-expressing mechanosensory neurons along the fly pharynx. Because of the lack of specific driver lines and the technique to record a single neuron's activity during feeding, their roles in feeding regulation are interesting open questions and await in-depth investigation. Moreover, the receptors of MIP peptide have not been identified, especially the ones involved in feeding regulation, making it difficult to establish a connection between MIP neurons and DSOG1 neurons (Yang, 2021).

Classification and genetic targeting of cell types in the primary taste and premotor center of the adult Drosophila brain
Sterne, G. R., Otsuna, H., Dickson, B. J. and Scott, K. (2021). Elife 10. PubMed ID: 34473057

Neural circuits carry out complex computations that allow animals to evaluate food, select mates, move toward attractive stimuli, and move away from threats. In insects, the subesophageal zone (SEZ) is a brain region that receives gustatory, pheromonal, and mechanosensory inputs and contributes to the control of diverse behaviors, including feeding, grooming, and locomotion. Despite its importance in sensorimotor transformations, the study of SEZ circuits has been hindered by limited knowledge of the underlying diversity of SEZ neurons. This study generate a collection of split-GAL4 lines that provides precise genetic targeting of 138 different SEZ cell types in adult D. melanogaster, comprising approximately one third of all SEZ neurons. The single cell anatomy of these neurons was characterized, and they were found to cluster by morphology into six supergroups that organize the SEZ into discrete anatomical domains. The majority of local SEZ interneurons are not classically polarized, suggesting rich local processing, whereas SEZ projection neurons tend to be classically polarized, conveying information to a limited number of higher brain regions. This study provides insight into the anatomical organization of the SEZ and generates resources that will facilitate further study of SEZ neurons and their contributions to sensory processing and behavior (Sterne, 2021).

This study describes the SEZ Split-GAL4 Collection, a library of 277 split-GAL4 lines covering 138 SEZ cell types, which affords unprecedented genetic access to SEZ neurons for behavioral and functional study. These studies provide insight into the diversity of SEZ cell types and their organization into discrete anatomical domains. The SEZ Split-GAL4 Collection will enable further investigation of how local SEZ circuitry and ascending SEZ paths process sensory inputs and control specific behaviors (Sterne, 2021).

Most of the SEZ Split-GAL4 lines are specific, with 149/277 lines classified as ideal or excellent. These lines will be useful to manipulate individual SEZ cell types for behavioral, functional, and imaging experiments. The remaining, less specific, lines (those belonging to the good or poor categories) will still be useful for imaging and as starting points for creating more specific reagents. Good and poor lines may be used to generate CDM masks to search for new hemidrivers to make further split-GAL4 lines. Alternatively, their expression patterns may be refined using Killer Zipper or three-way intersections with LexA or QF lines. All lines in the SEZ Split-GAL4 Collection may be used to generate further tools including complementary split-LexA and split-QF reagents. Split-LexA and split-QF lines may be used in concert with the split-GAL4 lines reported here to simultaneously manipulate two independent neuronal populations for advanced intersectional experiments, including behavioral epistasis (Sterne, 2021).

By combining insights from a single-cell transcriptome atlas with direct cell counts of SEZ neuromeres, it is estimated that the SEZ Split-GAL4 Collection labels 30% of the ~1700 neurons in the SEZ. Because of the lack of stereotyped neuronal cell body positions in D. melanogaster, it is not possible to assign cell bodies to defined neuropil regions without a genetic marker. The advantage of this method of estimating SEZ neuron number is that it is based on analysis of the four genetically defined SEZ neuromeres, the tritocerebral, the mandibular, the maxillary, and the labial neuromeres. However, previous reports demonstrate that some deutocerebral commissures cross below the esophageal foramen, and therefore an unknown number of deutocerebral cell bodies may be part of the SEZ. The limitations of this estimate of SEZ neuron number therefore include the inability to directly count cells derived from the tritocerebral neuromere, the inability to directly count neurons rather than glia, and the inability to assess deutocerebral contributions. Thus, the estimate of SEZ cell number is likely an underestimate. Once all SEZ neurons are densely reconstructed in an EM volume, direct counts of SEZ neuronal cell bodies obtained by EM will provide a more accurate assessment of SEZ neuron number. Regardless, the SEZ Split-GAL4 Collection targets 510 neuronal cell bodies, which represents a substantial improvement in the ability to precisely target SEZ cell types for functional and morphological analysis. This study did not ascertain the neuromere or neuroblast of origin of the SEZ cell types in the SEZ Split-GAL4 Collection. However, recent work has established reliable anatomical criteria that define the boundaries between the four SEZ neuromeres and has mapped all secondary lineages of the SEZ. Future efforts should focus on bridging previously identified fascicle, neuropil, and sensory domains into a common template or coordinate space to determine the neuromere and neuroblast origin of SEZ cell types (Sterne, 2021).

Discovering and genetically targeting SEZ cell types required the use of registered light-level imagery and computer-assisted searching. Four distinct strategies were used to identify 129 novel and 9 previously reported SEZ cell types in registered light-level imagery. Critically, each of these strategies allowed use of CDM mask searching to identify additional hemidrivers with which to target each cell type of interest. CDM mask searching enabled combing of large datasets and greatly increased the ease and speed of split-GAL4 generation over previous methods. The same strategies can be leveraged to gain genetic access to yet-undiscovered SEZ cell types. The recent electron microscopy (EM) volumes of the D. melanogaster brain provide an avenue for identifying SEZ cell types that are not covered by the SEZ Split-GAL4 Collection. Notably, this approach awaits comprehensive reconstruction of the SEZ, a region that is not included in the recently published dense reconstruction of the 'hemibrain' volume. Another EM volume, 'FAFB,' provides imagery of an entire adult female fly brain at synaptic resolution and includes the SEZ. Improvements in automated reconstruction of EM volumes coupled with large-scale human annotation should soon provide exhaustive reconstruction of the SEZ from which to identify additional SEZ cell types. Furthermore, available bridging registrations between EM volumes and light-level imagery should facilitate the identification of hemidrivers to target SEZ cell types discovered from EM reconstructions. Even without identifying additional SEZ cell types, the split-GAL4 reagents described will allow behavioral and functional evaluation of circuit hypotheses derived from EM imagery (Sterne, 2021).

These analyses of the SEZ Split-GAL4 Collection provide insight into the cellular architecture of the SEZ. To computationally probe the organization of the SEZ, 121 SEZ cell types were morphologically clustered using NBLAST. This approach reveals six cellular domains in the SEZ that are organized in a largely layered fashion from anterior to posterior. This layered structure is also hinted at by the recent description of SEZ neuropil domains throughout development from the larva to the adult. Based on anatomical position and the known function of a few SEZ neurons, it is tempting to speculate that different morphological clusters may participate in different behavioral functions. Group 1 contains projection neurons that innervate the region of the SMP surrounding the pars intercerebralis (PI), suggesting that group 1 neurons may impinge on neurosecretory neurons or function in energy and fluid homeostasis circuits. The proximity of group 1 interneurons to previously described interoceptive SEZ neurons (ISNs) and ingestion neurons (IN1) supports this hypothesis. Group 2 contains Fdg, a feeding-related neuron, as well as cell types (indigo, tinctoria) that are located near pumping motor neurons, suggesting that group 2 neurons have roles in feeding sequence generation. Group 3 contains G2N-1, a candidate second-order gustatory neuron, and projection neurons that innervate recently described taste-responsive SLP regions, suggesting that group 3 may, in part, be composed of taste-responsive neurons. Many interneurons in group 4 are located near proboscis motor neurons that control rostrum protraction, haustellum extension, and labellar spreading, indicating that group 4 members function in proboscis motor control. The proximity of neurons in group 5 to previously described stopping neuron MAN, and the inclusion of an antennal grooming neuron, suggests that group 5 neurons may participate in circuits that control grooming and stopping behaviors. Group 6 is located in the posterior SEZ and posterior slope, regions implicated in flight behaviors, including wing and neck control. While potential behavioral functions are hypothesized for each supergroup, it is readily acknowledged that the roles of the neurons described in this study are likely more diverse (Sterne, 2021).

These studies also shed light on information flow both within the SEZ and out of the SEZ to the higher brain. 91 local interneurons, 30 projection neurons, 16 descending neurons, and 1 sensory neuron were identified. Polarity analysis of 121/138 of the SEZ cell types covered by the SEZ Split-GAL4 Collection revealed that SEZ interneurons tend to have mixed or biased polarity while SEZ projection neurons tend to be classically polarized. Polarity analyses of the lateral horn, mushroom body, descending neurons, and protocerebral bridge identified few neurons with completely mixed polarity. Unlike these brain regions, the SEZ contains a large number of local interneurons. The mixed polarity of the SEZ interneurons argues for local and reciprocal connectivity between neurons, with information flowing in networks rather than unidirectional streams. Projection neurons, in contrast, may serve chiefly to pass information from highly interconnected SEZ circuits to other brain regions in a unidirectional manner. Notably, many SEZ projection neurons were identified that innervate the SMP-a region known to contain neurosecretory cell types. This may betray a role for acute taste detection or feeding circuit activation in the regulation of hormone secretion. In addition, the frequent innervation of the superior lateral protocerebrum and lateral horn by SEZ projection neurons may hint at the site of olfactory-gustatory synthesis. In contrast, this study did not identify projection neurons that link the SEZ directly to the central complex or mushroom body. If dense reconstruction of EM volumes corroborates the lack of direct connectivity between the SEZ and these regions, information must be conveyed through indirect pathways. As an example, taste information influences local search behaviors during foraging, a task that is expected to involve the central complex. Indirect relay of taste information to the central complex to inform foraging behavior would be consistent with previous anatomical studies suggesting that the central complex receives diverse indirect sensory inputs. Furthermore, the mushroom body is known to respond to taste, raising the possibility that taste information from gustatory sensory neuron axons in the SEZ must be relayed through yet another brain region before reaching mushroom body cell types. Thus, this analysis of SEZ neuron polarity indicates local SEZ processing and demonstrates direct pathways to a subset of higher brain regions (Sterne, 2021).

Overall, the SEZ Split-GAL4 Collection represents a valuable resource that will facilitate the study of the SEZ. This analysis of the collection reveals the cellular anatomy and polarity of individual SEZ neurons and their organization into six discrete domains in the SEZ. Coupled with emerging insights from reconstruction of EM volumes, the SEZ Split-GAL4 Collection will allow the use of genetic dissection to test circuit-level hypotheses about sensory processing and motor control in the SEZ (Sterne, 2021).

Alteration in information flow through a pair of feeding command neurons underlies a form of Pavlovian conditioning in the Drosophila brain
Sakurai, A., Littleton, J. T., Kojima, H. and Yoshihara, M. (2021). Curr Biol. PubMed ID: 34352215

Pavlovian conditioning is a broadly used learning paradigm where defined stimuli are associated to induce behavioral switching. To define a causal relationship between activity change in a single neuron and behavioral switching, this study took advantage of a 'command neuron' that connects cellular function to behavior. To examine the cellular and molecular basis of Pavlovian conditioning, previous work identified a pair of feeding command neurons termed 'feeding neurons' in the adult Drosophila brain using genetic screening and opto- and thermo-genetic techniques. The feeding neuron is activated by sweet signals like sucrose and induces the full complement of feeding behaviors, such as proboscis extension and food pumping. Ablation or inactivation of the pair of feeding neurons abolishes feeding behavior, suggesting that this single pair of neurons is indispensable for natural feeding behaviors. This study describes a novel conditioning protocol to associate a signal-mediating rod removal from legs (conditioned stimulus [CS]) to feeding behavior induced by sucrose stimulation (unconditioned stimulus [US]). Calcium imaging of the feeding neuron demonstrated it acquires responsiveness to CS during conditioning, with inactivation of the feeding neuron during conditioning suppressing plasticity. These results suggest conditioning alters signals flowing from the CS into the feeding circuit, with the feeding neuron functioning as a key integrative hub for Hebbian plasticity (Sakurai, 2021).

This study demonstrate Pavlovian conditioning between tactile (CS) and gustatory (US) stimuli results in altered information processing by a pair of command neurons that control the Drosophila feeding circuit. This conditioning paradigm creates CS-induced excitement of the feeding neuron that commands feeding behavior in this animal, with the conditioned response requiring activity of the feeding neuron during pairing. Pioneering studies by Kandel and colleagues demonstrated the first synaptic and cellular mechanism underlying classical conditioning using the Aplysia gill withdrawal response. In Aplysia, the presynaptic terminal of a sensory neuron innervating the motor neuron was modulated by serotonin. Presynaptic modulation as a mechanism to generate Drosophila valence behaviors has been extensively studied, and recent progress indicates presynaptic terminals innervating mushroom body output neurons are modulated by dopaminergic neurons to establish Drosophila valence through appetitive and aversive olfactory association. Neither Aplysia plasticity nor Drosophila valence in these paradigms requires postsynaptic activity during learning. In contrast, Hebb proposed general principles to explain mechanisms for memory formation that better match results from commonly used mammalian experimental models, such as hippocampal long-term potentiation (LTP).Hebb postulated sequential firing of a presynaptic neuron and postsynaptic partner strengthens their connection. The requirement of feeding neuron activity for the conditioned response observed in this study fits well to a Hebbian mechanism if the underlying change is manifested in altered synaptic properties (although it cannot be excluded that inactivation of the feeding neuron and subsequent behavioral changes also alter neuromodulation, influencing memory formation). During association, CS-conveying neurons and the feeding neuron driven by sucrose stimulation would now fire together, resulting in strengthened connection between CS-conveying neurons and the feeding neuron according to a Hebbian mechanism. The response to US, however, did not change during conditioning, suggesting that connections between US-conveying neurons and the feeding neuron were not altered. Thus, one can hypothesize that the CS-feeding neuron circuit was newly established, whereas the pre-existing US-feeding neuron connection was not changed. These results suggest that Pavlovian conditioning is established through a change in information processing by the command neuron, which functions as the integrative hub of the feeding circuit (Sakurai, 2021).

This Pavlovian conditioning mechanism can also accommodate presynaptic modulation as demonstrated in Aplysia plasticity and Drosophila valence if reward signals are coupled to Hebbian plasticity through presynaptic neuromodulation. For Drosophila valance memory, reward signals consist of both sweet sensing and nutrition. Similar reward signals are likely to be relevant in vivo for Pavlovian conditioning, although the nutrition reward is eliminated in the current study due to removal of the esophagus from the preparation and application of a sucrose-wet paper strip only to the sensilla of the proboscis. Therefore, reward signals are likely constant between the groups that were tested, even for different US responses in the halorhodopsin experiments. Thus, differences in reward signal can be excluded from the altered conditioned responses observed between the groups. It is hypothesized that inactivation of the feeding neuron results in weaker memory due to postsynaptic activity in this neuron contributing to memory formation independent of changes in the reward signal. It is speculated that reward signals in the current model may also be mediated by dopamine, octopamine, or serotonin, similar to their role as reward signals in the mushroom bodies for Drosophila valence memory. In Aplysia, presynaptic adenylyl cyclase, which synthesizes cAMP, is believed to associate CS and US in this conditioning paradigm through US-driven serotonin modulation of the presynaptic terminal of the CS-conveying neuron. Adenylyl cyclase is encoded by rut, while dnc encodes a cAMP phosphodiesterase that degrades cAMP. As demonstrated in Aplysia and Drosophila, cAMP functions as a signal to modulate synaptic transmission. Given its role in LTP, cAMP is likely to play a critical role in Hebbian plasticity as well, consistent with the disruption of CS-US pairing in rut and dnc mutants. Considering the involvement of postsynaptic cells in Hebbian plasticity, retrograde signals from the postsynaptic cell can also be coupled to presynaptic cAMP signaling, as demonstrated previously at the Drosophila neuromuscular junction (Sakurai, 2021).

In the original experiment conducted by Pavlov, it is speculated there are groups of neurons that command feeding behavior in the dog. CS/US association may change responsiveness of a subset of those neurons that result in sound-induced saliva secretion, even in the absence of food signals. Electrophysiological studies have shown neural responses to CS are altered after Pavlovian conditioning in cat red nucleus and rabbit cerebellum, although how this kind of plastic change leads to alterations in command neuron function is unknown. Neurons with command function have been identified across many species. A command neuron is pivotally located within the sensorimotor watershed of a neuronal circuit and triggers a behavioral program after integrating numerous sensory inputs. Command neurons were first identified in crayfish through experiments where electrical stimulation of a certain neuron switched on or off behaviors, such as rhythmical movement of the swimmeret or escape responses. After identification of command neurons in invertebrate CNSs Mauthner cells were demonstrated to command escape behavior in fish. Recently, a group of neurons commanding feeding behavior have been identified in the mouse brain. Therefore, the scheme shown in Figure 4D may represent a common mechanism underlying Pavlovian conditioning across species, given the role of command neurons as an integrative hub within the sensorimotor watershed of neuronal circuits (Sakurai, 2021).

The feeding neuron in the Drosophila brain functions as a single command neuron pair that triggers the entire feeding program.3 This feature allowed reliable demonstration that CS-induced activation of the feeding neuron after conditioning was as robust as US-induced activation, suggesting the CS-induced activation of the feeding neuron can trigger the conditioned behavior. Thus, neurophysiological changes can be unambiguously correlated with behavioral change, making the causal relationship clear and allowing reliable manipulation. The current results are consistent with the assumption that both the CS signal and the US signal converge at a single identified neuron through a Hebbian mechanism. Taking advantage of the defined circuit with the feeding neuron at the center, it is not possible to define the cellular and molecular mechanisms for synaptic plasticity using this experimentally accessible neuron within the CNS. This approach, coupled with real-time live imaging, may allow tracking of changes in the structure or activity of identified synapses responsible for memory formation once CS-conveying neurons are defined in the experimental system. If so, it may be possible to directly observe pre- and/or postsynaptic changes mediating memory formation on the dendrite of the feeding neuron. Whether a new circuit is generated by strengthening a rudimentary pre-existing connection or a new connection forms de novo during associative conditioning will require future analysis. Molecular and cellular mechanisms underlying this plastic change can be investigated in detail as previously characterized at neuromuscular junctions. Taken together, the study of synaptic plasticity in the feeding neuron provides a model system to characterize basic principles of memory formation at the single-cell level (Sakurai, 2021).

A functional division of Drosophila sweet taste neurons that is value-based and task-specific
Chen, H. L., Motevalli, D., Stern, U. and Yang, C. H. (2022). Proc Natl Acad Sci U S A 119(3). PubMed ID: 35031566 4

Sucrose is an attractive feeding substance and a positive reinforcer for Drosophila. But Drosophila females have been shown to robustly reject a sucrose-containing option for egg-laying when given a choice between a plain and a sucrose-containing option in specific contexts. How the sweet taste system of Drosophila promotes context-dependent devaluation of an egg-laying option that contains sucrose, an otherwise highly appetitive tastant, is unknown. This study reports that devaluation of sweetness/sucrose for egg-laying is executed by a sensory pathway recruited specifically by the sweet neurons on the legs of Drosophila First, silencing just the leg sweet neurons caused acceptance of the sucrose option in a sucrose versus plain decision, whereas expressing the channelrhodopsin CsChrimson in them caused rejection of a plain option that was "baited" with light over another that was not. Analogous bidirectional manipulations of other sweet neurons did not produce these effects. Second, circuit tracing revealed that the leg sweet neurons receive different presynaptic neuromodulations compared to some other sweet neurons and were the only ones with postsynaptic partners that projected prominently to the superior lateral protocerebrum (SLP) in the brain. Third, silencing one specific SLP-projecting postsynaptic partner of the leg sweet neurons reduced sucrose rejection, whereas expressing CsChrimson in it promoted rejection of a light-baited option during egg-laying. These results uncover that the Drosophila sweet taste system exhibits a functional division that is value-based and task-specific, challenging the conventional view that the system adheres to a simple labeled-line coding scheme (Chen, 2022).

A neural circuit integrates pharyngeal sensation to control feeding
Yang, T., Yuan, Z., Liu, C., Liu, T. and Zhang, W. (2021). Cell Rep 37(6): 109983. PubMed ID: 34758309

Swallowing is an essential step of eating and drinking. However, how the quality of a food bolus is sensed by pharyngeal neurons is largely unknown. This study finds that mechanical receptors along the Drosophila pharynx are required for control of meal size, especially for food of high viscosity. The mechanical force exerted by the bolus passing across the pharynx is detected by neurons expressing the mechanotransduction channel NOMPC (no mechanoreceptor potential C) and is relayed, together with gustatory information, to IN1 neurons in the subesophageal zone (SEZ) of the brain. IN1 (ingestion neurons) neurons act directly upstream of a group of peptidergic neurons that encode satiety. Prolonged activation of IN1 neurons suppresses feeding. IN1 neurons receive inhibition from DSOG1 (descending subesophageal neurons) neurons, a group of GABAergic neurons that non-selectively suppress feeding. These results reveal the function of pharyngeal mechanoreceptors and their downstream neural circuits in the control of food ingestion (Yang, 221).

A closed-loop optogenetic screen for neurons controlling feeding in Drosophila
Lau, C. K. S., Jelen, M. and Gordon, M. D. (2021). G3 (Bethesda) 11(5). PubMed ID: 33714999

Feeding is an essential part of animal life that is greatly impacted by the sense of taste. Although the characterization of taste-detection at the periphery has been extensive, higher order taste and feeding circuits are still being elucidated. This study used an automated closed-loop optogenetic activation screen to detect novel taste and feeding neurons in Drosophila melanogaster. Out of 122 Janelia FlyLight Project GAL4 lines preselected based on expression pattern, this study identified six lines that acutely promote feeding and 35 lines that inhibit it. As proof of principle, R70C07-GAL4, which labels neurons that strongly inhibit feeding, was analyzed. Using split-GAL4 lines to isolate subsets of the R70C07-GAL4 population, both appetitive and aversive neurons were found. Furthermore, this study shows that R70C07-GAL4 labels putative second-order taste interneurons in the subesophageal zone that contact both sweet and bitter sensory neurons. These results serve as a resource for further functional dissection of fly feeding circuits (Lau, 2021).

Convergence of monosynaptic and polysynaptic sensory paths onto common motor outputs in a Drosophila feeding connectome
Miroschnikow, A., Schlegel, P., Schoofs, A., Hueckesfeld, S., Li, F., Schneider-Mizell, C. M., Fetter, R. D., Truman, J. W., Cardona, A. and Pankratz, M. J. (2018). Elife 7. PubMed ID: 30526854

This study reconstructed, from a whole CNS EM volume, the synaptic map of input and output neurons that underlie food intake behavior of Drosophila larvae. Input neurons originate from enteric, pharyngeal and external sensory organs and converge onto seven distinct sensory synaptic compartments within the CNS. Output neurons consist of feeding motor, serotonergic modulatory and neuroendocrine neurons. Monosynaptic connections from a set of sensory synaptic compartments cover the motor, modulatory and neuroendocrine targets in overlapping domains. Polysynaptic routes are superimposed on top of monosynaptic connections, resulting in divergent sensory paths that converge on common outputs. A completely different set of sensory compartments is connected to the mushroom body calyx. The mushroom body output neurons are connected to interneurons that directly target the feeding output neurons. These results illustrate a circuit architecture in which monosynaptic and multisynaptic connections from sensory inputs traverse onto output neurons via a series of converging paths (Miroschnikow, 2018).

Motor outputs of a nervous system can be broadly defined into those carried out by the muscles to produce movements and by the glands for secretion. Both of these behavioral and physiological events are regulated by a network of output neurons, interneurons and sensory neurons, and a major open question is how one neural path is selected from multiple possible paths to produce a desired output. Nervous system complexity and tool availability have strongly dictated the type of experimental system and analysis that can be used to address this issue, such as a focus on a particular organism, behavior or type of neuron. In this context, the detailed illustrations of different parts of nervous systems at neuronal level as pioneered by Cajal, to the first complete description of a nervous system wiring diagram at synaptic level for C. elegans, demonstrate the power of systematic neuroanatomical analysis in providing a foundation and guide for studying nervous system function. However, the technical challenges posed by such analysis have limited the type of organisms for which synaptic resolution mapping can be performed at the scale of an entire nervous system (Miroschnikow, 2018).

Analysis of the neural circuits that mediate food intake in the Drosophila larvae offers numerous advantages in meeting the challenge of neuroanatomical mapping at a whole brain level, and combining it with the ability to perform behavioral and physiological experiments. The muscle system that generates the different movements necessary for transporting food from the pharynx to the esophagus, as well as the endocrine system responsible for secreting various hormones for metabolism and growth, have both been well described. These are also complemented by the analysis of feeding behavior in adult flies. Although there is broad knowledge at the morphological level on the organs underlying larval feeding behavior and physiology, as well as on the nerves innervating them in the periphery, the central connectivity of the afferent and efferent neurons within these nerves are largely unknown. At the same time, advances in the EM reconstruction of an entire CNS of a first instar larva offers an opportunity to elucidate an animals' feeding system on a brain-wide scale and at synaptic resolution. As part of this community effort, an integrated analysis of fast synaptic and neuropeptide receptor connections for an identified cluster of 20 interneurons that express the neuropeptide hugin, a homolog of the mammalian neuropeptide neuromedin U, and which regulates food intake behavior. This analysis showed that the class of hugin neurons modulating food intake receives direct synaptic inputs from a specific group of sensory neurons, and in turn, makes mono-synaptic contacts to output neuroendocrine cells. The study not only provided a starting point for a combined approach to studying synaptic and neuropeptidergic circuits, but a basis for a comprehensive mapping of the sensory and output neurons that innervate the major feeding and endocrine organs (Miroschnikow, 2018).

Feeding is one of the most universal and important activities that animals engage in. Despite large differences in the morphology of the external feeding organs, the internal gut structures are quite similar across different animals; indeed, even within closely related species, there can be large differences in the external organs that detect and gather food, whereas the internal organs that transport food through the alimentary canal are much more similar. Recent studies have also pointed out the functional similarities between the subesophageal zone in insects and the brainstem in vertebrates for regulating feeding behavior. In mammals, the different cranial nerves from the medulla innervate distinct muscles and glands of the foregut (Figure 1A). For example, the VIIth cranial nerve (facial nerve) carries taste sensory information from anterior 2/3 of the tongue, and innervates the salivary glands, and lip and facial muscles. The IXth cranial nerve (glossopharyngeal nerve) receives taste inputs from the posterior 1/3 of the tongue, and innervates the salivary glands and pharynx muscles. The Xth cranial nerve (vagus nerve) receives majority of the sensory inputs from the enteric nervous system of the gut, and innervates pharynx and esophagus muscles. The XIth cranial nerve (spinal accessory nerve) and the XIIth cranial nerve (hypoglossal nerve) are thought to carry strictly motor information which innervate the pharynx and neck muscles, and the tongue muscles. The distinct cranial nerves project onto topographically distinct areas in the medulla of the brainstem. It is also noted that olfactory information is carried by cranial nerve I, a strictly sensory nerve that projects to the olfactory bulb (OB), an area topographically distinct from the brainstem. In addition, there are direct neuronal connections between the brainstem and the hypothalamus, the key neuroendocrine center of vertebrates (Miroschnikow, 2018).

Analogously, distinct pharyngeal nerves of the Drosophila larva are connected to the subesophageal zone (SEZ), and also carry sensory and motor information that regulate different parts of the body. The AN (antennal nerve) carries sensory information from the olfactory, pharyngeal and internal organs, and innervates the pharyngeal muscles for pumping in food. The serotonergic neurons that innervate the major endocrine center and the enteric nervous system also project through the AN. Note also that the olfactory sensory organs project to the antennal lobe (AL), which abuts the SEZ yet is topographically separate. The MxN (maxillary nerve) carries external and pharyngeal sensory information, and innervates the mouth hooks, whose movements are involved in both feeding and locomotion. The PaN (prothoracic accessory nerve) carries external sensory information from the upper head region, and innervates the muscles involved in head tilting (see EM reconstruction of the pharyngeal nerves of Drosophila larva). Furthermore, the SEZ has direct connections to median neurosecretory cells (mNSCs) and the ring gland. In sum, although a large body of knowledge exists on the gross anatomy of the nerves that target the feeding organs in vertebrates and invertebrates, the synaptic pathways within the brain that interconnect the sensory inputs and output neurons of the individual nerves remain to be elucidated (Miroschnikow, 2018).

This study has reconstructed all sensory, serotonergic modulatory (Se0) and motor neurons of the three pharyngeal nerves that underlie the feeding motor program of Drosophila larvae. The activity of these nerves has previously been shown to be sufficient for generating the feeding motor pattern in isolated nervous system preparations, and that the central pattern generators (CPGs) for food intake lie in the SEZ. All monosynaptic connections were identified between the sensory inputs and the motor, Se0 and previously described median neurosecretory ouput neurons, thus providing a full monosynaptic reflex circuit for food intake. Polysynaptic pathways that are integrated onto the monosynaptic reflex circuits. In addition, the multisynaptic non-olfactory neuron connections from the sensory neurons to the mushroom body memory circuit were also mapped, and these were shown to be different from those involved in monosynaptic reflex circuits. Finally, a set of mushroom body output neurons were traced onto the neurosecretory and other feeding output neurons. Reflex circuits can be seen to represent the simplest synaptic architecture in the nervous system, as formulated by Charles Sherrington. Anatomical reconstructions of monosynaptic and polysynaptic reflex circuits can also be seen in the works of Cajal. A model is proposed of how different mono- and polysynaptic pathways can be traversed from a set of sensory neurons to specific output neurons, which has relevance for understanding the mechanisms of action selection (Miroschnikow, 2018).

It was asked how the hugin neuropeptide circuit, which relays gustatory information to the protocerebrum, would be positioned with respect to the monosynaptic reflex and multisynaptic MB memory circuits. Based on earlier studies on mapping sensory inputs onto hugin protocerebrum neurons (huginPC), it was expected that most inputs from the ACp, which is the primary gustatory sensory compartment. However, most of the huginPC neurons receive inputs from the sensory compartments ACa and AVa, which are the two major monosynaptic compartments that originate from enteric regions. HuginPC neurons do receive inputs from the external and pharyngeal organs (i.e., through sensory compartment ACp), but to a much smaller degree. Thus, unlike the MB circuit that utilizes a completely new set of sensory inputs, the huginPC circuit is associated with a feeding related monosynaptic circuit (Miroschnikow, 2018).

Based on these observations from the hugin neuropeptide circuit in interconnecting sensory and neuroendocrine outputs, a broader question concerning input-output connections was asked: for any given pair of neurons comprising the monosynaptic reflex circuit, how many additional polysynaptic paths exist and what could be the functional significance of such parallel pathways? To illustrate, a target neuron was selected from a cluster of neurosecretory and serotonergic modulatory output cells (Dilps and Se0ens), and all sensory neurons that make monosynaptic connections with at least two synapses were listed listed. It was then asked, using the same threshold, how many different di-synaptic paths (2-hop) exist and how often a particular interneuron is used for the different possible converging paths ('degree' of convergence). The relative synaptic strengths of the connection among the various paths ('ranking index' of 1.0 represents highest synaptic strength from all possible inputs to the output neuron). Several properties are revealed: (1) different sensory neurons make monosynaptic contacts to a common output target (2) each output neuron can be reached from a given sensory neuron by multiple routes through the use of different interneurons (3) a given interneuron can receive inputs from different sensory neurons to target the same output neuron; this would fit the definition of the ‘common path’ that Sherrington described. These observations hold true for the majority of monosynaptic sensory-output pairs examined. However, no correlation was seen between the relative synaptic strength and the commonness of the respective paths (i.e., how often a path is used) (see Integration of polysynaptic connections onto monosynaptic circuits) (Miroschnikow, 2018).

This study provides a comprehensive synaptic map of the sensory and output neurons that underlie food intake and metabolic homeostasis in Drosophila larva. Seven topographically distinct sensory compartments, based on modality and peripheral origin, subdivide the SEZ, a region with functional similarities to the vertebrate brainstem. Sensory neurons that form monosynaptic connections are mostly of enteric origin, and are distinct from those that form multisynaptic connections to the mushroom body (MB) memory circuit. Different polysynaptic connections are superimposed on the monosynaptic input-ouput pairs that comprise the reflex arc. Such circuit architecture may be used for controlling feeding reflexes and other instinctive behaviors (Miroschnikow, 2018).

Reflex circuits represent a basic circuit architecture of the nervous system, whose anatomical and physiological foundations were laid down by Cajal and Sherrington. The Drosophila larval feeding reflex circuit comprises the motor neurons that innervate the muscles involved in pharyngeal pumping, as well as the neurosecretory neurons that target the endocrine organs. They also include a cluster of serotonergic neurons that innervate the entire enteric nervous system, and which may have neuromodulatory effects on the feeding system in a global manner. The vast majority of output neurons are targeted monosynaptically from a set of topographically distinct sensory synaptic compartments in the CNS. These compartments target the output neurons in overlapping domains: the first, ACa, targets all neuroendocrine cells as well as the serotonergic neurons; the second, AVa, targets a subset of neuroendocrine cells, the serotonergic neurons and most of the pharyngeal motor neurons, while the third, AVp, targets the serotonergic neurons and a different set of pharyngeal motor neurons. With these outputs, one can in principle fulfill the most basic physiological and behavioral needs for feeding: neurosecretory cells for metabolic regulation and pharyngeal motor neurons for food intake. This set of monosynaptic connections can thus be seen to represent an elemental circuit for feeding, since the connections between the input and output neurons cannot be broken down any further (Miroschnikow, 2018).

Vast majority of the sensory inputs comprising this 'elemental feeding circuit' derive from the enteric nervous system to target the pharyngeal muscles involved in food intake and neuroendocrine output organs. However, there is a small number of monosynaptic reflex connections that originate from the somatosensory compartment. The output neurons targeted by these somatosensory neurons are motor neurons that control mouth hook movements and head tilting, movements which are involved in both feeding and locomotion. In this context, it is noteworthy that monosynaptic reflex connections are found to a much lesser degree in the larval ventral nerve cord, which generates locomotion. An analogous situation exists in C. elegans, where majority of the monosynaptic reflex circuits are found in the head motor neurons and not in the body. One reason could be due to the relative complexity in the response necessary for food intake as compared to locomotion. For example, a decision to finally not to swallow a harmful substance, once in the mouth, may require a more local response, for example muscles limited to a very specific region of the pharynx and esophagus, where monosynaptic arc might suffice. By contrast, initiating escape behaviors requires a more global response with respect to the range and coordination of body movements involved, although it also employs multimodal sensory integration via a multilayered circuit (Miroschnikow, 2018).

The inter-sensory connections show a combination of hierarchical and reciprocal connections, which may increase the regulatory capability and could be especially important for monosynaptic circuits. By contrast, very few monosynaptic connections exist between the larval olfactory, chordotonal or nociceptive class IV sensory neurons in the body. Interestingly, there is also a much higher percentage of intersensory connections between olfactory receptor neurons in the adult as compared to the larva, which could function in gain modulation at low signal intensities. This might be attributable to adults requiring faster processing of olfactory information during flight navigation (or mating), and/or to minimize metabolic cost. Whether such explanation also applies to the differences in intersensory connection between the different types of sensory neurons in the larvae remains to be determined (Miroschnikow, 2018).

This study found very few cases where a monosynaptic path between any sensory-output pair is not additionally connected via a polysynaptic path. An interesting question in the context of action selection mechanism is which path a sensory signal uses to reach a specific target neuron. For example, a very strong sensory signal may result in a monosynaptic reflex path being used. However, a weaker sensory signal may result in using a different path, such as one with less threshold for activation. This would also enable the integration of different types of sensory signals through the usage of multiple interneurons, since the interneurons may receive sensory inputs that are not present in monosynaptic connections. For example, sensory neurons can target the neuroendocrine cells directly (monosynaptically), or through a hugin interneuron (di-synaptically). The sensory compartments that directly target the neuroendocrine cells are of enteric origin; however, when hugin neurons are utilized as interneurons, not only is the number of sensory neurons from the same sensory compartment increased, but sensory neurons are added from a completely new peripheral origin. Thus, the hugin interneurons enable sensory inputs from different peripheral origins, for example to integrate enteric inputs with pharyngeal gustatory inputs, to influence an output response, which, in this case, is to stop feeding (Schoofs et al., 2014a) (Miroschnikow, 2018).

The coexistence of polysynaptic and monosynaptic paths could also be relevant for circuit variability and compensation: destruction of any given path would still enable the circuit to function, but with more restrictions on the precise types of sensory information it can respond to. In certain cases, this may even lead to strengthening of alternate paths as a form of synaptic plasticit (Miroschnikow, 2018).

An open issue is how the sensory synaptic compartments might be connected to the feeding central pattern generators (CPGs) which have been demonstrated to exist in the SEZ, especially since CPGs are defined as neural circuits that can generate rhythmic motor patterns in the absence of sensory input. However, the modulation of CPG rhythmic activity can be brought about by sensory and neuromodulatory inputs. A complete circuit reconstruction of the larval SEZ circuit may shed some light on the circuit structure of feeding CPGs (Miroschnikow, 2018).

A more complex circuit architecture is represented by the MB, the site of associative learning and memory in insects: a completely different set of sensory synaptic compartments is used to connect the various projection neurons to the MB calyx. Thus, the MB module is not superimposed onto the monosynaptic reflex circuits but rather forms a separate unit. The classical studies by Pavlov demonstrated conditioned reflex based on an external signal and an autonomic secretory response in response to food. Although a comparable autonomic response has not been analyzed in the larvae, analogous associative behavior based on odor choice response has been well studied. It is also noteworthy that in the Aplysia, classical conditioning of the gill withdrawal reflex involves monosynaptic connections between a sensory neuron (mechanosensory) and a motor neuron, and neuromodulation by serotonin. This constellation has similarities with the elemental feeding circuit consisting of sensory, motor and serotonergic modulatory neurons. For more complex circuits of feeding behavior in the mouse, a memory device for physiological state, such as hunger, has been reported involving synaptic and neuropeptide hormone circuits. Functional studies on MB output neurons such as the MBON-f1, which may be part of a ‘psychomotor’ pathway and which targets a number of interneurons that connect to the neurosecretory, serotonergic and pharyngeal motor neurons, may help address how memory circuits interact with feeding circuits (Miroschnikow, 2018).

Feeding behavior manifests itself from the most primitive instincts of lower animals, to deep psychological and social aspects in humans. It encompasses cogitating on the finest aspects of food taste and the memories evoked by the experience, to sudden reflex reactions upon unexpectedly biting down on a hard seed or shell. Both of these extremes are mediated, to a large degree, by a common set of feeding organs, but the way these organs become utilized can vary greatly. The architecture of the feeding circuit described in this study allows the various types of sensory inputs to converge on a limited number of output responses. The monosynaptic pathways would be used when fastest response is needed. The presence of polysynaptic paths would enable slower and finer control of these reflex events by allowing different sensory inputs, strengths or modalities to act on the monosynaptic circuit. This can be placed in the context in the control of emotions and survival circuits, or by cortex regulation of basic physiological or autonomic processes. In a striking example, pupil dilation, a reflex response, has been used as an indicator of cognitive activity. Here, a major function of having more complex circuit modules on top of monosynaptic circuits may be to allow a finer regulation of feeding reflexes, and perhaps of other reflexes or instinctive behaviors (Miroschnikow, 2018).

As an outlook, this analysis provides an architectural framework of how a feeding circuit is organized in the CNS. The circuit is divided into two main axes that connect the input to the output systems: the sensory-neurosecretory cell axis and the sensory-motor neuron axis. The sensory system targets overlapping domains of the output neurons; for example, a set of sensory neurons targets exclusively the neuroendocrine cells, other targets both neuroendocrine and pharyngeal motor neurons, and another just the pharyngeal motor neurons. The inputs derive mostly from the internal organs. These connections form the monosynaptic reflex circuits. With these circuits, one can perform the major requirements of feeding regulation, from food intake and ingestion to metabolic homeostasis. Additional multisynaptic circuits, such as the CPGs, those involving sensory signaling from the somatosensory system (external inputs), or those comprising the memory circuits, are integrated or added to expand the behavioral repertoire of the animal see Input-output synaptic organization of the larval feeding system and its connectivity architecture in the brain. Although circuit construction may proceed from internal to the external, the sequence is reversed in a feeding animal: the first sensory cues are external (olfactory), resulting in locomotion (somatic muscles) that can be influenced by memory of previous experience; this is followed by external taste cues, resulting in food intake into the mouth; the final action is the swallowing of food, involving pharyngeal and enteric signals and reflex circuits. However, regardless of the types of sensory inputs, and whether these are transmitted through a reflex arc, a memory circuit or some other multisynaptic circuits in the brain, they will likely converge onto a certain set of output neurons, what Sherrington referred to as the ‘final common path’. The current work is a first step towards finding the common paths (Miroschnikow, 2018).

A pair of interneurons influences the choice between feeding and locomotion in Drosophila
Mann, K., Gordon, M. D. and Scott, K. (2013). Neuron 79: 754-765. PubMed ID: 23972600

The decision to engage in one behavior often precludes the selection of others, suggesting cross-inhibition between incompatible behaviors. For example, the likelihood to initiate feeding might be influenced by an animal's commitment to other behaviors. This study examined the modulation of feeding behavior in the fruit fly, Drosophila melanogaster, and identified a pair of interneurons in the ventral nerve cord that is activated by stimulation of mechanosensory neurons and inhibits feeding initiation, suggesting that these neurons suppress feeding while the fly is walking. Conversely, inhibiting activity in these neurons promotes feeding initiation and inhibits locomotion. These studies demonstrate the mutual exclusivity between locomotion and feeding initiation in the fly, isolate interneurons that influence this behavioral choice, and provide a framework for studying the neural basis for behavioral exclusivity in Drosophila (Mann, 2013).

The neurons that inhibit proboscis extension (which are named PERin) have cell bodies and processes in the first leg neuromeres of the VNC and projections to the SOG, the brain region that contains gustatory sensory axons and proboscis motor neuron dendrites. Labeling with the presynaptic synaptotagmin- GFP marker and the postsynaptic DenMark marker indicated that the dendrites of PERin neurons are restricted to the first leg neuromeres, whereas axons are found in both the SOG and the first leg neuromeres. The anatomy of these neurons suggests that they convey information from the leg neuromeres to a region of the fly brain involved in gustatory processing and proboscis extension. Anatomical studies examining the proximity of PERin fibers to gustatory sensory dendrites or proboscis motor axons revealed that PERin neurons do not come into close contact with known neurons that regulate proboscis extension (Mann, 2013).

Many behaviors are mutually exclusive, with the decision to commit to one behavior excluding the selection of others. This study shows that feeding initiation and locomotion are mutually exclusive behaviors and that activity in a single pair of interneurons influences this behavioral choice. PERin neurons are activated by stimulation of mechanosensory neurons and activation of PERin inhibits proboscis extension, suggesting that they inhibit feeding while the animal is walking. Consistent with this, leg removal or immobilization enhances proboscis extension probability and this is inhibited by increased PERin activity. The opposite behavior is elicited upon inhibiting activity in PERin neurons: animals show constitutive proboscis extension at the expense of locomotion. This work shows that activity in a single pair of interneurons dramatically influences the choice between feeding initiation and movement (Mann, 2013).

The precise mechanism of activation of PERin neurons remains to be determined. PERin dendrites reside in the first leg neuromere, suggesting that they process information from the legs. Stimulation of leg chemosensory bristles with sucrose or quinine or activation of sugar, bitter, or water neurons using optogenetic approaches did not activate PERin neurons, nor did satiety state change tonic activity. Stimulation of sensory nerves into the ventral nerve cord and stimulation of mechanosensory neurons, using a nompC driver, activated PERin. In addition, by monitoring activity of PERin while flies moved their legs, it was demonstrated that activity was coincident with movement (Mann, 2013).

These studies argue that PERin is activated by nongustatory cues in response to movement, likely upon detection of mechanosensory cues. Additional cues may also activate PERin. Studies of behavioral exclusivity in other invertebrate species suggest two mechanisms by which one behavior suppresses others. One strategy is by competition between command neurons that activate dedicated circuits for different behaviors. More common is a strategy in which decision- making occurs by distributed activity changes across neural populations. Although this studies are a starting point to begin to examine these models in Drosophila, the circuits for proboscis extension and locomotion drive different motor neurons, muscles, and behaviors, suggesting that they may be connected by a few links rather than largely overlapping circuitry. PERin is likely to inhibit feeding initiation while the animal is moving and is one critical link. The observation that simply gluing the proboscis in an extended state, but not in a retracted state, inhibits locomotion suggests that motor activity or proprioceptive feedback from the proboscis acts as a reciprocal link to locomotor circuits (Mann, 2013).

Neurons act over different timescales and in response to different sensory cues to influence behavior. The powerful molecular genetic approaches available in Drosophila enable the precise manipulation of individual neurons and allow for the examination of their function in awake, behaving animals. Modulatory neurons such as PERin are difficult to identify by calcium imaging or electrophysiological approaches because they influence gustatory-driven behavior but are not activated by gustatory stimulation. The ability to probe the function of neurons in unbiased behavioral screens facilitates the identification of neurons that act as critical nodes to influence behavior. The identification and characterization of PERin as a significant modulator of feeding initiation provides a foundation for future studies determining how PERin influences proboscis extension circuits to alter behavioral probability and how mechanosensory inputs activate PERin. In addition, examining how proboscis extension suppresses locomotion will provide important insight into the links between different behaviors (Mann, 2013).

Neural circuits for a given behavior do not work in isolation. Information from multiple sensory cues, physiological state, and experience must be integrated to guide behavioral decisions. This work uncovers a pair of interneurons that influences the choice between feeding initiation and locomotion. The discovery of the PERin neurons will aid in examining the neural basis of innate behaviors and the decision-making processes that produce them (Mann, 2013).

Mushroom Body, Circuits, and Learning

The anterior paired lateral neuron normalizes odour-evoked activity in the Drosophila mushroom body calyx
Prisco, L., Deimel, S. H., Yeliseyeva, H., Fiala, A. and Tavosanis, G. (2021). Elife 10. PubMed ID: 34964714

To identify and memorize discrete but similar environmental inputs, the brain needs to distinguish between subtle differences of activity patterns in defined neuronal populations. The Kenyon cells (KCs) of the Drosophila adult mushroom body (MB) respond sparsely to complex olfactory input, a property that is thought to support stimuli discrimination in the MB. To understand how this property emerges, the role was explored of the inhibitory anterior paired lateral (APL) neuron in the input circuit of the MB, the calyx. Within the calyx, presynaptic boutons of projection neurons (PNs) form large synaptic microglomeruli (MGs) with dendrites of postsynaptic KCs. Combining electron microscopy (EM) data analysis and in vivo calcium imaging, it was shown that APL, via inhibitory and reciprocal synapses targeting both PN boutons and KC dendrites, normalizes odour-evoked representations in MGs of the calyx. APL response scales with the PN input strength and is regionalized around PN input distribution. These data indicate that the formation of a sparse code by the KCs requires APL-driven normalization of their MG postsynaptic responses. This work provides experimental insights on how inhibition shapes sensory information representation in a higher brain centre, thereby supporting stimuli discrimination and allowing for efficient associative memory formation (Prisco, 2021).

Compartment specific regulation of sleep by mushroom body requires GABA and dopaminergic signaling
Driscoll, M., Buchert, S. N., Coleman, V., McLaughlin, M., Nguyen, A. and Sitaraman, D. (2021). Sci Rep 11(1): 20067. PubMed ID: 34625611

Sleep is a fundamental behavioral state important for survival and is universal in animals with sufficiently complex nervous systems. As a highly conserved neurobehavioral state, sleep has been described in species ranging from jellyfish to humans. Biogenic amines like dopamine, serotonin and norepinephrine have been shown to be critical for sleep regulation across species but the precise circuit mechanisms underlying how amines control persistence of sleep, arousal and wakefulness remain unclear. The fruit fly, Drosophila melanogaster, provides a powerful model system for the study of sleep and circuit mechanisms underlying state transitions and persistence of states to meet the organisms motivational and cognitive needs. In Drosophila, two neuropils in the central brain, the mushroom body (MB) and the central complex (CX) have been shown to influence sleep homeostasis and receive aminergic neuromodulator input critical to sleep-wake switch. Dopamine neurons (DANs) are prevalent neuromodulator inputs to the MB but the mechanisms by which they interact with and regulate sleep- and wake-promoting neurons within MB are unknown. This study investigated the role of subsets of PAM-DANs that signal wakefulness and project to wake-promoting compartments of the MB. PAM-DANs were found to be GABA responsive and required GABA(A)-Rdl receptor in regulating sleep. In mapping the pathways downstream of PAM (protocerebral anterior medial) neurons innervating γ5 and β'2 MB compartments it was found that wakefulness is regulated by both DopR1 and DopR2 receptors in downstream Kenyon cells (KCs) and mushroom body output neurons (MBONs). Taken together, this study has identified and characterized a dopamine modulated sleep microcircuit within the mushroom body that has previously been shown to convey information about positive and negative valence critical for memory formation. These studies will pave way for understanding how flies balance sleep, wakefulness and arousal (Driscoll, 2021).

The mushroom body lobes are tiled by discrete anatomic compartments defined by the axons of a specific subset of DANs and the dendrites of one or two mushroom body output neurons (MBONs). This anatomical arrangement positions DANs to strategically convey positive and negative reinforced information by changing the synaptic weight of KC-MBONs in producing aversive and appetitive responses (Driscoll, 2021).

While, the most in-depth analysis of these synapses and distinct DAN-KC-MBON connectivity and behavioral output comes from studies of olfactory conditioning, there is evidence that these synapses play a critical role in innate behaviors like feeding and sleep. Although, role of DA on sleep has been extensively investigated in Drosophila, the commonly used TH-Gal4 driver line labels most dopamine neuron clusters, but is absent from the several PAM clusters that projects to MB (Driscoll, 2021).

This study specifically probed PAM subsets that project to γ5, γ4, and β'2 MB compartments. This study focused on this subset because KCs and MBONs downstream of these PAM neurons can be neuroanatomically resolved and have been shown to be required for wakefulness. Further, KCs and MBONs that form the γ5, γ4, and β'2 synaptic compartments alter their spontaneous neural activity in response to sleep need (induced by mechanical sleep-deprivation). The ability to use cell-specific split-GAL4 tools provides opportunity to resolve the precise circuit mechanisms by which PAM neurons regulate wakefulness (Driscoll, 2021).

GABA signaling also modulates sleep and wake microcircuits within MB. The key source of GABA in the MB is anterior paired lateral neurons, APL and dorsal paired medial neurons (DPM), which are electrically coupled and increase sleep by GABAergic inhibition of wake-promoting KCs. In the context of associative learning, there is strong evidence for interactions between KCs, APL, DPM and DANs but it is not clear if GABA and dopamine signaling represent opposing inputs to the KCs and MBONs in the regulation of sleep. This study found that the excitability of PAM DANs involved in wakefulness is blocked by sleep-promoting GABA signaling and mediated by ionotropic receptor subtype GABAA-Rdl (Driscoll, 2021).

A recent study showed that GABA inhibitory input to the presynaptic terminals of the PAM neurons regulates appetitive memory and that this interaction is mediated by GABA-B3 receptors that are clustered in PAM boutons localized to PAM-γ5 and -α1 compartments. These data are consistent with the findings that PAM-γ5 are GABA responsive and that multiple receptors are critical to this interaction. Since, no role was found for GABA-B3 in PAM mediated sleep regulation, it is likely that PAM γ5, γ4, and β'2 express multiple GABA receptors which are differentially recruited in sleep and learning. How and what regulates the expression of these receptors in PAM subsets presents a potential mechanism of presynaptic gating to MB core circuits. Transcriptomic analysis of PAM neurons reveals extremely high levels of Rdl expression followed by GABA-B3. Among the PAM subsets mean TPM or transcripts per million of Rdl receptor in PAM γ5, γ4, and β'2 are much higher as compared to other PAM subsets (Driscoll, 2021).

Simple connection query search of the recently released hemibrain data85 reveals there is significant bidirectional connectivity between APL, DPM, and PAM neurons. Further, a recent study showed that APL neurons express the inhibitory D2R receptor55. APL mediated GABAergic inhibition of the PAM neurons was recently shown to control the intensity and specificity of olfactory appetitive memory but previous results show that blocking GABA release from APL neurons only modestly affects sleep phenotypes (Driscoll, 2021).

While, the role of APL in GABA signaling to PAM γ5, γ4, and β'2 cannot be completely ruled out, other inputs to wake-regulating PAM DANs could also be GABAergic and critical for promoting sleep. A recent study using EM dataset of a Full Adult Female Fly Brain (FAFB) mapped the inputs and outputs of the PAMγ5 DANs and identified that this cell type is highly heterogenous and in addition to recurrent feedback from MBON01 γ5β'2a, it receives extensive input from other MBONs, sub-esophageal output neurons (SEZONs) and lateral horn output neurons86. The EM data also reveals that octopaminergic neurons synapse onto PAM γ5, γ4, and β'2 DANs. Whether, these inputs play a role in wakefulness is unknown but suggests that the PAMγ5 could serve as a key link between sensory inputs, wake-promoting octopamine signal and core sleep regulating circuitry within the MB. Each of these inputs could modulate PAM-DAN activity and dopamine release in regulating wakefulness via the MB (Driscoll, 2021).

In addition to probing the release and activity of these PAM-DANs the dopamine receptors and their location within the MB in signaling wakefulness were also explored. To this end validated RNAi lines were expressed in subsets of KCs and MBONs; DopR1 and DopR2 were found to be critical in mediating the wakefulness signal via KCs and γ5β'2 MBONs. Knocking down the receptor consistently increased total sleep and bout length. Furthermore, specific manipulations of DopR receptors within the MB did not directly alter locomotor activity as observed by manipulation of these receptors in CX. Although, loss-of-function mutations of D1 dopamine receptor DopR are shown to enhance repetitive air puff startle-induced arousal and increase sleep. Expression and restoration of DopR in the mutant background specifically in the central complex rescues the startle response, while, the sleep phenotype is rescued via a broad MB driver. The current data extends these findings by showing that the DopR receptors regulate sleep via the MB γ5 and β'2 compartment. Although, targeted RNAi experiments show that DopR's are required for sleep regulation by KCs and MBONs, the lack of a sleep phenotype in DopR2 mutant could be a result of global loss of receptor in the mutant as opposed to targeted loss of receptor function within MB. Dopamine signals wakefulness by activation of wake-promoting neurons of MB via DopR1 and DopR2 and within. the central complex, neurons of dFB are inhibited by dopamine via DopR2. Hence, DopR2 has opposing effects within MB and CX (Driscoll, 2021).

In vitro characterization indicates that DopR's signal through distinct G-proteins, with DopR1 via Gαs to stimulate cAMP production and DopR2 coupling to Gαq via increased calcium. These receptors are thought to have differential sensitivity to dopamine and could be potentially recruited by varying DA release or DAN activity. In the context of sleep regulation, this work reveals that both DopR1 and DopR2 induce wakefulness via the γ5 β'2 MB compartment but not γ4 compartment. Although, chronic activation of PAM γ4 induces wakefulness, the glutamatergic MBON γ4 < γ1,2 projects to multiple compartments and could potentially activate or inhibit MBONs and PAMs projecting to γ1 and γ2 compartment. The interaction between compartments is not well understood in the context of sleep and wake regulation and requires further investigation to better understand the role of DopR2 in regulating the γ4 compartment. The neuroanatomical specificity obtained from split-Gal4 lines combined with EM data has paved way for more detailed analysis of the role of dopamine signaling to MB in the context of sleep and other behaviors (Driscoll, 2021).

The sleep-regulating PAM DANs and associated KCs and MBONs identified in this study are also involved in mediating satiety, novelty, caffeine induced arousal, punishment and reward associated experiences suggesting that the activity of these neurons is tuned to several wake and arousal associated behaviors. This is further supported by the EM connectome data showing that MB receives extensive gustatory, auditory and visual input in addition to olfactory input (Driscoll, 2021).

Current models of sleep regulation rely on two main processes, the circadian clock and the sleep homeostat and don't completely account for multiple external and internal factors that influence wakefulness. The ability to sleep, however, is influenced by motivational or cognitive stimuli. It is therefore envisioned that sleep, wakefulness and arousal within MB are not located in distinct circuits, but rather mediated by distinct processes within a common circuit (Driscoll, 2021).

Circuits for integrating learned and innate valences in the insect brain
Eschbach, C., Fushiki, A., Winding, M., Afonso, B., Andrade, I. V., Cocanougher, B. T., Eichler, K., Gepner, R., Si, G., Valdes-Aleman, J., Fetter, R. D., Gershow, M., Jefferis, G. S., Samuel, A. D., Truman, J. W., Cardona, A. and Zlatic, M. (2021). Elife 10. PubMed ID: 34755599

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. This study used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all Mushroom Body output neurons (encoding learned valences) and characterized their patterns of interaction with Lateral Horn neurons (encoding innate valences) in Drosophila larva. The connectome revealed multiple convergence neuron types that receive convergent Mushroom Body and Lateral Horn inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. Functional connectivity from LH and MB pathways and behavioral roles of two of these neurons was confirmed. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this it is speculated that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, this study provides insights into the circuits that integrate learned and innate valences to modify behavior (Eschbach, 2021).

Selecting whether to approach or avoid specific cues in the environment is essential for survival across the animal kingdom. Many cues have both innate valences acquired through evolution and learned valences acquired through experience that can guide action selection. Innate and learned valences are thought to be computed in distinct brain areas, but the circuit mechanisms by which they are integrated and by which learned valences can override innate ones are poorly understood. Using the tractable Drosophila larva as a model system, this study describes with synaptic resolution the patterns of convergence between the output neurons of a learning center (the MB) and an innately attractive pathway in the lateral horn (the LH). 62 neurons per brain hemisphere were identified that represent direct points of convergence between the MB and the LH, that fall into a number of different subtypes based on their patterns of MB and LH inputs and potentially encode a number of distinct features. One subtype of 10 convergence neurons (CNs) receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. Functional connectivity from LH and MB pathways and behavioral roles of two of these neurons were confirmed. These neurons encode integrated odor value (coding for positive value with an increase in their activity) and regulate turning. They are activated by an attractive odor, and when activated they repress turning. Conversely, when inactivated, they increase turning. Based on this, it is speculated that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. For one of these neurons, this study indeed verified that aversive learning skews inputs towards inhibition. Together, this study provides insights into the circuit mechanisms by which learned valences could interact with innate ones to modify behavior (Eschbach, 2021).

The brain areas that compute innate and learned valences of stimuli interact with each other, but despite recent progress, their patterns of interaction are not fully understood. In principle, MBONs could synapse directly onto LHNs thereby directly modifying innate valences. Alternatively, LHNs could directly synapse onto MBONs. Finally, learned and innate valences could initially be kept separate, and MBONs and LHNs could converge on downstream neurons. This study found that in Drosophila larva (1) some MBONs synapse directly onto some LHNs; (2) some MBONs received direct synaptic input from LHNs and (3) many MBONs and LHNs converge onto downstream CNs, similar to findings in the adult. One MBON (m1) was also a CN, receiving significant direct input from other MBONs and from LHNs. Overall, the architecture suggests some early mixing of representations of innate and learned valences, but to some extent these representations are also kept separate in the LH and MB, and then integrated by the downstream CNs. Maintaining some initial separation of representations of innate and learned valences prior to integration could offer more flexibility and independent regulation, for example by context or internal state. Convergence neurons could compute learned valence by comparing odor-drive to positive- and negative-valence MBONs (Eschbach, 2021).

The prevailing model of MB function in adult Drosophila proposes that in naive animals the odor drive to positive- and negative-valence MBONs is equal such that their outputs cancel each other out and the LH circuits guide olfactory behavior. Learning alters the overall output towards positive- or negative-valence MBONs by modifying specific KC-to-MBON connections. This model raises several important questions. First, how is the output from MBONs of opposite valence integrated to compute a learned valence? Second, how does it interact with the output of the LH. The current findings provide further support for this model and shed insight into these questions (Eschbach, 2021).

EM reconstruction combined with neurotransmitter information has revealed a class of 10 CNs that receive excitatory input from positive-valence MBONs and inhibitory input from negative-valence MBONs. These CNs are well poised to compute the learned odor valence by comparing the odor drive to positive- and negative-valence MBONs (Eschbach, 2021).

For two members of this class (MBON-m1 and CN-33), their MB drive was tested in untrained larvae, in vivo or in explants. On average, across the population of untrained individuals, KC activation did not induce a significant change in ∂F/F0 in either CN. However, it was found that in some individuals the MB drive onto the CNs was excitatory, and in others inhibitory, indicating that the MB can provide both excitatory and inhibitory drive to the CNs. Consistently, when inhibitory neurotransmission was blocked using PTX, MBON-m1 and CN-33 showed strong excitatory responses to KC activation (Eschbach, 2021).

High variability was observed in the responses of both CN-33 and MBON-m1 both to activation of the whole MB pathway, as well as to odor presentation. This variability may in part be due to technical reasons. Indeed, the variable responses to pan-KC optogenetic activation could be due to differences in CsChrimson expression in KCs across individuals (the expression of CsChrimson was verified for each individual recording but it was not quantified). However, such a difference is unlikely to be a reason for a range of responses that spans inhibition to excitation following the stimulation of the same neuronal population. Likewise, the exposure of the sensory organ to an odor may vary from one animal to the other depending on the location of the larva's head in the chip's channel. Together with other technical aspects, this may account for some of the variance observed in in vivo. Indeed, a decomposition of the variance within the datasets by ANOVA revealed a significant effect of the identity of the individual on the variance. Interestingly though, the inter-individual variability contributed to a higher fraction of the overall variance in odor response in larvae with functional MBs than in larvae with silenced MBs. This analysis suggests that the MB pathway is a significant source of variability in odor-evoked responses in MBON-m1 and CN-33 and is consistent with the highly variable responses of these CNs to direct KC activation. The variability in response of CNs to MB inputs across untrained individuals could be due to different experiences prior to these experiments, as suggested also by the fact that MBON-m1 responses to trained odors are modified with training. High variability in MBON responses to odor across individuals has previously also been observed in the adult flies and has been related to different individual experiences. The MBs can also compute other kinds of information, such as internal state which may modulate an individual's disposition toward sensory stimuli. Therefore, the average response across untrained individuals might be similar to the response of a single individual in a naive neutral state (with any interindividual differences averaged out across a population), and the variability may represent the degree of freedom for the MB to tune this response to a stimulus depending on previous experience or state (Eschbach, 2021).

How do the learned valences modify the innate ones? How is conflict between opposite innate and learned valences resolved during action selection? One possibility could involve the integration of conflicting signals into a unified representation of value, a notion similar to common currency valuation of options, which could then be used to promote or suppress specific actions. The findings suggest that the 10 CNs that can read out the learned valence by comparing MBON inputs of opposite valence also integrate the learned valence with the innate one. Thus, the 10 CNs that receive inhibitory input from negative-valence MBONs and excitatory input from positive-valence MBONs, also receive inputs from a positive-valence LHN pathway. These neurons are therefore well poised to compute an integrated odor value and code for a positive value with an increase in their activity. For two members of this class (MBON-m1 and CN-33) it was possible to confirm these predictions. This study has shown they are activated by an innately attractive odor via the LH pathway in untrained animals. Furthermore, when the innate attractiveness of an odor was reduced through aversive training, the activity of MBON-m1 was also reduced. Finally, it was shown that activating MBON-m1 and CN-33 represses turning, further supporting the idea that their activation encodes positive value. Interestingly, it was also found that a decrease in their activity promotes turning, raising the possibility that they could bi-directionally encode value, coding for negative value with a decrease in their activity (Eschbach, 2021).

In principle, a single CN of this type could potentially be sufficient to compute integrated odor value and regulate turning, but a population of 10 CNs with similar patterns of input from positive- and negative-valence pathways was found that likely operate partially redundantly with each other. Each CN also had unique aspects of connectivity, raising the possibility that they may also encode partially complementary features and that the integrated value could be distributed across the CN population (Eschbach, 2021).

Based on these findings the following model is proposed that could explain the way in which learning could modulate innate responses to odors through a population of integrative CNs: (1) In naive animals, the CNs are activated by innately attractive odors, mainly via the LH pathway (3) when activated these neurons repress turning, which enables crawling towards an attractive odor source; (3) in naive animals the net MB drive onto these CNs is close to 0; (4) aversive learning can skew the net MB output onto CNs towards inhibition, so that aversively-conditioned odor fails to activate these neurons; (5) if CNs are not activated, turning rate remains high when crawling towards the odor; (6) without sufficient suppression of turning by an odor, the animals' ability to approach the odor source is impaired. This proposed model could explain how aversive learning suppresses approach of innately attractive odors. To fully suppress approach, multiple CNs of this class would likely need to be silenced (Eschbach, 2021).

The model presented above could readily be extended to explain how appetitive learning could enhance odor approach and how strong aversive learning could switch innate odor approach to learned avoidance. Thus, appetitive learning could skew the net MB drive towards excitation thereby repressing turning even more. In contrast, strong aversive learning could skew the conditioned odor drive towards inhibitory negative-valence MBONs so much that the inhibition would become stronger than the excitatory LH drive. The CN would then be inhibited by the aversively conditioned odor. Since inhibition of CNs promotes turning, the aversively conditioned odor could promote odor avoidance by inducing turning. Consistent with this idea, inhibitory responses to the innately attractive odor were observed in MBON-m1 and in CN-33, in some untrained individuals, and strong excitatory responses in others, proving that odor drive onto CNs can range all the way from strong excitation to inhibition. Inhibition of MBON-m1 following aversive learning in the microfluidic device was not observed, but this could be because the animals did not form a very strong aversive memory under these conditions. Testing these proposed extensions of the model will require the future development of automated single-animal training assays and calcium imaging tracking microscopes to correlate the strength of the learned behavior with the conditioned-odor response of the CNs (Eschbach, 2021).

Finally, EM reconstruction did reveal a potentially opposite population of CNs that are inhibited by MBONs of positive value. It will be interesting to test in the future whether these neurons potentially encode negative value with an increase in their activity and positive value with a decrease in their activity and regulate turning in the opposite way: promoting turning when they are activated and repressing it when they are inhibited. Having two different populations of neurons that encode value in opposite ways could further increase the dynamic range of a distributed value code (Eschbach, 2021).

This study found that many of the CNs that receive input from both MBONs and LHNs also provide direct (including CN-33) or indirect (including MBON-m1) feedback to MB modulatory neurons that provide teaching signals for learning (n = 18). In a former study, it was shown that at least some of these feedback connections are functional and can influence memory formation. For example, CN-33/FAN-7 is capable of generating an olfactory memory when it is paired with an odor. This type of connectivity is consistent with learning theories that propose that future learning is influenced by predicted value computed based on prior learning. A major role of the CNs discovered in this study may therefore be not only to organize current actions, but also to regulate learning (Eschbach, 2021).

In summary, the comprehensive synaptic-resolution architecture of the circuits downstream of the learning center output neurons presented in this study is a valuable resource for constraining future modelling and function studies of value computation, action selection, and learning (Eschbach, 2021).

Response competition between neurons and antineurons in the mushroom body
Vrontou, E., Groschner, L. N., Szydlowski, S., Brain, R., Krebbers, A. and Miesenbock, G. (2021). Curr Biol. PubMed ID: 34610272

The mushroom bodies of Drosophila contain circuitry compatible with race models of perceptual choice. When flies discriminate odor intensity differences, opponent pools of αβ core Kenyon cells (on and off αβ(c) KCs) accumulate evidence for increases or decreases in odor concentration. These sensory neurons and "antineurons" connect to a layer of mushroom body output neurons (MBONs) which bias behavioral intent in opposite ways. All-to-all connectivity between the competing integrators and their MBON partners allows for correct and erroneous decisions; dopaminergic reinforcement sets choice probabilities via reciprocal changes to the efficacies of on and off KC synapses; and pooled inhibition between αβc KCs can establish equivalence with the drift-diffusion formalism known to describe behavioral performance. The response competition network gives tangible form to many features envisioned in theoretical models of mammalian decision making, but it differs from these models in one respect: the principal variables-the fill levels of the integrators and the strength of inhibition between them-are represented by graded potentials rather than spikes. In pursuit of similar computational goals, a small brain may thus prioritize the large information capacity of analog signals over the robustness and temporal processing span of pulsatile codes (Vrontou, 2021).

Two-alternative forced-choice tasks, in which a subject must commit to one of two alternatives, sometimes under time pressure and nearly always with uncertain information, are a commonly studied laboratory simplification of real-world decision making. The neural processes that culminate in a binary choice have been compared to the deliberations of a jury before a verdict: neurons, like jurors, gather evidence from witnesses over the course of a trial and then reconcile their divergent views in a majority vote (Vrontou, 2021).

The problem of how neural circuits implement this form of trial by jury has been approached in a range of species, from primates and rodents to fish and flies. A pioneering and influential body of work is built on a two-alternative forced-choice task in which monkeys distinguish directions of motion in a noisy random dot display. Recordings of correlated neuronal activity suggest that motion-sensitive neurons in the middle temporal visual area (MT or V5) provide momentary evidence that is temporally integrated in lateral intraparietal cortex (LIP) before passing an unspecified thresholding mechanism. Although the precise role attributed to LIP is a matter of debate, the principle that ephemeral sensory signals flow into integrators whose fill levels rise to a response threshold appears general; similar arrangements have been inferred to support visual motion discrimination in zebrafish and odor intensity discrimination in the fly (Vrontou, 2021).

In Drosophila, a rate-limiting integration step takes place in a particular group of third-order olfactory neurons. When flies decide on the direction of an odor concentration change, the membrane potentials of Kenyon cells (KCs) in the αβ core (αβc) division of the mushroom bodies drift noisily toward action potential threshold, just as accumulating evidence would drift toward a response bound. Consistent with the proposed correspondence of membrane voltage and integrated sensory information, and of action potential and decision thresholds, neurometric functions based on the average timing of the first odor-evoked spikes in the αβc KC population can account for the speed and accuracy of the decision-making animal; psychophysical estimates of noise in the decision process match the measured membrane potential noise of αβc KCs; and genetically targeted manipulations that alter the latencies of αβc KC spikes have the expected impact on reaction times (Vrontou, 2021).

Two functionally separate groups of αβc KCs, termed up and down or on and off cells, respond to increases or decreases in odor concentration and can therefore represent the strength of evidence for either of the two alternatives in the choice. This explicit representation of support for each of the competing hypotheses (as opposed to an aggregate representation of the extent to which one hypothesis is favored over the other) suggests that a decision involves a race between two integrators-one built from neurons that accumulate evidence for an increase in odor concentration and another composed of 'antineurons' that do the opposite. Changes in odorant receptor occupancy at the periphery alter the baseline activity of olfactory receptor neurons and the second-order projection neurons (PNs) with which they form receptor-specific glomerular channels. Large odor concentration changes in a channel's preferred direction drive high-frequency transmission from PNs to αβc KCs that promotes steep depolarizations to spike threshold and fast, accurate decisions, whereas small concentration changes in the preferred direction, or any change in the null direction, cause only a trickle of synaptic release; shallow, undulating membrane potential rises; and long spike delays that lead to slow, error-prone choices (Vrontou, 2021).

This study examined whether the circuitry downstream of αβc KCs is compatible with a model of two competing integrators. Three predictions of such a model were tested. First, to adjudicate the rival hypotheses advocated by on and off αβc KCs, mushroom body output neurons (MBONs) sampling the cores of the αβ lobes must listen to both. It is therefore expected that each core-innervating MBON is excited by increases as well as decreases in odor concentration. Second, as an animal learns the rules of the two-alternative forced-choice task-that an increase in odor intensity predicts imminent electric shock, whereas a decrease signals protection-the influence of αβc KCs championing the correct choice should be enhanced while that of proponents of the incorrect choice should be diminished. In other words, antagonistic changes are expected in the strengths of connections of on and off αβc KCs with the same action selection neurons if evidence for the competing alternatives is accumulated separately. Third, race models become equivalent to a drift-diffusion process-the formalism shown accurately to describe the psychophysics of the decision-making animal-only if they include an element of mutual or pooled inhibition to establish response competition between the integrators. Inhibition is needed to ensure that the integrators are anti-correlated so that evidence for one choice simultaneously counts as evidence against the other. This study therefore predicts the existence of inhibitory interactions between αβc KCs (Vrontou, 2021).

The idea that decisions are based on the accumulated spikes of oppositely tuned sensors was born in early attempts to unite psychophysical and neurophysiological measurements under the umbrella of signal detection theory. The recorded spike count distributions of direction-selective units in the monkey's area MT to motion in the preferred or null directions were taken to represent the responses of two neurons-the recorded neuron and its imagined antineuron conjugate-to movement in the neuron's preferred direction. The likely direction of motion can then be inferred as the probability that a draw from the neuron's response distribution yields a larger spike count than a draw from the antineuron's. At minimal motion strengths, when the two distributions are congruent, these odds are even and choices are random, but as the neuron responds ever more vigorously to increasingly coherent motion while the antineuron's response stays flat, the distributions unmix and the probability of a correct choice rises toward one. Comparing the spike counts of two sensors rather than thresholding the output of one removes shared sources of variation and with them the need of adjusting the discrimination threshold to achieve the best separation of the changing response distributions: a neuron-antineuron pair always returns a quantity proportional to likelihood ratio, the optimal hypothesis test. Although opponent sensory channels in one or another guise feature prominently in many decision-making models, their involvement in the brain is unproven: neurons and antineurons owe their status to each other, as inputs to comparator circuits, but these circuits remain uncharacterized (Vrontou, 2021).

This study draws back the curtain on one such circuit in the fly. Changes in odor intensity are registered by pools of on and off αβc KCs, which represent the strengths of the accumulated evidence for an increase or decrease in odor concentration. These pools of sensory neurons and antineurons couple to a second layer of neurons and antineurons, the core-innervating MBONs, which bias behavioral intent in opposite ways. Members of both neuronal pools in the sensory layer connect to both types of MBON in the action selection layer via plastic synapses. With two sets of neurons and antineurons and all-to-all feedforward connectivity between them, the comparator circuit allows for approach or avoidance following judgments of upward or downward changes in odor intensity-that is, it comprises neural pathways representing the possible contingencies seen behaviorally. The perceptual decision is won-correctly or incorrectly-by the αβc KC pool that reaches spike threshold first, and it is expressed in the behavior instructed by that pool's favored MBON partners (Vrontou, 2021).

Unlike neurons comprising the ON and OFF pathways of motion vision, on and off αβc KCs cannot be distinguished and manipulated genetically. This study has therefore exploited the sensitivity of KC-to-MBON synapses to the timing of reinforcement to reveal the convergence of separate on and off channels onto the same MBONs. KC-to-MBON synapses in their ground state exert finely balanced drive on the MBON ensemble, so that votes cast by its members cancel one another as in a hung jury, but experience can shift the synaptic weight distribution and the resulting pattern of MBON activation away from net zero. This study has documented such shifts for the approach-advocating MBON-γ1pedc>αβ: pairing odor on- or offset with electric shock weakens transmission from the on αβc KC pool and strengthens transmission from the off αβc KC pool (or vice versa), synergistically changing odor preference. The underlying mechanism is a switch from synaptic depression to synaptic potentiation when the order of odor-evoked KC activation and dopaminergic reinforcement is reversed. This mechanism operates at KC connections with all core-innervating MBONs but is likely engaged at different timescales that may reflect sequential memory phases; to demonstrate the mechanism's ubiquity, this temporal sequence was artificially collapsed by photostimulating DANs directly. Within the short time frame of these behavioral experiments, only PPL1-γ1pedc, but not PPL1-α'2α2, shows significant pain responses that modulate its sensitivity to a predictive odor, consistent with the view that PPL1-γ1pedc and its cognate MBON-γ1pedc>αβ represent the core circuit for the storage and expression of short-term aversive memories (Vrontou, 2021).

A crucial element of many neural network models of decision making is inhibitory feedback from a common interneuron pool driven by the competing integrators, which helps to amplify small differences in conflicting sensory evidence until, eventually, one integrator prevails. The response competition circuit this study has delineated contains such an inhibitory element but with the intriguing twist that the key variables are represented by membrane voltages rather than spikes. Analog processing may be a consequence of numerical constraints: if the mushroom bodies lack the neuron numbers needed to approximate continuous quantities with discrete-time action potentials, there may be little choice but to swap the advantages regenerative spikes could provide (such as long time windows for adding and retaining sensory evidence) for the greater information capacity of graded potentials. Perhaps more is different (Vrontou, 2021).

Circuit reorganization in the Drosophila mushroom body calyx accompanies memory consolidation
Baltruschat, L., Prisco, L., Ranft, P., Lauritzen, J. S., Fiala, A., Bock, D. D. and Tavosanis, G. (2021). Cell Rep 34(11): 108871. PubMed ID: 33730583 The formation and consolidation of memories are complex phenomena involving synaptic plasticity, microcircuit reorganization, and the formation of multiple representations within distinct circuits. To gain insight into the structural aspects of memory consolidation, this study focused on the calyx of the Drosophila mushroom body. In this essential center, essential for olfactory learning, second- and third-order neurons connect through large synaptic microglomeruli, which this study dissected at the electron microscopy level. Focusing on microglomeruli that respond to a specific odor, it was revealed that appetitive long-term memory results in increased numbers of precisely those functional microglomeruli responding to the conditioned odor. Hindering memory consolidation by non-coincident presentation of odor and reward, by blocking protein synthesis, or by including memory mutants suppress these structural changes, revealing their tight correlation with the process of memory consolidation. Thus, olfactory long-term memory is associated with input-specific structural modifications in a high-order center of the fly brain (Baltruschat, 2021).

The capacity to use past experience to guide future action is a fundamental and conserved function of the nervous system. Associative memory formation, initiated by the coincident detection of a conditioned stimulus (CS; e.g., odor) and an unconditioned stimulus (US; e.g., sugar reward), leads to a short-lived memory (STM) trace within distinct circuits. Memories can be consolidated into long-term memories (LTMs) through processes that depend on de novo protein synthesis, require structural modifications within the involved neuronal circuits, and might lead to the recruitment of additional ones. Compared with modulation of existing connections, the reorganization of circuits affords the unique possibility of sampling for potential new partners. Nonetheless, only few examples of rewiring associated with learning have been established thus far (Baltruschat, 2021).

The formation and retrieval of olfactory-associative memories in Drosophila require the mushroom body (MB). Within the main MB input compartment, the calyx (MBC), second-order projection neurons (PNs), delivers olfactory information through cholinergic synapses to the intrinsic MB neurons, the Kenyon cells. In the MBC, large, olfactory PN boutons are enwrapped by the claw-like dendrite termini of ∼11 KCs on average, thereby forming characteristic synaptic complexes, the microglomeruli (MGs), which display functional and structural plasticity in adaptation and upon silencing. To start systematically addressing the mechanisms that support memory consolidation, this study sought to investigate the properties of identifiable synaptic MGs in the MB of the adult brain of Drosophila after the establishment of LTMs (Baltruschat, 2021).

Combining behavioral experiments with high-resolution microscopy and functional imaging, this study demonstrates that the consolidation of appetitive olfactory memories closely correlates with an increase in the number of MGs formed by the PNs that deliver the conditioned stimulus and their postsynaptic KC partners. These structural changes result in additional, functional synaptic connections. Thus, the circuit in the calyx of the fly MB reorganizes accompanying the consolidation of associative memories (Baltruschat, 2021).

This study reports input-specific reorganization of the adult MBC circuit associated with the formation of long-term, appetitive memory. By visualizing presynaptic markers in PNs and the KC postsynaptic densities, this study uncovered an increase in the number of PN boutons and, at the same time, reveal that these boutons are enveloped by KC postsynaptic profiles, suggesting that new MGs are formed during memory consolidation. These findings are particularly remarkable, given the high degree of complexity of the MG microcircuits revealed by EM reconstruction and including the dendrite claws of multiple KCs of distinct subtypes. The cellular mechanisms leading to the increased number of odor-specific complex MGs remain to be clarified, but they will require a tight coordination between pre- and postsynaptic partners. In this context, mutations in synaptic proteins or in proteins mediating cell-cell interactions, which specifically block LTM, will be of great interest (Baltruschat, 2021).

It is suggested that remodeling could be driven by intrinsic reactivation of KCs during the consolidation phase or by modulatory inputs into the calyx. In either case, a complex pattern of activation is expected, that might be difficult to reproduce in artificial settings. Although the present observations are limited for technical reasons to the specific case of cVA, the overall density of PN boutons in the MBC increases after appetitive long-term conditioning in honeybees, as well as in leaf-cutting ants after avoidance learning. Based on that and given that the olfactory pathway of cVA is not distinguishable from that of other odors, it is thus suggested that the findings might be generalizable. In comparison with those systems, however, genetic and functional identification of PN subsets were used to reveal that the structural modifications are specific and limited to the PNs conveying the conditioned odor. Importantly, in vivo functional imaging data support the view that the circuit reorganization leads to additional functional MGs responding to the conditioned odor. In addition, they demonstrate a specific change in functional response in the KC dendrites toward the trained odor because the calcium levels drop faster toward baseline after appetitive associative conditioning. The faster decay kinetics and more skewed response toward the onset of the stimulus could contribute to a more-efficient temporal summation of responses or refine the KC response and might be related to inhibitory modifications. An important open question is the effect of the increased number of responding MGs on the pattern of KC activation. KCs respond sparsely to odor input and require the coincident activation of multiples of their claws to produce an action potential. The data might underlie the addition of connections between the active PNs and a set of already-responding KCs, leading to facilitated response to the conditioned odor without changing the set of responding KCs. A recent publication, however, suggests an exciting alternative view. After aversive LTM establishment, the number of KCs responding to the conditioned odor is increased (Delestro, 2020). If it is hypothesized that appetitive conditioning leads to a similar outcome, the data could provide anatomical and functional support to these findings. The pattern of KC response could, thus, be modulated by experience in adulthood and might represent a rich signifier of sensory stimulus and context. Reconstruction of an MG from EM serial sections derived from FAFB dataset (Baltruschat, 2021).

Coordination through Inhibition: Control of Stabilizing and Updating Circuits in Spatial Orientation Working Memory
Han, R., Huang, H. P., Chuang, C. L., Yen, H. H., Kao, W. T., Chang, H. Y. and Lo, C. C. (2021). eNeuro 8(5). PubMed ID: 34385152

Spatial orientation memory plays a crucial role in animal navigation. Recent studies of tethered Drosophila melanogaster (fruit fly) in a virtual reality setting showed that the head direction is encoded in the form of an activity bump, i.e., localized neural activity, in the torus-shaped ellipsoid body (EB). However, how this system is involved in orientation working memory is not well understood. This study investigated this question using free moving flies (D. melanogaster) in a spatial orientation memory task by manipulating two EB subsystems, C and P circuits, which are hypothesized for stabilizing and updating the activity bump, respectively. To this end, two types of inhibitory ring neurons (EIP and P) which innervate EB were suppressed or activated, and it was discovered that manipulating the two inhibitory neuron types produced distinct behavioral deficits, suggesting specific roles of the inhibitory neurons in coordinating the stabilization and updating functions of the EB circuits. The neural mechanisms underlying such control circuits were further elucidated using a connectome-constrained spiking neural network model (Han, 2021).

Maintaining spatial orientation is a crucial cognitive capability required for animal navigation, and understanding the detailed neural mechanisms of spatial orientation is of great interest to researchers in the fields of neurobiology or neuromorphic engineering. In recent years, significant progress has been made in identifying the neural circuits that support spatial orientation in the central complex of Drosophila melanogaster. The central complex has long been associated with short-term spatial memory, visual pattern memory, and motor control. The recent discoveries of head-direction selectivity and localized neural activity in two central complex neuropils, the ellipsoid body (EB) and the protocerebral bridge (PB), have also linked the central complex to the function of spatial orientation. These studies suggested that the head orientation is encoded by localized neural activity, called activity bump, and the bump location in EB shifts in accordance with changes of heading during movement. The function of the EB neurons resemble that of a compass and is, therefore, termed 'neural compass' (Han, 2021).

In light of these empirical observations, several neural circuit models of the central complex have been proposed to elucidate the neural circuit mechanisms of head-direction selectivity or other functions associated with the central complex. Some models focused on the stability of the activity bump or on the differences in the circuit dynamics between locus and fruit fly. Other models studied the plasticity involved in the flexible retinotopic mapping but used simpler firing rate models or schematic models. A large-scale firing-rate neural network model that covered the entire central complex was able to reproduce the steering and homing behavior of bees, but the EB circuits were rather simple with minimal details (Han, 2021).

Recently, a spiking-neuron model of the EB-PB circuits was proposed. The model used a more realistic spiking-neuron model and synaptic dynamics to elucidate how the circuits can maintain a stable activity bump when fruit flies switch between forward movement and rotation states in the absence of landmarks. The model suggested the involvement of two subcircuits: one forms an attractor network and maintains (or stabilizes) an activity bump; the other forms a shifter network and shifts (or updates) the bump position in accordance with changes in body orientation. The model successfully demonstrated the angular errors when a fly moved in darkness and predicted the asymmetric activity in the PB during rotation (Han, 2021).

The model made an important and unique prediction: the function of spatial orientation working memory requires coordinated activation of the bump-maintaining (or stabilizing) and bump-shifting (or updating) circuits that are controlled by the upstream ring neurons (Han, 2021).

However, most of the experimental studies used tethered flies in a virtual reality setting and focused on how manipulation of neurons affects the bump activity. It is not clear how these neurons, in particular those involved in stabilizing and updating the activity bump, play roles in cognition-relevant behavior such as spatial orientation memory in free-moving flies with a more realistic behavioral setting. This study aimed to address these questions and designed a behavioral task of spatial orientation working memory based on the classic Buridan's paradigm. Specifically, two types of GABAergic ring neurons were manipulated that are hypothesized to control these neurons. Ring neurons project their axons into EB and inhibit neurons including those display the activity bump. Previous studies have reported the roles of the ring neurons in visually-guided behavior, ethanol sensitivity, sleep regulation, olfactory memory and mating behavior. However, their roles in the working memory of spatial orientation in the presence or absence of visual cues remain unclear. In addition to the neural functional experiments, computer simulations were performed using the EB-PB model, which produced neural activities that were consistent with the behavioral changes observed in the fruit flies with different experimental conditions. The present study provides a detailed picture on how coordinated activation between the neural processes of stabilization and update plays a crucial role in spatial orientation working memory (Han, 2021).

It was hypothesized that the C circuit and P circuit in the EB circuits stabilize and update the orientation-encoding activity bump and they are regulated by corresponding GABAergic ring neurons. We tested this hypothesis by manipulating two types of GABAergic ring neurons in a spatial orientation working memory task with free moving fruit flies, and discovered manipulating each ring neuron type led to different behavioral abnormality. By performing computer simulations on a previously proposed EB-PB neural circuit model, it was possible to explain the results of the experiments and provided a picture of the neural circuit mechanism underlying spatial orientation working memory: the orientation-encoding bump is maintained through two alternately activated neural processes: one that stabilizes the position of the activity bump and one that updates the position of the bump. The former is activated when a fruit fly maintains a steady head direction and the latter is activated when the fly rotates its body. The control of this process is performed through specific GABAergic ring neurons. Therefore, overactivating or suppressing the ring neurons disrupts the alternation of the two processes and leads to incorrect or even loss of orientation memory (Han, 2021).

There are a few more interesting discoveries worth discussing. Performing fixation toward previous landmark directions requires two things to be remembered: the earlier event of the landmark presentation (what) and the directions of the landmarks (where). Flies that fail to remember the former would not exhibit the fixation behavior at all, while flies that forget the latter would still perform the fixation but toward incorrect directions. Discoveries of strong fixation but with large deviation from the true directions of the landmarks for flies with EIP-ring neuron suppression during the third stage may imply the segregation of the neural mechanisms of orientation memory regarding the 'where' and 'what' of a landmark (Han, 2021).

One interesting finding of the present study is a long duration of spatial orientation working memory during the poststimulus stage. Previous studies reported the occurrence of poststimulus fixation behavior that lasted only for a few seconds immediately following the offset of the landmarks. Indeed, this study observed that the flies tended to stop their movement a few seconds after the sudden disappearance of the landmarks in the third stage. But they usually resumed the movement in a few seconds. This might be the reason why earlier studies only claimed a few seconds of fixation if their analyses did not include the resumed movement. Further studies are needed to investigate this issue (Han, 2021).

A couple issues regarding the choice of molecular tools should be discussed. In the present study tub-GAL80ts was used in combination with UAS-Kir2.1 or UAS-TNT to suppress targeted ring neurons. The method involves raising the temperature 1 d before the behavioral experiments and therefore taking effects on a much longer time scale than using optogenetic tools. This long-term suppression may induce other effects at the cellular or circuit levels, which are beyond what the model can simulate. Further study may be required to carefully examine the long-term effects. An ideal solution is to transiently suppress the ring neurons using optogenetic tools such as UAS-NpHR (peak sensitivity wavelength ~589 nm) or GtACRs (peak sensitivity wavelength ~ 527 nm for GtACR1 and ~457 nm for GtACR2). However, the wavelength of the required activation light is within the visible range of the fruit flies. Preliminary tests on UAS-NpHR showed that the onset of the activation light seriously disrupted the fixation pattern of wild-type flies. A new optogenetic tool or a carefully re-designed optical system is required to transiently suppress targeted ring neurons while not interfering the visual experiments. The second issue is related to the GAL4 lines. In the present study only two most specific lines, c105-GAL4 and VT5404-GAL4, were used to target the EIP-ring and P-ring neurons, respectively. There are several other less specific GAL4 lines available for the two types of neurons. It is necessary to conduct the same experiments using these overlapping lines to further confirm the results presented in this study (Han, 2021).

Several other important questions remain to be addressed. Previous studies showed that EB does not maintain a fixed retinotopic map and a bump can start from a random location in the beginning of a trial. For the sake of modeling simplicity, this study did not model the random starting point feature in the model. But this feature is easy to implement and does not affect the conclusion of this study. A global excitation needs to be applied to the entire EB to reset the system. The excitation will induce strong competition between the EIP neurons and a new bump will start at a random location through the winner-take-all dynamics. Following this issue, random regeneration of an activity bump also needs to be discussed. The model showed that photoactivation of either EIP-ring or P-ring neurons during the poststimulus stage permanently abolished the activity bump. However, based on the observation of spontaneous generation of activity bump in other studies, the bump is likely to be regenerated at a random location after the offset of photoactivation. The regeneration can be easily implemented in the current model using the same mechanism described above. Since the regenerated bump starts from a random location, the fruit flies lose the reference to the landmark locations. Thus, adding a spontaneous bump or not both lead to the same conclusion: the files fail to fixate on the previous landmark locations. Although not affecting the conclusion of the present study, the spontaneous bump feature may be crucial in future studies that involve modeling of the steering mechanism (Han, 2021).

Another issue is that a couple experimental and modeling studies suggested that ring neurons provides the mechanisms underlying flexible retinotopic mapping in EPG (or EIP) neurons rather than the simple suppression/activation mechanism as hypothesized in the present study. However, the ring neurons (R2 and R4d) tested in one study are of different types from what was tested (R1 and R6) in this study. Additional experiments that measure the activities of R2 and R4d using the setups described in previous studies are required to clarify this issue (Han, 2021).

It is important to compare and discuss differences between computational models of the central complex in terms of the functions investigated in the present study. However, most models focused on different aspects of the compass circuit functions. The major difference from previous models is that they proposed that the PB intrinsic neurons as the main source of inhibition that regulates the attractor dynamics, while in the current model this function is conducted by the EIP ring neurons with two additional ring neuron types (C-ring and P-ring neurons) modulating different subcircuits of the system. An in-depth model comparison and experimental manipulation of PB intrinsic neurons and ring neurons under the present behavioral task may be able to clarify this issue (Han, 2021).

A final issue is related to the function of the activity bump which is commonly thought to represent the fly's sense of orientation in a manner similar to that of the head-direction system found in rodents. However, as aforementioned 'what' and 'where' mechanisms, performing the fixation behavior as an indication of orientation working memory may require several serial or parallel neural components beyond EB and PB. For example, how is this innate fixation behavior initiated (motivation)? When a fly stops fixating, it is not clear whether the fly forgets the landmark directions or simply enters a different behavior state (but still remembers the landmark directions). It also remains unclear whether the memory is stored in another neural circuit and the EB merely provides a reference frame for orientation, or whether the activity bump in the EB represents the actual memory of the landmarks. The current experimental setup is not able to address this issue. A novel task that can disassociate these two components is required for further investigation (Han, 2021).

The present study concludes the following. First, the experiment indicated that long-term suppression of EIP-ring neurons reduced the accuracy of orientation working memory (fixation with an increased deviation angle), whereas long-term suppression of P-ring neurons abolished the memory completely (no fixation). Similarly, transiently activating either ring neuron types in the absence of landmark immediately abolished the memory. Second, the experimental observation can be explained by the EB-PB neural circuit model in which the EIP-ring neurons are responsible for controlling the width of the bump and the P-ring neurons are responsible for shifting (updating) the position of the bump. Third, put the experiment and the theory together, the present study suggests that coordinated activation of the two ring neuron types which control the downstream EB-PB subcircuits is crucial for spatial orientation working memory (Han, 2021).

Predictive olfactory learning in Drosophila
Zhao, C., Widmer, Y. F., Diegelmann, S., Petrovici, M. A., Sprecher, S. G. and Senn, W. (2021). Sci Rep 11(1): 6795. PubMed ID: 33762640

Olfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. This study presents behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and two alternative models are suggested for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offers a framework to dissect MBON circuits and interpret DAN activity during olfactory learning (Zhao, 2021).

Predicting the future from sensory input is fundamental for survival. Co-appearing stimuli can be used for improving a prediction, or for predicting important events themselves, as observed in classical conditioning. In fruit fly odor conditioning, an odor that will become the conditioned stimulus (CS), is paired with the unconditioned stimulus (US), in this study an electroshock, that triggers an avoidance behavior and in internal representation of a negative value (valence). After conditioning, and the negative value representation (although not the full unconditioned response) previously elicited by the electroshock will be reproduced by the odor itself. Classical conditioning theories posit that throughout learning the odor becomes predictive for the electroshock. During learning, the prediction error decreases, and learning stops when the predictive odor value matches the strength of the electroshock (Zhao, 2021).

Predictive olfactory learning in fruit flies is a widely recognised concept in the experimental literature, and dopaminergic neurons (DANs) in the mushroom body (MB) have been suggested to predict punishment or reward. Yet, despite the acknowledgment of its predictive nature, computational models on fruit fly conditioning are mostly guided by the formation of associations, a notion that relates more to memories rather than predictions. Similarly, the concept of predictive learning is well recognized for olfactory conditioning in insects in general, but synaptic plasticity models are not formulated in terms of explicit predictions, but rather in terms associations and correlations, with plasticity being driven by two or three factors, each representing a temporal nonlinear function of the pre- or postsynaptic activities or of a modulatory signal, sometimes combined with homeostatic plasticity. This type of associative models exist for fruit flies, locusts or honey bees. They differ from target learning, where the unconditioned stimulus sets a target that is learned to be reproduced by the conditioned stimulus. Target learning becomes predictive learning when including a temporal component. It involves a difference operation, and learning stops when the target is reached. The stop-learning feature is difficult to be reproduced by purely correlation-based associative learning, while a purely predictive model also intrinsically captures associative properties (Zhao, 2021).

Associative learning was suggested to be implemented through spike- or stimulus-timing dependent plasticity (STDP) that would underlie conditioning. STDP strengthens or weakens a synapse based on the temporal correlation between the US (electroshock) and the CS (odor), both on the neuronal time scale of 10s of milliseconds and on the behavioral time scale of 10s of seconds. Whether an association is strengthened by just repeating the pairing until the behavioral saturation is reached, or the association saturates due to a faithful prediction, however, has not been investigated in the fruit fly so far. This study shows that olfactory conditioning in Drosophila is better captured as predictive plasticity that stops when a US-imposed target is reached, rather than by correlation-based plasticity, such as STDP, that does not operate with an explicit error or a target. According to this scheme, it is only the aversive/appetitive value of the US that is predicted by the CS after faithful learning, not the US itself. Based on the common value representation in the mushroom body output neurons (MBONs), the corresponding avoidance/approach reaction as one aspect of the unconditioned response is elicited by the CS alone (Zhao, 2021).

The Drosophila olfactory system represents a unique case for studying associative /predictive learning, and the MB is known to be essential in olfactory learning. The Kenyon cells (KCs) receive olfactory input from olfactory projection neurons and form a sparse representation of an odor. The parallel axons of the Kenyon cells (KCs) project to the MB lobes, along which the compartmentalized dendritic arbors of the MB output neurons (MBONs) collect the input from a large number of KCs. Reward or punishment activates specific clusters of DANs PAM and PPL1, respectively which project to corresponding compartments of the MB lobes, modulating the activity of the MBONs and the behavioral response. Recently, a detailed mapping of the MB connectome has been accomplished for larvae and of the vertical lobe for the adult Drosophila. Several studies show that not only the feedforward modulation from DANs to MBONs, but also the feedback from MBONs to DANs play an important role in olfactory learning (Zhao, 2021).

Previous studies have given insights into the possible cellular and subcellular mechanisms of olfactory conditioning. Yet, the suggested learning rules remain correlation-based and miss the explicit predictive element postulated by the classical conditioning theories. This study presents distinctive conditioning experiments showing that olfactory learning is best explained by predictive plasticity. These experiments, in contrast, could not be reproduced by various types of correlation-based associative learning rules. A mathematical model captures the new and previous data on olfactory conditioning, including trace conditioning. The model encompasses the odor/shock encoding and the learning of the aversive odor value with the stochastic response. It is further suggested how the predictive plasticity could be implemented in the MB circuit, with MBONs encoding the value ('valence') of the odor stimulus, and DANs calculating either the error or the target that drives the KC-to-MBON plasticity. The predictive plasticity rule for the KC-to-MBON synapses is shown to be consistent with the experimental results showing the involvement of these synapses in the novelty-familiarity representation (Zhao, 2021).

This study has reconsidered classical odor conditioning in the fruit fly and presents experimental and modeling evidence showing that olfactory learning, also on the synaptic level, is better described as predictive rather than associative. The key observation is that repetitive and time-continuous odor-shock pairing stops strengthening the conditioned response after roughly 1 minute of pairing, even if the shock intensity is below the behavioral saturation level. During conditioning, the odor is learned to predict the co-applied shock stimulus. As a consequence, the odor-evoked avoidance reaction stops strengthening at a level that depends on the shock strength, irrespective of the pairing time beyond 1 min. Associative synaptic plasticity, defined by a possibly nonlinear function of the CS-US correlation strength, as suggested by STDP models, fails to reproduce the early saturation of learning (Zhao, 2021).

A simple phenomenological model for predictive plasticity is suggested according to which synapses change their strength proportionally to the prediction error. This error is expressed as a difference between the internal shock representation and the value representation of the odor. The model encompasses a description of the shock and value representation, the stochastic response behavior of individual flies, and the synaptic dynamics (using a total of 5 parameters). It faithfully reproduces the conditioning experiments (with a total of 28 data points from 3 different types of experiments) as well as previously studied trace conditioning experiments (without need for further fitting). As compared to the associative rules (Hebbian, linear and nonlinear STDP, covariance rule), the predictive plasticity rule obtained the best fits with the least number of parameters. The model was further compared by the Akaike information criterion that considers the number of parameters beside the fitting quality. This criterion yields a likelihood for the predictive plasticity rule to be the best one that is at least 7 orders of magnitude larger as compared to the other four associative rules considered (Zhao, 2021).

The same phenomenological model of predictive learning may be implemented in two versions by the recurrent MB circuitry. In both versions the MBONs code for the odor value ('valence') that drives the conditioned response. For the error-driven predictive plasticity, the DANs directly represent the shock-prediction error by comparing the shock strength with its MBON estimate, and this prediction error modulates the KC-to-MBON plasticity (see Suggested implementation of error- and target-driven predictive plasticity). For the target-driven predictive plasticity, the DANs represent the shock stimulus itself that is then provided as a target for the KC-to-MBON plasticity. In this target-driven predictive learning, the DANs may also learn to predict the shock stimulus based on the MBON feedback, preventing a fast extinction of the KC-to-MBON memory (Zhao, 2021).

Predictive plasticity for both types of implementation has its experimental support. In general, MBON activity is well recognized to encode the aversive or appetitive value of odors and to evoke the corresponding avoidance or approach behavior, while KC-to-MBON synapses were mostly shown to undergo long-term depression, but also potentiation. DAN responses are shown to be involved in both the representation of punishment and reward that drive the aversive or appetitive olfactory conditioning. This conditioning further involves the recurrent feedback from MBONs to DANs that may be negative or positive. Moreover, the connectome from the larvae and adult fruit fly MBON circuit reveals feedback projections from DANs to the presynaptic side on the KC and the postsynaptic side on the MBONs at the KC-to-MBON synaptic connection giving different handles to modulate synaptic plasticity (Zhao, 2021).

With regard to the specific implementations, the error-driven predictive plasticity is consistent with the observation that DAN activity decreases during the conditioning. The two models have opposite predictions for learning while blocking MBON activity. The error-driven predictive plasticity would yield a higher learning index (LI) while the target-driven predictive plasticity would yield a lower LI. It was also shown that some DANs increased their activity with learning while other DANs, in the same PPL1 cluster that is supposed to represent aversive valences, decreased their activity. In fact, error- and target-driven predictive plasticity may both act in concert to enrich and stabilize the representations. DAN activity would decrease in those DANs involved in error-driven predictive plasticityand increase in those involved in target-driven predictive plasticity (Zhao, 2021).

While error-driven predictive plasticity offers access to an explicit error representation in DANs, target-driven predictive plasticity has its own merits. If DANs and MBONs code for similar information, they can support a positive feedback-loop to represent a short-term memory beyond the presence of an odor or a shock, as it was observed for aversive valences in PPL1 DANs and for appetitive PAM DANs. A positive feedback-loop between MBONs and DANs is further supported by the persistent firing between these cells after a rejected courtship that may consolidate memory of the rejection, linked to a specific pheromone (Zhao, 2021).

Target-driven plasticity has further functional advantages in terms of memory retention time. Any odor-related input to the DANs, arising either through a forward hierarchy from KC48 or a recurrence via MBONs to the DANs, will extend the memory life-time in a 2-stage prediction process: the unconditioned stimulus (s) that drives the DAN activity (d) to serve as a target for the value learning in the MBONs via KC-to-MBON synapses, will itself be predicted in the DANs. Extending the memory life-time through circuit plasticity might be attractive under the light of energy efficiency, showing that long-term memory in a synapse involving de novo protein synthesis can be costly, while cheaper forms of individual synaptic memories likely have limited retention times. Moreover, distributed memory that includes the learning of an external target representation offers more flexibility, including the regulation of the speed of forgetting (Zhao, 2021).

Target-driven predictive plasticity may also explain the novelty-familiarity representation observed in the recurrent triple of KCs, DANs and MBONs. The distributed representation of valences allows for expressing temporal components of the memories. Spontaneous activity in the KCs and their downstream cells injures a minimal strength of the KC-to-MBON synapses through predictive plasticity. A novel odor that drives KCs will then also drive MBONs and, to a smaller extent (as is assumed in this study), also DANs. If the DANs that represent the target for the KC-to-MBON plasticity are only weakly activated by the odor, the KC-to-MBON synapses learn to predict this weaker activity and depress. The depression results in a repetition suppression of MBONs and the corresponding familiarization of the fly to the ongoing odor. However, when the odor is cleared away, the MBON activity induced by spontaneously active KCs via depressed synapses now becomes lower than the spontaneous DAN activity, and predictive plasticity recovers the original synaptic strength. Eventually the spontaneous MBON and DAN activites match again and the response to the originally novel odor is also recovered, as seen in the experiment (Zhao, 2021).

Olfactory learning is likely distributed across several classes of synapses in the MB. The acquisition of olfactory memories was shown to be independent of transmitter release in KC-to-MBON synapses, although the behavioral recall of these memories required the intact transmission. In fact, learning may also be supported by plasticity upstream of the MBONs such that the effect of blocking KC-to-MBON transmission during learning is behaviorally compensated. Predictive plasticity at the KC-to-MBON synapses requires the summed synaptic transmissions across all synapses to be compared with the target d, also during the memory acquisition. This type of plasticity would therefore be impaired by blocking the release (Zhao, 2021).

Distributed learning also offers flexibility in acquiring predictions from new cues. While the original Rescorla-Wagner rule would predict blocking, this has not been observed in the fruit fly. Blocking refers to the phenomenon that, if the first odor of a compound-CS is pre-conditioned, the second odor of the compound will not be learned to become predictive for the shock. Because the predictive plasticity rules are expressed at the neuronal but not at the phenomenological level, predictions about blocking will depend on the neuronal odor representation. If the two odors activate the same MBONs, blocking would be observed since the MBONs are already driven to the correct value representation by the first odor. If they activate different MBONs, however, blocking would not be observed since the MBONs of the second odor did not yet have the chance to learn the correct value during the first conditioning. Hence, since blocking has not been observed in the fruit fly, it is postulated that the odors of the compound-CS in these experiments were represented by different groups of MBONs (Zhao, 2021).

How does this model relate to the concentration-specificity and the timing-specifity of odor conditioning? First, olfactory learning was found to be specific to the odor concentration, with different concentrations changing the subjective odor identity. The response behavior was described to be non-monotonic in the odor intensity, with the strongest response for the specific concentration the flies were conditioned with. It was suggested that this may arise from a non-monotonic odor representation in the KC population as a function of odor intensity. Given such a presynaptic encoding of odor concentrations, the predictive olfactory learning in the KC-to-MBON connectivity would also inherit the concentration specificity from the odor representation in the KCs. This predictive plasticity, and also the Rescorla-Wagner model, further predicts that learning with a higher odor concentration (but the same electroshock strength) only speeds up learning, but would not change the asymptotic performance (Zhao, 2021).

Second, olfactory conditioning was also shown to depend on the timing of the shock application before or after the conditioning odor. While a shock application 30s after an odor assigns this odor an aversive valence, an appetitive valence is assigned if the shock application arises 30s before the odor presentation. Modeling the approaching behavior in the context of predictive plasticity would require duplicating this model to also represent appetitive valences, and the action selection would depend on the difference between aversive and appetitive valences. Inverting the timing of CS and US may explain 'relief learning' if a stopping electroshock would cause a decrease of the target for aversive MBONs and an increase of the target for appetitive MBONs. An odor presented after the shock would then predict the increased appetitive target and explain the relief from pain behavior, similar to the model of relief learning in humans (Zhao, 2021).

Overall, these behavioral experiments and the plasticity model for the KC-to-MBON synapses support the notion of predictive learning in olfactory conditioning, with the DANs representing either the CS-US prediction error or the prediction itself. While predictive coding is recognized as a hierarchical organization principle in the mammalian cortex that explains animal and human behavior it may also offer a framework to investigate the logic of the MB and the multi-layer MBON readout network as studied by various experimental work (Zhao, 2021).

Transsynaptic mapping of Drosophila mushroom body output neurons
Scaplen, K. M., Talay, M., Fisher, J. D., Cohn, R., Sorkac, A., Aso, Y., Barnea, G. and Kaun, K. R. (2021). Elife 10. PubMed ID: 33570489

The mushroom body (MB) is a well-characterized associative memory structure within the Drosophila brain. Analyzing MB connectivity using multiple approaches is critical for understanding the functional implications of this structure. Using the genetic anterograde transsynaptic tracing tool, trans-Tango, this study identified divergent projections across the brain and convergent downstream targets of the MB output neurons (MBONs). This analysis revealed at least three separate targets that receive convergent input from MBONs: other MBONs, the fan-shaped body (FSB), and the lateral accessory lobe (LAL). A multilayer circuit is described, both anatomically and functionally, in which inhibitory and excitatory MBONs converge on the same genetic subset of FSB and LAL neurons. This circuit architecture enables the brain to update and integrate information with previous experience before executing appropriate behavioral responses. This use of trans-Tango provides a genetically accessible anatomical framework for investigating the functional relevance of components within these complex and interconnected circuits (Scaplen, 2021).

The MB is a high-level integration center in the Drosophila brain with an established role in learning and memory. The iterative nature of converging and diverging MB neural circuits provides an excellent example of the anatomical framework necessary for complex information processing. For instance, on a rapid timescale, interactions between MB compartments could generate different output patterns to drive behavior, whereas on a slower timescale, interactions between MB compartments could reevaluate memories of a context (Scaplen, 2021).

This study sought to map the projections from the MB using the genetic anterograde transsynaptic technique, trans-Tango. The connectivity of MBONs is reported across multiple subjects in both males and females and the variability in connectivity is highlighted that potentially exists across animals. This study complements the ongoing efforts of EM reconstruction of a whole brain of a single female fruit fly and confirms previous anatomical predictions. Although the complete EM dataset of an adult fly brain has been an invaluable resource that significantly accelerated the mapping of the neural circuits underlying innate and learned behaviors, the massive undertaking of acquiring a full EM dataset renders it impractical to perform for multiple individuals. Thus, trans-Tango, expands the value of the EM reconstruction data by examining circuit connectivity across multiple individuals. Further, trans-Tango can be readily adapted to functional studies in which the activity of the postsynaptic neurons is altered by expressing optogenetic/thermogenetic effectors or monitored by expressing genetically encoded sensors. Tracing studies reported in this study serve as the foundation for these future experiments (Scaplen, 2021).

These studies reveal that the MB circuits are highly interconnected with multiple regions of converging projections both within and downstream of the MB. These experiments also show diverging projections in the downstream postsynaptic targets. A multilayer circuit is identified that includes GABAergic and cholinergic MBONs that converge on the same subset of FSB and LAL neurons. This circuit architecture allows for rapid updating of the online processing of sensory information before executing behavior. Further, this circuit organization is likely a conserved motif among insects (Scaplen, 2021).

Successive levels of convergence and divergence across the brain permit functional flexibility. Like the mushroom body, cerebellar circuits in mammals exhibit large divergence in connectivity, and this can support diverse types of synaptic plasticity. Previous neuroanatomical work in insects described divergent afferent and efferent MB neurons, although the extent of this divergence was unknown. The data revealed varying levels of divergence of postsynaptic connections of MBONs across the brain. Every one of the analyzed MBONs had postsynaptic partners projecting to multiple brain regions. Further, nearly the entire superior protocerebrum as well as portions of the inferior protocerebrum received input from at least one MBON, providing opportunities for comprehensive integration of signals from the MBON network (Scaplen, 2021).

Multiple feedforward and feedback circuits exist within the MB. The current data revealed at least two MBONs that receive convergent input from multiple MBONs and are also reciprocally connected. The convergent MBON input to β'2mp is especially interesting as cholinergic (MBON γ2α'1), GABAergic (MBON γ3β'1), and glutamatergic (MBON γ5β'2a) MBONs drive opposing behaviors. For instance, activation of the cholinergic or GABAergic MBON results in naive odor preference, whereas activation of the glutamatergic MBON results in robust naive avoidance. Similarly, the cholinergic MBON activity mediates aversive associations, whereas glutamatergic MBON activity mediates appetitive associations and extinction of aversive (Scaplen, 2021).

Considering that MBON β'2mp receives convergent input from these parallel and opposing pathways, it likely serves as a decision hub by integrating activity to modulate cue-induced approach and avoidance behavior. How MBON β'2mp integrates information across MBONs and drives behavioral responses remains to be determined. Naive activation of MBON β'2mp does not appear to influence behavioral choice, it instead acts as a sleep suppressor. Inhibition of MBON β'2mp during sleep enhances long-term memory. Separately, local protein synthesis within MBON β'2mp, has been implicated in the consolidation of long-term memory. This makes MBON β'2mp an ideal model for understanding how sleep and memory signals might be integrated at a molecular level. It should be mentioned that MBON γ3β'1 reportedly acts as a sleep activator and local protein synthesis within this MBON is also important for the consolidation of long-term memory. Thus, MBON γ3β'one likely also plays a role in integrating sleep and memory signals through its reciprocal connections MBON β'2mp (Scaplen, 2021).

This provides a well-characterized anatomical framework to understand how opposing memories are acquired, consolidated, expressed and updated. Since the roles of these converging MBONs in naive and learned behaviors are state dependent, it is hypothesized that MBON γ3β'1 and MBON β'2mp, both receiving convergent input from other MBONs, providing opportunities for feedforward networks to update information processing depending on the state of the animal (Scaplen, 2021).

Some of the feedback connections originally hypothesized to exist in the MB were between MBONs and DANs. The current analysis revealed neurons postsynaptic to MBONs that are TH positive. Recent studies that combined EM annotation and calcium imaging to identify specific MBON-DAN connections suggest extensive recurrent connectivity between MBONs and DANs, validating these findings. For example, previous studies using both GFP Reconstitution Across Synaptic Partners (GRASP) and EM annotation revealed that MBON α1 and DAN α1 are synaptically connected. This study similarly identified a few DAN neurons that innervate the horizontal MB lobes within the MBON α1 postsynaptic signal. A recent study showed that the 20 DANs that innervate the γ5 MB compartment are clustered into five different subtypes that innervate distinct anatomical regions within the γ5 compartment. According to this study, only one of the γ5 DANs receives direct recurrent feedback from γ5β'2a MBONs. Based on these recent anatomical characterizations, it is believed that the TH+ neurons within the postsynaptic signal of γ5β'2a are the γ5 DANs (Scaplen, 2021).

The FSB is the largest substructure of the central complex, and it serves as a sensory-motor integration center. The FSB comprises nine horizontal layers that are innervated by large-field neurons. Previous work in blow flies and, later work in Drosophila, predicted that the FSB was postsynaptic to output neurons of the MB. The current data confirm that the large-field, tangential neurons of the dorsal FSB are postsynaptic to the majority of MBONs. Although there exists some variation across brains, glutamatergic and GABAergic MBONs predominately project to FSB layers 4 and 5, whereas cholinergic MBONs mainly project to FSB layer 6. Connections between MBONs and FSB were consistent across different split-GAL4 lines that have overlapping expression patterns. Similar extensive direct connectivity between these MBONs and the dorsal FSB, especially layers 4 and 5, were found in the recently annotated EM hemibrain dataset. Together, these observations suggest that the connectivity between the MB and FSB are structurally, and perhaps in some cases functionally, conserved across insect species (Scaplen, 2021).

How are FSB layers 4/5 and 6 functionally distinct? The dorsal FSB has a well-established role in modulating sleep and arousal, locomotor control, courtship, and visual memory. FSB layer 5 has been specifically implicated in processing information regarding elevation in a foraging- and rutabaga-dependent manner. More recent studies have implicated the dorsal FSB in processing nociceptive information. FSB layer 6 plays a specific role in avoidance of a conditioned odor, whereas layers 4 and 5 respond to aversive stimuli and are responsible for innate, but not conditioned, avoidance. Moreover, recent connectome data suggest that differences exist in the postsynaptic connections of layers 4/5 and 6 as well. Overall, there is high degree of interconnectivity within the FSB. The predominate output of FSB layer 6 neurons are other FSB neurons. In fact, many FSB layer 6 neurons project exclusively to other FSB neurons. In contrast, FSB layer 4 neurons send direct projections to other brain structures -- CRE, SMP, and LAL -- in addition to projecting to other FSB neurons. The connections with the LAL position the FSB layer 4 to directly influence downstream motor output signals prior to executing behavior. Recent EM analysis also suggests that some FSB layer 6 neurons synapse back onto PAM DAN neurons. This connectivity is in line with the associative role in conditioned nociception avoidance described for FSB layer 6 (Scaplen, 2021).

Interestingly, this study found that the pattern of FSB postsynaptic targets of the MBONα1 is dissimilar to other glutamatergic MBONs. FSB layers 4/5 and 6 are not present in the MBON α1 postsynaptic signal. Instead, MBON α1 project to neurons that innervate the ventral and most dorsal aspect of the FSB. The ventral FSB is implicated in innate avoidance of electric shock, and recent data suggest that its activity is tuned to airflow cues for orientation during flight. Artificial activation of MBON α1 does not result in significant avoidance behavior. However, it has been implicated in the acquisition, consolidation, and expression of 24 hr long-term sucrose memory. It is possible that MBON α1 provides appetitive valence signals to the ventral FSB to guide goal-directed flight. Functionally validating the role of MBON α1 and its relationship with its putative downstream neurons is key to appreciating how learning signals can drive behavioral decisions (Scaplen, 2021).

More research is necessary to further understand the functional role of different FSB layers and how information is integrated across these layers. Based on the anatomical data, it is clear that although the MB and FSB can function in parallel during memory formation, they act as parts of a dynamic system to integrate information and adjust behavioral responses (Scaplen, 2021).

The LAL is an important premotor waystation for information traveling from the central complex to descending neurons innervating thoracic motor centers across insects. Accordingly, the LAL has been implicated in orientation to pheromones in the moth, flight in the locust and dragonfly, locomotion in Drosophila stimulus-directed steering in Drosophila, the cockroach, cricket, and moth and in response to mechanosensory stimuli in the locust. In the moth, recordings from neurons innervating the LAL have a characteristic 'flip-flop' firing property, which is thought to mediate walking command. More recent work has suggested a functional organization whereby the neurons in the upper division of the LAL receive convergent input from the protocerebrum and neurons in the lower division generate locomotor command (Scaplen, 2021).

The current data show that the MB network converges with the protocerebrum input, thereby providing an opportunity for MBONs to indirectly influence descending motor outputs. It was also demonstrated that two MBONs (γ3β'1 and γ2α'1) synapse on the same subset of LAL and FSB cells, revealing a convergent circuit that connects both structures. Further, in support of anatomical observations, optogenetic activation of MBON γ2α'1 resulted in activation of both LAL and FSB layer four neurons. Given that MBON γ3β'1 is GABAergic, the equivalent experiment was not performed for this neuron. Thus, understanding the functional consequences of these inhibitory connections will require further investigation. Interestingly, despite the fact that MBON γ3β'1 and γ2α'1 express different neurotransmitters and innervate different MB compartments, their manipulation has similar behavioral phenotypes: both promote sleep, and artificial activation of either results in naive preference. Further, activation of both MBON γ3β'1 and γ2α'1 together has an additive effect, which results in a significant increase in preference (Aso et al., 2014b) (Scaplen, 2021).

The FSB and LAL have a well-established structural and functional connectivity. The LAL integrates information from the central complex, including the FSB, and provides a premotor signal to motor centers. However, the behavioral significance of MBON γ3β'1 and γ2α'1 projections to both the FSB and LAL is less clear. Previous work demonstrated that activation of these MBONs while the flies explored an open arena did not significantly affect average speed or angular speed of individual flies. By contrast, this study found that inactivation of the putative downstream LAL neurons significantly increased overall activity of behaving flies in a social context and locomotor assay. Thus, the γ3β'1 and γ2α'1 MBONs may play a modulatory rather than required role in influencing behavioral response to an associated cue (Scaplen, 2021).

Recent work in Drosophila has demonstrated that the DANs that innervate MBON γ2α'1 regulate flight bout durations, and may provide a motivation signal via MBONs to the FSB and LAL to regulate motor activities. The LAL neurons receive multisensory input, and some LAL neurons make direct connections to descending neurons that control movement. Thus, this circuit organization enables integration of sensory signals with punishment or reward to direct the motion of the animal. In contrast, MBON connections with the FSB might play a role in providing context for flexible navigation, goal-directed actions, and memory-based navigation (Scaplen, 2021).

If homology can be defined by shared expression of transcription factors and similar functional roles, the MB-FSB connection may be an appropriate model for understanding functional connections between the hippocampus and striatum and serve as an accessible model for understanding connectivity between more complex brain structures associated with memory. Further, given that the integrative relay role of the LAL is somewhat reminiscent of the vertebrate thalamus, the complex connectivity between the MBONs, FSB, and LAL may also serve as an effective model for predicting and understanding functional connections between the hippocampus, striatum, and thalamus in the context of memory formation and action selection (Scaplen, 2021).

Insects exhibit a great variety of complex behaviors, and significant effort has been devoted to understand the neural circuits that underlie these behaviors. The genetically accessible Drosophila is a great model for studying the interplay between circuit architecture and behavior owing to their complex yet tractable brains. The MB circuits and their role in learning and memory are among the most studied circuits in Drosophila. Although, the majority of these studies have focused on olfactory memory, it is clear that the MB plays a much broader role in insect behavior. In Drosophila, the MB is important for courtship memory, taste aversive memory as well as visual memory. In cockroaches, the MB has a role in place memory and recent data in two different species of ants implicate the MB in spatial navigation to learned locations using visual cues. In mammals, the hippocampus is similarly required for multiple forms of associative memory, including spatial navigation using visual cues. Thus, cross-species similarity in circuit organization and function may exist between the mushroom body and the hippocampus. However, such anatomical and functional cross-species comparisons can also be made between the mushroom body and the cerebellum, suggesting that similar convergent-divergent architecture may be a general principle of structures that encode and update memories (Scaplen, 2021).

In this context, the implementation of trans-Tango to study the MB has high potential in the era of EM reconstruction of the Drosophila brain. Through examination of the circuit connectivity in several individuals, easily afforded by trans-Tango, the value of the EM reconstruction data could be augmented by overlaying on it potential nuanced differences between individuals. In addition, trans-Tango-mediated discoveries in the fly could help illuminate principles of circuit organization in other species. Further, due to the modular design of trans-Tango, it could be readily reconfigured for other types of studies beyond circuit tracing. For example, only minimal modifications are required for implementing a configuration of trans-Tango for identifying the molecular composition of the postsynaptic partners. This strategy could be used to examine the evidence that MBONs stratify the FSB through different classes of peptidergic neurons. Confirmation of these observations would suggest that the MB plays a critical role in regulating modulatory systems of a midbrain region that shares structural and functional commonalities with the vertebrate basal ganglia. Finally, through combining it with new genome editing strategies, trans-Tango could become a useful tool for comparative anatomy in other insects. This would enable the study of synaptic connections in non-model organisms and lead to deeper understanding of biological diversity (Scaplen, 2021).

Understanding how memories are formed, stored, and retrieved necessitates knowledge of the underlying neural circuits. This characterization of the architecture of the neural circuits connecting the MB with downstream central complex structures lays the anatomical foundation for understanding the function of this circuitry.These studies may also provide insight into general circuitry principles for how information is processed to form memories and update them in more complex brains (Scaplen, 2021).

Dopamine-based mechanism for transient forgetting
Sabandal, J. M., Berry, J. A. and Davis, R. L. (2021). Nature. PubMed ID: 33473212

Active forgetting is an essential component of the memory management system of the brain. Forgetting can be permanent, in which prior memory is lost completely, or transient, in which memory exists in a temporary state of impaired retrieval. Temporary blocks on memory seem to be universal, and can disrupt an individual's plans, social interactions and ability to make rapid, flexible and appropriate choices. However, the neurobiological mechanisms that cause transient forgetting are unknown. This study identified a single dopamine neuron in Drosophila that mediates the memory suppression that results in transient forgetting. Artificially activating this neuron did not abolish the expression of long-term memory. Instead, it briefly suppressed memory retrieval, with the memory becoming accessible again over time. The dopamine neuron modulates memory retrieval by stimulating a unique dopamine receptor that is expressed in a restricted physical compartment of the axons of mushroom body neurons. This mechanism for transient forgetting is triggered by the presentation of interfering stimuli immediately before retrieval (Sadandal, 2021).

Memory formation, consolidation and retrieval are well-known functions that support memory expression; however, the processes that limit these functions -- including forgetting -- are less understood. Forgetting has been characterized as either passive or active, and is crucial for memory removal, flexibility and updating. Memory may be removed completely, resulting in permanent forgetting; or temporarily irretrievable, resulting in transient forgetting (Sadandal, 2021).

One form of active forgetting-known as intrinsic forgetting-involves one dopamine neuron (DAN) that innervates the γ2α'1 compartment of the axons of mushroom body neurons (MBNs) and the dendrites of the downstream, compartment-specific mushroom-body output neurons (MBONs). This DAN resides in a cluster of 12 DANs in each brain hemisphere that is known as the protocerebral posterior lateral 1 (PPL1) cluster. Current evidence indicates that the ongoing activity of these DANs after aversive olfactory conditioning slowly and chronically erodes labile and nonconsolidated behavioural memory, as well as a corresponding cellular memory trace that forms in the MBONs. This intrinsic forgetting mechanism is shaped by external sensory stimulation and sleep or rest, and is mediated by a signalling cascade in the MBNs that is initiated by the activation of the dopamine receptor DAMB, which leads to the downstream activation of the actin-binding protein Cofilin and the postulated reorganization of the synaptic cytoskeleton (Sadandal, 2021).

By contrast, there is little understanding of the mechanisms that arbitrate transient forgetting. Neuropsychological studies of failures or delays in retrieval in humans have primarily focused on lexical access. Phonological blockers or interfering stimuli produce a tip-of-the-tongue state-the failure to recall the appropriate word or phrase. Tip-of-the-tongue states are resolved when the distracting signals dissipate. Several brain regions have been implicated in tip-of-the-tongue states from functional magnetic resonance imaging studies, but the neurobiological mechanisms that produce a temporary state of impaired retrieval are unknown. This study offers an entry point into this area of brain function (Sadandal, 2021).

Memory retrieval has been proposed to consist of an interplay between internal or external cues and memory engrams, with cue-induced reactivation of engrams across multiple regions of the brain facilitating memory expression. But a central question about this process is how interfering stimuli temporarily block memory retrieval, resulting in transient forgetting. This study offers insights into one such mechanism. Behavioural and functional imaging data reveal that PPL1-α2α'2, working through the DAMB receptor expressed in the α2α'2 MBN axonal compartment, mediates the transient forgetting of PSD-LTM. This effect occurs without altering a cellular memory trace in the postsynaptic MBON-α2sc. This process can be triggered by distracting stimuli, illustrating a neural-genetic-environmental interplay that modifies memory expression (Sadandal, 2021).

This study considered why the cellular memory trace remains unaffected by DAN stimulation despite the occurrence of behavioural forgetting. Because blocking synaptic output from MBON-α2sc reduces PSD-LTM expression, the simplest hypothesis posits that cellular memory traces form with conditioning in the MBON in addition to the cytoplasmic Ca2+-based memory trace that was detected in this study. This is expected: neurons undergo broad changes in physiology as they adopt new states, so it is plausible that such plastic mechanisms-especially ones that gate synaptic release-are inactivated by DAN activity while leaving the Ca2+-based memory trace intact (Sadandal, 2021).

The discovery that loss of function of DAMB leads to enhanced PSD-LTM was surprising, because of a previous study reporting that this insult attenuates PSD-LTM. The experiments argue strongly that DAMB functions normally to suppress expression of PSD-LTM. However, this leads to the question of why a receptor involved in transient forgetting would lead to enhanced PSD-LTM when inactivated. Previous experiments have shown that PPL1-α2α'2-similar to PPL1-γ2α'1-exhibits ongoing activity, leading to a slow release of dopamine onto MBNs. This activity should slowly degrade or suppress existing memory so that when the receptor is inactivated memory expression is enhanced (Sadandal, 2021).

PPL1-α2α'2 has no important role in the forgetting of labile nonconsolidated memory. Instead, previous studies have identified a different DAN (PPL1-γ2α'1) as having a role in this process and the apparent erasure of the downstream cellular memory trace-perhaps an indication of 'permanent forgetting'. This process is modulated by internal and external factors, and is mediated by key molecules expressed in the MBN that receive PPL1-γ2α'1 input. No robust decrement was found in expression of PSD-LTM after PPL1-γ2α'1 stimulation, which points to the existence of two separate dopamine-based circuits for permanent and transient forgetting. This functional separation may indicate a fundamental principle in the organization of circuits that mediate several forms of forgetting (Sadandal, 2021).

However, the DAMB receptor is used for both permanent and transient forgetting. DAMB is widely expressed across the MBN axons but alters synaptic plasticity differently across MBN compartments. It is possible that DAMB signalling may be distinct for the two forms of forgetting. DAMB preferentially couples with Gq, the knockdown of which inhibits the potent erasure of memory, but its potential role in transient forgetting is unknown. The scaffolding protein Scribble orchestrates the activities of Rac, Pak and Cofilin, all of which are important for the permanent forgetting pathway. However, Scribble knockdown or inhibition of Rac1 does not enhance the PSD-LTM as is the case in DAMB-knockdown flies, which suggests that this scaffolding signalosome does not have a large role in transient forgetting. In summary, the two distinct forms of forgetting-transient and permanent-share a dopaminergic mechanism and a common dopamine receptor, but differ in upstream and downstream neural circuits and in downstream signalling pathways within MBNs (Sadandal, 2021).

The connectome of the adult Drosophila mushroom body provides insights into function
Li, F., Lindsey, J. W., Marin, E. C., Otto, N., Dreher, M., Dempsey, G., Stark, I., Bates, A. S., Pleijzier, M. W., Schlegel, P., Nern, A., Takemura, S. Y., Eckstein, N., Yang, T., Francis, A., Braun, A., Parekh, R., Costa, M., Scheffer, L. K., Aso, Y., Jefferis, G. S., Abbott, L. F., Litwin-Kumar, A., Waddell, S. and Rubin, G. M. (2020). Elife 9. PubMed ID: 33315010

Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory and activity regulation. This study identified new components of the MB circuit in Drosophila, including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. Unexpected structure was found in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). This study provides insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. The results provide a foundation for further theoretical and experimental work (Li, 2020).

Understanding how memories of past events are formed and then used to influence ongoing behavior are key challenges in neuroscience. It is generally accepted that parallel changes in connection strength across multiple circuits underlie the formation of a memory and that these changes are integrated to produce net changes in behavior. Animals learn to predict the value of sensory cues based on temporal correlations with reward or punishment. Such associative learning entails lasting changes in connections between neurons. It is now clear that different parts of the brain process and store different aspects of the information learned in a single event. In both flies and mammals, dopaminergic neurons play a key role in conveying information about whether an event has a positive or negative valence, and there are compelling parallels between the molecular diversity of dopaminergic cell types across these evolutionarily distant animals. However, there is only a limited understanding of how information about the outside world or internal brain state reaches different dopaminergic populations. Nor is the nature of the information that is stored in each parallel memory system understood, nor how these parallel memories interact to guide coherent behavior. It is believed such processes are governed by general and evolutionarily-conserved principles. In particular, it is believed the circuit logic that allows a brain to balance the competing demands of rapid learning with long-term stability of memory are likely to be the same in flies and mammals. Developing a comprehensive understanding of these circuits at the resolution of individual neurons and synapses will require the synergistic application of a variety of experimental methods together with theory and modeling. Many of the required methods are well developed in Drosophila, where the circuits underlying learning and memory are less complex than in mammals, and where detailed anatomical knowledge of the relevant circuits, which are believed will be essential, has just now become available. This study provide analysis of the complete connectome of a circuit involved in parallel processing of associative memories in adult fruit flies. The core architecture of this circuit is strikingly similar to that of the vertebrate cerebellum (see The shared circuit architecture of the mushroom body and the cerebellum) (Li, 2020).

The MB is the major site of associative learning in insects, and species that perform more complex behavioral tasks tend to have larger MBs. In the MB of each brain hemisphere, sensory stimuli are represented by the sparse activity of ~2000 Kenyon cells (KCs) whose dendrites form a structure called the MB calyx and whose parallel axonal fibers form the lobes of the MB (see Anatomy of the adult Drosophila MB) (Li, 2020).

The major sensory inputs to the Drosophila MB are olfactory, delivered by ~150 projection neurons (PNs) from the antennal lobe to the dendrites of the KCs in the MB calyx. KCs each receive input from an average of six PNs. For a KC to fire a spike, several of its PN inputs need to be simultaneously activated. This requirement, together with global feedback inhibition, ensures a sparse representation where only a small percentage of KCs are activated by an odor. The MB has a three layered divergent-convergent architecture in which the coherent information represented by olfactory PNs is expanded and decorrelated when delivered to the KCs. But the degree to which the structure of the sensory input representation is maintained by the KCs has been debated. This issue is explored, taking advantage of a nearly comprehensive dataset of KC inputs and outputs (Li, 2020).

While best studied for its role in olfactory associative learning, the MB also receives inputs from several other sensory modalities. A subset of projection neurons from the antennal lobe delivers information about temperature and humidity in both the larva. Taste conditioning also requires the MB and is believed to depend on specific KC populations, although the relevant inputs to these KCs have not yet been reported. This study identified one likely path for gustatory input to the MB (Li, 2020).

Drosophila MBs are also known to be able to form memories based on visual cues. Until a few years ago, it was thought that visual input reached the Drosophila MBs using only indirect, multisynaptic pathways as direct visual input from the optic lobes to the MBs, well known in Hymenoptera, had not been observed in any dipteran insect. A previous study identified two types of visual projection neurons (VPNs) connecting the optic lobes and the MB and additional connections have been observed recently by light microscopy. This study found that visual input was much more extensive than previously appreciated, with about 8% of KCs receiving predominantly visual input, and present in this study is a detailed description of neuronal pathways connecting the optic lobe and the MB. Visual sensory input appears to be segregated into distinct KC populations in both the larva and the adult, as is the case in honeybees. This study found two classes of KCs that receive predominantly visual sensory input, as well as MBONs that get the majority of their input from these segregated KC populations (Li, 2020).

MBONs provide the convergence element of the MB's three layer divergent-convergent circuit architecture. Previous work has identified 22 types of MBONs whose dendrites receive input from specific axonal segments of the KCs. The outputs of the MBONs drive learned behaviors. Approximately 20 types of dopaminergic neurons (DANs) innervate corresponding regions along the KC axons and are required for associative olfactory conditioning. Specifically, the presynaptic arbors of the DANs and postsynaptic dendrites of the MBONs overlap in distinct zones along the KC axons, defining the 15 compartmental units of the MB lobes. A large body of evidence indicates that these anatomically defined compartments of the MB are the units of associative learning (Li, 2020).

The DANs innervating different MBON compartments appear to play distinct roles in signaling reward vs. punishment, novelty vs. familiarity, the presence of olfactory cues and the activity state of the fly. These differences between DAN cell types presumably reflect in large part the nature of the inputs that each DAN receives, but knowledge of these inputs is just emerging and is far from comprehensive. DANs adjust synaptic weights between KCs and MBONs with cell type-specific rules and, in at least some cases, these differences arise from the effects of co-transmitters. In general, a causal association of KC responses with the activation of a DAN in a compartment results in depression of the synapses from the active KCs onto MBONs innervating that compartment. Different MB compartments are known to store and update non-redundant information as an animal experiences a series of learning events. In rodent and primate brains, recent studies have revealed that dopaminergic neurons are also molecularly diverse and encode prediction errors and other information based on cell type-specific rules (Li, 2020).

MBONs convey information about learned associations to the rest of the brain. Activation of individual MBONs can cause behavioral attraction or repulsion, according to the compartment in which their dendrites arborize. The combined output of multiple MBONs is likely to be integrated in downstream networks, but it is not understood how memories stored in multiple MB compartments alter these integrated signals to guide coherent and appropriate behaviors. Prior anatomical studies implied the existence of multiple layers of interneurons between MBONs and descending motor pathways. What is the nature of information processing in those layers? Anatomical studies using light microscopy provided the first hints. MBONs from different compartments send their outputs to the same brain regions, suggesting that they might converge on shared downstream targets. DANs often project to these same brain areas, raising the possibility of direct interaction between MBONs and DANs. The functional significance of such interactions has just begun to be investigated, and studies of the Drosophila larva, where a connectome of a numerically less complex MB is available, are providing valuable insights (Li, 2020).

The recently determined connectome of a portion of an adult female fly brain (hemibrain) provides connectivity data for ~22,500 neurons. Among them, ~2600 neurons have axons or dendrites in the MB, while ~1500 neurons are directly downstream of MBONs (using a threshold of 10 synapses from each MBON to each downstream target) and ~3200 are upstream of MB dopaminergic neurons (using a threshold of five synapses from each upstream neuron to each DAN). Thus this study will consider approximately one-third of the neurons in the central brain in this analysis of the MB ensemble (Li, 2020).

Throughout the paper synaptic thresholds were set in order to focus the descriptions and analyses on the most strongly connected neurons. In the above analysis, a higher threshold for MBON connections was chosen to downstream targets than for DAN inputs because the typical MBON has many more output synapses than a DAN has input synapses. At a thresholds of five synapses, DANs have a median of 31 different input neurons, but if the threshold to 10 synapses were increased this would decrease to only six different neurons. In contrast, at the threshold of 10 synapses, MBONs are connected to a median of 90 downstream neurons. There were some limitations resulting from not having a wiring diagram of the full central nervous system, as complete connectivity information for neurons with processes that extended outside the hemibrain volume was lacking. It was generally possible to mitigate these limitations by identifying the corresponding neurons in other EM or light microscopic datasets when the missing information was important for the analyses. Thus the hemibrain dataset was able to support a nearly comprehensive examination of the full neural network underlying the MB ensemble (Li, 2020).

Studies of the larval MB are providing parallel information on the structure and function of an MB with most of the same cell types, albeit fewer copies of each. The microcircuits inside three MB compartments in the adult were previously described and this study reports that the overall organization of these three compartments is conserved in a second individual of a different gender. More importantly, this study extends the analysis of microcircuits within the MB lobes to all 15 compartments, revealing additional aspects of spatial organization within individual compartments (Li, 2020).

The current study led to discovery of new morphological subtypes of KCs and to determine the sensory inputs delivered to the dendrites of each of the ~2000 KC. Considerable structure was found in the organization of those inputs and unexpectedly high levels of visual input, which was the majority sensory input for two classes of KCs. This segregation of distinct sensory representations into channels is maintained across the MB, such that MBONs, by sampling from different KCs, have access to different sensory modalities and representations. A new class of 'atypical' MBONs was discovered, consisting of 14 cell types, that have part of their dendritic arbors outside the MB lobes, allowing them to integrate input from KCs with other information; at least five of them make strong, direct synaptic contact onto descending neurons that drive motor action. How MBONs from different compartments interact with each other to potentially integrate and transform the signals passed from the MB to the rest of the brain is described, revealing a number of circuit motifs including multi-layered MBON-to-MBON feedforward networks and extensive convergence both onto common targets and onto each other through axo-axonal connections. Finally, this study analyzed the inputs to all 158 DANs that innervate the MB. Extensive direct feedback was found from MBONs to the dendrites of DANs, providing a mechanism of communication within and between MB compartments. Groups of DANs were found that share common inputs, providing mechanistic insights into the distributed parallel processing of aversive and appetitive reinforcement and other experimental observations (Li, 2020).

The hemibrain dataset contains the most comprehensive survey of the cell types and connectivity of MB neurons available to date. This connectome allowed probing in fine detail the circuitry underlying canonically proposed functions of the MB, including the representation of olfactory information by KCs, computation of valence by MBONs, and reinforcement of associations by DANs. Patterns in the input to DANs, MBON-to-DAN and MBON-to-MBON connectivity were found that suggest how associative learning in the MB can affect both the acquisition of new information through learning and the expression of previously learned responses. The connectome also reveals circuitry that supports non-canonical MB functions, including selective structure in non-olfactory pathways, a network of atypical MBONs, extensive heterogeneity in DAN inputs, and connections to central brain areas involved in navigation and movement (Li, 2020).

This analysis of the hemibrain connectome relied heavily on an extensive catalog of previously identified and genetically isolated cell types and on decades of study illuminating the link between MB physiology and fly behavior. It is worth emphasizing the interdependency of anatomy, physiology and behavior at the beginnning the post-connectomic era in fly research. Some of the neurons described that appear similarly connected may turn out to have diverse functions due to different physiology and, conversely, neurons that are morphologically distinct may turn out to have similar functions. In addition, a set of inputs with high synapse counts might appear, at the connectome level, to represent a major pathway for activating a particular neuron, but this will not be true if these inputs rarely fire at the same time. Likewise, a set of highly correlated inputs can be effective even if their individual synapse counts are modest. Lack of knowledge about correlated activity is probably the most significant uncertainty when attempting to map synapse counts onto circuit function, likely larger than possible errors in synapse identification and the effects of imposing various thresholds (see below). Finally, the connectome does not reveal gap junction connections or identify more distant non-synaptic modulation. These caveats should be kept in mind when interpreting connectome data (Li, 2020).

A number of these studies involved imposing a cutoff on the number of synapses required to include a particular connection in the analysis. The intent of these thresholds is to focus the analysis on what are likely to be the strongest inputs and outputs. Whether this cutoff should be based on a fixed number of synapses or on a percentage of total synapse counts is open to debate as, of course, is the actual value that the cutoff should take. Neurons differ widely in their numbers of inputs and outputs and these differences need to be taken into account when choosing thresholds. That is why information is presented about percentage of total inputs and outputs as well as synapse numbers. An approach to thresholding that takes such information into account has been used in a previous stdu; in the case of MBON to CX connections explored both here and in the previous study, differences in the connectivity map obtained with different thresholding methods were limited to the weakest connections (Li, 2020).

Most neurons make a large number of weak connections to other neurons, often involving just a single synapse. Some cases of low synapse number may be the result of incomplete reconstruction of neuronal arbors. In the MB lobes, an extensive effort was made to fully reconstruct all neurites and >80% of all computationally predicted synapses were assigned to identified neurons. Likewise, the arbors of MBONs and DANs outside the MB were extensively proofread. However, in other brain regions, where MBON outputs and DAN inputs lie, reconstruction was often much less complete. In such regions, it is difficult to estimate the extent to which the mapped synapses are representative of the full set of connections. A previous study reports an analysis of connectivity determined at two stages of reconstruction in the CX and, while the number of assigned synapses increased with additional proofreading, there was little difference in the connectivity maps. Errors in either synapse prediction or developmental wiring are also likely to produce some false connections represented by only one or two synapses. Of course, real, but sparse, connections might still be impactful if they fire concurrently, but this is not something that can be judged from the available information. Therefore, it seemed reasonable to ignore weak connections in this analyses. Thresholds must obviously be chosen with care and the effects of any particular cutoff value on results and conclusions should be assessed, preferably in conjunction with experimental data (Li, 2020).

Fly research has been greatly facilitated by the development of numerous fly lines that provide cell-type specific genetic access. This analysis has revealed, particularly in the case of DANs, subtypes within groups of neurons that would previously have been considered a single type. Thus, the higher resolution view of cell types that connectomics provides points out the need to develop driver lines or other experimental methods for more fine-tuned genetic access (Li, 2020).

The cell type constituents and circuit motifs of the MB in the adult fly have many similarities with its precursor at the larval stage of development. Both the larval and adult MBs support associative learning and, in both, PNs from the antennal lobe that convey olfactory information provide the majority of the sensory input, complemented by thermal, gustatory and visual sensory information that is segregated into distinct KC populations. However, the multi-layered organization of non-olfactory inputs in the main and accessory calyces (including integration of diverse input sources by LVINs) suggests that the KC representation in the adult is more highly enriched and specialized for non-olfactory sensory features. It is worth noting that the earliest born types of each of the three main adult KC classes (KCγs, KCγd, KCγt, KCα'β'ap1, KCαβp) appear to be specialized for non-olfactory sensory cues, and in most cases their dendrites lie in the accessory calyces (Li, 2020).

In the first instar larval MB, the only larval stage for which a connectome is available, there are roughly 70 mature KCs, which is increased nearly 30-fold in the adult. This enrichment likely increases odor discrimination and olfactory memory capacity. The larval MB has only eight compartments in its horizontal and vertical lobes. Although the increase in the adult to 15 compartments is only about a factor of two, the extent of their DAN modulation is greatly expanded. The larva has only seven confirmed DANs and five additional cells of unknown neurotransmitter thought to provide modulatory input, a factor of 15-fold less than the adult. Whereas each larval KC innervates all eight compartments, individual adult KCs innervate only five out of 15 compartments. Therefore the DANs in the larva are capable of modulating all KCs, whereas in the adult, DANs in different compartments modulate specific subtypes of KCs. The expansion of the number of DANs within many compartments in the adult MB, and subcompartmental targeting of individual DANs within a compartment, further increases the difference in granularity of DAN modulation between the larva and adult (Li, 2020).

MBONs feedback onto DANs and converge onto common downstream targets in both the larva and adult, implying some shared computational strategies. However, the greatly increased DAN complexity in the adult fly and the presence of subcompartmental organization of DAN axon targets not present in the larva suggest a substantial increase in the specificity of the learning signals involved in memory formation and raises the possibility of modality-specific learning signals to complement the multimodal KC representation (Li, 2020).

Previous theoretical work has emphasized the advantages of mixing sensory input to the KCs so that they provide a high-dimensional representation from which MBONs, guided by DAN modulation, can derive associations between sensory input and stimulus-valence. The connectome data modifies this viewpoint in two ways. First, although olfactory input to the KCs is highly mixed, various structural features reduce the dimensionality of the KC odor representation. A recent analysis of EM data from an adult Drosophila MB identified groups of PNs thought to represent food odors that are preferentially sampled by certain KCs. Consistent with this observation, the current analysis revealed subtype-specific biases in PN sampling by KCs, including an overrepresentation of specific glomeruli by α/β and α'/β' KCs. These biases, as well as other structural features, appear to arise from the stereotyped arrangement of PN axons within the calyx and their local sampling by KCs. This may reflect a developmental strategy by which the KC representation is organized to preferentially represent particular PN combinations. Further analyses of KC connectomes across hemispheres and animals, as well as experimental studies, will help evaluate the impact of this structure (Li, 2020).

The hemibrain connectome also revealed a second, more dramatic, structural feature of sensory input to the MB: non-olfactory input streams corresponding to visual and thermo-hygro sensation are strongly segregated. This organization may reflect the nature of stimulus-valence associations experienced by flies. In purely olfactory learning, when valence is associated with particular sets of olfactory receptors, MBONs need to be able to sample those combinations to successfully identify the stimulus. This requires that KCs mix input from multiple glomeruli within the olfactory stream. However, KCs that mix across streams corresponding to different sensory modalities may not be necessary if each modality can be used separately to identify valence. For example, either the visual appearance of an object or its odor may individually be sufficient to identify it as a food source. This study asked whether there is an advantage in having separate modality-specific sensory pathways, as seen in the connectome data, when valences can be decomposed in this way (Li, 2020).

To address this question a model is considered in which KC input is divided into two groups, visual and olfactory. In one version of the model ('shared KC population'), all KCs receive sparse random input from both types of PNs, corresponding to a high degree of mixing across modalities. In the other ('separate KC populations'), half of the KCs receive sparse random input exclusively from visual PNs and half only from olfactory PNs, corresponding to no cross-modal mixing. Two tasks were defined that differ in the way valences are defined. In the first (factorizable) version of the task, each olfactory stimulus and each visual stimulus is assigned a positive or neutral subvalence, and the net valence of the combined stimulus is positive if either of these components is positive (olfactory OR visual). In the second (unfactorizable) version, a valence is randomly assigned independently to each olfactory+visual stimulus pair. The ability of a model MBON, acting as a linear readout, was evaluated to determine valence from these two different KC configurations. Separate modality-specific KC populations are indeed beneficial when the valence can be identified from either one modality or the other. Dedicating different KC subtypes to distinct sensory modalities allows the predictive value of each modality to be learned separately. This result suggests that the divisions into KCs specialized for visual, thermo/hygro and olfactory signals may reflect how natural stimuli of different modalities are predictive of valence (Li, 2020).

On the basis of light-level studies, DAN modulation of KC-to-MBON synapses has been considered to operate at the resolution of MB compartments. However, taken with other recent studies, the morphology and connectivity data indicate that functionally distinct PAM-DAN subtypes operate within a MB compartment. DAN subtypes receive different inputs and likely modulate different KC-MBON synapses within a compartment (Li, 2020).

A prior analysis showed that PAM01-fb DANs were required to reinforce the absence of expected shock during aversive memory extinction, whereas a different set of γ5 DANs were needed for learning with sugar reinforcement. It is conceivable that another γ5 DAN subtype is required for male flies to learn courtship rejection. The connectome data revealed DAN subtypes in every compartment that is innervated by PAM DANs (Li, 2020).

The γ3 compartment provides an interesting example of subcompartmental targeting of modulation by DANs and of KC input onto MBONs. There are two subtypes of PAM DANs and three types of MBONs in the γ3 compartment. MBON09 and MBON30 primarily receive olfactory information from γm KCs whereas MBON33 primarily receives visual information from γd KCs. PAM12-dd and PAM12-md DANs appear to modulate KC inputs to MBON09/MBON30 or MBON33, respectively. Although existing driver lines do not separate the dd and md subtypes, PAM-γ3 DAN activity is suppressed by sugar and activated by electric shock. This study found that PAM12-dd DANs share input with PPL1 DANs conveying punishment signals, while PAM12-md DANs are co-wired with PAM08 (γ4) DANs conveying reward signals. Thus, synaptic transmission from two sets of modality-specific KCs to different MBONs can be independently modulated by DANs signaling different valences, all within a single compartment (Li, 2020).

To explore the implications of DAN modulation that is specific to sensory modality,the model presented above was expanded by including two DANs, one conveying the visual component of valence and the other the olfactory component. KCs were divided into visual and olfactory modalities, and two configurations for DAN modulation, one, 'shared reward signal', that is compartment-wide and non-specific, and the other, 'separate reward signals' were considered, in which each DAN only induces plasticity onto KC synapses matching its own modality. This latter case models a set of DANs that affect synapses from visual KCs onto the MBON and another set that affect olfactory synapses (alternatively, it could model two MBONs in different compartments that are modulated independently and converge onto a common target). This study found that, when KCs are divided into separate populations and separate modalities can be used to identify valence, learning is more efficient if the pathways are modulated individually (Li, 2020).

This analysis revealed that DANs receive very heterogeneous inputs but, nonetheless, some DANs both within and across compartments often share common input. This combination of heterogeneity and commonality provides many ways of functionally combining different DAN subtypes. For example, it is expected that this combination allows DANs to encode many different combinations of stimuli, actions and events in a state-dependent manner and to transmit this information to specific loci within the MB network (Li, 2020).

In addition to heterogeneous inputs from a variety of brain regions, the DAN network receives a complex arrangement of within and across-compartment monosynaptic input from a variety of MBONs, using both excitatory and inhibitory neurotransmitters. It was found that nearly all MB compartments contain at least one direct within-compartment MBON-DAN feedback connection. MBON feedback onto these DAN subtypes allows previously learned associations that modify MBON activity to affect future learning. MBONs that feedback onto the same DANs that modulate them could, if the result of learning is reduced DAN activity, prevent excess plasticity for an already learned association. In cases where MBON activity excites the DAN, the self-feedback motif could assure that learning does not stop until the MBON has been completely silenced. More generally, MBON inputs to DANs imply that dopaminergic signals themselves reflect learned knowledge and the actions it generates. This could, in turn, allow MBON modulation of DAN activity to support a number of learning paradigms beyond pure classical conditioning, including extinction, second-order conditioning, operant conditioning and reinforcement learning (Li, 2020).

Flies can perform second-order conditioning, in which a stimulus that comes to be associated with reinforcement may itself act as a pseudo-reinforcement when associated with other stimuli. This computational motif of learning the value of sensory states and using the inferred value as a surrogate reinforcement to guide behavioral learning is the core principle behind a class of machine learning techniques known as actor-critic algorithms. These algorithms consist of two modules: the 'actor', whose job is to map sensory inputs to behavioral outputs and the 'critic', whose job is to map sensory inputs to their inferred values and provide these values as a learning signal for the actor. In the mammalian basal ganglia, the dorsal and ventral striatum, the latter of which strongly influences the activity of dopamine neurons in areas including VTA, have been proposed to represent actor and critic modules, respectively. In the MB, this perspective suggests a possible additional 'critic' function for some MBONs beyond their known 'actor' role in directly driving behaviors. Consistent with this view, activation of individual MBONs can excite DANs in other compartments. This study found strong direct monosynaptic connections between some MBONs and DANs in other compartments. Functional studies will be needed to determine which MBONs, if any, participate in an actor-critic arrangement, and which circuit mechanisms-for example, release from inhibition, or reduction of excitation-are at work (Li, 2020).

Another potential role of cross-compartment MBON-DAN feedback is to gate the learning of certain associations so that the learning is contingent on other associations having already been formed. Such a mechanism could support forms of memory consolidation in which long-term memories are only stored after repeated exposure to a stimulus and an associated reward or punishment. Prior studies have linked plasticity in the γ1 and γ2 compartments to short-term aversive memory and plasticity in the α2 and α3 compartments to long-term aversive memory. The cross-compartmental MBON-to-DAN connections observed in this study suggest an underlying cicuit mechanism for this 'transfer' of short to long term memory. Aversion drives PPL101 (γ1pedc) and depresses the conditioned odor-drive to the GABAergic MBON11 (γ1pedc>α/β). MBON11 is strongly connected with PPL1-γ1pedc and is more weakly connected with PPL105 and PPL106. Depression of MBON11 will therefore also release the PPL105 and PPL106 DANs from MBON11-mediated inhibition, increasing their activity in response to the conditioned odor and making them more responsive during subsequent trials. The net result is that short-term aversive learning by MBON11 (γ1pedc>α/β) promotes long-term learning in MBON18 (α2sc) and MBON14 (α3) by releasing the inhibition on the dopamine neurons that innervate the α2 and α3 compartments. Indeed pairing inactivation of MBON11 with odor presentation can form an aversive memory that requires output from PPL1-DANs and optogenetic stimulation of MBON11 during later trials of odor-shock conditioning impairs long-term memory formation (Li, 2020).

Cross-compartment MBON-DAN feedback may also enable context-dependent valence associations, such as the temporary association of positive valence with neutral stimuli when a fly is repeatedly exposed to aversive conditions. Multiple, spaced aversive conditioning trials were recently shown to form, in addition to an aversive memory for the shock-paired odor, a slowly emerging attraction, a 'safety' memory, for a second odor that was presented over the same training period without shock. The GABAergic MBON09 (γ3β'1) appears to play a critical role in the formation of this safety memory. The synapses from KCs conveying the shock-paired odor are depressed in that portion of MBON09's dendrite that arborizes in γ3, while the synapses from KCs conveying the safety odor are depressed in its β'1 arbor. These combined modulations should gradually release downstream neurons from MBON09 feedforward inhibition, consistent with the proposed mechanism for PAM13/14 (β'1) and PAM05/06 (β'2m and β'2p) DANs becoming more responsive to the safe odor. The connectome data revealed that MBON09 is directly connected to the PAM13/14 (β'1ap) and PAM05 (β'2p) DANs, consistent with release from inhibition underlying the delayed encoding of safety (Li, 2020).

DANs also make direct connections with MBONs in each MB compartment, and optogenetic activation of PAM11 DANs can directly excite MBON07 with slow dynamics. This might provide a mechanism to temporarily suppress memory expression without impairing the underlying memory, which is stored as depressed KC-to-MBON synapses. For example, DANs are known to control hunger and thirst-dependent memory expression, and their excitation of MBONs could provide a possible mechanism (Li, 2020).

Feedforward MBON-MBON connections were postulated, based on behavioral and light microscopic anatomical observations, to propagate local plasticity between compartments. The GABAergic MBON11 is poised to play a key role in such propagation as it is connected with 17 other MBONs (at a threshold of 10 synapses). Thus local depression of KC-MBON11 synapses by the shock responsive PPL1-γ1pedc DAN would be expected to result in disinhibition of MBONs in other compartments. Indeed enhanced CS+ responses of MBON01 and MBON03 after odor-shock conditioning have been ascribed to release from MBON11 inhibition. The consequence of releasing other strongly connected MBONs (MBON07, MBON14 and MBON29) from MBON11 inhibition awaits future study. As discussed above, MBON11 is also connected to DANs innervating its cognate compartment and to DANs innervating other compartments. MBON11 may therefore coordinate MBON network activity via both direct and indirect mechanisms. Analogous feedforward inhibitory connections were found from MBON09 (γ3β'1) to MBON01 and MBON03. Aversive learning therefore reduces both MBON11- and MBON09-mediated inhibition of these MBONs, which further skews the MBON network toward directing avoidance of the previously punished odor (Li, 2020).

Disinhibition likely also plays an important role in appetitive memory. The connectivity of MBON06 (β1>α) revealed here indicates that local plasticity in the β1 compartment can propagate to other MBONs. Similar to MBON11, MBON06 is directly connected with nine other MBONs with a threshold of 10 synapses. MBON06 gradually increases its response to repeated odor exposure and odor-evoked responses of β1 DANs vary with metabolic state. More compellingly, artificially triggering PAM10 (β1) DANs can assign appetitive valence to odors. However, the role of MBON06 in appetitive memory and how the PAM10 (β1) DANs modulate KC synapses to MBON06 has not been investigated. The glutamatergic MBON06 (β1>α) makes a large number of reciprocal axoaxonic connections with the GABAergic MBON11, whose activation favors approach. This reciprocal network motif and the positive sign of behavior resulting from β1 DAN-driven memory suggests that MBON06 released glutamate is likely to be inhibitory to MBON11 and its other downstream targets. MBON06 also makes twice as many connections onto the glutamatergic MBON07 and the cholinergic MBON14 as does MBON11. MBON14 (α3) and MBON07 (α1) have established roles in appetitive memory. Assuming that PAM10 (β1) DANs encode appetitive memory by depressing synapses from odor-specific KCs onto MBON06 (β1>α), MBON06 suppression will release the feedforward inhibition of MBON06 onto MBON07 (α1), freeing it to participate in driving the PAM11-aad (α1) DANs. Release of MBON06 inhibition should also simultaneously potentiate the responses of MBON14 (α3) to the conditioned odor. Lastly, releasing the strong inhibition from MBON06 frees MBON11 to provide weaker inhibition that would further favor odor-driven approach (Li, 2020).

Aversive learning will also alter the function of the MBON06:MBON11 network motif. Aversive reinforcement through the PPL101 (γ1pedc) DAN depresses KC-MBON11 connections. This depression releases MBON06 from MBON11-mediated suppression and allows MBON06 to then suppress output through MBON07 and MBON11, further favoring odor-driven avoidance (Li, 2020).

Several studies have described the influence of internal states such as hunger and thirst on the function and physiology of the MB. In essence, states appear to modulate the DAN-MBON network so that the fly preferentially engages in the pursuit of its greatest need. Since current knowledge suggests these deprivation states employ volume release of modulatory peptides or monoamines to control specific DANs and their downstream MBONs, the connectome analyzed in this study does not provide a complete description of this circuit. Nevertheless, direct connectivity does provide some interesting new insight concerning hunger and thirst-dependent control (Li, 2020).

The MBON06 (β1>α):MBON11 (γ1pedc>α/β) cross-inhibitory network motif is likely to be relevant for the dependence of learning and memory expression on hunger state. PPL101 (γ1pedc) DANs and MBON11 (γ1pedc>α/β) are sensitive to nutrient/satiety status, with MBON11 being more responsive in hungry flies. Therefore, the hungry state favors the activity of the MBONs that are normally repressed by MBON06 (Li, 2020).

Thirst-dependent seeking of water vapor requires the activity of DANs innervating the β'2 compartment. The current work shows that these DANs are likely to directly modulate thermo/hygrosensory KCs. In addition, a recent study showed that thirst-dependent expression of water memory required peptidergic suppression of the activity of both the PPL103(γ2α'1) and PAM02 (β'2a) DANs. Interestingly, blocking the PAM02 (β'2a) DANs released memory expression in water-sated flies whereas blocking the PPL103 (γ2α'1) DANs had no effect. However, if the PPL103 (γ2α'1) DANs were blocked together with PAM02 (β'2a) they further facilitated water memory expression. The connectome suggests circuit mechanisms that could reconcile these observations: MBON12 (γ2α'1) provides strong cholinergic input to the PAM02 (β'2a) DANs, suggesting that PPL103 (γ2α'1) DANs might facilitate water memory expression by suppressing MBON12's excitatory input onto PAM02 (β'2a) DANs (Li, 2020).

A role for the MB in guiding locomotion and navigation in ants and other insects has been proposed. The strong and direct connections observed from the majority of MBONs to the CX, the fly's navigation and locomotion control center, provide one circuit path for the MB to exert influence on motor behaviors. Discovering how this input is utilized by the CX will require additional experimental work (Li, 2020).

Optogenetic activation of Drosophila MBONs can promote attraction or avoidance by influencing turning at the border between regions with and without stimulating light. The effect of MBON activation is additive: coactivation of positive-valence MBONs produced stronger attraction, whereas coactivation of positive and negative-valence MBONs cancelled each other out. Because the fly needs to balance the outputs of different compartments, it is expected that those downstream neurons that integrate inputs from multiple MBONs will have a privileged role in motor control (Li, 2020).

The activity of some DANs has been shown to correlate with motor activity, and the optogenetic activation of PAM-β'2 or PPL1-α3 DANs can attract flies, indicating that DAN activity can itself in some circumstances drive motor behavior. The circuit mechanisms generating the correlation between DAN activity and motor behavior remain to be discovered. Downstream targets of MBONs provide extensive input to DANs, and this study found that neurons downstream of multiple MBONs are twice as likely as other MBON targets to provide such direct input to DANs (Li, 2020).

This study also discovered a direct pathway mediated by atypical MBONs that connects to the descending neurons (DNs) that control turning, an observation that provides additional support for the importance of the MB in the control of movement. The connections of these MBONs appear to be structured so as to promote directional movement, often involving a push-pull arrangement of MBONs signaling approach and avoidance. In addition to direct connections to DNs, there is a network of connections mediated by both local LAL interneurons and interneurons that connect the right and left hemisphere LALs. The atypical MBONs that connect directly to the descending steering system, MBON26, MBON27, MBON31 and MBON32, appear to be among the most integrative neurons in the MB system in the sense that they combine direct KC input from the MB compartments with both input from many other MBONs and non-MB input. At the level of the descending neurons, the highly processed signals from these MBONs are combined with inputs from many other sources, including the central complex, to affect a decision to turn. This high degree of integration presumably reflects the complexity and importance of this decision, with many factors involved that might act individually or in combination (Li, 2020).

Visual input to the MB is over-represented in the output to the descending neurons, predominantly through MBON27. Short- and long-term learning based on features in a visual scene has been reported to involve the CX. Plasticity in the CX enables visual feature input from the sky and surrounding scenery to be mapped flexibly onto the fly's internal compass. The visual input conveyed to the MB and, presumably, the learning at the synapses between visual KCs and MBON27, may be of lower resolution, encoding broader features such as color and contrast. An early study demonstrated that the MB is dispensable for flying Drosophila to learn shapes but that it is required for them to generalize their learning if the visual context changes between training and testing. Memory of visual features and the ability to generalize context could allow visual landmarks to help guide navigation either through the CX or by directly influencing descending neurons. The thermo/hygrosensory features conveyed by MBON26 could play a similar role, as could the large amount of odor-related information present in this MBON output pathway (Li, 2020).

The MB has an evolutionarily-conserved circuit architecture and uses evolutionarily-conserved molecular mechanisms of synaptic plasticity. The dense connectome analysed in this report has uncovered many unanticipated circuit motifs and suggested potential circuit mechanisms that now need to be explored experimentally. Drosophila provides access to many of the required tools such as cell-type-specific driver lines, genetically encoded sensors and microscopy methods to observe whole-brain neuronal activity and fine ultrastructure. These features make the fly an excellent system in which to study many general issues in neuroscience, including: the functional diversity of dopaminergic neurons that carry distributed reinforcement signals, the interactions between parallel memory systems, and memory-guided action selection, as well as the mechanisms underlying cell-type-specific plasticity rules, memory consolidation, and the influence of internal state. It is expected that studies of the MB will provide insight into general principles used for cognitive functions across the animal kingdom (Li, 2020).

As mentioned in the introduction, the MB shares many features with the vertebrate cerebellum, and the results should be informative for studies of the cerebellum proper as well as other cerebellum-like structures such as the dorsal cochlear nucleus and the electrosensory lobe of electric fish. A distinctive feature of these systems, and of the MB, is that learning is driven by a particular mechanism; for example DAN modulation in the MB or complex spiking driven by climbing fiber input in the cerebellum. Studies of learning in cortical circuits have traditionally focused on Hebbian forms of learning driven by the ongoing input and output activity of a neuron. However, recent results from both hippocampal circuits have stressed the importance of plasticity that is driven by dendritic plateau potentials or bursts that resemble the distinct learning events seen in cerebellar and MB circuits. Thus, the form of plasticity seen in the MB and its control by output and modulatory circuits may inform studies of learning in the cerebral cortex as well (Li, 2020).

Recurrent architecture for adaptive regulation of learning in the insect brain
Eschbach, C., Fushiki, A., Winding, M., Schneider-Mizell, C. M., Shao, M., Arruda, R., Eichler, K., Valdes-Aleman, J., Ohyama, T., Thum, A. S., Gerber, B., Fetter, R. D., Truman, J. W., Litwin-Kumar, A., Cardona, A. and Zlatic, M. (2020). Nat Neurosci 23(4): 544-555. PubMed ID: 32203499

Dopaminergic neurons (DANs) drive learning across the animal kingdom, but the upstream circuits that regulate their activity and thereby learning remain poorly understood. This study provides a synaptic-resolution connectome of the circuitry upstream of all DANs in a learning center, the mushroom body of Drosophila larva. Afferent sensory pathways and a large population of neurons were discovered that provide feedback from mushroom body output neurons and link distinct memory systems (aversive and appetitive). This was combined with functional studies of DANs and their presynaptic partners and with comprehensive circuit modeling. It was found that DANs compare convergent feedback from aversive and appetitive systems, which enables the computation of integrated predictions that may improve future learning. Computational modeling reveals that the discovered feedback motifs increase model flexibility and performance on learning tasks. This study provides the most detailed view to date of biological circuit motifs that support associative learning (Eschbach, 2020).

To behave adaptively in an ever-changing environment, animals must be able to learn new associations between sensory cues (conditioned stimuli, CS) and rewards or punishments (aversive and appetitive unconditioned stimuli, US), and continuously update previous memories, depending on their relevance and reliability (Eschbach, 2020).

Modulatory neurons (for example, DANs) convey information about rewards and punishments, and provide the teaching signals for updating the valence associated with CS in learning circuits across the animal kingdom (for example, the vertebrate basal ganglia or the insect mushroom body, MB). The co-occurrence of CS and modulatory neuron activity tuned only to the received US can support simple associative memory formation. To account for more complex behavioral phenomena, theories have been developed in which learning can be regulated by previously formed associations. According to reinforcement learning theories, learning is driven by errors between predicted and actual US (prediction errors) which are thought to be represented by the activity of DANs. Indeed, in many model organisms, the responses of modulatory neurons have been shown to be adaptive, including monkeys, rodents and insects. Despite recent progress the basic principles by which DAN activity is adaptively regulated and teaching signals are computed are not well understood (Eschbach, 2020).

A prerequisite for the adaptive regulation of modulatory neuron activity is convergence of afferent pathways that convey information about received US with feedback pathways that convey information about previous experiences. A comprehensive synaptic-resolution connectivity map of the feedback circuits that regulate modulatory neurons would provide a basis for understanding how learning is adaptively regulated by prior learning, but it has previously been out of reach (Eschbach, 2020).

Insects, especially in their larval stages, have small and compact brains that have recently become amenable to large-scale electron microscopy (EM) circuit mapping. Both adult and larval insect stages possess a brain center that is essential for associative learning, the MB. The MB contains neurons called Kenyon cells (KCs) that sparsely encode CS, MB modulatory neurons (collectively called MB input neurons, MBINs) that provide the teaching signals and MB output neurons (MBONs) whose activity represents learnt valences of stimuli. In the Drosophila larva, most modulatory neurons are DANs, some are octopaminergic neurons (OANs) and some have unidentified neurotransmitters (simply called MBINs). Modulatory neurons and MBONs project axon terminals and dendrites, respectively, onto the KC axons in a tiled manner, defining MB compartments, in both adult and larval Drosophila. In adult Drosophila, it has been shown that coactivation of KCs and DANs reduces the strength of the KC-MBON synapse in that compartment. Different compartments have been implicated in the formation of distinct types of memories, for example, aversive and appetitive, or short and long term. However, despite a good understanding of the structure and function of the core components of the MB in both adult and larval Drosophila, the circuits presynaptic to modulatory neurons that regulate their activity have remained relatively uncharacterized (Eschbach, 2020).

This study therefore reconstructed all neurons presynaptic to all modulatory neurons in an EM volume that spans the entire nervous system of a first instar Drosophila larva, in which all the core components of the MB were previously reconstructed. This study also determined which individual modulatory neurons are activated by punishments and reconstructed their afferent US pathways from nociceptive and mechanosensory neurons. The neurotransmitter profiles of some of the neurons in the network were characterized and some of the identified structural connections were functionally confirmed. Finally, a model was developed of the circuit constrained by the connectome, the neurotransmitter data and the functional data, and it was used to explore the computational advantages offered by the recently discovered architectural motifs for performing distinct learning tasks (Eschbach, 2020).

Modulatory neurons (for example, DANs) are key components of higher-order circuits for adaptive behavioral control, and they provide teaching signals that drive memory formation and updating. This study provides a synaptic-resolution connectivity map of a recurrent neural network that regulates the activity of modulatory neurons in a higher-order learning center, the Drosophila larval MB. Some of the recently identified structural pathways were functionally tested, and a model of the circuit was developed to explore the roles of these motifs in different learning tasks (Eschbach, 2020).

A large population was discovered of 61 feedback neuron pairs that provide one- and/or two-step feedback from the MBONs to modulatory neurons. Strikingly, it was found that many modulatory neurons receive more than 50% of their total dendritic input from feedback pathways. These results suggest that prior memories as represented by the pattern of MBON activity can strongly influence modulatory neuron activity (Eschbach, 2020).

Learning and memory systems in vertebrates and insects are often organized into distinct compartments implicated in forming distinct types of memories (for example, aversive and appetitive or short and long term). Interestingly, it was found that the majority of the discovered feedback pathways link distinct memory systems, suggesting that the MB functions as an interconnected ensemble during learning. Thus, prior memories formed about an odor in one compartment can influence the formation and updating of distinct types of memories about that odor in other compartments (Eschbach, 2020).

In adult Drosophila, functional connections between some MBONs and DANs have been reported, and some have been shown to play a role in short-term memory formation, long-term memory consolidation, extinction and reconsolidation, or in synchronizing DAN ensemble activity in a context-dependent manner. In some cases, direct MBON-to-DAN connections have been demonstrated. Although direct connections from several MBONs onto DANs exist in the larva, this study found that indirect connections via the feedback neurons account for a much larger fraction of a modulatory neuron's dendritic input than direct MBON synapses. This suggests that adaptive DAN responses may be largely driven by such indirect feedback (Eschbach, 2020).

Some of the one-step within-compartment feedback motifs that were found are analogous to the feedback motifs so far described for the DANs in the vertebrate midbrain. Although the diversity and the inputs of striatal feedback neurons have not yet been fully explored, in the future it will be interesting to determine whether many of the striatal feedback neurons also link distinct memory systems (Eschbach, 2020).

The use of internal predictions can dramatically increase the flexibility of a learning system. This study reveals candidate circuit motifs that could compute integrated predicted value signals across appetitive and aversive memory systems. A prominent motif that was identified is convergence of excitatory and inhibitory connections from MBONs from compartments of opposite valence onto DANs. In naive animals, odor-evoked MBON excitation in all compartments is thought to be similar. However, associative learning selectively depresses conditioned odor drive to MBONs in compartments where modulatory neuron activation has been paired with the odor. It is proposed that by comparing the conditioned odor-evoked MBON excitation in compartments of opposite valence via cross-compartment feedback connections, modulatory neurons compute an integrated predicted value signal across appetitive and aversive domains (Eschbach, 2020).

Convergence of feedback and US pathways could allow the computation of prediction errors An important aspect of reinforcement learning theories is the idea that modulatory neurons compare predicted and actual US (to compute so-called prediction errors) and drive memory formation or extinction depending on the sign of the prediction error. Although Drosophila modulatory neurons have not yet been directly shown to represent prediction errors, adult and larval Drosophila are capable of extinction, and the current study reveals candidate motifs that could support the comparison of expected and actual US. Modulatory neurons were found to receive convergent input from feedback pathways from MBONs and from US pathways. Modulatory neurons could therefore potentially compute prediction errors by comparing inhibitory drive from the feedback pathways with the excitatory drive from the US pathways, or vice versa. Consistent with this idea, some DANs were observed in this model that are inhibited by US alone and activated by CS+ alone, or vice versa (Eschbach, 2020).

This study also reveals that US pathways and feedback pathways converge at two levels: not only at the modulatory neurons themselves, but also at the FB2Ns. Actual and expected outcomes could therefore also be compared by FB2Ns. A recent study in the mouse ventral tegmental area has found that some pre-DAN neurons encoded only actual or only expected reward, whereas others encoded both variables. Thus, both in vertebrates and in insects, comparing predicted and actual outcomes may be a complex computation involving multiple levels of integration that eventually converge onto an ensemble of modulatory neurons (Eschbach, 2020).

An assumption in many reinforcement learning models is that all modulatory neurons receive a global scalar reward prediction error signal. The current study was able to analyze the comprehensive set of inputs of every individual uniquely identifiable modulatory neuron in a learning center. This revealed that each modulatory neuron receives a unique set of feedback inputs that could enable each neuron to compute a unique set of features. Consistent with this, a diversity of adaptive response types in the modulatory neurons was observed in this model This suggests that instead of computing a single global reward prediction error that is distributed to all modulatory neurons, the network uses a range of distinct compartmentalized and distributed teaching signals (Eschbach, 2020).

The connectivity and modeling studies revealed two architectural features of the circuit that provide input to the modulatory neurons that increase its performance and flexibility on learning tasks. The first is the multilevel feedback architecture that includes not only the previously known direct MBON feedback, but also multiple levels of indirect feedback. The second is the extensive set of cross-compartment connections. Modeling suggests that these motifs support improved performance on complex tasks that require the computation of variables such as predictions, prediction errors and context (Eschbach, 2020).

In summary, this study presents a complete circuit diagram of a recurrent network that computes teaching signals in a biological system, providing insights into the architectural motifs that increase its computational power and flexibility. The connectome-constrained model provides numerous predictions that can be tested in the future in a tractable model organism, for which genetic tools can be generated to monitor and manipulate individual neurons. The connectome, together with the functional and modeling studies, therefore provides exciting opportunities for elucidating the biological implementation of reinforcement learning algorithms (Eschbach, 2020).

Localized inhibition in the Drosophila mushroom body
Amin, H., Apostolopoulou, A. A., Suarez-Grimalt, R., Vrontou, E. and Lin, A. C. (2020). Elife 9. PubMed ID: 32955437

Many neurons show compartmentalized activity, in which activity does not spread readily across the cell, allowing input and output to occur locally. However, the functional implications of compartmentalized activity for the wider neural circuit are often unclear. This problem was addressed in the Drosophila mushroom body, whose principal neurons, Kenyon cells, receive feedback inhibition from a non-spiking interneuron called APL. This study used local stimulation and volumetric calcium imaging to show that APL inhibits Kenyon cells' dendrites and axons, and that both activity in APL and APL's inhibitory effect on Kenyon cells are spatially localized (the latter somewhat less so), allowing APL to differentially inhibit different mushroom body compartments. Applying these results to the Drosophila hemibrain connectome predicts that individual Kenyon cells inhibit themselves via APL more strongly than they inhibit other individual Kenyon cells. These findings reveal how cellular physiology and detailed network anatomy can combine to influence circuit function (Amin, 2020).

Input Connectivity Reveals Additional Heterogeneity of Dopaminergic Reinforcement in Drosophila
Otto, N., Pleijzier, M. W., Morgan, I. C., Edmondson-Stait, A. J., Heinz, K. J., Stark, I., Dempsey, G., Ito, M., Kapoor, I., Hsu, J., Schlegel, P. M., Bates, A. S., Feng, L., Costa, M., Ito, K., Bock, D. D., Rubin, G. M., Jefferis, G. and Waddell, S. (2020). Curr Biol. PubMed ID: 32619479

Different types of Drosophila dopaminergic neurons (DANs) reinforce memories of unique valence and provide state-dependent motivational control. Prior studies suggest that the compartment architecture of the mushroom body (MB) is the relevant resolution for distinct DAN functions. This study used a recent electron microscope volume of the fly brain to reconstruct the fine anatomy of individual DANs within three MB compartments. The 20 DANs of the γ5 compartment, at least some of which provide reward teaching signals, can be clustered into 5 anatomical subtypes that innervate different regions within γ5. Reconstructing 821 upstream neurons reveals input selectivity, supporting the functional relevance of DAN sub-classification. Only one PAM-γ5 DAN subtype γ5(fb) receives direct recurrent feedback from γ5β'2a mushroom body output neurons (MBONs) and behavioral experiments distinguish a role for these DANs in memory revaluation from those reinforcing sugar memory. Other DAN subtypes receive major, and potentially reinforcing, inputs from putative gustatory interneurons or lateral horn neurons, which can also relay indirect feedback from MBONs. The single aversively reinforcing PPL1-γ1pedc DAN was similarly reconstructed. The γ1pedc DAN inputs mostly differ from those of γ5 DANs and they cluster onto distinct dendritic branches, presumably separating its established roles in aversive reinforcement and appetitive motivation. Tracing also identified neurons that provide broad input to γ5, β'2a, and γ1pedc DANs, suggesting that distributed DAN populations can be coordinately regulated. These connectomic and behavioral analyses therefore reveal further complexity of dopaminergic reinforcement circuits between and within MB compartments (Otto, 2020).

Identification of Dopaminergic Neurons That Can Both Establish Associative Memory and Acutely Terminate Its Behavioral Expression
Schleyer, M., Weiglein, A., Thoener, J., Strauch, M., Hartenstein, V., Kantar Weigelt, M., Schuller, S., Saumweber, T., Eichler, K., Rohwedder, A., Merhof, D., Zlatic, M., Thum, A. S. and Gerber, B. (2020). J Neurosci 40(31): 5990-6006. PubMed ID: 32586949

An adaptive transition from exploring the environment in search of vital resources to exploiting these resources once the search was successful is important to all animals. The neuronal circuitry that allows larval Drosophila melanogaster of either sex to negotiate this exploration-exploitation transition was examined. This was done by combining Pavlovian conditioning with high-resolution behavioral tracking, optogenetic manipulation of individually identified neurons, and EM data-based analyses of synaptic organization. Optogenetic activation of the dopaminergic neuron DAN-i1 was found to both establish memory during training and acutely terminate learned search behavior in a subsequent recall test. Its activation leaves innate behavior unaffected, however. Specifically, DAN-i1 activation can establish associative memories of opposite valence after paired and unpaired training with odor, and its activation during the recall test can terminate the search behavior resulting from either of these memories. These results further suggest that in its behavioral significance DAN-i1 activation resembles, but does not equal, sugar reward. Dendrogram analyses of all the synaptic connections between DAN-i1 and its two main targets, the Kenyon cells and the mushroom body output neuron MBON-i1, further suggest that the DAN-i1 signals during training and during the recall test could be delivered to the Kenyon cells and to MBON-i1, respectively, within previously unrecognized, locally confined branching structures. This would provide an elegant circuit motif to terminate search on its successful completion (Schleyer, 2020).

Visual input into the Drosophila melanogaster mushroom body
Li, J., Mahoney, B. D., Jacob, M. S. and Caron, S. J. C. (2020). Cell Rep 32(11): 108138. PubMed ID: 32937130

The patterns of neuronal connectivity underlying multisensory integration, a fundamental property of many brains, remain poorly characterized. The Drosophila melanogaster mushroom body-an associative center-is an ideal system to investigate how different sensory channels converge in higher order brain centers. The neurons connecting the mushroom body to the olfactory system have been described in great detail, but input from other sensory systems remains poorly defined. This study used a range of anatomical and genetic techniques to identify two types of input neurons that connect visual processing centers-the lobula and the posterior lateral protocerebrum-to the dorsal accessory calyx of the mushroom body. Together with previous work that described a pathway conveying visual information from the medulla to the ventral accessory calyx of the mushroom body, this study defines a second, parallel pathway that is anatomically poised to convey information from the visual system to the dorsal accessory calyx (Li, 2020).

Sensory systems use different strategies to detect specific physical features of the outside world. For instance, the olfactory system contains many different types of sensory neuron that are each specialized in detecting a specific class of volatile chemicals. Through only two neuronal layers, olfactory information-the identity of an odor and its concentration-is relayed to higher brain centers. In contrast, the visual system contains far fewer types of sensory neuron, but through numerous neuronal layers, it relays a range of highly processed information-for instance, color, brightness, motion, and shape-to higher brain centers. Thus, higher brain centers have to integrate different types of processed information, bind that information into a coherent representation of the outside world, and use such representations to guide behavior. How higher brain centers achieve this feat remains largely unknown. This gap in knowledge mainly stems from the fact that higher brain centers are formed by a large number of neurons and that the projection neurons conveying information from different sensory systems to these centers often remain poorly characterized. This makes it difficult to understand whether there are specific patterns of neuronal connectivity that enable multisensory integration and what the nature of these patterns are. Deciphering the fundamental neuronal mechanisms that underlie multisensory integration requires a model system such as the Drosophila melanogaster mushroom body, which consists of a relatively small number of neurons whose connections can be charted reliably (Li, 2020).

The Drosophila mushroom body is formed by ∼2,000 neurons-called the Kenyon cells-and has long been studied for its essential role in the formation of olfactory associative memories. The identity of the projection neurons that connect the olfactory system to the mushroom body-and the way Kenyon cells integrate input from these neurons-has been characterized in great detail, highlighting fundamental connectivity patterns that enable this higher brain center to represent olfactory information efficiently. Evidence in Drosophila melanogaster shows that the mushroom body is more than an olfactory center, as it is also required for the formation of visual and gustatory associative memories. However, the identity of the neurons that connect the mushroom body to other sensory systems remains poorly characterized. Thus, a first step toward understanding how the mushroom body integrates multisensory information is to identify such non-olfactory mushroom body input neurons and the genetic tools necessary to manipulate these neurons (Li, 2020).

The mushroom body receives its input through its calyx and sends its output through its lobes. The calyx-a morphologically distinct neuropil containing the synapses formed between projection neurons and Kenyon cells-can be divided into four, non-overlapping regions: one main calyx as well as three accessory calyces named the dorsal, lateral, and ventral accessory calyces. The five output lobes-the α, α', β, β', and γ lobes-contain the synapses formed between Kenyon cells, mushroom body output neurons, and dopaminergic neurons. With respect to these input and output regions, Kenyon cells can be divided into seven distinct types. Of these seven types, five types-the α/βc, α/βs, α'/β'ap, α'/β'm, and γmain Kenyon cells-extend their dendrites only into the main calyx and their axons along one or two lobes. Most of the neurons that project to the main calyx emerge from the antennal lobe, the primary olfactory center in the Drosophila brain. Thus, α/βc, α/βs, α'/β'ap, α'/β'm, and γmain Kenyon cells receive input primarily from the olfactory system (Li, 2020).

In contrast, the two other classes of Kenyon cells do not extend their dendrites into the main calyx. Instead, the α/βp Kenyon cells extend their dendrites into the dorsal accessory calyx-avoiding completely the main, lateral, and ventral accessory calyces-and their axons along the α and β lobes. Likewise, the γd Kenyon cells extend their dendrites exclusively into the ventral accessory calyx and their axons along the γ lobe. Thus, both the α/βp and γd Kenyon cells are anatomically poised to receive non-olfactory input. There is evidence suggesting that the ventral accessory calyx receives input from the medulla, a region of the optic lobe that specializes in processing brightness and color. Furthermore, a recent study suggests that the dorsal accessory calyx is a multisensory center that integrates input from multiple sensory pathways, including the olfactory, gustatory, and visual systems (Li, 2020).

This study reports a strategy that uses a combination of genetic tools-including transgenic lines that drive expression in few neurons and a photo-labeling technique used to identify individual neurons and their pre-synaptic partners-to characterize the input neurons of the α/βp Kenyon cells. Two types of mushroom body input neuron were identified in that, together, form about half of the total input the α/βp Kenyon cells receive in the dorsal accessory calyx. The first neuronal type-henceforth referred to as LOPNs-consists of a neuron that projects from the lobula, a region of the optic lobe specialized in detecting visual features, such as shape and motion. The second type of neuron-henceforth referred to as PLPPNs-consists of projection neurons that emerge from the posterior lateral protocerebrum, a brain region that receives input from the optic lobe. Interestingly, LOPN and PLPPNs do not project to the ventral accessory calyx and do not connect to the γd Kenyon cells. Based on these findings, it is concluded that there are two parallel pathways that convey visual information to the mushroom body: a pathway projecting from the medulla to the γd Kenyon cells and another pathway projecting from the lobula and posterior lateral protocerebrum to the α/βp Kenyon cells (Li, 2020).

This study has identified and characterized neurons projecting to the dorsal accessory calyx of the mushroom body and show that these neurons are pre-synaptic to the α/βp Kenyon cells. Using a combination of genetic and anatomical techniques, it was possible to distinguish two different types of projection neuron: LOPN projecting from the lobula-an area of the optic lobe processing visual features, such as shape and motion-and the PLPPNs projecting from the posterior lateral protocerebrum. Although the posterior lateral protocerebrum remains poorly characterized in D. melanogaster, evidence from other insects shows that this brain region receives input from the optic lobe. Interestingly, it was found that the dendrites formed by the PLPPNs in the posterior lateral protocerebrum are in close proximity to neurons that project from the ventral medulla. Based on these results-and considering insights from the connectome-it is estimated that LOPNs and PLPPNs account for half of total input that α/βp Kenyon cells receive in the dorsal accessory calyx. LOPNs and PLPPNs do not extend axonal terminals into the ventral accessory calyx, the other calyx known to receive visual input, but rather extend axonal terminals into the dorsal accessory calyx and into the superior lateral protocerebrum. Likewise, the α/βp Kenyon cells do not connect to the visual projection neurons that are associated with the ventral accessory calyx. These findings suggest that the visual system is connected to the mushroom body via two parallel pathways: the α/βp Kenyon cells receive input from the lobula and the posterior lateral protocerebrum, whereas the γd Kenyon cells receive input directly from the medulla. Further functional studies are necessary to determine what kind of visual information is processed by the α/βp Kenyon cells (Li, 2020).

In Drosophila melanogaster, the mushroom body has long been studied as an olfactory processing center. However, evidence from many insects, including the honeybee Apis mellifera, shows that the mushroom body integrates sensory information across different modalities. In honeybees, the input region of the mushroom body, also called the calyx, is divided into different layers, and each layer receives input from either the olfactory or visual system. Because the dendrites of Kenyon cells are also restricted to specific layers, it has been suggested that, in the honeybee, multisensory integration does not occur at the level of individual Kenyon cells but rather at the population level. Although the honeybee mushroom body differs greatly from the Drosophila mushroom body-it contains about a hundred times as many Kenyon cells and its input region is divided in multiple complex layers-it appears that both mushroom bodies share a common fundamental connectivity principle: the segregation of input based on sensory modality. This connectivity mechanism is immediately apparent in the structural organization of the Drosophila melanogaster mushroom body: the Kenyon cells receiving input from the olfactory system all extend their dendrites into the main calyx, whereas the Kenyon cells receiving input from the visual system extend their dendrites either in the dorsal accessory calyx or the ventral accessory calyx. Many studies have demonstrated that the Kenyon cells that process olfactory information-those associated with the main calyx-integrate input broadly across the different types of olfactory projection neuron. Interestingly, it appears that the Kenyon cells that process visual information are wired differently (Li, 2020).

A thorough understanding is available of how olfactory Kenyon cells integrate input from the antennal lobe: most Kenyon cells receive, on average, input from seven projection neurons, and the projection neurons connecting to the same Kenyon cell share no apparent common features. Theoretical studies have shown that this random-like connectivity pattern enables the mushroom body to form sparse and decorrelated odor representations and thus maximizes learning. Randomization of sensory input is a connectivity pattern that is well suited for representing olfactory information-as an odor is encoded based on the ensemble of olfactory receptors it activates-and might not be suitable for representing visual information. Indeed, the results of this study suggest that specific visual features-the signals processed by the medulla and the ones processed by the lobula and the posterior lateral protocerebrum-need to be represented by two separate subpopulations of Kenyon cells. This observation mirrors anatomical studies of the honeybee brain: the neurons projecting from the lobula terminate in a different layer than the neurons projecting from the medulla. This arrangement might be essential to preserve distinct visual features when forming associative memories. Functional and behavioral studies are required to determine whether indeed the mushroom body represents multisensory stimuli in this manner (Li, 2020).

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Localized inhibition in the Drosophila mushroom body
Amin, H., Apostolopoulou, A. A., Suarez-Grimalt, R., Vrontou, E. and Lin, A. C. (2020). Localized inhibition in the Drosophila mushroom body. Elife 9. PubMed ID: 32955437

Many neurons show compartmentalized activity, in which activity does not spread readily across the cell, allowing input and output to occur locally. However, the functional implications of compartmentalized activity for the wider neural circuit are often unclear. This problem was addressed in the Drosophila mushroom body, whose principal neurons, Kenyon cells, receive feedback inhibition from a non-spiking interneuron called APL. This study used local stimulation and volumetric calcium imaging to show that APL inhibits Kenyon cells' dendrites and axons, and that both activity in APL and APL's inhibitory effect on Kenyon cells are spatially localized (the latter somewhat less so), allowing APL to differentially inhibit different mushroom body compartments. Applying these results to the Drosophila hemibrain connectome predicts that individual Kenyon cells inhibit themselves via APL more strongly than they inhibit other individual Kenyon cells. These findings reveal how cellular physiology and detailed network anatomy can combine to influence circuit function (Amin, 2020).

This study has shown that activity in APL is spatially restricted intracellularly for both sensory-evoked and local artificial stimulation. This local activity in APL translates into a spatially non-uniform inhibitory effect on Kenyon cells that is strongest locally and becomes weaker farther from the site of APL stimulation. Finally, combining physiological and anatomical data -- APL's estimated space constant and the spatial arrangement of KC-APL and APL-KC synapses -- predicts that each Kenyon cell disproportionately inhibits itself more than other individual Kenyon cells (Amin, 2020).

This study showed that APL can locally inhibit Kenyon cells in multiple locations in the mushroom body. Remarkably, inhibition of Ca2+ influx in Kenyon cell axons could be stronger closer to the axon initial segment (in the posterior peduncle than farther from it, for example, stronger at the lower vertical lobe than the tip of the vertical lobe, both when stimulating APL with ATP or when directly applying GABA. At first glance, this observation is puzzling given the direction of action potential travel. GABA should act on Kenyon cells by suppressing depolarization through shunting inhibition in both dendrites and axons, as the GABAA receptor Rdl is expressed in both. Therefore, the observation of stronger proximal than distal inhibition appears to suggest that as action potentials travel from the axon initial segment toward the distal tip of the axon, they can enter a zone of shunting inhibition and be suppressed, yet recover on the other side. Such a scenario could occur if depolarization is suppressed enough to reduce voltage-gated Ca2+ influx in a local zone, yet remains sufficient on the other side of the inhibitory zone to trigger enough voltage-gated Na+ channels to regenerate the action potential. However, this interpretation seems unlikely. More likely, local inhibition might particularly suppress Ca2+ influx rather than depolarization, perhaps by acting through GABAB receptors; Kenyon cells express GABABR1 and GABABR2 and APL inhibits KCs partly via GABAB receptors, although their subcellular localization is unknown. Given that synaptic vesicle release requires Ca2+ influx, such inhibition would still locally suppress Kenyon cell synaptic output (Amin, 2020).

Local inhibition of Kenyon cell output predicts that activity of MBONs near the site of APL activation would be more strongly inhibited than MBONs far away. This prediction may be tested in future experiments, for example locally stimulating APL in the tip of the vertical lobe and comparing the inhibitory effect on MBONs in nearby compartments like α3 and α'3 vs. on MBONs in distant compartments like γ5 and β2 (Amin, 2020).

While APL inhibits Kenyon cells locally, the inhibitory effect spreads somewhat more widely than APL's own activity, though weakly. Local GABA application produces similar results to locally activating APL with ATP, suggesting that GCaMP6f signals in APL accurately predict GABA release. How can APL inhibit Kenyon cells where it itself is not active? Wider inhibition when inhibiting Kenyon cell dendrites can be easily explained as blocking action potentials, but the wider inhibition when inhibiting the axons is more puzzling. It is speculated that this result might arise from wider network activity. For example, Kenyon cells form recurrent connections with DPM and dopaminergic neurons and form synapses and gap junctions on each other. Through such connections, an odor-activated Kenyon cell might excite a neighboring Kenyon cell's axon; the neighbor might passively spread activity both forward and backward or, not having fired and thus not being in a refractory period, it might even be excited enough to propagate an action potential back to the calyx. Alternatively, Kenyon cells indirectly excite antennal lobe neurons in a positive feedback loop. In these scenarios, locally puffing GABA or activating APL artificially in the vertical lobe tip would block the wider network activity, thus reducing Ca2+ influx in the calyx. Although the calyx was not activated when stimulating Kenyon cells in the vertical lobe tip, this might be because simultaneous activation of all Kenyon cells (but not odor-evoked activation of ~10% of Kenyon cells) drives strong-enough local APL activation to block wider network activity. Future experiments may test these possibilities (Amin, 2020).

By combining physiological measurements of localized activity with the detailed anatomy of the hemibrain connectome, a model was built that predicts that the average Kenyon cell inhibits itself more than it inhibits other individual Kenyon cells. This prediction is supported by previous experimental results that some Kenyon cells can inhibit some Kenyon cells more than others, and that an individual Kenyon cell can inhibit itself. The model goes beyond these results in predicting that the average Kenyon cell actually preferentially inhibits itself, and by explaining how differential inhibition can arise from local activity in APL and the spatial arrangement of KC-APL and APL-KC synapses (Amin, 2020).

Note that these results do not contradict previous findings that Kenyon cell lateral inhibition is all-to-all. The finding of all-to-all inhibition was based on findings that whereas blocking synaptic output from all Kenyon cells vastly increases Kenyon cell odor responses (by blocking negative feedback via APL), blocking output from one subset of Kenyon cells has no effect on (for α'β' and γ Kenyon cells), or only weakly increases (for αβ Kenyon cells), odor responses of that subset. This finding is consistent with findings that predict only preferential, not exclusive, self-inhibition. For example, while blocking output from only γ Kenyon cells would remove γ-to-γ inhibition, γ Kenyon cells (only 1/3 of all Kenyon cells) should still get enough lateral inhibition from the other 2/3 of Kenyon cells to suppress their activity to normal levels (Amin, 2020).

The findings show that localized activity within APL has two broader implications for mushroom body function. First, local activity in APL leads to stronger inhibition of Kenyon cells nearby than far away, to the point that different compartments of the mushroom body lobes defined by dopaminergic and output neuron innervation can receive different inhibition. This local inhibition would allow the single APL neuron to function effectively as multiple inhibitory interneurons, much like mammalian and fly amacrine cells. Each 'sub-neuron' of APL could locally modulate the function of one mushroom body 'compartment', that is, a unit of dopaminergic neurons/Kenyon cells / mushroom body output neurons. Different compartments are innervated by different dopaminergic neurons (e.g., reward vs. punishment) and different mushroom body output neurons (e.g., avoid vs. approach), and they govern synaptic plasticity and hence learning by different rules (e.g., different speeds of learning/forgetting). Thus, APL could locally modulate different compartment-specific aspects of olfactory learning, especially given that different regions of APL respond differently to dopamine and electric shock punishment. If such local inhibition is important for learning, the fact that spatial attenuation of APL's inhibitory effect is gradual and incomplete could explain why mushroom body compartments are arranged in their particular order, with reward and punishment dopaminergic neurons segregated into the horizontal and vertical lobes, respectively. Under this scenario, APL would serve two distinct, spatially segregated functions: enforcing Kenyon cell sparse coding in the calyx, and modulating learning in the compartments of the lobes (Amin, 2020).

Second, the finding of disproportionate self-inhibition compared to other-inhibition provides a new perspective on APL's function. Inhibition from APL sparsens and decorrelates Kenyon cell odor responses to enhance learned odor discrimination but in general, decorrelation is better served by all-to-all lateral inhibition than by self-inhibition. Self-inhibition does help decorrelate population activity by pushing some neurons' activity below spiking threshold; this could occur if APL can be activated by subthreshold activity in Kenyon cells, for example, from KC-APL synapses in Kenyon cell dendrites. However, this effect of self-inhibition is better thought of, not as decorrelation per se, but rather as gain control, effectively equivalent to adjusting the threshold or gain of excitation according to the strength of stimulus. Of course, lateral inhibition is still a strong force in the mushroom body: given that there are ~2000 Kenyon cells, the sum total lateral inhibition that an individual Kenyon cell receives would still be stronger than its own self-inhibition, even with the predicted imbalance. Why might the predicted 'bonus' self-inhibition be useful? Beyond its role in sparse coding, APL inhibition is also thought to function as a gating mechanism to suppress olfactory learning; for such a function it would make sense for Kenyon cells to disproportionately inhibit themselves. Future work will address how lateral inhibition interacts with other functions for APL in this local feedback circuit (Amin, 2020).

A neural algorithm for Drosophila linear and nonlinear decision-making
Zhao, F., Zeng, Y., Guo, A., Su, H. and Xu, B. (2020). Sci Rep 10(1): 18660. PubMed ID: 33122701

It has been evidenced that vision-based decision-making in Drosophila consists of both simple perceptual (linear) decision and value-based (non-linear) decision. This paper proposes a general computational spiking neural network (SNN) model to explore how different brain areas are connected contributing to Drosophila linear and nonlinear decision-making behavior. First, the SNN model could successfully describe all the experimental findings in fly visual reinforcement learning and action selection among multiple conflicting choices as well. Second, the computational modeling shows that dopaminergic neuron-GABAergic neuron-mushroom body (DA-GABA-MB) works in a recurrent loop providing a key circuit for gain and gating mechanism of nonlinear decision making. Compared with existing models, this model shows more biologically plausible on the network design and working mechanism, and could amplify the small differences between two conflicting cues more clearly. Finally, based on the proposed model, the unmanned aerial vehicle (UAV) could quickly learn to make clear-cut decisions among multiple visual choices and flexible reversal learning resembling to real fly. Compared with linear and uniform decision-making methods, the DA-GABA-MB mechanism helps UAV complete the decision-making task with fewer steps (Zhao, 2020).

A neural circuit arbitrates between persistence and withdrawal in hungry Drosophila
Sayin, S., De Backer, J. F., Siju, K. P., Wosniack, M. E., Lewis, L. P., Frisch, L. M., Gansen, B., Schlegel, P., Edmondson-Stait, A., Sharifi, N., Fisher, C. B., Calle-Schuler, S. A., Lauritzen, J. S., Bock, D. D., Costa, M., Jefferis, G., Gjorgjieva, J. and Grunwald Kadow, I. C. (2019). Neuron 104(3):544-558. PubMed ID: 31471123

In pursuit of food, hungry animals mobilize significant energy resources and overcome exhaustion and fear. How need and motivation control the decision to continue or change behavior is not understood. Using a single fly treadmill, this study shows that hungry flies persistently track a food odor and increase their effort over repeated trials in the absence of reward suggesting that need dominates negative experience. It was further shown that odor tracking is regulated by two mushroom body output neurons (MBONs) connecting the MB to the lateral horn. These MBONs, together with dopaminergic neurons and Dop1R2 signaling, control behavioral persistence. Conversely, an octopaminergic neuron, VPM4, which directly innervates one of the MBONs, acts as a brake on odor tracking by connecting feeding and olfaction. Together, these data suggest a function for the MB in internal state-dependent expression of behavior that can be suppressed by external inputs conveying a competing behavioral drive (Sayin, 2019).

Flexibility is an important factor in an ever in-flux environment, where scarcity and competition are the norm. Without persistence to achieve its goals, however, an animal's strive to secure food, protect its offspring, or maintain its social status is in jeopardy. Therefore, sensory cues related to food or danger often elicit strong impulses. However, these impulses must be strictly controlled to allow for coherent goal-directed behavior and to permit behavioral transitions when sensible. Inhibition of antagonistic behavioral drives at the cognitive and physiological level has been proposed as a major task of a nervous system. Which sensory cues and ultimately which behaviors are prioritized and win depends on the animal's metabolic state, internal motivation, and current behavioral context. How this is implemented at the level of individual neurons, circuit motifs, and mechanisms remains an important open question (Sayin, 2019).

Like most animals, energy-deprived flies prioritize food seeking and feeding behavior. To find food, flies can follow olfactory or visual cues over long distances. External gustatory cues provide information about the type and quality of the eventually encountered food. However, only internal nutrient levels will provide reliable feedback about the quality and quantity of a food source and ultimately suppress food-seeking behaviors. Therefore, food odor, the taste of food, and post-ingestive internal feedback signals induce sequential and partly antagonistic behaviors. Interestingly, chemosensory and internal feedback systems typically mediated by distinct neuromodulators appear to converge in the mushroom body (MB). How neurons and neural circuits signal and combine external and internal cues to maintain or suppress competing behavioral drives is not well understood (Sayin, 2019).

In mammals, norepinephrine (NE) released by a brain stem nucleus, the locus coeruleus, has been implicated in controlling the balance between persistence and action selection. The potential functional counterpart of NE in insects could be octopamine (OA). Flies lacking OA indeed show reduced arousal, for instance upon starvation. Additionally, OA neurons (OANs) gate appetitive memory formation of odors and also modulate taste neurons and feeding behavior. OANs are organized in distinct clusters and project axons to diverse higher brain regions in a cell type-specific manner. The precise roles and important types of OA and NE neurons in state-dependent action selection remain to be elucidated (Sayin, 2019).

Similar to NE and OA, dopamine (DA) is being studied in many aspects of behavioral adaptation and flexibility. Different classes of DA neurons (DANs) innervating primarily the MB signal negative or positive context, or even wrong predictions (Sayin, 2019 and references therein).

This study took advantage of the small number and discrete organization of neuromodulatory neurons in the fly brain to analyze the mechanistic relationship between motivation-dependent persistence in one behavior and the decision to disengage and change to another behavior. Using a single fly spherical treadmill assay, this study found that hungry flies increase their effort to track a food odor with every unrewarded trial. MB output through two identified MBONs (MBON-γ1pedc>α/β and MBON-α2sc) is required for persistent odor tracking. MBON-α2sc provides a MB connection to the lateral horn (LH), where it can modify innate food odor attraction. Furthermore, this study pinpoints a specific type of OAN, VPM4 (ventral paired medial), which connects feeding centers directly to MBON-γ1pedc>α/β and disrupts food odor tracking. Finally, the experimental data suggest that persistent tracking depends on DANs, including PPL1-γ1pedc, and signaling through dopamine receptor Dop1R2 in αβ-type KCs. Based on these results, it is proposed that MB output and a direct external input, depending on internal state and motivation, gradually promote or interrupt ongoing behavior (Sayin, 2019).

What drives gradually increasing persistence in behavior? For the fly, a model is proposed by which a circuit module of KCs, MBONs, and DANs drive gradually increasing odor tracking, which can be efficiently suppressed by extrinsic MBON-innervating feeding-related OANs. Behavioral persistence has been previously analyzed in flies in a different context. For instance, courtship of fly males and copulation with a female are maintained by dopaminergic neurons in the ventral nerve cord, where they counteract GABAergic neurons. In that scenario, DANs in the ventral nerve cord maintain an ongoing behavior and prevent male premature disengagement before successful insemination (Sayin, 2019).

The experimental data also implicate DANs, primarily from within the PPL1 (e.g., PPL1-γ1pedc) and PPL2ab clusters, and Dop1R2 signaling. In particular, inactivation of synaptic output of DANs positive for TH-Gal4 as well as loss of Dop1R2 in αβ-type KCs reduced the increase in odor tracking from trial to trial, while not affecting the speed at first odor stimulation. These data suggest that TH+ DANs promote goal-directed movement, i.e., odor tracking, through a Dop1R2-dependent mechanism in KCs (Sayin, 2019).

MBON-γ1pedc>αβ, which receives dopaminergic input by PPL1-γ1pedc, is required for odor tracking. Moreover, this study also observed a trial-to-trial decrease in odor response of this MBON, matching the dopamine-induced synaptic depression previously observed in MBONs upon learning. Notably, PPL1-γ1pedc activates Dop1R2 in MBON-γ1pedc>αβ, a signal recently found to be critical for appetitive long-term memory. Nevertheless, it appears that, in addition to PPL1-γ1pedc, other DANs regulate behavioral persistence by modulating in particular αβ-KCs. It is intriguing to speculate about a common function of Dop1R2 in the formation of long-lasting aversive memory induced by repeatedly pairing odor with an aversive experience and the behavior examined in this study: increased and persistent expression of a behavior induced by the experience of repeated failure to reach a goal (Sayin, 2019).

The experimental data further implicated MBON-α2sc, which is connected to MBON-γ1pedc>αβ. Calcium imaging data are consistent with an inhibitory interaction between the two MBONs. However, some of the behavioral data and prior imaging data do not support an inhibitory connection. Furthermore, MBON-γ1pedc>αβ projects to other brain regions and downstream targets, and similarly MBON-α2sc receives additional inputs—all of which could be equally or more important for persistent behavior than a direct connection between these two MBONs. Finally, some DANs respond to movement, including PPL1-γ2α'1/MV1. Although no essential role of this particular neuron was found in odor tracking persistence, movement might contribute to the activity of MBONs responding the odorant (Sayin, 2019).

Remarkably, MBON-α2sc connects the MB to neurons within the LH. Thus, it is speculated that the LH might assign an odor to its corresponding behavioral category, such as 'food-related' for vinegar, while the MB acts as a top-down control to gauge the expression of an innate behavior (i.e., tracking an appetitive odor) according to state and experience (Sayin, 2019).

The behavioral data led to the proposal of a circuit model. Using computational modeling, this study tested whether the MB network including DANs and MBONs could, in theory, produce the observed behavior. Indeed, it was found that a simplified recurrent circuit of KCs, DANs, and MBONs can account for the observed behavioral persistence and also the measured MBON-γ1pedc>αβ odor responses. While this model cannot replace experimental evidence, it forms a useful theoretical framework for future studies on the role of the MB in behavioral persistence (Sayin, 2019).

Based on the present data and computational predictions, a model is proposed by which the recurrent circuit architecture of the MB, in addition to storing information for future behavior, is ideally suited to maintain and gradually change ongoing behavior, for instance by modulating output of the LH, according to the animal's internal state and needs (Sayin, 2019).

The use of an olfactory treadmill has allowed dissection of the different aspects of a food search. In particular, how does food and feeding suppress food search if the sensory cue, the odor, is still present? OA-VPM4 connects feeding centers (i.e., SEZ) directly with odor tracking-promoting MBON-γ1pedc>αβ and inhibits its activity suggesting an inhibitory connection between VPM4 and the MBON. Nevertheless, it cannot be excluded that OA-VPM4 signals through multiple mechanisms including OA and possibly other neurotransmitters. In addition, a recent study showed that activation of VPM4 promotes proboscis extension to sugar. Although a direct role in taste detection through pharynx or labellum appears unlikely, it is possible that feeding behavior itself (e.g., lymphatic sugar, food texture, activity of feeding muscles) are detected and/or promoted by these neurons and then brought to the MB. It is proposef that VPM4 is a direct mediator between olfactory-guided food search and the rewarding experience of feeding and related behavior (Sayin, 2019).

The data provide a neural circuit mechanism empowering flies to express and prioritize behavior in a need- and state-dependent manner. It is exciting to speculate that fundamentally similar circuit motifs might exist in NE and DA neuron-containing circuits in the mammalian brain, governing the organization of behavior in a flexible and context-dependent manner by integrating internal and external context. For instance, noradrenergic neurons of the brainstem nucleus of the solitary tract (NST) receive taste information, and input from the gastrointestinal tracts, lungs, and heart. Neurons in the NST project to multiple brain regions including the amygdala, hypothalamus, and insular cortex, all of which receive internal state as well as other sensory information (Sayin, 2019).

The data in the fly provide an experimental and theoretical framework for a better understanding of the fundamental circuit mechanisms underpinning neuromodulation of context-dependent behavioral persistence and withdrawal (Sayin, 2019).

Nitric oxide acts as a cotransmitter in a subset of dopaminergic neurons to diversify memory dynamics
Aso, Y., Ray, R. P., Long, X., Bushey, D., Cichewicz, K., Ngo, T. T., Sharp, B., Christoforou, C., Hu, A., Lemire, A. L., Tillberg, P., Hirsh, J., Litwin-Kumar, A. and Rubin, G. M. (2019). Elife 8. PubMed ID: 31724947

Animals employ diverse learning rules and synaptic plasticity dynamics to record temporal and statistical information about the world. However, the molecular mechanisms underlying this diversity are poorly understood. The anatomically defined compartments of the insect mushroom body function as parallel units of associative learning, with different learning rates, memory decay dynamics and flexibility. This study shows that nitric oxide (NO) acts as a neurotransmitter in a subset of dopaminergic neurons in Drosophila. NO's effects develop more slowly than those of dopamine and depend on soluble guanylate cyclase in postsynaptic Kenyon cells. NO acts antagonistically to dopamine; it shortens memory retention and facilitates the rapid updating of memories. The interplay of NO and dopamine enables memories stored in local domains along Kenyon cell axons to be specialized for predicting the value of odors based only on recent events. These results provide key mechanistic insights into how diverse memory dynamics are established in parallel memory systems (Aso, 2019).

An animal's survival in a dynamically changing world depends on storing distinct sensory information about their environment as well as the temporal and probabilistic relationship between those cues and punishment or reward. Thus it is not surprising that multiple distributed neuronal circuits in the mammalian brain have been shown to process and store distinct facets of information acquired during learning. Even a simple form of associative learning such as fear conditioning induces enduring changes, referred to as memory engrams, in circuits distributed across different brain areas. Do these multiple engrams serve different mnemonic functions, what molecular and circuit mechanisms underlie these differences, and how are they integrated to control behavior? Localizing these distributed engrams, understanding what information is stored in each individual memory unit and how units interact to function as one network are important but highly challenging problems. The Drosophila mushroom body (MB) provides a well-characterized and experimentally tractable system to study parallel memory circuits. Olfactory memory formation and retrieval in insects requires the MB. In associative olfactory learning, exposure to an odor paired with a reward or punishment results in formation of a positive- or negative-valence memory, respectively. In the MB, sensory stimuli are represented by the sparse activity of ~2,000 Kenyon cells (KCs). Each of 20 types of dopaminergic neurons (DANs) innervates compartmental regions along the parallel axonal fibers of the KCs. Similarly, types of mushroom body output neurons (MBONs) arborize their dendrites in specific axonal segments of the KCs; together, the arbors of the DANs and MBONs define the compartmental units of the MB. Activation of individual MBONs can cause behavioral attraction or repulsion, depending on the compartment in which their dendrites arborize, and MBONs appear to use a population code to govern behavior (Aso, 2019).

A large body of evidence indicates that these anatomically defined compartments of the MB are also the units of associative learning. Despite the long history of behavioral genetics in fly learning and memory, many aspects of the signaling pathways governing plasticity -- especially whether they differ between compartments -- remain poorly understood. Nevertheless, dopaminergic neurons and signaling play a key role in all MB compartments, and flies can be trained to form associative memories by pairing the presentation of an odor with stimulation of a single dopaminergic neuron. Punishment or reward activates distinct sets of DANs that innervate specific compartments of the MB. Activation of the DAN innervating a MB compartment induces enduring depression of KC-MBONs synapses in those specific KCs that were active in that compartment at the time of dopamine release. Thus, which compartment receives dopamine during training appears to determine the valence of the memory, while which KCs were active during training determines the sensory specificity of the memory (Aso, 2019).

Compartments operate with distinct learning rules. Selective activation of DANs innervating specific compartments has revealed that they can differ extensively in their rates of memory formation, decay dynamics, storage capacity, and flexibility to learn new associations. For instance, the dopaminergic neuron PAM-α1 can induce a 24h memory with a single 1-minute training session, whereas PPL1-α3 requires ten repetitions of the same training to induce a 24h memory. PPL1-γ1pedc (aka MB-MP1) can induce a robust short-lasting memory with a single 10-second training, but cannot induce long-term memories even after 10 repetitions of a 1-minute training. PAM-α1 can write a new memory without compromising an existing memory, whereas PPL1-γ1pedc extinguishes the existing memory when writing a new memory. What molecularand cellular differences are responsible for the functional diversity of these compartments? Some differences might arise from differences among KC cell types, but memory dynamics are different even between compartments that lie along the axon bundles of the same Kenyon cells (for example, α1 and α3). This paper shows that differences in memory dynamics between MB compartments can arise from the deployment of distinct cotransmitters by the DAN cell types that innervate them (Aso, 2019).

Evidence from a wide range of organisms establishes that dopaminergic neurons often release a second neurotransmitter, but the role of such cotransmitters in diversifying neuronal signaling is much less clear. In rodents, subsets of dopaminergic neurons co-release glutamate or GABA. In mice and Drosophila, single-cell expression profiling reveals expression of diverse neuropeptides in dopaminergic neurons. EM connectome studies of the mushroom body in adult and larval Drosophila reveal the co-existence of small-clear-core and large- dense-core synaptic vesicles in individual terminals of dopaminergic neurons; moreover, the size of the observed large-dense-core 02 vesicles differs between DAN cell types (Aso, 2019).

This study found that NOS, the enzyme that synthesizes NO, was located in the terminals of a subset of DAN cell types. NOS catalyzes the production of nitric oxide (NO) from L-arginine. Drosophila NOS is regulated by Ca2+/calmodulin, raising the possibility that NO synthesis might be activity dependent. Furthermore, the localization of the NOS1 protein in the axonal terminals of DANs is consistent with NO serving as a cotransmitter. The conclusion that NO acts as a neurotransmitter is supported by the observation that NO signaling requires the presence of a putative receptor, soluble guanylate cyclase, in the postsynaptic Kenyon cells. This role contrasts with the proposed cell-autonomous action of NOS in the ellipsoid body, in which NO appears to target proteins within the NOS-expressing ring neurons themselves, rather than conveying a signal to neighboring cells. The valence-inversion phenotype observed when PPL1-γ1pedc was optogenetically activated in a dopamine-deficient background can be most easily explained if NO induces synaptic potentiation between odor-activated KCs and their target MBONs. Modeling work is consistent with this idea, but testing this idea and 19 other possible mechanisms for NO action will require physiological experiments (Aso, 2019).

During olfactory learning, the concentration of Ca2+ in KC axons represents olfactory information. The coincidence of a Ca2+ rise in spiking KCs and activation of the G-protein-coupled Dop1R1 dopamine receptor increases adenylyl cyclase activity. The resultant cAMP in turn activates protein kinase A, a signaling cascade that is important for synaptic plasticity and memory formation throughout the animal phyla. In contrast, when DANs are activated without KC activity, and thus during low intracellular Ca2+ in the KCs, molecular pathways involving the Dop1R2 receptor, Rac1 and Scribble facilitate decay of memory (Aso, 2019).

This study found that NOS in PPL1-γ1pedc shortens memory retention, while facilitating fast updating of memories in response to new experiences. These observations could be interpreted as indicating that NO regulates forgetting. Indeed, NO-dependent effect requires scribble in KCs, a gene previously reported as a component of active forgetting. However, it is an open question whether the signaling pathways for forgetting, which presumably induce recovery from synaptic depression, are related to signaling cascades downstream of NO and guanylate cyclase, which appear to be able to induce memory without prior induction ofsynaptic depression by dopamine. Lack of detectable 1-day memory formation after spaced training with PPL1-γ1pedc can be viewed as a balance between two distinct, parallel biochemical signals, one induced by dopamine and the other by NO, rather than the loss of information (that is, forgetting). Confirming this interpretation will require better understanding of the signaling pathways downstream of dopamine and NO. The search for such pathways will be informed by the prediction from modeling that dopamine and NO may alter two independent parameters that define synaptic weights with a multiplicative interaction (Aso, 2019).

In the vertebrate cerebellum, which has many architectural similarities to the MB, long-term-depression at parallel fiber-Purkinje cell synapses (equivalent to KC-MBON synapses) induced by climbing fibers (equivalent to DANs) can coexist with long-term-potentiation by NO. In this case, the unaltered net synaptic weight results from a balance between coexisting LTD and LTP rather than recovery from LTD. This balance was suggested to play an important role in preventing memory saturation in the cerebellum 59 and allowing reversal of motor learning. In the Drosophila MB, a similar facilitation was observed of reversal learning by NO. The antagonistic roles of NO and synaptic depression may be a yet another common feature of the mushroom body and the cerebellum (Aso, 2019).

Opposing cotransmitters have been observed widely in both invertebrate and vertebrate neurons. A common feature in these cases is that the transmitters have distinct time courses of action. For instance, hypothalamic hypocretin-dynorphin neurons that are critical for sleep and arousal synthesize excitatory hypocretin and inhibitory dynorphin. When they are released together repeatedly, the distinct kinetics of their receptors result in an initial outward current, then little current, and then an inward current in the postsynaptic cells. In line with these observations, this study found that dopamine and NO show distinct temporal dynamics: NO-dependent memory requires repetitive training and takes longer to develop than dopamine-dependent memory. What molecular mechanisms underlie these differences? Activation of NOS may require stronger or more prolonged DAN activation than does dopamine release. Alternatively, efficient induction of the signaling cascade in the postsynaptic KCs might require repetitive waves of NO input. Direct measurements of release of dopamine and NO, and downstream signaling events by novel sensors will be needed to address these open questions (Aso, 2019).

Decades of behavioral genetic studies have identified more than one hundred genes underlying olfactory conditioning in Drosophila. Mutant andtargeted rescue studies have been used to map the function of many memory-related genes encoding synaptic or intracellular signaling proteins (for example, rutabaga, DopR1/dumb, DopR2/DAMB, PKA-C1/DC0, Synapsin, Bruchpilot, Orb2 and Rac1) to specific subsets of Kenyon cells. However, it is largely unknown if these proteins physically colocalize at the same KC synapses to form intracellular signaling cascades. Some of 97 these proteins might preferentially localize to specific MB compartments. Alternatively, they may distribute uniformly along the axon of Kenyon cells, but be activated in only specific compartments. Identification of cell-type-specific cotransmitters in DANs enabled a beginning to the exploration of this question (Aso, 2019).

Optogenetic activation of specific DANs was used to induce memory in specific MB compartments, while manipulating genes in specific types of KCs. This approach allowed mapping and characterization of the function of memory-related genes at a subcellular level. For example, the Gycbeta100B gene, which encodes a subunit of sGC, has been identified as 'memory suppressor gene' that enhances memory retention when pan-neuronally knocked down, but the site of its action was unknown. Gycbeta100B appears to be broadly dispersed throughout KC axons, based on the observed distribution of a Gycbeta100B-EGFP fusion protein. The experiments ectopically expressing NOS in PPL1-α3 DANs that do not normally signal with NO is most easily explained if sGC is available for activation in all MB compartments. What are the molecular pathways downstream to cGMP? How do dopamine and NO signaling pathways interact in regulation of KC synapses? Previous studies and RNA-Seq data suggest several points of possible crosstalk. In cultured KCs from cricket brains, cGMP-dependent protein kinase (PKG) mediates NO-induced augmentation of a Ca2+ channel current. However, no expression of either of the genes encoding Drosophila PKGs (foraging and Pkg21D) was detected in KCs in RNA-Seq studies. On the other hand, cyclic nucleotide-gated channels and the cGMP-specific phosphodiesterase Pde9 are expressed in KCs. Biochemical studies have shown that the activity of sGC is calcium dependent and that PKA can enhance the NO-induced activity of sGC by phosphorylating sGC; sGC isolated from flies mutant for adenylate cyclase, rutabaga, show lower activity than sGC from wild-type brains, suggesting crosstalk between the cAMP and cGMP pathways (Aso, 2019).

All memory systems must contend with a tension between the strength and longevity of the memories they form. The formation of a strong immediate memory interferes with and shortens the lifetimes of previously formed memories, and reducing this interference requires a reduction in initial memory strength that can only be overcome through repeated exposure. Theoretical studies have argued that this tension can be resolved by memory systems that exhibit a heterogeneity of timescales, balancing the need for both fast, labile memory and slow consolidation of reliable memories. The mechanisms responsible for this heterogeneity, and whether they arise from complex signaling within synapses themselves), heterogeneity across brain areas, or both, have not been identified (Aso, 2019).

NO acts antagonistically to dopamine and reduces memory retention while facilitating the rapid updating of memory following a new experience. Viewed in isolation, the NO-dependent reduction in memory retention within a single compartment may seem disadvantageous, but in the presence of parallel learning pathways, this shortened retention may represent a key mechanism for the generation of multiple memory timescales that are crucial for effective learning. During shock conditioning, for example, multiple DANs respond to the aversive stimulus, including PPL1-γ1pedc, PPL1-γ2α'1, PPL1-α3. This study has shown that optogenetic activation of these DAN cell types individually induces negative-valence olfactory memory with distinct learning rates. The NOS-expressing PPL1-γ1pedc induces memory with the fastest learning rate in a wild-type background, and this study shows that it induces an NO-dependent memory trace when dopamine synthesis is blocked, with a much slower learning rate and opposite valence (Aso, 2019).

Robust and stable NO-dependent effects were only observed when training was repeated 10 times. Under such repeated training, compartments with slower learning rates, such as α3, form memory traces in parallel to those formed in γ1pedc. Thus, flies may benefit from the fast and labile memory formed in γ1pedc without suffering the potential disadvantages of 58 shortened memory retention, as long-term memories are formed in parallel in other compartments. The Drosophila MB provides a tractable experimental system to study the mechanisms and benefits of diversifying learning rate, retention, and flexibility in parallel memory units, as well as exploring how the outputs from such units are integrated to drive behavior (Aso, 2019).

Aversive training induces both pre- and postsynaptic suppression in Drosophila
Zhang, X., Noyes, N. C., Zeng, J., Li, Y. and Davis, R. L. (2019). J Neurosci. 39(46):9164-9172. PubMed ID: 31558620

The alpha'beta' subtype of Drosophila mushroom body neurons (MBn) is required for memory acquisition, consolidation and early memory retrieval after aversive olfactory conditioning. However, in vivo functional imaging studies have failed to detect an early forming memory trace in these neurons as reflected by an enhanced G-CaMP signal in response to presentation of the learned odor. This study shows that aversive olfactory conditioning suppresses the calcium responses to the learned odor in both alpha'3 and alpha'2 axon segments of alpha'beta' MBn and in the dendrites of alpha'3 MBOn immediately after conditioning using female flies. Notably, the cellular memory traces in both alpha'3 MBn and alpha'3 MBOn are short-lived and persist for less than 30 min. The suppressed response in alpha'3 MBn is accompanied by a reduction of acetylcholine (ACh) release, suggesting that the memory trace in postsynaptic alpha'3 MBOn may simply reflect the suppression in presynaptic alpha'3 MBn. Furthermore, this study shows that the alpha'3 MBn memory trace does not occur from the inhibition of GABAergic neurons via GABAA receptor activation. Since activation of the alpha'3 MBOn drives approach behavior of adult flies, the results demonstrate that aversive conditioning promotes avoidance behavior through suppression of the alpha'3 MBn-MBOn circuit (Zhang, 2019).

Animals learn to avoid a neutral stimulus that is repeatedly coupled with an unpleasant one. This type of learning, aversive associative learning, induces cellular memory traces in engram cells in the brain and changes the representation of the neutral stimulus. In Drosophila, several memory traces detected with the calcium indicator G-CaMP have been observed in the mushroom body (MB), a brain region critical for olfactory learning and memory. These memory traces are detectable across discrete time periods extending from 30 min to several days after training. However, memory traces that form immediately in the MB after conditioning have not been detected with in vivo Ca2+ imaging (Zhang, 2019).

The MB is composed of ~2000 intrinsic neurons in each hemisphere that integrates olfactory cues received from antennal lobe projection neurons with aversive or rewarding stimuli from two clusters (PPL1, PAM) of dopamine neurons. MBn are classified into three major subtypes: α'β', αβ, and γ neurons, based on their birth order and projection patterns of their axons in the brain. The axons of α'β' and αβ MBn bifurcate and project within the vertical α'/α lobe and horizontal β'/β lobe neuropil, whereas the axons of γ neurons project only within the horizontal γ lobe neuropil. Although each of these MBn subtypes contributes to aversive olfactory memory, they do so at different times after conditioning, with synaptic transmission from the α'β' and γ MBn required for robust expression of early and intermediate-term memory (immediate to 3 h) and synaptic transmission from the αβ MBn having a more pronounced role for memory expression after 3 h. Importantly, although the α'β' MBn are required for memory acquisition, consolidation and early memory retrieval, no immediate memory trace in α'β' MBns has been detected using in vivo Ca2+ imaging (Zhang, 2019).

Five different types of MB output neurons (MBOns) tile the α'β' lobe with their dendritic trees into five discrete compartments, matching the tiling by axon terminals from presynaptic DAns. Several of these MBOns are required for aversive memory or appetitive memory expression, and intermediate-term memory traces (~1-2 h after conditioning) have been detected in some of these neurons. However, early memory traces have not been documented in these MBOns, and the relationship between such putative traces and those in the presynaptic MBn is unexplored. Connectome studies revealed that DAns make direct connection with MBOns, opening the possibility that MBOns form traces independently of the MBn (Zhang, 2019).

This study shows that a cellular memory trace forms immediately after conditioning in the MBn axons occupying the α'3 compartment and in the downstream α'3 MBOn. Functional Ca2+ imaging reveals that aversive conditioning suppresses subsequent responses to the learned odor in both the presynaptic α'3 compartment and the postsynaptic α'3 MBOn across a similar time period, suggestive of a causal relationship. In vivo ACh imaging revealed that the suppressed Ca2+ responses are accompanied by reduced ACh release in the α'3 compartment, supporting the model that the α'3 MBOn memory trace occurs from suppressed presynaptic activity. This study also shows that the conditioning-induced suppression in the α'3 compartment does not occur from increased inhibition through the Resistance to dieldrin (Rdl) GABAA receptor, indicating that mechanisms other than Rdl receptor activation are responsible for the suppression of activity (Zhang, 2019).

This study provides evidence for the existence of immediate cellular memory traces that form in at least two adjacent segments of the axons in the vertical lobe neuropil of the α'β' MBn and at least one (α'3 MBOn) of the corresponding output neurons. These memory traces, detected as decreased Ca2+ responses to the CS+ odor immediately after conditioning when compared with preconditioning responses, and persisting for >30 min before the response properties return to the naive state, are consistent with the fact that α'β' MBn are required for memory acquisition, consolidation and early memory retrieval. Several other previously characterized early memory traces due to odor conditioning provide an interesting background to these newly discovered traces. The neurites of the DPM neurons innervating the vertical MB lobe neuropil exhibit an increased Ca2+ response to the learned odor from ~30-70 min after conditioning. A memory trace forms in the antennal lobe, registered as the recruitment of new projection neuron activity in response to the learned odor, that lasts <10 min after conditioning. The activity of GABAergic APL neurons that synapse in the vertical lobe neuropil of the MBn is suppressed for a period of a few minutes after conditioning. Further, in vivo functional imaging of the α'β' MBn axons revealed an early memory trace displayed as increased Ca2+ influx by 30 min after conditioning that persists for at least 1 h. The action of these five memory traces, together along with other unknown traces, may provide the cellular modifications required for behavioral performance gains to be made across the first hour after conditioning. Memory traces in compartments other than α'3 and/or their MBOns may underlie the requirement of α'β' MBn for memory retrieval beyond the first hour (Zhang, 2019).

However, the developmental trajectory of the memory traces forming in the α'β' MBn lobe is of additional interest. As indicated above, a cellular memory trace forms in these neurons by 30 min after conditioning that is manifested as an increased Ca2+ response to the conditioned odor. The data presented in this study show that the α'β' MBn axons become suppressed across the first ~15 min after conditioning. The combined studies thus indicate that the CS+ odor response properties in the α'β' MBn axons are initially suppressed after conditioning but then become enhanced at later times. The time courses for the two cellular memory traces do not match exactly (0-15 min for the suppression and ~30-60 min for the increase) given the current data showing no detectable increase at 30 or 45 min, but this is easily explained by variation in the strength of conditioning or minor technical differences between the two studies. Thus, the most parsimonious conclusion is that the vertical axon compartments of the α'β' MBn initially exhibit a suppressed response to the CS+ followed by an increased response with the transition from suppression to enhancement occurring somewhere between ~30-45 min after conditioning. How this evolution in response properties from negative to positive with time translates into behavioral memory expression remains unclear (Zhang, 2019).

The suppressed responses to the CS+ odor were found in both the axon segments of the α'β' MBn and the dendrites of α'3 MBOn. Given that activation of α'3 MBOn drives approach behavior, the results are consistent with the model that aversive conditioning promotes avoidance through suppressing the MBn-MBOn circuits that signal positive valence, at least across the time that the MBOn responses are suppressed. Notably, the memory traces in α'3 MBn and α'3 MBOn persisted for the similar time, raising the question of whether the suppressed responses form independently or whether the α'3 MBOn memory trace simply reflects the presynaptic one. The data support the model in which the suppressed α'β' MBn responses are simply transmitted to the MBOn from reduced synaptic activity: the suppressed Ca2+ response in α'3 MBn axon compartment is correlated with reduced ACh release and the suppressed response in the α'3 MBOn dendrites. Behavioral data suggest that if the early cellular memory traces that form in the α'3 MBn-MBOn circuit cannot be readout precisely, the expression of behavioral memory early after conditioning becomes impaired. However, the possibility that memory traces can be formed independently in α'3 MBOn cannot be excluded (Zhang, 2019).

This study formulated the hypothesis that the immediate suppression in α'3 MBn axons after aversive conditioning might be due to enhanced GABAergic input to the α'3 compartment in an effort to delineate the underlying mechanism. However, attempts to detect any impairment of the immediate suppression in α'3 axonal compartment failed when Rdl GABAA receptor was knocked down in α'β' neurons. Thus, the data argue against attributing the suppression in the α'3 compartment to GABAergic inhibition through GABAA receptor (Zhang, 2019).

Identification and characterization of mushroom body neurons that regulate fat storage in Drosophila
Al-Anzi, B. and Zinn, K. (2018). Neural Dev 13(1): 18. PubMed ID: 30103787

Two neuronal populations, c673a and Fru-GAL4, regulate fat storage in fruit flies. Both populations partially overlap with a structure in the insect brain known as the mushroom body (MB), which plays a critical role in memory formation. This overlap prompted an examination of whether the MB is also involved in fat storage homeostasis. Using a variety of transgenic agents, the neural activity of different portions of the MB and associated neurons were selectively manipulated to decipher their roles in fat storage regulation. The data show that silencing of MB neurons that project into the &alpha:'β' lobes decreases de novo fatty acid synthesis and causes leanness, while sustained hyperactivation of the same neurons causes overfeeding and produces obesity. The &alpha:'β' neurons oppose and dominate the fat regulating functions of the c673a and Fru-GAL4 neurons. It was also shown that MB neurons that project into the γ lobe also regulate fat storage, probably because they are a subset of the Fru neurons. It was possible to identify input and output neurons whose activity affects fat storage, feeding, and metabolism. The activity of cholinergic output neurons that innervating the β'2 compartment (MBON-β'2mp and MBON-γ5β'2a) regulates food consumption, while glutamatergic output neurons innervating α' compartments (MBON-γ2α'1 and MBON-α'2) control fat metabolism. This study has identified a new fat storage regulating center, the α'β' lobes of the MB. The study also delineated the neuronal circuits involved in the actions of the α'β' lobes, and showed that food intake and fat metabolism are controlled by separate sets of postsynaptic neurons that are segregated into different output pathways (Al-Anzi, 2018).

Reciprocal synapses between mushroom body and dopamine neurons form a positive feedback loop required for learning
Cervantes-Sandoval, I., Phan, A., Chakraborty, M. and Davis, R. L. (2017). Elife 6. PubMed ID: 28489528

Current thought envisions dopamine neurons conveying the reinforcing effect of the unconditioned stimulus during associative learning to the axons of Drosophila mushroom body Kenyon cells for normal olfactory learning. This study shows, using functional GFP reconstitution experiments, that Kenyon cells and dopamine neurons form axoaxonic reciprocal synapses. The dopamine neurons receive cholinergic input via nicotinic acetylcholine receptors from the Kenyon cells; knocking down these receptors impairs olfactory learning revealing the importance of these receptors at the synapse. Blocking the synaptic output of Kenyon cells during olfactory conditioning reduces presynaptic calcium transients in dopamine neurons (DAn), a finding consistent with reciprocal communication. Moreover, silencing Kenyon cells decreases the normal chronic activity of the dopamine neurons. These results reveal a new and critical role for positive feedback onto dopamine neurons through reciprocal connections with Kenyon cells for normal olfactory learning (Cervantes-Sandoval, 2017).

The results demonstrate that DAn are both pre- and post-synaptic to KC through axoaxonic reciprocal connections, in contrast to current models which envision them as providing only pre-synaptic input. The DAn>KC half of the reciprocal synapse employs DA as neurotransmitter, although the possibility cannot be ruled out that other neurotransmitters are co-released with DA. The KC>DAn half of the reciprocal synapse is cholinergic. However, the fact that it was not possible to observe both cAMP and calcium responses in DAn with KC stimulation suggests that there may be other mediators of this reciprocal connection. Blocking the cholinergic input to DAn attenuates aversive olfactory learning, providing evidence that its function is, at least in part, to provide an amplification signal for the initial DA release due to activating the US pathway. Consistent with this role it was found that silencing KC impairs DAn presynaptic calcium responses to conditioning, odor and shock stimuli, presumably influencing dopamine release and explaining the learning phenotype. Overall, results support the existence of a positive feedback loop required for optimal learning. It is envisioned that DAn receive direct input from the US during conditioning which is conveyed to KC. The KCs also receive coincident olfactory input and this coincidence provides positive feedback onto the DAn through cholinergic synapses to further increase DAn activity (Cervantes-Sandoval, 2017).

The results also show that KC input to DAn shapes their ongoing or chronic activity. It is plausible that ongoing activity in the DAn provides a moment-by-moment update of the external environment and internal states and the behavioral status of the fly that appropriately reconfigures the KC>MBOn flow of information. Thus, the DAn/KC/MBOn circuit may form a recurrent network that serves as the insect's brain center for the rapid integration of sensory information and decision-making. Local feedback loops, achieved by reciprocal connectivity like that described in this study, may provide computational benefits to fine tune and optimize the output. Behavioral flexibility may be achieved by passing information through local reentrant loops with constant updating from the external or internal state of the organism (Cervantes-Sandoval, 2017).

A caveat in this and other studies is that it is not possible to exclude that other, non-KC, cholinergic input to DAn contributes to memory acquisition. Massive efforts to generate 'connectomes' in multiple species may offer resolution to this issue at some point in the future. Alternatively, they may continue to reveal additional connections and complexities that defy an immediate understanding. Studies like the present one, that reveal unexpected relationships between synaptic partners in difficult-to-untangle circuits, expose the need to advance beyond 'connectomics' and develop new tools that allow silencing or activation of specific channels and specific synaptic connections between neurons of interest without affecting other functions in the same cells (Cervantes-Sandoval, 2017).

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The complete connectome of a learning and memory centre in an insect brain
Eichler, K., Li, F., Litwin-Kumar, A., Park, Y., Andrade, I., Schneider-Mizell, C. M., Saumweber, T., Huser, A., Eschbach, C., Gerber, B., Fetter, R. D., Truman, J. W., Priebe, C. E., Abbott, L. F., Thum, A. S., Zlatic, M. and Cardona, A. (2017). Nature 548(7666): 175-182. PubMed ID: 28796202

Associating stimuli with positive or negative reinforcement is essential for survival, but a complete wiring diagram of a higher-order circuit supporting associative memory has not been previously available. This study reconstructed one such circuit at synaptic resolution, the Drosophila larval mushroom body. Most Kenyon cells were found to integrate random combinations of inputs, but a subset receives stereotyped inputs from single projection neurons. This organization maximizes performance of a model output neuron on a stimulus discrimination task. A novel canonical circuit in each mushroom body compartment with previously unidentified connections is reported: reciprocal Kenyon cell to modulatory neuron connections, modulatory neuron to output neuron connections, and a surprisingly high number of recurrent connections between Kenyon cells. Stereotyped connections found between output neurons could enhance the selection of learned behaviours. The complete circuit map of the mushroom body should guide future functional studies of this learning and memory centre (Eichler, 2017).

Massively parallel, higher-order neuronal circuits such as the cerebellum and insect mushroom body (MB) serve to form and retain associations between stimuli and reinforcement in vertebrates and evolutionarily complex invertebrates. Although these systems provide a biological substrate for adaptive behaviour, no complete synapse-resolution wiring diagram of their connectivity has been available to guide analysis and aid understanding. The MB is a higher-order parallel fibre system in many invertebrate brains, including hemimetabolous as well as holometabolous insects and their larval stages. MB function is essential for associative learning in adult insects and in Drosophila larvae from the earliest larval stages onwards. Indeed, the basic organization of the adult and the larval MB and their afferent circuits is very similar; however, larvae have about an order of magnitude fewer neurons. Thus, to systematically investigate the organizational logic of the MB, this study used serial section electron microscopy to map with synaptic resolution the complete MB connectome in a first-instar Drosophila larva. L1 are foraging animals capable of all behaviours previously described in later larval stages including adaptive behaviours dependent on associative learning. Their smaller neurons enable fast electron microscopy imaging of the entire nervous system and reconstruction of complete circuits (Eichler, 2017).

Models of sensory processing in many neural circuits feature neurons that fire in response to combinations of sensory inputs, generating a high-dimensional representation of the sensory environment. The intrinsic MB neurons, the Kenyon cells (KCs), integrate in their dendrites inputs from combinations of projection neurons (PNs) that encode various stimuli, predominantly olfactory in both adult and larva1, but also thermal, gustatory, and visual in adult and larva. Previous analyses in adults and larvae suggest that the connectivity between olfactory PNs and KCs is random, but they do not eliminate the possibility of some degree of bilateral symmetry, which requires access to the full PN-to-KC wiring diagram in both hemispheres (Eichler, 2017).

The MB contains circuitry capable of associating reward or punishment with the representation of the sensory environment formed by KCs. KCs have long parallel axons that first run together, forming the peduncle, and then bifurcate, forming the so-called lobes, in both larvae and adults. KCs receive localized inputs along their axonal fibres from dopaminergic as well as octopaminergic modulatory neurons (DANs and OANs, respectively) that define separate compartments. DANs and OANs have been shown to convey reinforcement signals in adult insects and larval Drosophila. The dendrites of the mushroom body output neurons (MBONs) respect the DAN compartments in adults and larvae. It has been shown in adult Drosophila that co-activation of KCs and DANs can associatively modulate the KC-MBON synapse. Thus, the compartments represent anatomical and functional MB units where sensory input (KCs) is integrated with internal reinforcement signals (DANs/OANs) to modulate instructive output for behavioural control (MBONs). However, the synaptic connectivity of KCs, DAN/OANs, and MBONs at this crucial point of integration was previously unknown (Eichler, 2017).

Furthermore, studies in adult Drosophila have shown that, despite the compartmental organization of the MB, many MBONs interact with MBONs from other compartments, suggesting that the MBON network functions combinatorially during memory formation and retrieval. However, a comprehensive account of all MB neuron connections is lacking. Thus, to provide a basis for understanding how the MB, a prototypical parallel fibre learning and memory circuit, functions as an integrated whole, this study provides a full, synapse-resolution connectome of all MB neurons of an L1 Drosophila larvaxxWe provide the first complete wiring diagram of a parallel fibre circuit for adaptive behavioural control. Such circuits exist in various forms, for example the cerebellum in vertebrates and the MB in insects. They contribute to multiple aspects of behavioural control including stimulus classification, the formation and retrieval of Pavlovian associations, and memory-based action selection. A comprehensive wiring diagram of such a multi-purpose structure is an essential starting point for functionally testing the observed structural connections and for elucidating the circuit implementation of these fundamental brain functions (Eichler, 2017).

Even though individual neurons may change through metamorphosis, many of the basic aspects of the MB architecture are shared between larval and adult Drosophila stages and with other insects. It is therefore expected that the circuit motifs identified in this study are not unique to the L1 developmental stage, but instead represent a general feature of Drosophila and insect MBs (Eichler, 2017).

Electron microscopy reconstruction revealed a canonical circuit in each MB compartment featuring two unexpected motifs in addition to the previously known MBIN-to-KC and KC-to-MBON connections. First, it was surprising to observe that the number of KC-to-MBIN and KC-to-MBON synapses are comparable. As KCs were shown to be cholinergic in adults, KC-to-MBIN connections could be potentially depolarizing. Untrained, novel odours can activate DANs in adult Drosophila and OANs in bees. Similar brief short-latency activations of dopamine neurons by novel stimuli are observed in monkeys, too, and are interpreted as salience signals. Learning could potentially modulate the strength of the KC-to-MBIN connection, either weakening it or strengthening it. The latter scenario could explain the increase in DAN activation by reinforcement-predicting odours observed in adult Drosophila, bees, and monkeys. In addition, dopamine receptors have been shown to be required in Drosophila KCs for memory formation. Another unexpected finding was that MBINs synapse directly onto MBONs, rather than only onto KCs. Such a motif could provide a substrate for neuromodulator-gated Hebbian spike-timing dependent plasticity, which has been observed in the locust MB (Eichler, 2017).

In addition to random and bilaterally asymmetric olfactory and structured non-olfactory PN-to-KC connectivity, the analysis identified single-claw KCs whose number and lack of redundancy are inconsistent with random wiring. Random wiring has previously been shown to increase the dimension of sensory representations when the number of neurons participating in the representation is large compared with the number of afferent fibres, as in the cerebellum or adult MB. However, the current model shows that when the number of neurons is limited, random wiring alone is inferior to a combination of random and structured connectivity that ensures each input is sampled without redundancy. The presence of single-claw KCs may reflect an implementation of such a strategy. In general, the results are consistent with a developmental program that produces complete and high-dimensional KC sensory representations to support stimulus discrimination at both larval and adult stages (Eichler, 2017).

This study reveals the complete MBON-MBON network at synaptic resolution. Previous studies in the larva have shown that odour paired with activation of medial and vertical lobe DANs leads to learned approach8 and avoidance, respectively. This connectivity analysis reveals that glutamatergic MBONs from the medial lobe laterally connect to MBONs of the vertical lobe. The glutamatergic MBON-MBON connections could be inhibitory, although further studies are needed to confirm this. Furthermore, inhibitory GABAergic MBONs from the vertical lobe laterally connect to MBONs of the medial lobe. An example is the feedforward inhibition of medial lobe MBON-i1 output neuron by the vertical lobe GABAergic MBON-g1, -g2 output neurons. A similar motif has been observed in the Drosophila adult, where aversive learning induces depression of conditioned odour responses in the approach-promoting MBON-MVP2 (MBON-11), which in turn disinhibits conditioned odour responses in the avoidance-promoting MBON-M4/M6 (MBON-03) because of the MBON-MVP2 to MBON-M4/M6 feedforward inhibitory connection (Eichler, 2017).

Combining the present connectivity analysis of the MBON-MBON network in the larva and previous studies in the adult Drosophila, the rule seems to be that MBONs encoding opposite learned valance laterally inhibit each other. Such inhibitory interactions have been proposed as a prototypical circuit motif for memory-based action selection (Eichler, 2017).

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Representations of novelty and familiarity in a mushroom body compartment Hattori, D., Aso, Y., Swartz, K. J., Rubin, G. M., Abbott, L. F. and Axel, R. (2017)
. Cell 169(5): 956-969. PubMed ID: 28502772

Animals exhibit a behavioral response to novel sensory stimuli about which they have no prior knowledge. This study has examined the neural and behavioral correlates of novelty and familiarity in the olfactory system of Drosophila. Novel odors elicit strong activity in output neurons (MBONs) of the α'3 compartment of the mushroom body that is rapidly suppressed upon repeated exposure to the same odor. This transition in neural activity upon familiarization requires odor-evoked activity in the dopaminergic neuron innervating this compartment. Moreover, exposure of a fly to novel odors evokes an alerting response that can also be elicited by optogenetic activation of α'3 MBONs. Silencing these MBONs eliminates the alerting behavior. These data suggest that the α'3 compartment plays a causal role in the behavioral response to novel and familiar stimuli as a consequence of dopamine-mediated plasticity at the Kenyon cell-MBONα'3 synapse (Hattori, 2017).

Novel stimuli can elicit a behavioral response that alerts an organism to unexpected, potentially salient events. An alerting response to sensory stimuli not previously encountered by an animal, such as the orienting response described by Pavlov, provides an organism the opportunity to explore the potential significance of the novel stimulus. A behavioral response to novelty is elicited by sensory cues about which an animal has no prior knowledge. Most behaviors, in contrast, are based upon past experience acquired either over long periods of evolutionary time (innate behaviors) or by learning over the life of an animal. The observation that sensory cues can be identified as novel and can evoke a behavioral response in the absence of prior knowledge poses an interesting problem (Hattori, 2017).

A neural circuit encoding novelty should respond to all novel stimuli, but this response should be suppressed upon familiarization. The memory of a familiar sensory cue should be stimulus specific and long-lasting, distinguishing it from sensory adaptation. Neural responses that correlate with novelty and familiarity are seen in a number of mammalian brain regions. The transition from novelty to familiarity is associated with suppression of neural responses in higher brain centers that appears distinct from intrinsic or sensory adaptation. Electrophysiologic recordings along the visual and auditory pathways reveal that neurons exhibit activity in response to novel or unexpected cues that diminish upon repeated exposure. In the auditory pathway, neurons in the inferior colliculus and the auditory cortex exhibit responses to novel or unexpected tones that attenuate upon repetition. Similarly, neurons in the perirhinal and inferior temporal cortices respond to novel visual stimuli, and this response attenuates rapidly upon repetition, a phenomenon known as repetition suppression (Hattori, 2017).

Dopaminergic neurons in the substantia nigra (SN) pars compacta and ventral tegmental area (VTA) also exhibit phasic bursting activity in response to novel or unexpected sensory events. Unexpected flashes of light or auditory tones evoke burst firing in 60%-70% of the dopaminergic neurons that attenuates as the novel stimulus becomes familiar. Related neural events may underlie attenuation in the BOLD signal observed in extra striate cortex as well as SN and VTA in fMRI studies of humans upon repeated exposure to sensory stimuli. Thus, mammals have evolved neural systems that distinguish novel from familiar sensory stimuli that may facilitate the determination of the potential salience of unfamiliar environmental events (Hattori, 2017).

This study has analyzed the behavioral and neural correlates of novelty and familiarity in the olfactory system of Drosophila. Olfactory perception in the fly is initiated by the binding of an odor to an ensemble of olfactory sensory neurons in the antennae that results in the activation of a unique and topographically fixed combination of glomeruli in the antennal lobe. Each antennal lobe projection neuron extends dendrites into one of the 54 glomeruli and extends axons that bifurcate to innervate two distinct brain regions, the lateral horn, and the mushroom body (MB). The invariant circuitry of the lateral horn is thought to mediate innate behaviors, whereas the unstructured projections to the MB translate olfactory sensory information into learned behavioral responses. In the MB, each odor activates a sparse representation (5%-10%) of principal neurons, the Kenyon cells (KCs). KCs extend axons that form en passant synapses in the compartments of the MB lobes. The KCs synapse on the MB output neurons (MBONs), which have distinct spatially stereotyped dendritic arbors within compartments that collectively tile the lobes. MBONs provide the only output of the MB and the activity of different MBON combinations biases behavior. Each of the 15 compartments is also innervated by the axons of one to three of 20 dopaminergic cell types (dopaminergic neurons, or DANs). Distinct DANs respond to different unconditioned stimuli and dopamine release elicits plasticity in the synapses between the KCs and MBONs. The alignment of DAN arbors with compartmentalized KC-MBON synapses creates a unit for learning that transforms the disordered KC representation into ordered MBON output to collectively bias behavioral responses to sensory stimuli (Hattori, 2017).

The transition from novelty to familiarity involves memory formation, and learning and memory in the fly are accomplished by the circuitry of the MB. This study has identified a neural circuit in the MB that appears to encode a representation of novelty and familiarity. MBONs were observed innervating the α'3 compartment respond to novel odors and that their activity is rapidly suppressed upon repeated exposure to the same stimulus. This suppression upon familiarization is observed for all novel odors tested regardless of innate valence, is stimulus specific, lasts for more than 20 min, and recovers in 1 hr. Repetition suppression of MBON-α'3 is distinct from sensory adaptation and requires odor-evoked activity in the DAN innervating the α'3 compartment. These data suggest that repeated exposure to an odor mediates dopamine-dependent plasticity at the KC synapses onto MBON-α'3 that suppresses MBON output. Moreover, behavioral experiments demonstrate that the α'3 MBONs mediate an alerting response to novel odors. Exposure of a fly to novel olfactory stimuli evokes an alerting behavior. This behavioral response can be elicited by optogenetic activation of α'3 MBONs and eliminated by α'3 MBON silencing. These observations suggest that the behavioral response to novelty and the transition to familiarity is mediated by the circuitry of KCs, DANs, and MBONs within the α'3 compartment (Hattori, 2017).

This study has examined the neural and behavioral correlates of novelty and familiarity in the olfactory system of Drosophila. Exposure of flies to a novel odor interrupts grooming. This alerting response is dependent upon the activity of output neurons of the α'3 compartment of the MB. Optogenetic activation of the α'3 MBONs elicits an alerting response, whereas silencing these neurons eliminates the behavioral response to novel odors. A neural correlate of this behavioral response is observed in the activity of MBON-α'3. Novel odors elicit strong activity in these neurons that is rapidly suppressed upon repeated exposure to the same odor. This transition in MBON-α'3 response upon familiarization requires the activity of PPL1-α'3, the DAN innervating the α'3 compartment, and dopamine receptors in the MBONs. These data suggest that the α'3 compartment may play a causal role in the behavioral response to novel and familiar stimuli as a consequence of dopamine-mediated plasticity at the KC-MBONα'3 synapse. Although the circuitry of the α'3 compartment is central to the behavioral response to novel and familiar odors, the data do not exclude a contribution from other compartments (Hattori, 2017).

Plasticity at the KC-MBON synapses has been invoked to explain olfactory learning and memory (Heisenberg, 2003). In associative learning, exposure to a conditioned stimulus (CS), when paired with an unconditioned stimulus (US), imposes an associative memory upon the CS. The identity of the CS is represented by activity in a specific ensemble of KCs, whereas USs of different valence activate distinct DANs. Dopamine input depresses the KC-MBON synapse in specific compartments to transform the unstructured KC representation of an odor into an ordered MBON representation encoding behavioral bias. The neural mechanism governing the novelty response differs from this classical model of associative learning. In the α'3 compartment, a novel odor elicits strong MBON output and also activates the DAN. Dopamine release from PPL1-α'3 depresses the KC-MBONα'3 synapse, suppressing MBON output on further exposure to this odor. In this manner, a novel odor effectively serves as both a CS and a US to drive the transition from novelty to familiarity (Hattori, 2017).

A second distinction between the novelty response and associative learning emerges from the observation that the response to novelty is suppressed by learning whereas the conditioned response depends on learning. The stereotyped alerting behavior in response to novel odor does not require learning and is therefore innate. In associative learning models, exposure to odor prior to learning activates all MBONs examined, but this combinatorial of MBONs does not elicit a behavior. Rather, behavioral bias is imposed by the suppression of specific MBON output after learning. In the novelty response, innate alerting behavior is elicited by strong output from MBON-α'3 in response to novel odors prior to learning. Learning that accompanies the transition to familiarity suppresses MBON-α'3 activity and the behavioral response to novelty. If, however, the novel odor is accompanied by salient events in the environment, this will result in activation of additional DANs, leading to the formation of associations in other compartments. The alerting response evoked by MBON-α'3 may enhance the awareness of these environmental events. Thus, α'3 output may elicit an immediate and stereotyped response to an odor independent of its salience, which is then assessed by the remaining MB compartments to mediate more measured associative responses (Hattori, 2017).

Odor-evoked dopamine release by PPL1-α'3 appears to be essential to modulate MBON output in the transition from novelty to familiarity. Dopamine release also contributes to decay in the memory of familiar odors. MBON-α'3 activity in response to novel odors is suppressed upon repeated exposure, but activity is restored after 1 hr. Dopamine release in the absence of odor, following repetition suppression, accelerates this recovery process. These observations are consistent with recent experiments demonstrating that dopamine release within a compartment in the absence of odor can lead to synaptic facilitation and the restoration of MBON output. In this manner, familiarity in the fly is a transient phenomenon and the restoration of the perception of novelty may be accelerated by dopamine (Hattori, 2017).

It is suggested that the neural events responsible for the transition from novelty to familiarity involve depression of only those KC-MBON synapses activated by the novel odor. In this manner, novelty and familiarity can be both universal and odor specific. A given odor activates about 5%-10% of the KCs in the MB and by inference 5%-10% of the KC-MBON synapses. An organism is likely to encounter multiple odors that may be construed as novel in the course of hours. If a single novel odor suppresses 5%-10% of the KC-MBON synapses and this synaptic depression is long term, all KC-MBON synapses within the α'3 compartment would be depressed after exposure to roughly 20 novel odors. Depression of all the synapses would prevent subsequent response to novel odors. The data suggest this problem may be obviated in two ways. First, the depression is relatively short lived. Second, although novel odors result in the depression of active KC-MBON synapses, they also enhance the recovery of previously suppressed but currently inactive synapse. This implies that the rate of synaptic recovery is proportional to the rate of exposure to novel odors. Thus, the α'3 compartment has evolved a mechanism to assure that novelty responses can be generated in both dense and sparse odor environments without saturation (Hattori, 2017).

The MB is an associative center in invertebrate brains thought to impose valence on sensory representations. The current data suggest that the MB not only functions in classical learning paradigms, but also supports novelty detection and the transition to familiarity. An organism can have no knowledge of a novel stimulus, and hence it exhibits an indiscriminate alerting response. The MB also integrates information about the organism's internal state (hunger, satiety, sleep, wakefulness, roaming, dwelling) allowing the fly to more comprehensively contextualize the diverse sensory experiences it may encounter throughout its life. Thus, the MB may afford the fly an 'individuality' allowing different flies to respond differently to the same stimuli in accord with its unique history and current state (Hattori, 2017).

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A connectome of a learning and memory center in the adult Drosophila brain
Takemura, S. Y., Aso, Y., Hige, T., Wong, A., Lu, Z., Xu, C. S., Rivlin, P. K., Hess, H., Zhao, T., Parag, T., Berg, S., Huang, G., Katz, W., Olbris, D. J., Plaza, S., Umayam, L., Aniceto, R., Chang, L. A., Lauchie, S., Ogundeyi, O., Ordish, C., Shinomiya, A., Sigmund, C., Takemura, S., Tran, J., Turner, G. C., Rubin, G. M. and Scheffer, L. K. (2017). Elife 6. PubMed ID: 28718765

Understanding memory formation, storage and retrieval requires knowledge of the underlying neuronal circuits. In Drosophila, the mushroom body (MB) is the major site of associative learning. This study reconstructed the morphologies and synaptic connections of all 983 neurons within the three functional units, or compartments, that compose the adult MB's alpha lobe, using a dataset of isotropic 8 nm voxels collected by focused ion-beam milling scanning electron microscopy. It was found that Kenyon cells (KCs), whose sparse activity encodes sensory information, each make multiple en passant synapses to MB output neurons (MBONs) in each compartment. Some MBONs have inputs from all KCs, while others differentially sample sensory modalities. Only 6% of KC>MBON synapses receive a direct synapse from a dopaminergic neuron (DAN). Two unanticipated classes of synapses, KC>DAN and DAN>MBON, were identified. DAN activation produces a slow depolarization of the MBON in these DAN>MBON synapses and can weaken memory recall (Takemura, 2017).

Associative memory helps animals adapt their behaviors to a dynamically changing world. The molecular mechanisms of memory formation are thought to involve persistent changes in the efficiency of synaptic transmission between neurons. In associative learning, persistent changes in synaptic efficacy correlated with memory formation have been found at points of convergence between two neuronal representations: one providing information from sensory inputs about the outside world and a second indicating whether the current environment is punitive or rewarding. Such sites of convergence have been identified for multiple forms of associative learning. However, a comprehensive synaptic level description of connectivity at such a site of convergence is not available for an animal as complex as the fruit fly, Drosophila (Takemura, 2017).

The mushroom body (MB) is the center of associative learning in insects. Sensory information enters the MB via the calyx, where the dendritic claws of Kenyon cells (KCs) receive synaptic inputs from projection neurons of olfactory and other modalities including visual, gustatory and thermal. The parallel axonal fibers of the KCs form the MB-lobes, the output region of the MB. A pattern of sparse activity in the KC population represents the identity of the stimulus. This sparseness is maintained through two mechanisms. First, individual KCs generally only spike when they receive simultaneous inputs from multiple projection neurons. Second, overall KC excitability is regulated by feedback inhibition from a GABAergic neuron, MB-APL, that arborizes throughout the MB. Thus, only a small subset of KCs respond to a given sensory stimulus. Upon this representation of the sensory world, dopaminergic or octopaminergic neurons convey information of punishment or reward and induce memories that associate the sensory stimulus with its valence (Takemura, 2017).

The functional architecture of the MB circuit is best understood in adult Drosophila (see Diagram of the α lobe of the mushroom body). In each MB, the parallel axonal fibers of ~2000 KCs can be divided into 16 compartmental units by the dendrites of 21 types of MB output neurons (MBONs) and the axon terminals of 20 types of dopaminergic neurons (DANs). A large body of behavioral and physiological studies suggests that these anatomical compartments are also parallel units of associative learning. In each compartment, the dendrites of a few MBONs overlap with axon bundles of hundreds of KCs. Punishment and reward activate distinct sets of DANs. DAN input to a compartment has been shown to induce enduring changes in efficacy of KC>MBONs synapses in those specific KCs that were active in that compartment at the time of dopamine release. The valence of the memory appears to be determined by which compartment receives dopamine during training, while the sensory specificity of the memory is determined by which KCs were active during training (Takemura, 2017).

Compartments can have distinct rates of memory acquisition and decay, and the 16 compartments together appear to form a set of parallel memory units whose activities are coordinated through both direct and indirect inter-compartmental connections. The DANs which project to the α1 compartment, the ventral-most compartment of the vertical lobe, play a key role in the formation of appetitive long-term memory of nutritional foods. DANs that project to the other α lobe compartments, α2 and α3, play roles in aversive long-term memory. All three of these compartments receive feedforward inputs from GABAergic and glutamatergic MBONs whose dendrites lie in other MB compartments known to be involved in aversive or appetitive memory. In addition, two types of MB-intrinsic neurons send arbors throughout the MB-lobes: a large GABAergic neuron, MB-APL, which provides negative feedback important for sparse coding, and the MB-DPM neuron, which is involved in memory consolidation and sleep regulation (Takemura, 2017).

Previous EM studies in the MB lobes of cockroaches, locusts, crickets, ants, honey bees and Drosophila identified KCs by their abundance, fasciculating axons and small size. Additionally, large GABA immunoreactive neurons that contact KC axons were identified in the locust pedunculus. While these data provided early insights to guide modeling of the MB circuit, the volumes analyzed were limited and most neuronal processes could not be definitively assigned to specific cell types. This paper reports a dense reconstruction of the three compartments that make up the α lobe of an adult Drosophila male. Because a dense reconstruction was performed, with the goal of determining the morphology and connectivity of all cells in the volume, it can be confidently stated that all cell types with processes in the α lobe have been identified (Takemura, 2017).

Comprehensive knowledge of the connectivity in the α lobe has allowed addressing of several outstanding issues. The first concerns the nature of KC>MBON connectivity. Although each KC passes through all three compartments, it is not known if individual KCs have en passant synapses in each compartment. Thus, it remains an open question whether the sensory representation provided to each compartment and each MBON within a compartment is the same or whether different MBONs within a compartment might sample from non-overlapping sets of KCs, and thus use independent sensory representations for learning. It was also not known which, if any, other cell types are direct postsynaptic targets of KCs (Takemura, 2017).

The second concerns dopamine modulation. What are the locations of dopaminergic synapses and what does this distribution imply about the targets of dopaminergic modulation as well as volume versus local transmission? Cell-type-specific rescue of dopamine receptor mutants suggests that dopamine acts presynaptically in the KCs of KC>MBON synapses. However, postsynaptic mechanisms have also been proposed and a recent study detected expression of dopamine receptors in MBONs, raising the possibility that MBONs might also be direct targets of DAN modulation. Behavioral, imaging and electrophysiological data indicate that dopamine modulation respects the borders between compartments, but it is not known whether these borders have a distinct structure, such as a glial sheet (Takemura, 2017).

The third concerns the two MBON types that send feedforward projections into the α lobe. These MBONs have important roles in associative learning as revealed by behavioral assays and have been postulated to integrate memories of opposing valence and different time scales. However, it is not known which cell types these feedforward MBON projections targets within the MB (Takemura, 2017).

The fourth concerns the two neurons, MB-APL and MB-DPM, which arborize throughout the MB and are thought to regulate MB function globally. What is their local synaptic connectivity within the α lobe and what can this inform about how they perform their roles (Takemura, 2017)?

Finally, the three compartments of the α lobe differ in important aspects, including valence of the memory formed, the time course of memory formation and retrieval, and the numerical complexity of their DAN inputs and MBON outputs. Are there obvious differences in the microcircuits of different compartments (Takemura, 2017)?

In this paper reports the answers to these questions. In addition, the utility of detailed anatomy at the electron microscopic level to provide novel insights is demonstrated: It is shown that nearly all cell types in the α lobe contain more than one morphological class of synaptic vesicle, raising the possibility that these cells utilize multiple neurotransmitters. In addition, two prevalent sets of synaptic motifs - from DANs to MBONs and from KCs to DAN s- are described that were unanticipated despite the extensive anatomical, physiological, behavioral and theoretical studies that have been performed on the insect MB. These novel DAN to MBON connections are characterized using behavioral and physiological assays and find that DAN activation produces a slow depolarization of postsynaptic MBONs and can weaken memory recall (Takemura, 2017).

The connections between the neurons observed in this study are are summarized in a Summary diagram of the connectome reconstruction of the α lobe. In each of the lobe's three compartments, parallel axonal fibers of ~1000 KCs project through the dendrites of a few MBONs and the terminal arbors of a few DANs. The results provide support for several aspects of the generally accepted model for MB circuit function. First, it was found that each KC forms en passant synapses with multiple MBONs down the length of its axon, making it possible for parallel processing across the different compartments of the MB lobes. Secondly, with the assumption that released dopamine diffuses locally, KC>MBON synapses would receive dopaminergic input close to the sites of vesicle release, consistent with the prevailing hypothesis that plasticity occurs at the presynaptic terminals of KCs. However, several circuit motifs were found that were not anticipated by previous work. For example, synaptic connections were found from KCs to DANs, indicating that DANs get axo-axonal inputs within the MB lobes themselves. A recent report provides evidence that these KC>DAN synapses are functional (Cervantes-Sandoval, 2017). An even more unexpected motif was the direct synaptic contacts from DAN to MBON found in every compartment. Functional connectivity experiments confirmed that these connections are monosynaptic, and showed that they give rise to a slow depolarization in the MBON. Moreover, stimulating DANs in freely behaving flies yields effects consistent with a net excitatory DAN>MBON connection. Finally, the synaptic connections are described of two feedforward MBONs, which have been proposed to mediate the interaction of the various parallel memories within the MB lobes, as well as two intrinsic MB neurons, APL and DPM (Takemura, 2017).

This work not only provides definitive evidence for, and quantitative detail about, many previously observed circuit motifs, but also reveals several motifs not anticipated by prior anatomical, behavioral or theoretical studies. These additional circuit motifs provide new insights and raise new questions about the computations carried out by the MB. It is noted that these same novel connections were also found in a parallel study of the larval MB. Not only were the same circuit motifs found in the larval MB and adult α lobe, but also the relative prevalence of these connections was strikingly similar: DAN>MBON synapses were 4.5% the number of KC>MBON synapses in the adult α lobe and 3.4% in the larval MB. KC>DAN synapses were 1.5 times as prevalent as DAN>KC synapses in the adult α lobe, as compared with 1.1 in the larval MB. KCs make 48% of their synapses onto other KCs in the adult α lobe and 45% in the larval upper vertical lobe compartments. It is tempting to speculate that the conservation of the relative abundances of these connections across developmental stages reflects important functional constraints on the circuit (Takemura, 2017).

A large body of work supports the idea that individual KC>MBON synapses are the elemental substrates of associative memory storage in the MB. The dominant hypothesis in the field is that coincidence detection occurs within the presynaptic terminals of the KCs. The Conditioned Stimulus (CS, for example an odor) evokes a spiking response in a sparse subset of KCs, which in turn leads to Ca2+ influx. The Unconditioned Stimulus (US, for example electric shock) activates dopaminergic inputs to the MB lobes, where they likely activate G-protein-coupled dopamine receptors on the KC cell membrane. The coincidence of these two events is thought to be detected by the Ca2+ sensitive, calmodulin-dependent adenylate cyclase rutabaga, which initiates a cAMP signaling cascade that leads to the biochemical changes underlying synaptic plasticity (Takemura, 2017).

The tiling of MBON and DAN projections down the length of the KC axons suggests that each of these compartments serves as an independent module, with the association of reinforcement with sensory input taking place in parallel across several different modules. One important assumption in this model is that each KC sends parallel input to each compartment by making synapses all the way down the length of its axon. Light microscopic imaging established that the axons of individual α/β KCs do indeed run through all three compartments of the α lobe. However, they also revealed that the axonal branching patterns differ between KC classes. For example, the axons of α/βp KCs branch in α2, whereas those of α/βc and α/βs KCs do not, raising the question of how extensive KC outputs are across the different compartments. The dense EM reconstruction established that in fact all α/β KCs form en passant synapses on MBONs in each of the three α lobe compartments (Takemura, 2017).

In many cases, these synapses were found at enlarged boutons that contained the presynaptic machinery. However, output sites were also found on the smooth axons of the α/βc KCs, which lack obvious bouton-like swellings. Only occasional, short (generally <5 μm) segments of KC axons where the axon became thinner than 300 nm in diameter lacked presynaptic sites. Of course, it is not known whether all these synapses are functional. EM analysis showed that within each compartment, every KC passing through a layer of the compartment that was extensively innervated by an MBON made at least one synapse with that MBON. Previous electrophysiological measurements of connectivity in the α2 compartment indicated that only about 30% of KCs connect to MBON-α2sc, suggesting the possibility that the majority of KC>MBON synapses are functionally silent, as they are in cerebellar cortex, where 98% of the parallel fiber-to-Purkinje cell synapses are believed to be silent. However, a more trivial explanation cannot be ruled out: These measurements were made in the presence of cholinergic antagonists that could have partially blocked synaptic events and lead to an underestimate of total connectivity levels (Takemura, 2017).

The EM data revealed that the the number of synapses made by individual KCs was well-described by a Poisson distribution, where each synapse connects with a uniform, independent, and random probability to one of the KCs. Although the predicted distributions strongly depend on the number of connections between two cell types, almost all KC connections to other cells obeyed Poisson statistics. This was true of every KC in the α1 and α3 compartments, where each MBON has compartment-filling dendrites. The α2 compartment is somewhat unusual in that its MBONs innervate only subzones of the compartment. While light microscopy showed that MBON-α2sc primarily innervates the surface and core of the compartment, MBON-α2sp was found to project more to the surface and posterior. The connectome results bore out these observations from the light and electron microscopy, although EM reconstructions also showed that these borders were not sharp, and these MBONs receive less extensive and weaker connections outside these subzones. Nevertheless, within the primary area of innervation, it was again the case that every KC made synapses with all MBONs along its axon. Thus each of the 949 α/β KCs can deliver information to the MBONs in each of the three α lobe compartments (Takemura, 2017).

A strictly feed-forward view of the circuit may miss important processing, however, as earlier studies suggested, and the current results re-emphasize. Firstly, gap junctions between KCs have been reported. This opens up the possibility for lateral propagation of signals across KCs, either biochemical or electrical. For example, in mammalian systems, axo-axonal gap junction coupling can synchronize firing between neurons. Secondly, chemical synapses between KCs have been reported in the MB pedunculus in the locust. The reconstructions show that such KC>KC connections are also present in the lobes, where they are surprisingly prevalent. In fact, the most frequent outputs of the α/βs KCs are other α/βs KCs, assuming the morphologically defined KC>KC connections are functional synapses (Takemura, 2017).

A high percentage (55%) of these putative KC>KC synapses occur in rosette-like structures where multiple KCs also converge on a single dendritic process of an MBON . These are relatively unusual structures, not observed in EM reconstructions of the Drosophila visual system and, indeed, there is no direct evidence that they are functional synapses. At present it is only possible to speculate on their role. As points of heavy convergence, they might allow the effects of synapses from different KCs onto the same dendrite to act synergistically. Activity of a single KC may spread to its neighbors within the rosette, potentially generating a large compound synaptic release event onto the MBON in the middle. Such a signal amplification mechanism may be important to ensure that individual KCs can have a significant impact on MBON membrane potential by recruiting their rosette partners. How the specificity of learning could be maintained in this scenario is, however, unclear. Several basic questions will need to be answered before it is possible to begin to understand the functional significance of these rosettes. For example, can a single KC in the rosette indeed activate its neighbors? And how similar are the response properties of the different KCs that contribute to one rosette (Takemura, 2017)?

In conclusion, the connectivity of the KCs that carry olfactory and other sensory representations supports a model where parallel distributed memory processing occurs in each compartment. However, several circuit motifs that seem designed to spread and possibly amplify signals at the sites of KC output indicate that this circuit is likely more complicated than a simple feed-forward view of the system suggests (Takemura, 2017).

Dopamine-induced plasticity of the KC>MBON synapse is thought to be central to associative learning in this system. The reconstructions showed that dopaminergic neurons make well-defined synaptic contacts within the α lobe, with closely apposed post-synaptic membranes. This contrasts somewhat with dopaminergic innervation in the mammalian system, where there is typically not such close contact with a single clear post-synaptic partner, and volume transmission is the predominant model for dopamine release. It is not known whether the direct and indirect dopaminergic release sites have different functional consequences. Nevertheless, it seems likely that some type of volume transmission happens in the mushroom body. First, ~10 times more KC>MBON synapses than presynaptic sites of dopamine release were found in the α lobe, but previous work showed that learning-induced plasticity depresses MBON responses so strongly that most inputs are likely affected. Second, dopamine would need to diffuse only ~2 μm to reach every KC>MBON synapse within a compartment, but would also be sufficiently short range to prevent significant spill-over of dopamine to neighboring compartments, ensuring that the modularity of plasticity is maintained (Takemura, 2017).

Functional connectivity measurements showed that stimulating the DANs elicits large amplitude calcium signals from MBONs, similar to previous results. Intracellular recordings revealed that this was a surprisingly strong connection, sufficient to elicit spikes in the MBON. The response persisted when both spiking and nicotinic transmission was blocked, to limit the possibility that the DANs act through the KCs, which are cholinergic. Conversely, the response was strongly reduced by adding a dopamine receptor antagonist. Taken together, these results indicate that the response is likely a direct action of dopamine released by the DANs on the MBON, although a more complex mechanism or a role for the transmitter contained in the dense core vesicles observed in the DANs cannot be formally rule out. The depolarization exhibited markedly slow dynamics, peaking >2 s after stimulation offset, and then decaying over tens of seconds. Dopaminergic responses of similar amplitude and time course have been reported in both mammalian systems and in Aplysia, where it is mediated by cAMP-driven changes in a non-selective cation conductance (Takemura, 2017).

It is possible to induce memory formation in this circuit by pairing odor delivery with artificial activation of DANs. Targeting this optogenetic training procedure to DANs that innervate different compartments within the α lobe gives rise to memories with different valence, induction threshold and persistence. In the α1 compartment, a single pairing for 1 min induces an appetitive memory that lasts for 1 day. In contrast, optogenetic training focused on the α3 compartment requires multiple 1 min pairings, repeated at spaced intervals, and induces an aversive memory that lasts for 4 days. Although it seems likely that the different valences reflect the different projection sites of the MBONs for each of these compartments, where the differences in induction threshold and memory persistence might arise is less clear. There is no simple explanation for these differences from the EM-level circuit structure, as the basic wiring motifs were very similar in each compartment. Moreover, any explanation that invokes biochemical differences in KC>MBON synapses would require crisp spatial localization of the signaling pathway machinery that triggers plasticity, as exactly the same KCs participate in memory formation in different compartments. However, the observation that there are DAN>MBON synapses raises the possibility that biochemical differences in the MBONs might contribute to these differences in plasticity induction and maintenance. Indeed, RNAseq data from a set of four different MBONs showed expression of dopamine receptors. An alternative possibility, suggested by the findings in this study, is that the cotransmitter found in the dense core vesicles in the DANs is responsible for these differences. The size of these vesicles differs between DANs innervating the different compartments. Thus, these cells might release distinct co-transmitters, as has been observed in mammalian brain, which could trigger different signaling cascades in either the KCs or the MBONs to differentially modulate the induction and expression of plasticity across compartments (Takemura, 2017).

Models of MB function have generally considered the role for DANs to be confined to relaying signals about punishment or reward to the MB. However, in the mammalian brain, DANs can dynamically change their responses to both US and CS. In this study, it was found that the axonal terminals of the DANs receive many inputs from KCs within the lobes. In other words, both MBONs, DANs and even KCs receive extensive synaptic input from KCs in each compartment. If the current model that plasticity is pre-synaptic proves to be correct, this suggests that the responses of the DANs themselves would be subject to plasticity. If the synaptic depression observed at KC>MBON synapses also acts at KC>DAN connections, odor-evoked DAN responses would be diminished as a result of learning. This would serve as a negative feedback loop, reducing the strength of plasticity on successive training cycles with the same odor. Indeed, a gradually plateauing of the learning curve is a common feature of memory formation in different systems, including olfactory conditioning in Drosophila (Takemura, 2017).

One of the more surprising findings of this study was the observation that there are many direct DAN>MBON synaptic connections. Moreover, the functional connectivity measures indicate that these were relatively strong excitatory inputs. The excitatory sign of the DAN>MBON connection is also consistent with the behavioral effects of DAN activation that was observed. What role these DAN>MBON connections play in overall circuit function is an important question for future work. There are two general possibilities that are felt to be interesting to consider. Dopaminergic modulation has been proposed to play a general role in routing of information through the MB to different downstream neurons. Although changes in KC>MBON strength contribute to this process, the current results suggest that such state changes could also potentially be conveyed to the MBONs directly from the DANs. State-dependent changes in DAN activity have indeed been observed with calcium imaging. The slow synaptic dynamics observed in the DAN>MBON connection in MBON-α1 suggest the possibility that small changes in DAN firing might be capable of producing sustained changes in MBON membrane potential reflecting the current internal state of the animal (Takemura, 2017).

A second possibility, suggested from the framework of reinforcement learning established in vertebrates, is related to motivation and the comparison of expected versus actual reward. In Drosophila, prior work on odor-sugar conditioning in larvae provided evidence that flies form a comparison between the current state of reward and the reward expected from the conditioned cue. This work showed that animals behaviorally express memories only when the expected reward intensity is higher than the currently available reward. This is similar to the results presented in this study; just as the presence of reward diminished memory expression in the larvae, stimulating the DANs suppressed performance of animals trained by the optogenetic conditioning. The need to compare current and expected reward could potentially explain why there is an opponent relationship between the depression of KC>MBON synapses that drives associative learning and the excitatory effects of the DAN>MBON connection. If depression dominates, the association drives behavior, but this can be overridden by sufficient levels of DAN activity. In this respect, it is noteworthy that DANs appear to be able to act directly on the MBON, without participation of the KCs. Overall, this comparison could ensure that learned behavior is motivated not strictly by the expectation of reward, but rather the expected increase in reward, assessed at the moment of testing (Takemura, 2017).

The organization of the MB into a set of compartments arranged in series along the KC axons is well suited for simultaneously storing multiple independent memories of a given sensory stimulus. However, there must be some means by which these modules interact with one another to ensure coordinated, coherent expression of memory. Feedforward connections that link different compartments, first discovered by light microscopic anatomy, have recently been shown to be important for mediating such interactions. In particular, MBON-γ1pedc>α/β is an inhibitory neuron that connects aversive and appetitive learning compartments; it ensures that the circuit can readily toggle between different behavioral outputs (Takemura, 2017).

The EM reconstructions included both MBON-γ1pedc>α/β and MBON-β1>α, two feedforward neurons which project from their respective compartments to widely innervate other parts of the MB. Memories stored in the α lobe compartments are long-term and relatively inflexible, whereas the short-term memories formed in β1 and γ1pedc are readily updated by recent experiences. The feedforward connections are thought to enable the short-term memories in β1 and γ1pedc to temporarily mask expression of the stable memories stored in the α lobe. Indeed training an animal with either a multi-component aversive/appetitive food stimulus, or by simultaneous optogenetic activation of a composite set of DANs covering both appetitive and aversive compartments results in a compound memory that is initially aversive and later transitions to appetitive. The connectome results show that the primary synaptic targets of these feedforward neurons are the MBONs in the downstream compartment. By contrast, relatively few connections onto KCs were observed. Overall, this suggests that the feedforward connections can strongly influence the output from a compartment, but likely have little impact on the sensory information delivered to each compartment from the KCs. This is consistent with observations that MBON-γ1pedc>α/β strongly modulates activity of glutamatergic neurons at the tip of the horizontal lobe, but not their dendritic responses. Targeting these feedforward connections to the MBON may ensure that conflicting memories can form simultaneously in response to a complex sensory input, but with the behavioral manifestation of those memories capable of undergoing a crisp switch (Takemura, 2017).

This study has provided synapse level anatomical information on neuronal circuits involved in learning and memory in Drosophila. The comprehensive nature of this dataset should enable modeling studies not previously possible and suggests many experiments to explore the physiological and behavioral significance of the circuit motifs that were observed. That many of these motifs were not anticipated by over 30 years of extensive anatomical, experimental and theoretical studies on the role of the insect MB argues strongly for the value of electron microscopic connectomic studies (Takemura, 2017).

A dense (complete) reconstruction of neurons and synapses is resource intensive, so it is reasonable to ask if tracing a subset of cells or synapses could have yielded similar results with less effort. This is hard to answer in general, since there are many sparse tracing strategies, and each can be pursued to differing degrees of completeness. It is likely that most sparse tracing strategies would have discovered the new pathways reported in this, as the connections are numerous and connect well known cell types. Conversely, the conclusions that all cell types in this circuit had been identified would have been more difficult to make with confidence and a rare cell type, such as the SIFamide neuron, might have been missed. Perhaps, most importantly, statistical arguments, particularly those that require an accurate assessment of which cells are not connected, such as the absence of network structures such as rings or chains, would have been hard to make from sparse tracing. More generally, the model independent nature of dense tracing helps to discover any 'unknown unknowns', provides the strongest constraints on how neural circuits are constructed, and allows retrospective analysis of network properties not targeted during reconstruction (Takemura, 2017).

Trace conditioning in Drosophila induces associative plasticity in mushroom body kenyon cells and dopaminergic neurons
Dylla, K. V., Raiser, G., Galizia, C. G. and Szyszka, P. (2017). Front Neural Circuits 11: 42. PubMed ID: 28676744

Dopaminergic neurons (DANs) signal punishment and reward during associative learning. In mammals, DANs show associative plasticity that correlates with the discrepancy between predicted and actual reinforcement (prediction error) during classical conditioning. Also in insects, such as Drosophila, DANs show associative plasticity that is, however, less understood. This study examined ssociative plasticity in DANs and their synaptic partners, the Kenyon cells (KCs) in the mushroom bodies (MBs), while training Drosophila to associate an odorant with a temporally separated electric shock (trace conditioning). In most MB compartments DANs strengthened their responses to the conditioned odorant relative to untrained animals. This response plasticity preserved the initial degree of similarity between the odorant- and the shock-induced spatial response patterns, which decreased in untrained animals. Contrary to DANs, KCs (α'/β'-type) decreased their responses to the conditioned odorant relative to untrained animals. No evidence was found for prediction error coding by DANs during conditioning. Rather, the data supports the hypothesis that DAN plasticity encodes conditioning-induced changes in the odorant's predictive power (Dylla, 2017).

Associative learning enables animals to anticipate negative or positive events. The neural mechanisms of associative learning are commonly studied in classical conditioning paradigms, in which animals are trained to associate a cue (conditioned stimulus; CS) with a punishment or reward (unconditioned stimulus; US). In the standard conditioning paradigm CS and US overlap in time, while in the trace conditioning paradigm there is a temporal gap between the CS and US. During both standard conditioning and trace conditioning, the US is mediated by dopaminergic neurons (DANs), in animals as diverse as monkeys and fruit flies (Dylla, 2017).

Genetic tools for monitoring and manipulating neuronal activity in the fruit fly Drosophila melanogaster promoted the understanding of the neural mechanisms of dopamine-mediated learning. Those mechanisms are well-described for standard 'odor-shock conditioning' in Drosophila, in which an olfactory CS is paired with a temporally overlapping electric shock US. During conditioning, an odor-shock association is formed in the mushroom body (MB) neuropil. The intrinsic neurons of the MB, the Kenyon cells (KCs), receive olfactory input in the MB-calyx and project to the vertical (α and α'), and the medial (β, β', and γ) MB-lobes. During odor-shock conditioning, the olfactory CS activates an odorant-specific KC population, and the electric shock US activates DANs that innervate the MB-lobes. In KCs, the CS-induced increase in intracellular calcium and the US-(dopamine)-induced second messengers synergistically activate an adenylyl cyclase, which alters the synaptic strength between KCs and MB output neurons (MBONs). This change in KC-to-MBON synapses is thought to encode the associative odor memory (Dylla, 2017).

The MB-lobes are divided into 15 compartments (α1-3, β1-2, α'1-3, β'1-2, and γ1-5), each of which is innervated by a distinct population of DANs and MBONs. These compartments constitute functional units, which are involved in different forms of associative learning. In compartments such as γ1, γ2, and β2, DANs mediate electric shock reinforcement. Besides mediating reinforcement during classical conditioning, Drosophila DANs are involved in long-term memory formation, forgetting, extinction learning and memory reconsolidation, and in integrating internal states with memory and sensory processing. A single DAN can even serve different functions, for example, PPL1-γ1pedc (also referred to as MB-MP1) signals reinforcement, and controls state-dependent memory retrieval (Dylla, 2017).

The functional complexity of Drosophila DANs is further increased by the fact that DANs show learning-induced associative plasticity: they increase their response to the CS during classical conditioning. Mammalian DANs also increase their CS-induced responses during classical conditioning. In addition, they decrease their response to the US, and when a predicted US does not occur, they decrease their activity below baseline level. This pattern of response plasticity in mammalian DANs is compatible with the hypothesis that animals only learn to associate a CS with a US, when the US occurs unpredictably. Thus, mammalian DANs appear to encode this prediction error. In Drosophila, however, DANs do not change their response to the US. Therefore, Drosophila DANs appear to encode the US prediction by the CS rather than encoding the US prediction error during classical conditioning. It is not clear, whether classical conditioning in insects is driven by US prediction error. There is evidence for prediction error-driven conditioning in crickets, but there is also a controversy about whether or not blocking (a failure to learn, when the US is already predicted by another CS) occurs (Dylla, 2017).

This study reassessed the hypothesis that Drosophila DANs do not encode the prediction error during classical conditioning. Different from Riemensperger (2005) who pooled DAN activity across the mushroom body lobes, this study differentiated between DAN types that innervate different compartments of the MB lobes. Moreover, instead of using standard conditioning, trace conditioning with a 5 s gap between the CS and the US was used, allowing for precise distinguishing between responses to either the CS or the US (Dylla, 2017).

This study investigated associative plasticity in the responses of DANs and their synaptic partners, the KCs, across the compartments of the Drosophila MB. Using calcium imaging, CS- and US-induced responses of a subpopulation of DANs (labeled by TH-GAL4) and of KCs (labeled by OK107-GAL4) were recorded during odor-shock trace conditioning. Note, that most compartments are innervated by multiple TH-GAL4-labeled DANs. Therefore, the average activity that was recorded in most of the compartments might mask possible differences in the response properties and plasticity between individual DANs and KCs. Only DAN responses in the compartments γ2 and α'1 reflect the responses of a single neuron (Dylla, 2017).

Across MB compartments, DANs and KCs differed in their response strength to odorants and electric shock, and they differed in CS-US pairing-induced plasticity. Compared to the unpaired control groups, KCs decreased their responses to the CS in all compartments of the β'-lobe and in the junction, while DANs increased their responses to the CS in all compartments of the γ- and β'-lobe, and in the junction. The occurrence of associative plasticity in DANs in the compartments γ3-5 and β'1 is surprising, given that these DANs are not known to be involved in odor-shock conditioning, after training there was neither an associative change in US-induced DAN responses nor a change of activity during US-omission after CS presentation. It is therefore concluded that Drosophila DANs do not encode the US-prediction error during classical conditioning (Dylla, 2017).

Previous studies suggested that DANs in the MB lobes respond strongly to electric shock and weakly to odorants. The compartment-resolved analysis of the calcium imaging data refines this picture: It is confirmed that DANs of all imaged compartments respond to both electric shock and odorants, and it was shown that their relative response strength to odorants and electric shock differs across compartments. For example, DANs innervating γ1 responded stronger to electric shock than to odorants, while DANs innervating β'2 responded equally strong to odorants and electric shock. The strongest DAN responses to electric shock were shown to be in the compartments γ1 and γ2. These compartments receive input from PPL1-γ1pedc and PPL1-γ2α'1 DANs that mediate electric shock reinforcement. In all compartments, except in α1/α'1, the DAN response strength correlated positively with the current strength encountered by individual flies. Thus, DANs are capable of encoding the strength of the electric shock US, and this property may account for the positive dependence between electric shock strength and learning performance in flies (Dylla, 2017).

Calcium responses in KCs differ between MB lobes, and they differ between the compartments of a given lobe, possibly due to compartment-specific modulation by DANs and MBONs. KCs in γ2 and γ3 responded strongest to odorants, confirming the results of Cohn (2015). KCs generally responded only weakly to electric shocks. Previously published strong KC responses to electric shock may be because electric shocks were applied to the flies' abdomen rather than to their legs, which might have resulted in a stronger stimulation (Dylla, 2017).

The associative strengthening of DAN responses to the olfactory CS (as compared to the unpaired control group), confirms the previous report by Riemensperger (2005). Associative plasticity occurred in those DANs that innervate the MBs (PPL1 and PAM cluster DANs; note that the used TH-GAL4 driver line covers only a small subpopulation of PAM neurons but not in DANs that innervate the central complex (PPL1 and PPM3 cluster DANs). This is in line with the established role of MB innervating-DANs in associative memory formation, while central complex-innervating DANs are involved in behaviors such as locomotion, wakefulness, arousal, and aggression, and are therefore not expected to show odor-shock conditioning-induced plasticity (Dylla, 2017).

In contrast to previous studies, this study did not find an associative increase in KC calcium responses to the CS in the MB-lobes after odor-shock conditioning. This may indicate either a difference between trace conditioning and standard conditioning, or a difference in other experimental parameters that may also account for inconsistencies in the published effects of odor-shock conditioning (Dylla, 2017).

The associative decrease in KC responses in the β'-lobe compartments is in line with previous studies that showed conditioning-induced depression of KC-to-MBON synapses (Cohn, 2015; Hige, 2015). Therefore, it propose that the associative decrease in KC responses to the CS reflects a presynaptic depression at KC-to-MBON synapses in β'-lobe compartments (Dylla, 2017).

What is the site of neuronal plasticity that underlies the relative increase in DANs' responses to the olfactory CS? Riemensperger (2005) proposed that DANs get odorant-driven excitatory input via a MBON feedback loop that is strengthened during odor-shock conditioning. However, the DAN population is composed of different neuron types that do not share a common input either from MBONs or from other neurons that could explain the global associative plasticity across MB compartments. Because KCs presumably provide the only common odor-driven input to all MB-innervating DANs, it is suggested that the site of associative plasticity is located in a KC-to-DAN synapse. Indeed, KC-to-DAN synapses have recently been reported in Drosophila (Cervantes-Sandoval, 2017). Associative increase in CS-induced DAN responses occurred despite unaltered or decreased KC responses in the same compartment. This suggests that the associative plasticity occurs post-synaptic in DANs and is not inherited from KCs (Dylla, 2017).

What is the neuronal substrate of CS-US coincidence detection in DANs and KCs? Drosophila trace conditioning depends on dopamine receptor-triggered signaling in KCs, as is the case for standard conditioning. However, the CS-US coincidence detection mechanism in trace conditioning is unknown. In standard conditioning the CS-induced increase in KCs' calcium concentration coincides with the US-(dopamine)-induced second messengers, which is thought to synergistically activate the rutabaga adenylyl cyclase, and ultimately alters the strength of KC-to-MBON synapses. This mechanism would not work for trace conditioning, because (1) at the time the US occurs, CS-induced increase in KCs' calcium concentration is back to baseline levels, and (2) trace conditioning does not involve the rutabaga adenylyl cyclase. It is therefore hypothesized that a non-rutabaga adenylyl cyclase or a protein kinase C could serve as a molecular coincidence detector for the CS trace and the US. For example, the CS-induced calcium and dopamine signaling could lead to a sustained activation of an adenylyl cyclase or protein kinase C in KCs, which then would increase synergistically and drive synaptic plasticity during the US-induced dopamine signaling (Dylla, 2017).

DAN responses to odorants and associative strengthening of DAN responses to the CS-odorant are not included in current models of associative learning in the MB. However, associative plasticity is a common feature of US-mediating neurons, which occurs in mammalian and Drosophila DANs, and in an octopaminergic neuron in honey bees (Dylla, 2017).

What could be the function of odorant-induced responses and odor-shock conditioning-induced plasticity in DANs? MB-innervating DANs strengthened their response to the CS (as compared to the unpaired group) during odor-shock conditioning, in line with Riemensperger (2005). However, other than in monkey DANs, this study did not observe associative plasticity in DANs' response to the US. The data therefore support the idea that Drosophila DANs encode predictive power of the CS, e.g., US-prediction, but not the US-prediction error during classical conditioning (Dylla, 2017).

This study found shock-induced responses and associative plasticity in DANs that are not involved in odor-shock conditioning, for example in DANs innervating β'1, γ3, γ4, and γ5. This suggests that those DANs serve a function in aversive odor learning which is not captured by the commonly applied conditioning paradigms. For example, the relative strengthening of CS-induced responses could mediate reinforcement during second-order conditioning, in which a previously reinforced CS1 can act as US in subsequent conditioning of a second CS2. As Drosophila is capable of second-order learning, this theory can be tested in behavioral experiments: if associative strengthening of DAN responses to the CS underlies CS1-induced reinforcement in second-order conditioning, then preventing associative plasticity in DANs, or blocking their output during CS2-CS1 pairing should abolish second-order conditioning (Dylla, 2017).

The occurrence of CS-induced responses and associative plasticity in most of the MB-innervating DANs suggests that the separation between the CS- and US-pathway and between different US-pathways is less strict than suggested in current models of associative learning in the MB. Associative plasticity in the spatial pattern of CS-induced DAN responses makes them a potential neuronal substrate for encoding the US identity in CS-US memories and the predictive power of a CS (Dylla, 2017).

These data revealed similar response properties and plasticity rules across Drosophila DANs in the γ- and β'-lobe. This contrasts with their anatomical and functional heterogeneity, which indicates yet undiscovered mechanisms and functions of DAN plasticity. Note, that this study could not test whether the flies learned in the imaging setup, as currently no behavioral readout exists for odor-shock conditioning during physiological experiments. Nevertheless, since a conditioning protocol and stimulus application comparable to an established behavioral paradigm was used, it is believed that the associative plasticity in neuronal responses that was found underlies behavioral associative plasticity. Therewith the data lay the foundations for causal studies on the function of associative plasticity in DANs (Dylla, 2017).

Aversive learning and appetitive motivation toggle feed-forward inhibition in the Drosophila mushroom body
Perisse, E., Owald, D., Barnstedt, O., Talbot, C.B., Huetteroth, W. and Waddell, S. (2016). Neuron 90: 1086-1099. PubMed ID: 27210550

In Drosophila, negatively reinforcing dopaminergic neurons also provide the inhibitory control of satiety over appetitive memory expression. This study shows that aversive learning causes a persistent depression of the conditioned odor drive to two downstream feed-forward inhibitory GABAergic interneurons of the mushroom body, called MVP2, or mushroom body output neuron (MBON)-γ1pedc>α/β. However, MVP2 neuron output is only essential for expression of short-term aversive memory. Stimulating MVP2 neurons preferentially inhibits the odor-evoked activity of avoidance-directing MBONs and odor-driven avoidance behavior, whereas their inhibition enhances odor avoidance. In contrast, odor-evoked activity of MVP2 neurons is elevated in hungry flies, and their feed-forward inhibition is required for expression of appetitive memory at all times. Moreover, imposing MVP2 activity promotes inappropriate appetitive memory expression in food-satiated flies. Aversive learning and appetitive motivation therefore toggle alternate modes of a common feed-forward inhibitory MVP2 pathway to promote conditioned odor avoidance or approach (Perisse, 2016).

Prior work in Drosophila indicated that negative reinforcement and hunger-state-dependent motivational control of appetitive memory performance might be controlled by the same dopaminergic neurons (DANs). The presynaptic field of the MP1/PPL1-γ1pedc DANs occupies a defined region of the MB that also contains the MVP2/MBON-γ1pedc >αβ dendrites, suggesting that these DANs modulate the efficacy of this specific KC-MBON connection. The results of the current study demonstrate that the MVP2 MBONs also play a critical role in the expression of short-term aversive memory and the state-dependence of appetitive memory expression. Since these findings directly mirror the described roles for the MP1 DANs (Krashes, 2009), it is concluded that DAN modulation of the KC-MVP2 junction is critical for both negative reinforcement during olfactory learning and the motivational salience of appetitive odor cues (Perisse, 2016).

The GABA-ergic MVP2 neurons have postsynaptic and presynaptic processes in the MB, suggesting that they are interneurons of the MB and feed-forward inhibit other MBON compartments. Dendrites of MVP2 neurons (and the presynaptic terminals of the MP1 DANs) innervate the γ1 region and more densely innervate the αβs than the αβ core (αβc) region of the αβ ensemble (Krashes, 2009). MVP2 are therefore likely to be primarily driven by αβs KCs. Since αβs neurons contribute to conditioned approach and avoidance, whereas αβc are particularly important for conditioned approach (Perisse, 2013), there is an imbalance in the drive to approach and avoidance behaviors at this level of the MBON network (Perisse, 2016).

Artificial activation of MVP2 neurons in naive flies drives approach behavior, consistent with them preferentially inhibiting MBON compartments that direct avoidance -- as opposed to those that drive approach. Anatomical and functional connectivity and odor-directed behavioral data are consistent with such a model. MVP2 stimulation inhibits odor-evoked activity in M4/6 but not in V2αV2α' MBONs. MVP2 stimulation also promotes expression of approach memory in food-satiated flies, yet it inhibits naive odor avoidance behavior. It is concluded that MVP2 directly inhibit the M4/6 class of horizontal lobe MBONs through synapses made on the primary axonal segment as it exits the MB lobes. Inhibition exerted in this area might be expected to control the gain of the MBON responses following integration of KC inputs in the MBON dendrite in a manner similar to perisomatic inhibition in mammals. Consistent with this anatomy and idea, no obvious changes were found in the odor drive to the dendritic region of M4/6 neurons between hungry and satiated flies, but a hunger-dependent decrease was apparent when odor-evoked responses were measured in the efferent neurites. In contrast, MVP2 neurons do not functionally inhibit or densely innervate the neurites of V2αV2α' MBONs, nor does hunger reduce odor-evoked responses in V2αV2α' MBONs. It therefore seems likely that MVP2 neurons contact DANs or other neurons that occupy the α2 compartment of the MB lobe (Perisse, 2016).

The data also demonstrate that aversive learning reduces the relative conditioned odor drive to MVP2 neurons, which would presumably decrease feed-forward inhibition onto the relevant MBON compartments and thereby render them more responsive to odors. Output from the glutamatergic M4/6 neurons, which are postsynaptic to the KCs in the horizontal tip regions, is required for expression of aversive and appetitive memory. Furthermore, the relative odor-drive to M4/6 neurons was shown to be depressed by reward learning and potentiated by aversive learning. Since aversive learning reduces the conditioned odor drive of the MVP2 neuron, it is proposed that the observed increase in odor-drive to M4/6 after aversive learning results from reduced feed-forward inhibition from MVP2. This would mean that bi-directional output plasticity could emerge via a direct junctional plasticity following reward conditioning, but a network property of reduced MVP2 feed-forward inhibition after aversive conditioning. Such a layered feed-forward network architecture linking one site of DAN-driven KC-MBON plasticity to another KC-MBON connection would provide a means to achieve odor-specific bi-directional plasticity at a particular synaptic junction using dopamine-driven synaptic depression in two different places. It is proposed that this circuit design principle in which plasticity at one site of a neuron can, via feed-forward inhibition, indirectly alter the efficacy of output elsewhere in the same neuron, could be a general feature in the brain of the fly and other animals. It is possible that the KC-MVP2 junction also exhibits bi-directional plasticity, notably with inverted polarity relative to M4/6 plasticity traces (Perisse, 2016).

The layered network architecture places the aversive memory relevant MVP2 plasticity on top of the M4/6 plasticity that is relevant for appetitive memory (Owald, 2015). This organization could accommodate the co-existence of aversive and appetitive olfactory memories following conditioning reinforced by sugar laced with bitter taste. Immediately after such training flies avoid the conditioned odor because the aversive taste memory relieves feed-forward inhibition onto the sites that are depressed by appetitive sugar plasticity and therefore over-rides the expression of approach memory. However, as the aversive memory decays, feed-forward inhibition returns and appetitive memory is then expressed. A similar mechanism might account for the time-dependent switch from conditioned aversion to approach following odor conditioning reinforced by alcohol (Kau, 2011). It is notable that learning-induced plasticity of relative odor-drive to MVP2 persists for at least 3 hr after training whereas output from MVP2 is dispensable for the expression of aversive memory at that time. Since expression of different phases of aversive memory requires distinct combinations of MBON pathways (Bouzaiane, 2015), it is proposed that more persistent MVP2 plasticity might provide a permissive gate for both the formation of aversive memory in, and the expression from, other parts of the MBON network. This would be reminiscent of fear conditioning in the neural circuitry of the mouse amygdala, where dopamine suppresses feed-forward GABA-ergic inhibition from local interneurons to facilitate the induction of long-term potentiation (Perisse, 2016).

MVP2 neuron output is required for the expression of sugar-reinforced approach memory at all times. Moreover, odors evoked larger MVP2 responses in hungry than in food-satiated flies, and elevating MVP2 activity in satiated flies promoted inappropriate expression of appetitive memory. These results are consistent with the model that hunger generally increases feed-forward inhibition through MVP2 to support appetitive memory expression). This result is also the mirror-image of that with MP1 DANs whose activity increases when the flies are satiated and whose inhibition leads to the expression of appetitive memory in satiated flies. Taken with prior work, it is therefore proposed that hunger increases dNPF, which releases MP1 inhibition over the KC-MVP2 connection. This results in an increase of odor-evoked MVP2 feed-forward inhibition onto the MBON compartments such as M4/6 that contain the KC-MBON synapses that are directly modified by appetitive conditioning. The increase of MVP2 inhibition into these, and other, compartments allows more efficient expression of the appetitive memory-directed approach behavior by effectively raising the motivational salience of learned food-related odors. Appetitive conditioning may also increase odor-specific recruitment of MVP2 feed-forward inhibition (Perisse, 2016).

The current findings therefore suggest that the MVP2 neuron pathway functions in at least three modes that are presumably selected by the aversively reinforcing MP1 DANs. If the flies are aversively conditioned, phasic MP1 specifically depresses conditioned-odor drive to MVP2 neurons. In a food-satiated fly, tonic MP1 limits general odor-driven MVP2 activity. Lastly, in the hungry fly, lower MP1 activity generally enhances odor-drive to MVP2. In the OFF modes, low-level MVP2 feed-forward inhibition skews the MBON network toward behavioral avoidance, whereas in the ON mode the increased feed-forward inhibition from MVP2 skews the MBON network toward favoring conditioned approach. The MP1 DANs signal the aversive reinforcing properties of electric shock, heat, and bitter taste, suggesting they provide general aversive influence. The satiated state presumably uses a tonic version of this aversive signal to limit the fly approaching an appetitive odor cue (Perisse, 2016).

The parallels between the fly and mammalian dopaminergic systems appear striking. DANs in the basal ganglia of the mammalian brain also support reinforcement learning and the prediction of stimuli that potentially lead to rewarding outcomes. Furthermore, like the fly DANs, mammalian DANs can be anatomically divided into those that generate aversion and different types of reward. GABA-ergic neurons in the mouse ventral tegmental area, whose cell bodies are interspersed with the DANs, have been proposed to signal the value of expected reward and provide a source of subtraction to DANs that calculate a reward prediction error. Negatively reinforcing MP1 DANs in the fly modulate odor-drive to the MVP2 neurons to provide the motivational control over actions to gain reward. Therefore, MVP2 neurons may provide an inhibitory bridge between MBON domains that are controlled by aversive and rewarding DANs (Perisse, 2016).

Suppression of Dopamine Neurons Mediates Reward
Yamagata, N., Hiroi, M., Kondo, S., Abe, A. and Tanimoto, H. (2016). PLoS Biol 14(12): e1002586. PubMed ID: 27997541

Massive activation of dopamine neurons is critical for natural reward and drug abuse. In contrast, the significance of their spontaneous activity remains elusive. In Drosophila melanogaster, depolarization of the protocerebral anterior medial (PAM) cluster dopamine neurons en masse signals reward to the mushroom body (MB) and drives appetitive memory. Focusing on the functional heterogeneity of PAM cluster neurons, a single class of PAM neurons, PAM-γ3, mediates sugar reward by suppressing their own activity. PAM-γ3 is selectively required for appetitive olfactory learning, while activation of these neurons in turn induces aversive memory. Ongoing activity of PAM-γ3 gets suppressed upon sugar ingestion. Strikingly, transient inactivation of basal PAM-γ3 activity can substitute for reward and induces appetitive memory. Furthermore, the satiety-signaling neuropeptide Allatostatin A (AstA) was identified as a key mediator that conveys inhibitory input onto PAM-γ3. These results suggest the significance of basal dopamine release in reward signaling and reveal a circuit mechanism for negative regulation (Yamagata, 2016).

Sugar ingestion triggers multiple reward signals in the fly brain. This study has provided lines of evidence that part of the reward is signaled by inactivating dopamine neurons. The role of PAM-γ3 highlights the striking functional heterogeneity of PAM cluster dopamine neurons. The decrease and increase of dopamine can convey reward to the adjacent compartments of the same MB lobe-γ3 and γ4-. The reward signal by the transient decrease of dopamine is in stark contrast to the widely acknowledged role of dopamine. Midbrain dopamine neurons in mammals were shown to be suppressed upon the presentation of aversive stimuli or the omission of an expected reward, implying valence coding by the bidirectional activity. As depolarization of PAM-γ3 can signal aversive reinforcement, these neurons convey the opposite modulatory signals to the specific MB domain by the sign of their activity. Intriguingly, the presentation and cessation of electric shock act as punishment and reward, respectively. Such bidirectional activity of PAM-γ3 may represent the presentation and omission of reward. (Yamagata, 2016).

While thermoactivation of PAM-γ3 induced robust aversive memory, blocking their synaptic transmission did not affect shock learning, leaving a question regarding their role in endogenous aversive memory process. PAM-γ3 may only be involved in processing aversive reinforcement different from electric shock-like heat. However, two studies show that dopamine neurons mediating aversive reinforcement of high temperature and bitter N,N-Diethyl-3-methylbenzamide (DEET) are part of those for electric shock. Identification of such aversive stimuli that are signaled by PAM-γ3 activation is certainly interesting, as it is perceived as the opposite of sugar reward and thus provides the whole picture of the valence spectrum. Another scenario where sufficiency and necessity do not match is the compensation of the reinforcing effect by other dopamine cell types (e.g. MB-M3). The lack of PAM-γ3 requirements for electric shock memory may be explained by a similar mechanism. (Yamagata, 2016).

How can the suppression of PAM-γ3 modulate the downstream cell and drive appetitive memory? Optogenetic activation of the MB output neurons from the γ3 compartment induces approach behavior. This suggests that the suppression of the PAM-γ3 neurons upon reward leads to local potentiation of Kenyon cell output. This model is supported by recent studies showing the depression of MB output synapses during associative learning. A likely molecular mechanism is the de-repression of inhibitory D2-like dopamine receptors, DD2R. As D2R signaling is a widely conserved mechanism, it may be one of the most ancestral modes of neuromodulation. (Yamagata, 2016).

Furthermore, recent anatomical and physiological studies demonstrated that different MB-projecting dopamine neurons are connected to each other and act in coordination to respond to sugar or shock. Therefore, memories induced by activation or inhibition of PAM-γ3 may well involve the activity of other dopamine cell types (Yamagata, 2016).

The finding that appetitive reinforcement is encoded by both activation and suppression of dopamine neurons raises the question as to the complexity of reward processing circuits (see Reward signals by excitation and inhibition of dopamine neurons). It is, however, reasonable to implement a component like PAM-γ3 as a target of the satiety-signaling inhibitory neuropeptide AstA. Intriguingly, the visualization of AstA receptor distribution by DAR-1-GAL4 revealed expression in two types of MB-projecting dopamine neurons: PAM-γ3 and MB-MV1 (also named as PPL1- γ2α'1). Given the roles of MB-MV1 in aversive reinforcement and locomotion arrest, AstA/DAR-1 signaling may also inhibit a punishment pathway upon feeding. It is thus speculated that this complex dopamine reward circuit may be configured to make use of bidirectional appetitive signals in the brain (Yamagata, 2016).

Sweet taste and nutrient value subdivide rewarding dopaminergic neurons in Drosophila
Huetteroth, W., Perisse, E., Lin, S., Klappenbach, M., Burke, C. and Waddell, S. (2015). Curr Biol 25(6):751-8. PubMed ID: 25728694

Dopaminergic neurons provide reward learning signals in mammals and insects. Recent work in Drosophila has demonstrated that water-reinforcing dopaminergic neurons are different to those for nutritious sugars. This study tested whether the sweet taste and nutrient properties of sugar reinforcement further subdivide the fly reward system. They found that dopaminergic neurons expressing the OAMB octopamine receptor specifically conveyed the short-term reinforcing effects of sweet taste. These dopaminergic neurons projected to the β'2 and γ4 regions of the mushroom body lobes. In contrast, nutrient-dependent long-term memory required different dopaminergic neurons that project to the γ5b regions, and it could be artificially reinforced by those projecting to the β lobe and adjacent α1 region. Surprisingly, whereas artificial implantation and expression of short-term memory occurred in satiated flies, formation and expression of artificial long-term memory required flies to be hungry. These studies suggest that short-term and long-term sugar memories have different physiological constraints. They also demonstrate further functional heterogeneity within the rewarding dopaminergic neuron population (Huetteroth, 2015).

These results demonstrate that the sweet taste and nutrient properties of sugars are independently processed and reinforce memories of different duration. Sweet taste is transduced through octopaminergic neurons whose released octopamine, via the OAMB receptor, activates dopaminergic neurons that project to the β'2am and γ4 regions of the mushroom body. Octopaminergic reinforcement also modulates the state dependence of STM via the OCTβ2R receptor that is required in the dopaminergic MB-MP1 neurons (Huetteroth, 2015).

Nutrient-dependent LTM does not involve octopamine or sweet-taste-reinforcing dopaminergic neurons. Nutrient reinforcement instead requires dopaminergic neurons innervating γ5b of the mushroom body, whereas those going to β1, β2, and the adjacent α1 region are sufficient. More work will be required to understand this distributed process, which apparently has an immediate and delayed dynamic (Huetteroth, 2015).

Whereas formation and expression of sweet-taste-reinforced STM is insensitive to satiety state, artificial formation and expression of nutrient-relevant memory require flies to be hungry. Even direct stimulation of the relevant rewarding dopaminergic neurons cannot implant appetitive LTM in food-satiated flies. These experiments suggest that hunger establishes an internal state that permits the nutrient-reinforcing signals to be effective. It will be interesting to understand what the permissive state involves and where it is required. Others have previously described a role for CREB-regulated transcription co-activator 1 (CRTC) in enabling hunger-dependent LTM in the fly and promoting persistent memory in the mouse. It therefore seems plausible that such a mechanism might be required in the mushroom body neurons to permit nutrient-dependent reinforcement (Huetteroth, 2015).

Parallel circuits control temperature preference in Drosophila during ageing
Shih, H.W., Wu, C.L., Chang, S.W., Liu, T.H., Sih-Yu Lai, J., Fu, T.F., Fu, C.C. and Chiang, A.S. (2015). Nat Commun 6: 7775. PubMed ID: 26178754

The detection of environmental temperature and regulation of body temperature are integral determinants of behaviour for all animals. These functions become less efficient in aged animals, particularly during exposure to cold environments, yet the cellular and molecular mechanisms are not well understood. This study identifies an age-related change in the temperature preference of adult fruit flies that results from a shift in the relative contributions of two parallel mushroom body (MB) circuits-the β'- and β-systems. The β'-circuit primarily controls cold avoidance through dopamine signalling in young flies, whereas the β-circuit increasingly contributes to cold avoidance as adult flies age. Elevating dopamine levels in β'-afferent neurons of aged flies restores cold sensitivity, suggesting that the alteration of cold avoidance behaviour with ageing is functionally reversible. These results provide a framework for investigating how molecules and individual neural circuits modulate homeostatic alterations during the course of senescence (Shih, 2015).

Coordinated and compartmentalized neuromodulation shapes sensory processing in Drosophila
Cohn, R., Morantte, I. and Ruta, V. (2015). Cell 163(7): 1742-1755. PubMed ID: 26687359

Learned and adaptive behaviors rely on neural circuits that flexibly couple the same sensory input to alternative output pathways. This study shows that the Drosophila mushroom body functions like a switchboard in which neuromodulation reroutes the same odor signal to different behavioral circuits, depending on the state and experience of the fly (see Compartmentalized Architecture of the Mushroom Body). Using functional synaptic imaging and electrophysiology, it was shown that dopaminergic inputs to the mushroom body modulate synaptic transmission with exquisite spatial specificity, allowing individual neurons to differentially convey olfactory signals to each of their postsynaptic targets. Moreover, the dopaminergic neurons function as an interconnected network, encoding information about both an animal's external context and internal state to coordinate synaptic plasticity throughout the mushroom body. These data suggest a general circuit mechanism for behavioral flexibility in which neuromodulatory networks act with synaptic precision to transform a single sensory input into different patterns of output activity (Cohn, 2015).

This study took advantage of the mushroom body's orderly architecture to gain insight into the circuit mechanisms through which neuromodulation mediates flexible sensory processing. Compartmentalized dopaminergic signaling permits independent tuning of synaptic transmission between an individual KC and its repertoire of postsynaptic MBON targets. As a consequence, the same KC odor representation can evoke different patterns of output activity, depending on the state of the animal and the dopaminergic network. Recent data indicate that the ensemble of MBONs acts in concert to bias an animal's behavioral response to an odor such that altering the balance of their activity can modify the olfactory preferences of both naive and trained animals. In accord with such a model, this study revealed how a distributed neuromodulatory network is poised to orchestrate plasticity across all 15 compartments of the mushroom body and reweight the net output of the MBONs, allowing for adaptive behavioral responses based on the immediate needs or past experience of the animal (Cohn, 2015).

Distinct subsets of DANs are sufficient to drive learned olfactory associations, leading to the suggestion they may act autonomously to encode the rewarding or punishing contextual stimuli that assign meaning to an odor. The current data, however, suggest a more complex circuit architecture, in which rich functional interconnectivity between compartments contributes to coordinated and bidirectional patterns of activity across the DAN population. This raises the possibility that reinforcement experiences may be represented by combinatorial patterns of DAN excitation and inhibition in different compartments, endowing the dopaminergic population with a greater capacity to instruct behavior via the limited repertoire of mushroom body outputs. Intriguingly, midbrain dopaminergic neurons responsive to punishment and reward also project to distinct targets in the mammalian brain and display a similar functional opponency as a consequence of reciprocal network interactions. Thus, the concerted and partially antagonistic action of neuromodulatory pathways may represent a general and conserved circuit principle for generating adaptive behavioral responses (Cohn, 2015).

Distinct DAN network activity states are evoked by electric shock and sugar ingestion, reinforcers classically used in associative olfactory conditioning paradigms because of their strong inherent valence. However, similarly distributed patterns of DAN activity are correlated with the fly's motor activity, implying that an animal's behavioral state might serve as a reinforcement stimulus that itself drives synaptic plasticity to shape odor processing. Metabolic states, such as thirst and hunger, have been shown to gate appetitive reinforcement by water and sugar rewards, permitting state-dependent formation of olfactory associations only in motivated animals. The current data highlight an additional facet of how an animal's internal state can regulate dopamine release to adjust the salience of contextual cues. Together, these observations indicate that the distributed DAN network integrates information about external context and internal state with MBON feedback to represent the moment-by-moment experience of an animal and dynamically regulate the flow of olfactory signals through the mushroom body (Cohn, 2015).

The independent regulation of synapses along an axon is thought to permit a single neuron to convey specialized information to different downstream targets, providing additional flexibility and computational power to neural circuits. In the mushroom body, synapse-specific plasticity is achieved through spatially restricted patterns of dopaminergic modulation that divide a KC axon into functionally distinct segments. Thus, the ensemble of synapses within a compartment, as the site of convergence for sensory and contextual signals, represents the elementary functional unit that underlies experience-dependent mushroom body output (Cohn, 2015).

Within a compartment, multiple neuromodulatory mechanisms appear to shape synaptic signaling. Broad potentiation of KC-MBON synapses is seen after DAN activation, but odor-specific depression is seen if DANs were coincidently activated with KCs, consistent with the synaptic changes previously proposed to occur after learning. Taken together, these findings indicate that neuromodulation in the mushroom body instructs opposing forms of synaptic plasticity, analogous to the bidirectional tuning of synaptic strength by dopamine in mammalian brain centers. The molecular mechanisms through which dopamine can direct diverse synaptic changes within a compartment remain to be elucidated, but they may depend on signaling through different dopamine receptors or downstream signaling cascades that function as coincidence detectors. Indeed, while DopR1 in KCs is essential to the formation of learned olfactory associations, this receptor was found to play only a subtle role in the context-dependent patterning of Ca2+ along their axons. Conversely, DopR2 strongly influences the topography of presynaptic Ca2+ along KC axons, in accord with evidence that tonic release of dopamine during ongoing behavior acts through this receptor to interfere with the maintenance of specific learned olfactory associations. Thus, distinct molecular pathways may transform the same dopaminergic reinforcement signals into synaptic changes of opposite polarity to shape olfactory processing based on both the present context and prior experiences of an individual (Cohn, 2015).

The mushroom body has been most extensively studied as a site for associative learning in which the temporal pairing of an odor with a reinforcement experience selectively alters subsequent behavioral responses to that odor. The current data suggest that the convergence of DAN network activity and KC olfactory representations within the mushroom body lobes may drive associative plasticity in each compartment, allowing the odor tuning of the MBON repertoire to reflect the unique experiences of an individual. However, these observations also provide insight into the mushroom body's broader role in the context-dependent regulation of innate behaviors. The ongoing activity of the distributed DAN network, encoding information about an animal's current environmental context and behavioral state, is poised to continuously reconfigure the activity patterns of the MBON population to allow for adaptive responses based on the acute needs of the animal. This context-dependent synaptic modulation could potentially erode odor-specific learned associations within the mushroom body, permitting the immediate circumstances of an animal to dominate over previously learned olfactory associations that may no longer be predictive or relevant. The axons of MBONs ultimately converge with output pathways from the lateral horn, a Drosophila brain center thought to mediate stereotyped responses to odors, providing a potential substrate for learned and context-dependent output from the mushroom body to influence inherent olfactory preferences (Cohn, 2015).

Thus, the dual role of neuromodulation in the mushroom body-to select among alternative circuit states that regulate both innate and learned behaviors-is reminiscent of its function in other higher integrative brain centers. In the basal ganglia, for example, different temporal patterns of dopamine release are thought to select the relevant circuit configurations that control inherently motivated behaviors as well as reinforcement learning. The generation of flexible behavioral responses based on experience, whether past or present, may therefore rely on common integrative brain structures in which neuromodulatory networks act with exquisite spatial precision to shape sensory processing (Cohn, 2015).

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The neuronal architecture of the mushroom body provides a logic for associative learning
Aso, Y., Hattori, D., Yu, Y., Johnston, R. M., Iyer, N. A., Ngo, T. T., Dionne, H., Abbott, L., Axel, R., Tanimoto, H. and Rubin, G. M. (2014). Elife 3. PubMed ID: 25535793.

Animals discriminate stimuli, learn their predictive value and use this knowledge to modify their behavior. In Drosophila, the mushroom body (MB) plays a key role in these processes. Sensory stimuli are sparsely represented by approximately 2000 Kenyon cells, which converge onto 34 output neurons (MBONs) of 21 types (see Circuit diagrams of the mushroom body). The role of MBONs were studied in several associative learning tasks and in sleep regulation, revealing the extent to which information flow is segregated into distinct channels and suggesting possible roles for the multi-layered MBON network. Optogenetic activation of MBONs can, depending on cell type, induce repulsion or attraction in flies. The behavioral effects of MBON perturbation are combinatorial, suggesting that the MBON ensemble collectively provides an adaptive mechanism to assign valence-positive or negative survival value-to a sensory stimulus then store that information, and recall it when that same stimulus is encountered again. It is proposed that local, stimulus-specific dopaminergic modulation selectively alters the balance within the MBON network for those stimuli. These results suggest that valence encoded by the MBON ensemble biases memory-based action selection (Aso, 2014: PubMed).

To survive in a dynamic environment, an animal must discover and remember the outcomes associated with the stimuli it encounters. It then needs to choose adaptive behaviors, such as approaching cues that predict food and avoiding cues that predict danger. The neural computations involved in using such memory-based valuation of sensory cues to guide action selection require at least three processes: (1) sensory processing to represent the identity of environmental stimuli and distinguish among them; (2) an adaptive mechanism to assign valence-positive or negative survival value-to a sensory stimulus, store that information, and recall it when that same stimulus is encountered again; and (3) decision mechanisms that receive and integrate information about the valence of learned stimuli and then bias behavioral output. To understand such decision-making processes, one approach is to locate the sites of synaptic plasticity underlying memory formation, identify the postsynaptic neurons that transmit stored information to the downstream circuit and discover how their altered activities bias behavior (Aso, 2014).

The mushroom body (MB) is the main center of associative memory in insect brains. While the MB processes several modalities of sensory information and regulates locomotion and sleep, MB function has been most extensively studied in the context of olfactory memory-specifically, associating olfactory stimuli with environmental conditions in order to guide behavior. In Drosophila, olfactory information is delivered to the MB by projection neurons from each of ~50 antennal lobe glomeruli. Connections between the projection neurons and the ~2000 Kenyon cells (KCs), the neurons whose parallel axonal fibers form the MB lobes, are not stereotyped; that is, individual flies show distinct wiring patterns between projection neurons and KCs. Sparse activity of the KCs represents the identity of odors. The output of the MB is conveyed to the rest of the brain by a remarkably small number of neurons-34 cells of 21 cell types per brain hemisphere (Aso, 2014).

The information flow from the KCs to the MB output neurons (MBONs) has been proposed to transform the representation of odor identity to more abstract information, such as the valence of an odor based on prior experience (see discussion in Aso, 2014a). In contrast to KCs, MBONs have broadly tuned odor responses; any given odor results in a response in most MBONs, although the magnitude of the response varies among MBON cell types. Unlike the stereotyped response to odors of the olfactory projection neurons that deliver odor information to the MB, the odor tuning of the MBONs is modified by plasticity and varies significantly between individual flies, suggesting that MBONs change their response to odors based on experience (Aso, 2014).

For olfactory associative memory in Drosophila, multiple lines of evidence are consistent with a model in which dopamine-dependent plasticity in the presynaptic terminals of KCs alters the strength of synapses onto MBON dendrites. This is thought to provide a mechanism by which the response of MBONs to a specific odor could represent that odor's predictive value. D1-like dopamine receptors and components of the cAMP signaling pathway, such as the Ca2+/Calmodulin-responsive adenylate cyclase encoded by the rutabaga gene, are required specifically in the KCs for memory formatio and rutabaga was shown to be required for the establishment of the differences in MBON odor tuning between individuals. Reward and punishment recruit distinct sets of dopaminergic neurons (DANs) that project to specific regions in the MB lobes. Moreover, exogenous activation of these DANs can substitute for reinforcing stimuli to induce either appetitive or aversive memory, depending on DAN cell type. In sum, while the identity of the learned odor is likely encoded by the small subset of KCs activated by that odor, whether dopamine-mediated modulation assigns positive or negative valence to that odor would be determined by where in the MB lobes KC-MBON synapses are modulated and thus which MBON cell types alter their response to the learned odor (Aso, 2014ab).

Combining the above observations with the comprehensive anatomical characterization of MB inputs and outputs lays the groundwork for testing models of how the MB functions as a whole. It is suggested that each of the 15 MB compartments-regions along the MB lobes defined by the arborization patterns of MBONs and DANs (see Circuit diagrams of the mushroom body)-functions as an elemental valuation system that receives reward or punishment signals and translates the pattern of KC activity to a MBON output that serves to bias behavior by altering either attraction or aversion. This view implies that multiple independent valuation modules for positive or negative experiences coexist in the MB lobes, raising the question of how the outputs across all the modules are integrated to result in a coherent, adaptive biasing of behavior (Aso, 2014).

Although several MBON cell types have been shown to play a role in associative odor memory, the functions of most MBONs have not been studied. Based on anatomical analyses (Aso, 2014a), it is believed that just 34 MBONs of 21 types provide the sole output pathways from the MB lobes. To gain mechanistic insight into how the ensemble of MBONs biases behavior, it would be first important to know the nature of the information conveyed by individual MBONs and the extent to which their functions are specialized or segregated into different information channels. Then it would be necessary to discover how the activities of individual MBONs contribute to influence the behavior exerted by the complete population of MBONs. Thus, in order to understand how memory is translated into changes in behavior, experimental access would be needed to a comprehensive set of MBONs and investigate how the outputs from different MBONs bias behavior, singly and in combination (Aso, 2014).

In the accompanying paper (Aso, 2014a), the detailed anatomy is described of the DANs and MBONs (see Circuit diagrams of the mushroom body and the generation of intersectional split-GAL4 driver lines to facilitate their study. All but one of the 21 MBON cell types consists of only one or two cells per hemisphere. Dendrites of MBONs that use the same neurotransmitter-GABA, glutamate or acetylcholine-are spatially clustered in the MB lobes. Intriguingly, this spatial clustering resembles the innervation patterns of modulatory input by two clusters of dopaminergic neurons, PPL1 and PAM. MBONs have their axonal terminals in a small number of brain regions, but their projection patterns also suggest pathways for relaying signals between compartments of the MB lobes; three MBONs send direct projections to the MB lobes and several other MBONs appear to target the dendrites of specific DANs (Aso, 2014).

Split-GAL4 drivers give the capability to express genetically encoded effectors in identified MBONs to modify their function. This study examine the roles of specific MBONs in various learning and memory tasks as well as in the regulation of locomotion and sleep. Whether direct activation of specific MBONs are sufficient to elicit approach or avoidance was also studied. The results indicate that the ensemble of MBONs does not directly specify particular motor patterns. Instead, MBONs collectively bias behavior by conveying the valence of learned sensory stimuli, irrespective of the modality of the stimulus or the specific reward or punishment used during conditioning (Aso, 2014).

In the insect brain, a sparse and non-stereotyped ensemble of Kenyon cells represents environmental cues such as odors. The behavioral response to these cues can be neutral, repulsive or attractive, influenced by the prior experiences of that individual and how dopaminergic and other modulatory inputs have changed the weight of its KC-MBON synapses. MBONs are thought to encode the predictive value associated with a stimulus. A fly would then use that information to bias its selection of behavioral responses in an ever-changing environment. The accompanying paper (Aso, 2014), describes in detail the projection patterns of the MBON and DAN cell types that comprise the MB lobes in Drosophila. This report begins the process of determining the nature of the information conveyed by MBONs. Specific MBON cell types were correlated with roles in associative memory and sleep regulation (see A map of MBON functions). These anatomical and behavioral results lay the groundwork for understanding the circuit principles for a system of memory-based valuation and action selection (Aso, 2014b).

Optogenetic activation of MBONs in untrained flies can induce approach or avoidance. The ability of the MBONs to induce changes in behavior in the absence of odors suggests that MBONs can bias behavior directly. This observation is consistent with a recent study showing that flies are able to associate artificial activation of a random set of KCs-instead of an odor stimulus-with electric shock, and avoid reactivation of the same set of KCs in the absence of odors (Vasmer, 2014), a result that recapitulates a finding in the potentially analogous piriform cortex of rodents. This study found that the sign of the response to MBON activation was highly correlated with neurotransmitter type; all the MBONs whose activation resulted in avoidance were glutamatergic, whereas all the attractive MBONs were cholinergic or GABAergic (Aso, 2014).

By tracking flies as they encounter a border between darkness and CsChrimson-activating light, activation of an MBON was shown to bias walking direction. Although activation of glutamatergic MBONs repelled flies, the avoidance behaviors were not stereotyped; flies showed a variety of motor patterns when avoiding the red light. This observation implies that MBONs are unlikely to function as command neurons to drive a specific motor pattern, as has been observed, for example, in recently identified descending neurons that induce only stereotyped backward walking (Aso, 2014).

Rather, fly locomotion can be considered as a goal-directed system that uses changes in MBON activity as an internal guide for taxis. For example, walking in a direction that increases the relative activity of aversive-encoding MBONs, which would occur as a fly approaches an odorant it had previously learned to associate with punishment (or when a fly expressing CsChrimson in an avoidance-inducing MBON approaches the CsChrimson activating light), signals the locomotive system to turn around and walk the other direction. Detailed studies of locomotor circuitry will be required to determine the mechanisms of executing such taxic behaviors and should help elucidate how MBON inputs guide this system (Aso, 2014b).

In this view, the MBON population functions as neither a purely motor nor a purely sensory signal. From the motor perspective, as described above, MBONs bias locomotive outcomes rather than dictate a stereotyped low-level motor program. From the sensory perspective, this study has shown that the same MBONs can be required for experience-dependent behavioral plasticity irrespective of whether a conditioned stimulus is a color or an odor, and irrespective of the specific identity of the odor. Taken together with the fact that MBONs lie immediately downstream of the sites of memory formation, these observations support the proposal that MBONs convey that a stimulus has a particular value-but not the identity of the stimulus itself. This contrasts with sensory neurons whose activity can also induce approach or avoidance, but which do convey the stimulus per se. In mammals, neural representations of abstract variables such as 'value', 'risk' and 'confidence' are thought to participate in cognition leading to action selection. From the point of view of this framework, the MBON population representing the value of a learned stimulus and informing locomotion might be operationally viewed as a cognitive primitive (Aso, 2014).

Co-activating multiple MBON cell types revealed that the effects of activating different MBONs appear to be additive; that is, activating MBONs with the same sign of action increases the strength of the behavioral response, whereas activating MBONs of opposite sign reduces the behavioral response. Thus, groups of MBONs, rather than individual MBONs, likely act collectively to bias behavioral responses. Consistent with the idea of a distributed MBON population code, all 19 MBON cell types imaged so far show a calcium response to any given odor (Aso, 2014).

If it is the ensemble activity of a large number of MBONs that determines memory-guided behavior, how can local modulation of only one or a few MB compartments by dopamine lead to a strong behavioral response? Activation of a single DAN such as PPL1-γ1pedc that innervates a highly localized region of the MB can induce robust aversive memory, yet the odor associated with the punishment will activate MBONs from all compartments, including MBONs that can drive approach as well as those that drive avoidance. It is proposed that, in response to a novel odor stimulus, the activities of MBONs representing opposing valences may initially be 'balanced', so that they do not impose a significant bias. Behavior would then be governed simply by any innate preference a fly might have to that odor, using neuronal circuits not involving the MB. Now suppose an outcome associated with that stimulus is learned. Such learning involves compartment-specific, dopamine-dependent plasticity of the KC-MBON synapses activated by that stimulus. If that occurs, the subsequent ensemble response of the MBONs to that stimulus would no longer be in balance and an attraction to, or avoidance of, that stimulus would result. Consistent with this idea, eliminating MB function by disrupting KCs, which are nearly 10% of neurons in the central brain, had surprisingly minor effects on odor preference (Aso, 2014).

Recent studies of dopamine signaling have implicated distinct sites of memory formation within the MB lobes. Consistent with this large body of work, this study found that one type of PPL1 cluster DAN, PPL1-γ1pedc, played a central role in formation of aversive memory in both olfactory and visual learning paradigms. This DAN also mediates aversive reinforcement of bitter taste. For appetitive memory, PAM cluster DANs that innervate other regions of the MB lobes, in particular the compartments of glutamatergic MBONs, are sufficient to induce appetitive memory. These results strongly suggest that the synaptic plasticity underlying appetitive and aversive memory generally occurs in different compartments of the MB lobes (Aso, 2014).

The sign of preference observed in response to CsChrimson activation of particular MBONs was, in general, opposite to that of the memory induced by dopaminergic input to the corresponding MB compartments. For example, activation of MBON-γ1pedc>α/β and MBON-γ2α'1 attracted flies, whereas DAN input to these regions induced aversive memory. Conversely, activation of glutamatergic MBONs repelled flies, while DAN input to the corresponding regions is known to induce appetitive memory. These results are most easily explained if dopamine modulation led to synaptic depression of the outputs of the KCs representing the CS + stimulus. Consistent with this mechanism, the PE1 MBONs in honeybees as well as the V2 cluster MBONs in Drosophila reduce their response to a learned odor and depression of KC-MBON synapses has been shown for octopamine modulation in the locust MB. Moreover, long-term synaptic depression is known to occur in the granular cell synapses to Purkinje cells in the vertebrate cerebellum, a local neuronal circuit with many analogies to the MB. Other mechanisms are also possible and multiple mechanisms are likely to be used. For example, dopamine may modulate terminals of KCs to potentiate release of an inhibitory cotransmitter such as short neuropeptide F, which has been demonstrated to be functional in KCs and hyperpolarizes cells expressing the sNPF receptor. RNA profiling of MBONs should provide insights into the molecular composition of synapses between KCs and MBONs. It is also noteworthy that the effect of dopamine can be dependent on the activity status of Kenyon cells; activation of PPL1-γ1pedc together with odor presentation induces memory, while its activation without an odor has been reported to erase memory. In the vertebrate basal ganglia, dopamine dependent synaptic plasticity important for aversive and appetitive learning is known to result in both synaptic potentiation and synaptic depression (Aso, 2014).

This study sought the effects of selectively and specifically manipulating the activities of a comprehensive set of MBONs on several behaviors. As a consequence, some insights were gained into the extent to which the relative importance of particular MBONs differed between behaviors. Most obvious was the segregation between appetitive and aversive behaviors. For example, this study found that blocking MBON-γ1pedc>α/β impaired both short-term aversive odor and visual memory, suggesting a general role in aversive memory independent of modality. Conversely, a subset of glutamatergic MBONs was required in all three appetitive memory assays. It still remains to be demonstrated that the outputs of these MBONs are required transiently during memory retrieval. Nevertheless, CsChrimson activation experiments demonstrate that activation of these MBONs can directly and transiently induce attraction and avoidance behaviors (Aso, 2014).

In the cases described above, the DANs and MBONs mediating a particular behavior innervate the same regions of MB lobes. Cases were found where the DANs and MBONs required for a behavior do not innervate the same compartments of the MB lobes. For example, even though several cholinergic MBONs are required for appetitive memory, the compartments with cholinergic MBONs do not receive inputs from reward-mediating PAM cluster DANs, but instead from PPL1 cluster DANs that have been shown to be dispensable for odor-sugar memory. What accounts for this mismatch? Perhaps these cholinergic MBONs' primarily function is in memory consolidation rather than retrieval. But the fact that CsChrimson activation of the cholinergic MBON-γ2α'1 and V2 cluster MBONs resulted in attraction, strongly suggests that at least some of the cholinergic MBONs have a role in directly mediating the conditioned response. Indeed, previous studies found a requirement for cholinergic MBONs (the V2 cluster and MBON-α3) during memory retrieva. One attractive model is that requirement of cholinergic MBONs originates from the transfer of information between disparate regions of the MB lobes through the inter-compartmental MBONs connections within the lobes or by way of connections outside the MB, like those described in the next two sections (Aso, 2014).

The multilayered arrangement of MBONs provides a circuit mechanism that enables local modulation in one compartment to affect the response of MBONs in other compartments. Once local modulation breaks the balance between MBONs, these inter-compartmental connections could amplify the differential level of activity of MBONs for opposing effects. For example, the avoidance-mediating MBON-γ4>γ1γ2 targets the compartments of attraction-mediating MBON-γ2α'1 and MBON-γ1pedc>α/β (Aso, 2014).

This network topology might also provide a fly with the ability to modify its sensory associations in response to a changing environment. Consider the α lobe. Previous studies and the current results indicate that circuits in the α lobe play key roles in long-term aversive and appetitive memory. The α lobe is targeted by MBONs from other compartments and comprises the last layer in the layered output model of the MB. The GABAergic MBON-γ1pedc>α/β and the glutamatergic MBON-β1>α both project to α2 and α3, where their axonal termini lie in close apposition. DAN input to the compartments housing the dendrites of these feedforward MBONs induces aversive and appetitive memory, respectively. This circuit structure is well-suited to deal with conflicts between long-lasting memory traces and the need to adapt to survive in a dynamic environment where the meaning of a given sensory input may change. To test the proposed role of the layered arrangement of MBONs in resolving conflicts between old memories and new sensory inputs, behavioral paradigms will be needed that, unlike the simple associative learning tasks used in the current study, assess the neuronal requirements for memory extinction and reversal learning (Aso, 2014).

The neuronal circuits that are downstream of the MBONs and that might read the ensemble of MBON activity remain to be discovered. However, the anatomy of the MBONs suggests that, at least in some cases, summation and canceling effects may result from convergence of MBON terminals on common targets. For example, the terminals of the sleep-promoting cholinergic MBON-γ2α'1 overlap with terminals of wake-promoting glutamatergic MBONs (γ5β'2a, β'2mp and β'2mp bilateral) in a confined area in CRE and SMP. In addition, some MBONs appear to terminate on the dendrites of DANs innervating other compartments, forming feedback loops. Using these mechanisms, local modulation in a specific compartment could broadly impact the ensemble of MBON activity and how it is interpreted (Aso, 2014).

Testing these and other models for the roles of the MBON network, both within the MB lobes and in the surrounding neuropils, will be facilitated by an EM-level connectome to confirm the synaptic connections that were inferred based on light microscopy. Physiological assays will be needed to confirm the sign of synaptic connections and to measure plasticity. For example, the sign of action of glutamate in the targets of glutamatergic MBONs are not known, as this depends on the receptor expressed by the target cells. In this regard, it is noted that previous studies demonstrated a role for NMDA receptors in olfactory memory (Aso, 2014b).

Neurons that are thought to mediate innate response to odors (a subset of projection neurons from the antennal lobes and output neurons from the lateral horn) also project to these same convergence zones (see Convergence zone of MBON terminals as network nodes to integrate innate and learned valences). It is proposed that these convergence zones serve as network nodes where behavioral output is selected in the light of both the innate and learned valences of stimuli. What are the neurons downstream to these convergence zones? One obvious possibility is neurons that project to the fan-shaped body of the central complex whose dendrites are known to widely arborize in these same areas. It would make sense for the MB to provide input to the central complex, a brain region involved in coordinating motor patterns (Aso, 2014).

Using inactivation to uncover the roles of specific cell types is inherently limited by redundancy and resiliency within the underlying neural circuits. For example, consider the MBONs from the α/β lobes. The output of the α/β Kenyon cells is known to be required for retrieval of aversive memory. The current anatomical and behavioral results show that MBON-γ1pedc>α/β, a cell type that was found to be critical for aversive memory, has terminals largely confined inside the α/β lobes, well-positioned to regulate a total 6 types of MBONs from the α/β lobes. Yet no requirement was detected for any of these MBONs in short term aversive memory when tested individually. The ability to detect phenotypes also depends on the strength of the effector; for example, four glutamatergic MBON drivers showed aversive memory impairment in initial screening assays with a strong inhibitor of synaptic function, but these effects could not be confirmed using a weaker effector (Aso, 2014).

The failure to see effects when inactivating individual cell types is most easily explained by combinatorial roles and redundancy between MBONs. It is noted that this high level of resiliency is very reminiscent of observations made with genetic networks, where less than half of gene knockouts of evolutionarily conserved Drosophila genes result in a detectable phenotype. Whether or not a requirement is detected for a particular MBON in a particular learning paradigm is likely to depend on which DANs are recruited by the unconditioned stimulus used in that paradigm as well as the degree of redundancy in the MBON representation of valence. It will be informative to test systematically whether blocking combinations of MBONs, which did not show significant behavioral effect when blocked separately, results in significant memory impairment. It will also be important in future experiments to employ imaging and electrophysiological methods, in which the activities of individual neurons, and the consequences of plasticity, can be observed without being obscured by redundancy (Aso, 2014).

The MBs are implicated in functions beyond processing of associative memory. MBONs that influence approach to, or avoidance of, a learned stimulus may also have roles in innate preference behaviors for temperature and hunger-dependent CO2 avoidance. Moreover, the behavioral repertoire that MBONs govern are expected to go beyond simple approach and avoidance; the MB is known to play a role in experience-dependent regulation of proboscis extension as well as regulation of sleep and post-mating behaviors such as oviposition. Intriguingly, this study found that MBONs whose activation was repulsive promoted wakefulness, whereas MBONs whose activation was attractive promoted sleep; it would make sense for flies to be awake and attentive in an adverse environment. Other internal states, in addition to sleep, are likely to affect the decision to carry out a particular memory-guided behavior; for example, the state of satiety has been shown to regulate memory expression. The diverse influences of MBONs on behavior can be most easily explained if it is assumed that the activity of the ensemble of MBON conveys an abstract representation of both valence and internal state. In this view, the ensemble of MBONs may represent internal states along axes such as pleasant-unpleasant or aroused-not aroused. It is upon these axes that primitive forms of emotion are thought to have evolved (Aso, 2014).

Distinct dopamine neurons mediate reward signals for short- and long-term memories
Yamagata, N., Ichinose, T., Aso, Y., Placais, P., Friedrich, A. B., Sima, R. J., Preat, T., Rubin, G. M. and Tanimoto, H. (2014). Proc Natl Acad Sci U S A 112(2):578-83. PubMed ID: 25548178

Drosophila melanogaster can acquire a stable appetitive olfactory memory when the presentation of a sugar reward and an odor are paired. However, the neuronal mechanisms by which a single training induces long-term memory are poorly understood. This study shows that two distinct subsets of dopamine neurons in the fly brain signal reward for short-term (STM) and long-term memories (LTM). One subset induces memory that decays within several hours, whereas the other induces memory that gradually develops after training. They convey reward signals to spatially segregated synaptic domains of the mushroom body (MB), a potential site for convergence. Furthermore, a single type of dopamine neuron was identified that conveys the reward signal to restricted subdomains of the mushroom body lobes and induces long-term memory. Constant appetitive memory retention after a single training session thus comprises two memory components triggered by distinct dopamine neurons (Yamagata, 2014).

In Drosophila, sugar ingestion in a single training session induces stable appetitive odor memory. The results showed that observed memory represents the composite of STM and LTM that are induced by the distinct and complementary reward signals of dopamine. These separate reward signals very well corroborate parallel processing of STM and LTM in the MB. The stm-PAM neurons (a specific cluster of dopamine neurons) induce appetitive memory that decays within hours, whereas memory by ltm-PAM gradually develops after training. These dopamine neurons convey reward signals to spatially segregated synaptic domains of the MB, whereas the other PAM cluster neurons may also contribute to LTM reward. Furthermore, this study identified a single type of dopamine neurons (PAM-α1) encoding a reward signal for LTM. The PAM-α1 targets a spatially restricted subdomain in the α-lobe of the MB, suggesting local associative modulation in the α-lobe. These results indicate that sugar ingestion activates multiple reward signals of different qualities to form complementary memories, rather than a single reward system forming STM that later transforms into LTM (Yamagata, 2014).

In the defensive siphon and tail withdrawal reflex of Aplysia, different modes of 5-HT application to the sensory neurons in the pedal and pleural ganglion differentially induce short-term and long-term sensitization memories. As both ganglia are innervated by a single identified serotonergic neuron, it is likely that the tail shock activates the same cell to induce both forms of sensitization independently. This cellular configuration is in strong contrast to the reward system in Drosophila appetitive memory, despite parallel formation of STM and LTM in both systems. The sugar reward may be more intricately encoded in the fly, given the importance of long-lasting food-related memory in survival (Yamagata, 2014).

Representations of different reinforcing stimuli by the same transmitter seems to be variable. In Drosophila aversive memory, reinforcing signals of electric shock and heat punishment converge to the same dopamine neurons, whereas distinct dopamine neurons are recruited for different aversive stimuli in mammals. Appetitive memory of Drosophila is closer to the latter case. However, a critical difference is that stm- and ltm-PAM neurons seem to signal different properties of the same reward, again pointing to more complex representation of the sugar reward. It would be interesting to compare neuronal representations of different rewarding stimuli, such as ethanol and water. An important future question would be to understand physiological mechanisms by which the MB computes the distinct dopamine inputs to control approach behavior (Yamagata, 2014).

Memory induced by ltm-PAM develops gradually after training. This gradual increase may reflect the time to implement learning-dependent molecular changes. Many molecules that are specifically required for LTM have been identified, and some of these molecules are involved in learning-dependent gene transcription/translation. For instance, fasting-dependent LTM that is formed without training repetition requires CREB-regulated transcription coactivator (CRTC)-mediated cAMP response element binding protein (CREB) transcription in the MB. Such a transcription-dependent mechanism takes time and may thus underlie gradual formation of memory induced by the ltm-PAM (Yamagata, 2014).

The complementary memory dynamics as a consequence of the distinct reward signals suggest that the 'intent' of appetitive memory undergoes a transition from palatability to caloric content. Similar temporal transitions have been found in feeding choice, where flies initially choose sugars according to sweet taste, but later prioritize caloric contents. Similarly, ethanol exposure initially acts as an aversive reinforcer, but eventually turns into reward and induces LTM. The sequential regulation of appetitive behavior by the same stimulus may be conserved across relevant appetitive stimuli. As palatability is not always a faithful predictor of its nutritional value, it may be a general design of reward systems to balance short-term benefit and long-term fitness (Yamagata, 2014).

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Dopaminergic Modulation of cAMP Drives Nonlinear Plasticity across the Drosophila Mushroom Body Lobes
Boto, T., Louis, T., Jindachomthong, K., Jalink, K. and Tomchik, S. M. (2014). Curr Biol 24: 822-831. PubMed ID: 24684937

Activity of dopaminergic neurons is necessary and sufficient to evoke learning-related plasticity in neuronal networks that modulate learning. During olfactory classical conditioning, large subsets of dopaminergic neurons are activated, releasing dopamine across broad sets of postsynaptic neurons. It is unclear how such diffuse dopamine release generates the highly localized patterns of plasticity required for memory formation. This study has mapped spatial patterns of dopaminergic modulation of intracellular signaling and plasticity in Drosophila mushroom body (MB) neurons, combining presynaptic thermogenetic stimulation of dopaminergic neurons with postsynaptic functional imaging in vivo. Stimulation of dopaminergic neurons generated increases in cyclic AMP (cAMP) across multiple spatial regions in the MB. However, odor presentation paired with stimulation of dopaminergic neurons evoked plasticity in Ca2+ responses in discrete spatial patterns. These patterns of plasticity correlated with behavioral requirements for each set of MB neurons in aversive and appetitive conditioning. Finally, broad elevation of cAMP differentially facilitated responses in the gamma lobe, suggesting that it is more sensitive to elevations of cAMP and that it is recruited first into dopamine-dependent memory traces. These data suggest that the spatial pattern of learning-related plasticity is dependent on the postsynaptic neurons' sensitivity to cAMP signaling. This may represent a mechanism through which single-cycle conditioning allocates short-term memory to a specific subset of eligible neurons (gamma neurons) (Boto, 2014).

Dopaminergic neurons are involved in modulating diverse behaviors, including learning, motor control, motivation, arousal, addiction and obesity, and salience-based decision making. In Drosophila, dopaminergic neurons innervate multiple brain regions, including the mushroom body (MB), where they modulate aversive learning, forgetting, state-dependent modulation of appetitive memory retrieval, expression of ethanol-induced reward memory, and temperature-preference behavior (Boto, 2014).

Dopaminergic circuits play a particularly critical role in memory acquisition. During olfactory classical conditioning, where an odor (conditioned stimulus [CS]) is paired with an aversive event (e.g., electric shock; the unconditioned stimulus [US]), dopaminergic neurons respond strongly to the aversive US (Mao, 2009). Dopamine functions in concert with activity-dependent Ca2+ influx to synergistically elevate cyclic AMP (cAMP) (Tomchik, 2009) and PKA (Gervasi, 2010), suggesting that dopamine is one component of a molecular coincidence detector underlying learning. Proper dopamine signaling is necessary for aversive and appetitive memory. Moreover, driving activity of a subset of TH-GAL4+ dopaminergic neurons that differentially innervates the vertical α/α' MB lobes (with less dense innervation of the horizontal β/β'/γ lobes, peduncle, and calyx), is sufficient to induce behavioral aversion to a paired odorant in larvae and adult flies. Conversely, stimulation of a different set of Ddc-GAL4+ dopaminergic neurons, the PAM cluster that innervates mainly the horizontal β/β'/γ lobes, is sufficient to induce behavioral attraction to a paired odorant. Thus, dopaminergic neurons comprise multiple circuits with distinct roles in memory acquisition (Boto, 2014).

Multiple subsets of MB neurons receive CS and US information and express molecules associated with the coincidence detection, making them theoretically eligible to generate dopamine/cAMP-dependent plasticity. Yet only some subsets are required to support memory at any given time following conditioning, leaving open the question of how spatial patterns of plasticity are generated during conditioning. This question has been approached, by using a technique to probe the postsynaptic effects of neuronal pathway activation. Odor presentation was paired with stimulation of presynaptic dopaminergic neurons via ectopic expression of the heat-sensitive channel TRPA1, while monitoring postsynaptic effects with genetically encoded optical reporters for Ca2+, cAMP, and PKA in vivo (Boto, 2014).

The present data demonstrate four major points about how dopaminergic circuits function in neuronal plasticity underlying olfactory classical conditioning. (1) Stimulation of small subsets of dopaminergic neurons evokes consistent, compartmentalized elevations of cAMP across the MB lobes. (2) Broad stimulation of dopaminergic neurons generates broad postsynaptic elevation of cAMP, but Ca2+ response plasticity occurs in discrete spatial regions. (3) Stimulation of TH-GAL4+ neurons and Ddc/R58E02-GAL4+ neurons, which mediate opposing behavioral responses to conditioned stimuli, generates an overlapping pattern of Ca2+ response plasticity in the γ lobe, with additional regions recruited by Ddc/R58E02-GAL4+ stimulation. Finally, (4) the spatial pattern of plasticity coincides with differential sensitivity to cAMP in the γ lobe. Collectively, these data suggest that different subsets of neurons exhibit heterogeneous sensitivity to activation of second messenger signaling cascades, which might shape their responses to neuromodulatory network activity and modulate their propensity for recruitment into memory traces (Boto, 2014).

The data suggest that dopaminergic neurons mediate Ca2+ response plasticity largely in the γ lobe and suggest a potential mechanism for localization of short-term, learning-related plasticity. These data coincide with multiple previous studies that have demonstrated a critical role of γ neurons in short-term memory. Rescue of Rutabaga (Rut) in the γ lobe of rut mutants is sufficient to restore performance in short-term memory, whereas rescue in α/β lobes supports long-term memory. Rescue of the D1-like DopR receptor in the γ lobe is sufficient to rescue both short- and long-term memory in a mutant background, suggesting that the γ neurons mediate the dopaminergic input during conditioning. In addition, stimulating MP1 dopaminergic neurons innervating the heel of the γ lobe is sufficient as an aversive reinforcer. Finally, learning induces plasticity in synaptic vesicle release from MB γ lobes, which depends in part on G(o) signaling (Zhang, 2013). The data support a critical role for the γ lobe in short-term memory. Furthermore, the observation of differential sensitivity of the γ lobe to cAMP might provide an elegant explanation for why it is specifically recruited into short-term memory traces (Boto, 2014).

Direct elevation of cAMP was sufficient to generate localized, concentration-dependent Ca2+ response plasticity in the MB γ lobe in these experiments. Because applying forskolin in the bath is expected to elevate cAMP across the brain, the spatial specificity of the effect is remarkable. This was not an acute effect, because the forskolin was washed out before imaging the first postconditioning odor response. At the concentrations that were tested, only the γ lobe was facilitated. Therefore, it is concluded that the γ lobe is most sensitive to elevation of cAMP, which has the effect of differentially recruiting γ neurons into the representation of short-term memory via dopamine-mediated neuronal plasticity. It is possible that additional signaling cascades are involved in generating learning-related plasticity in α/β and α'/β' neurons, given that no Ca2+ response plasticity was observed in those neurons following forskolin application (Boto, 2014).

The dominant model for cellular mechanisms of olfactory associative learning is that integration of information about the conditioned and unconditioned stimuli are integrated by Rut, which functions as a molecular coincidence detector. This would suggest that MB neurons, which receive CS and US information, would exhibit at least somewhat uniform Ca2+ response plasticity. From this molecular and cellular perspective, the finding that the α/β and α'/β' neurons did not exhibit Ca2+ response plasticity when an odor was paired with stimulation of dopaminergic neurons is surprising. These neurons are theoretically eligible to encode memory, because they receive information about the CS and US. However, the finding that γ neurons differentially exhibit dopamine-dependent plasticity following single-cycle conditioning is consistent with the data from the behavioral experiments. In summary, the present results suggest that differential cAMP sensitivity provides a potential mechanism allowing specific subsets of eligible neurons in an array (γ neurons) to differentially encode CS-US coincidence relative to other subsets (α/β neurons) that also receive CS/US information (Boto, 2014).

Olfactory System

Odor mixtures of opposing valence unveil inter-glomerular crosstalk in the Drosophila antennal lobe
Mohamed, A. A. M., Retzke, T., Das Chakraborty, S., Fabian, B., Hansson, B. S., Knaden, M. and Sachse, S. (2019). Nat Commun 10(1): 1201. PubMed ID: 30867415

Evaluating odor blends in sensory processing is a crucial step for signal recognition and execution of behavioral decisions. Using behavioral assays and 2-photon imaging, this study has characterized the neural and behavioral correlates of mixture perception in the olfactory system of Drosophila. Mixtures of odors with opposing valences elicit strong inhibition in certain attractant-responsive input channels. This inhibition correlates with reduced behavioral attraction. Defined subsets of GABAergic interneurons provide the neuronal substrate of this computation at pre- and postsynaptic loci via GABAB- and GABAA receptors, respectively. Intriguingly, manipulation of single input channels by silencing and optogenetic activation unveils a glomerulus-specific crosstalk between the attractant- and repellent-responsive circuits. This inhibitory interaction biases the behavioral output. Such a form of selective lateral inhibition represents a crucial neuronal mechanism in the processing of conflicting sensory information (Mohamed, 2019).

This study analyzed the integration of binary odor mixtures of opposing hedonic valences and demonstrate how glomerular-specific inhibition and crosstalk results in an appropriate behavioral output. Glomeruli that strongly respond to the attractive odor are inhibited by the repellent odor in the mixture, which is mediated by defined subsets of GABAergic local interneurons (LNs; see Circuit model for glomerulus-specific crosstalk in the fly AL). Heterogeneity in responses to mixtures has been shown in previous studies where excitation of some glomeruli by one of the mixture components can inhibit the glomeruli activated by the other component. Similar to invertebrates, evidence for non-linearity of mixture interactions has been reported in individual mitral/tufted cells (PNs analogs) in the olfactory bulb of vertebrates. As an alternative scenario it is also conceivable that instead of inhibiting the attractant-coding pathway to shift the behavior towards aversion, the response of the repellent-responsive glomeruli could be boosted via lateral excitation. Lateral excitation has been described to drive synergistic interaction between the binary mixture of cis-vaccenyl acetate and vinegar. Although odors representing sex and food are mutually reinforcing, a binary mixture of odors with opposing valences means a conflicting input. It is therefore postulated that, in contrast to reinforcing input, conflicting sensory input is processed via lateral inhibition in the fly AL. An assumption that would be intriguing to be tested in the future (Mohamed, 2019).

No inhibition of the attractant-responsive glomeruli when stimulating with MIX(+) (a binary mixture of ethyl acetate and benzaldehyde). This lack of inhibition is probably due to the strong ORN input leading to high presynaptic firing rates in the attractant-responsive glomeruli. Consequently, lateral inhibition deriving from the aversive circuit has only a low impact and does not decrease the excitation of the attractant-responsive glomeruli (Mohamed, 2019).

Obviously not all glomeruli that are activated by an attractive odor are inhibited by a repellent in a mixture and might not contribute to the attractiveness of an odor. This observation makes sense in the light of accumulating evidence suggesting that the innate behavioral output is correlated either to the summed weights of specific activated glomeruli or to the activity of single processing channels. The latter argument is supported by the finding that only very few, special glomeruli seem to be valence-specific and induce clear attraction or aversion behavior upon artificial activation (Mohamed, 2019).

It is important to mention that the subset of repellent-responsive glomeruli does also respond to non-aversive and even partly attractive odors, such as E2-hexenal and ethyl benzoate. However, an attractive odorant may indeed activate some aversive input channels beside their main activation of the attractive circuitry (or the other way around). What actually matters is the behavioral output that is consequently elicited when a specific glomerulus becomes activated. For example, ORNs that respond to CO2 are also activated by ethyl benzoate and E2-hexenal. However, the CO2 circuit has been clearly demonstrated to mediate behavioral aversion. Following this argument, artificial activation of glomeruli DL1 and/or DL5 leads to aversive behavior, while silencing DM1 and DM4 abolished attraction to the attractant. These experiments provide evidence that activation of the repellent- and attractant-responsive glomeruli causes a valence-specific behavior, and can therefore be defined as attractive or aversive input channels, respectively (Mohamed, 2019).

Interestingly, one exception was observed in the data set: although the repellent odor geosmin reduced the attraction to balsamic vinegar in the mixture, no mixture inhibition was observed. The detection of geosmin is one of the rare cases, where an odor is detected by only one receptor type and consequently activates only one glomerulus. Similar specialized pathways have been described for the detection of sex pheromones and CO2. Glomeruli processing these ecologically labeled lines differ from broadly tuned glomeruli with regard to their neuronal composition. Hence, it is conceivable that the narrowly tuned geosmin-responsive glomerulus does not exhibit strong interglomerular interactions and has therefore a different impact on the attractant-responsive glomeruli. Mixture interactions between geosmin and attractive odors might be implemented in higher processing centers which contain circuit elements mediating interactions between odors (Mohamed, 2019).

Lateral inhibition, which is believed to enhance contrast and to facilitate discrimination of similar stimuli, is an important motif throughout the nervous system. In mice, dense center-surround inhibition refines mitral cell representation of a glomerular map56, while other evidence showed that lateral inhibition can be rather selective and biased between different mitral cells. In accordance with the olfactory bulb, the AL exhibits broad, selective or even both forms of lateral inhibition, whereby certain glomeruli can show different sensitivities towards an inhibitory input. Lateral inhibition in the Drosophila AL is largely mediated through GABA. Most of the GABAergic inhibition in the Drosophila AL has been shown to take place predominantly on the presynaptic site mediated through GABAA and GABAB receptors. In addition, PNs also receive GABAergic inhibition via GABAA and/or GABAB receptors from LNs. Notably, this study found that two out of four attractant-responsive glomeruli are inhibited on the pre- and postsynaptic levels (via GABAB- or GABAA-receptors), while the other two glomeruli are inhibited only presynaptically through GABAB-type receptors. Previous results have so far shown that GABAA-type receptors contribute weakly to lateral inhibition and shape the early phase of odor responses. However, the data demonstrate that GABAA-type receptors largely mediate mixture-induced inhibition during the full period of the odor presentation which is reminiscent to tonic inhibition in the mammalian system (Mohamed, 2019).

This study shows that mixture-induced lateral inhibition of the attractant-responsive glomeruli was abolished when GABA synthesis was silenced in mostly patchy LNs. Hence the data suggest, in consistency with previous studies, that LNs with more selective innervations mediate glomerulus-specific interactions and rather contribute to mixture processing, while pan-glomerular LNs (e.g., GH298-Gal4 and H24-Gal4), that globally release GABA, might be involved in gain control (Mohamed, 2019).

Interestingly, the repellent-responsive glomeruli DL1 and DL5 did not show any mixture interaction, but mediate the lateral inhibition of the attractant-responsive glomeruli. Two possible scenarios would provide the neuronal substrate for this mechanism dependent on either the donor (i.e. LNs) or the receiver (i.e. glomerulus) side. First, since glomeruli vary dramatically in their GABA sensitivity and consequently their sensitivity to LN activation14, lateral inhibition is heterogeneous across different glomeruli. Second, lateral inhibition is biased among different glomeruli due to a glomerulus-specific synaptic distribution of pre- and postsynapses of GABAergic LNs, i.e. the GABA release is not uniform. This assumption is supported by data revealing that GABAergic LNs possess a higher density of postsynapses in DL1 and DL5 than in the attractant-responsive glomeruli. In line with the current findings, EM based data from the larvae AL describe GABAergic, oligoglomerular 'choosy' LNs with a clear polarity contributing to postsynaptic inhibition for most glomeruli, while they receive inputs from only a small glomerular subset. Hence, there is strong evidence that some glomeruli can drive lateral inhibition in other glomeruli. Both scenarios could either occur separately or reinforce each other. Moreover, it might be ecological relevant not to inhibit the input of the aversive pathways since these are associated with life-threatening situations that should be coded reliably and rather override an attractive input (Mohamed, 2019).

In contrast to expectations, sole photoactivation of DL1 or DL5 or stimulation with the repellent alone did not induce inhibition in the attractant-responsive glomeruli. This might be due to the low spontaneous activity of ORNs innervating the attractant-responsive glomeruli, which correlates with spontaneous fluctuations in the membrane potential of the postsynaptic PNs. Consequently, inhibitory responses (i.e. hyperpolarizations) are difficult to capture with calcium imaging (Mohamed, 2019).

In other sensory systems, lateral inhibitory connections of neuronal subsets involved in sensory processing have been elucidated in great detail, such as in the retina of mice or the rat visual cortex. Also for the Drosophila AL, previous studies suggested that glomerular subgroups are connected via inhibitory LNs. However, these studies could neither pinpoint the precise connections nor their significance for behavioral perception. The data provide evidence for a specific inhibitory crosstalk between identified glomeruli and substantiate the existence of selective lateral inhibition in the fly AL. The postulated network circuits offer insights into the principle of sensory integration. It will be intriguing to see whether neuron-specific crosstalk represents a general phenomenon to integrate multiple and rather conflicting input channels in other sensory modalities (Mohamed, 2019).

Pioneer interneurons instruct bilaterality in the Drosophila olfactory sensory map
Kaur, R., Surala, M., Hoger, S., Grossmann, N., Grimm, A., Timaeus, L., Kallina, W. and Hummel, T. (2019). Sci Adv 5(10): eaaw5537. PubMed ID: 31681838 Interhemispheric synaptic connections, a prominent feature in animal nervous systems for the rapid exchange and integration of neuronal information, can appear quite suddenly during brain evolution, raising the question about the underlying developmental mechanism. This study showed in the Drosophila olfactory system that the induction of a bilateral sensory map, an evolutionary novelty in dipteran flies, is mediated by a unique type of commissural pioneer interneurons (cPINs) via the localized activity of the cell adhesion molecule Neuroglian. Differential Neuroglian signaling in cPINs not only prepatterns the olfactory contralateral tracts but also prevents the targeting of ingrowing sensory axons to their ipsilateral synaptic partners. These results identified a sensitive cellular interaction to switch the sequential assembly of diverse neuron types from a unilateral to a bilateral brain circuit organization (Kaur, 2019).

A Population of Interneurons Signals Changes in the Basal Concentration of Serotonin and Mediates Gain Control in the Drosophila Antennal Lobe
Suzuki, Y., Schenk, J. E., Tan, H. and Gaudry, Q. (2020). Curr Biol. PubMed ID: 32142699 Serotonin (5-HT) represents a quintessential neuromodulator, having been identified in nearly all animal species where it functions in cognition, motor control, and sensory processing. In the olfactory circuits of flies and mice, serotonin indirectly inhibits odor responses in olfactory receptor neurons (ORNs) via GABAergic local interneurons (LNs). However, the effects of 5-HT in olfaction are likely complicated, because multiple receptor subtypes are distributed throughout the olfactory bulb (OB) and antennal lobe (AL), the first layers of olfactory neuropil in mammals and insects, respectively. For example, serotonin has a non-monotonic effect on odor responses in Drosophila projection neurons (PNs), where low concentrations suppress odor-evoked activity and higher concentrations boost PN responses. Serotonin reaches the AL via the diffusion of paracrine 5-HT through the fly hemolymph and by activation of the contralaterally projecting serotonin-immunoreactive deuterocerebral interneurons (CSDns): the only serotonergic cells that innervate the AL. Concentration-dependent effects could arise by either the expression of multiple 5-HT receptors (5-HTRs) on the same cells or by populations of neurons dedicated to detecting serotonin at different concentrations. This study identify a population of LNs that express 5-HT7Rs exclusively to detect basal concentrations of 5-HT. These LNs inhibit PNs via GABAB receptors and mediate subtractive gain control. LNs expressing 5-HT7Rs are broadly tuned to odors and target every glomerulus in the antennal lobe. These results demonstrate that serotonergic modulation at low concentrations targets a specific population of LNs to globally downregulate PN odor responses in the AL (Suzuki, 2020).

Circuit variability interacts with excitatory-inhibitory diversity of interneurons to regulate network encoding capacity
Tsai, K. T., Hu, C. K., Li, K. W., Hwang, W. L. and Chou, Y. H. (2018). Sci Rep 8(1): 8027. PubMed ID: 29795277

Local interneurons (LNs) in the Drosophila olfactory system exhibit neuronal diversity and variability, yet it is still unknown how these features impact information encoding capacity and reliability in a complex LN network. This study used two strategies to construct a diverse excitatory-inhibitory neural network beginning with a ring network structure and then introduced distinct types of inhibitory interneurons and circuit variability to the simulated network. The continuity of activity within the node ensemble (oscillation pattern) was used as a readout to describe the temporal dynamics of network activity. Inhibitory interneurons were found to enhance the encoding capacity by protecting the network from extremely short activation periods when the network wiring complexity is very high. In addition, distinct types of interneurons have differential effects on encoding capacity and reliability. Circuit variability may enhance the encoding reliability, with or without compromising encoding capacity. Therefore, this study has described how circuit variability of interneurons may interact with excitatory-inhibitory diversity to enhance the encoding capacity and distinguishability of neural networks. This work has evaluate the effects of different types and degrees of connection diversity on a ring model, which may simulate interneuron networks in the Drosophila olfactory system or other biological systems (Tsai, 2018).

Diverse populations of local interneurons integrate into the Drosophila adult olfactory circuit
Liou, N. F., Lin, S. H., Chen, Y. J., Tsai, K. T., Yang, C. J., Lin, T. Y., Wu, T. H., Lin, H. J., Chen, Y. T., Gohl, D. M., Silies, M. and Chou, Y. H. (2018). Nat Commun 9(1): 2232. PubMed ID: 29884811

Drosophila olfactory local interneurons (LNs) in the antennal lobe are highly diverse and variable. How and when distinct types of LNs emerge, differentiate, and integrate into the olfactory circuit is unknown. Through systematic developmental analyses, this study found that LNs are recruited to the adult olfactory circuit in three groups. Group 1 LNs are residual larval LNs. Group 2 are adult-specific LNs that emerge before cognate sensory and projection neurons establish synaptic specificity, and Group 3 LNs emerge after synaptic specificity is established. Group 1 larval LNs are selectively reintegrated into the adult circuit through pruning and re-extension of processes to distinct regions of the antennal lobe, while others die during metamorphosis. Precise temporal control of this pruning and cell death shapes the global organization of the adult antennal lobe. These findings provide a road map to understand how LNs develop and contribute to constructing the olfactory circuit (Liou, 2018.

Mechanisms underlying population response dynamics in inhibitory interneurons of the Drosophila antennal lobe
Nagel, K.I. and Wilson, R.I. (2016). J Neurosci 36: 4325-4338. PubMed ID: 27076428

Local inhibitory neurons control the timing of neural activity in many circuits. To understand how inhibition controls timing, it is important to understand the dynamics of activity in populations of local inhibitory interneurons, as well as the mechanisms that underlie these dynamics. This study describes the in vivo response dynamics of a large population of inhibitory local neurons (LNs) in the Drosophila melanogaster antennal lobe, the analog of the vertebrate olfactory bulb, and dissects the network and intrinsic mechanisms that give rise to these dynamics. Some LNs respond to odor onsets ("ON" cells) and others to offsets ("OFF" cells), whereas still others respond at both times. Moreover, different LNs signal odor concentration fluctuations on different timescales. Some respond rapidly, and can track rapid concentration fluctuations. Others respond slowly, and are best at tracking slow fluctuations. A continuous spectrum of preferred stimulation timescales was found among LNs, as well as a continuum of ON-OFF behavior. Using in vivo whole-cell recordings, it was shown that the timing of an LN's response (ON vs OFF) can be predicted from the interplay of excitatory and inhibitory synaptic currents that it receives. Meanwhile, the preferred timescale of an LN is related to its intrinsic properties. These results illustrate how a population of inhibitory interneurons can collectively encode bidirectional changes in stimulus intensity on multiple timescales, and how this can arise via an interaction between synaptic and intrinsic mechanisms (Nagel, 2016).

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Shared mushroom body circuits underlie visual and olfactory memories in Drosophila
Vogt, K., Schnaitmann, C., Dylla, K. V., Knapek, S., Aso, Y., Rubin, G. M. and Tanimoto, H. (2014). Elife 3: e02395. PubMed ID: 25139953

In nature, animals form memories associating reward or punishment with stimuli from different sensory modalities, such as smells and colors. It is unclear, however, how distinct sensory memories are processed in the brain. This study established appetitive and aversive visual learning assays for Drosophila that are comparable to the widely used olfactory learning assays. These assays share critical features, such as reinforcing stimuli (sugar reward and electric shock punishment), and allow direct comparison of the cellular requirements for visual and olfactory memories. It was found that the same subsets of dopamine neurons drive formation of both sensory memories. Furthermore, distinct yet partially overlapping subsets of mushroom body intrinsic neurons are required for visual and olfactory memories. Thus, these results suggest that distinct sensory memories are processed in a common brain center. Such centralization of related brain functions is an economical design that avoids the repetition of similar circuit motifs (Vogt, 2014).

Devising a transparent electric shock grid module made it possible to apply the same visual stimulation in aversive and appetitive conditioning assays. Also an integrated platform was developed for fully automated high-throughput data acquisition using customized software to control the presentation of electric shock and visual stimuli while making video recordings of behavior. In these assays, memory performance is based on altered visual preference in walking flies, a task likely to be less demanding than the constant flight required for flight simulator learning. These advantages facilitate behavioral examination of many genotypes (Vogt, 2014).

Circuits underlying olfactory and visual memory can be optimally compared when the sugar reward and electric shock punishment are matched between the two modalities. Visual and olfactory memories share the same subsets of dopamine neurons that convey reinforcing signals. This shared requirement of the transmitter system between visual and olfactory learning has been described in crickets. However, the pharmacological manipulation used in these studies does not allow further circuit dissection (Vogt, 2014).

For electric shock reinforcement, identified neurons in the PPL1 cluster, such as MB-MP1, MB-MV1 and MB-V1, drive aversive memories in both visual and olfactory learning, while the MB-M3 neurons in the PAM cluster seem to be involved specifically in aversive olfactory memory. Thus, overlapping sets of dopamine neurons appear to represent electric shock punishment in both visual and olfactory learning with olfactory aversive memory probably recruiting a larger set. Previous studies have shown that the MB-M3 neurons induce aversive olfactory memory that increases stability of other memory components. Olfactory memories last longer than visual memories potentially due to the recruitment of additional dopamine neurons (Vogt, 2014).

In appetitive conditioning, PAM cluster neurons play crucial roles in both olfactory and visual memories. Which cell types in these clusters are involved and whether there is a cellular distinction between olfactory and visual memory requires further analysis at the single cell level. Most importantly, all these neurons convey dopamine signals to restricted subdomains of the MB. The blockade of octopamine neurons did not impair appetitive visual memories with sucrose. The involvement of octopamine neurons may be more substantial when non-nutritious sweet taste rewards are used, as has been shown in olfactory learning (Vogt, 2014).

In addition to these shared reinforcement circuits in the MB, the necessity of MB output for visual memory acquisition and retrieval is also consistent with olfactory conditioning. Taken together, these results suggest that the MBs harbor associative plasticity for visual memories and support the conclusion that similar coincidence detection mechanisms are used to form memories within the MBs. Centralization of similar brain functions spares the cost of maintaining similar circuit motifs in different brain areas and may be an evolutionary conserved design of information processing. Such converging inputs of different stimuli into a multisensory area have even been described in humans (Vogt, 2014).

'Flight simulator' visual learning was shown to require the central complex but not the MBs. Although this appears to contradict the current study, it is noted that there are important differences between the behavioral paradigms employed. In the flight simulator, a single tethered flying Drosophila is trained to associate a specific visual cue with a laser beam punishment, to later on avoid flying towards this cue in the test. Although this study controlled for visual context consistency and the 'operant component' of the flight simulator training, any other difference could account for the differential requirement of brain structures. Given that flies during flight show octopamine-mediated modulation of neurons in the optic lobe, similar state-dependent mechanisms might underlie different requirement of higher brain centers. Thus, it is critical to design comparable memory paradigms (Vogt, 2014).

This study together with previous results in associative taste learning highlights the fact that the role of the MB in associative learning is not restricted to one sensory modality or reinforcer. This study found that olfactory and visual memories recruit overlapping, yet partly distinct, sets of Kenyon cells (see Circuit model of olfactory and visual short-term memories). In contrast to the well-described olfactory projection neurons, visual inputs to the MB remain unidentified. No anatomical evidence has been reported in Drosophila for direct connections between optic lobes and MBs although such connections are found in other insects. Also afferents originating in the protocerebrum were found to provide multi-modal input to the MB lobes of cockroaches. Thus, Drosophila MBs may receive indirect visual input from optic lobes, and the identification of such a visual pathway would significantly contribute to understanding of the MB circuits (Vogt, 2014).

Given the general requirement of the γ lobe neurons, visual and olfactory cues may be both represented in the γ neurons. Consistently, the dopamine neurons that convey appetitive and aversive memories heavily project to the γ lobe. In olfactory conditioning, the γ lobe was shown to contribute mainly to short-term memory. This converging evidence from olfactory and visual memories suggests a general role for the γ lobe in short-lasting memories across different sensory modalities. Previous studies found that the MB is also involved in sensorimotor gating of visual stimuli or visual selective attention. Therefore, the MB circuits for visual associative memories might be required for sensorimotor gating and attention (Vogt, 2014).

Interestingly, the contribution of the α'/β' lobes is selective for olfactory memories. This Kenyon cell class is more specialized to odor representation, as the cells have the broadest odor tuning and the lowest response threshold among the three Kenyon cell types (Vogt, 2014).

The role of α/β neurons in visual memories is also limited. The α/β neurons might play more modulatory roles in specific visual memory tasks, such as context generalization, facilitation of operant learning and occasion setting. This modulatory role of the α/β neurons is corroborated in olfactory learning, where they are preferentially required for long-lasting memories (Vogt, 2014).

Differentiated but overlapping sensory representations by KCs may be conserved among insect species. In honeybees, different sensory modalities are represented in spatially segregated areas of the calyx, whereas the basal ring region receives visual and olfactory inputs. The MB might thus have evolved to represent the sensory space of those modalities that are subject to associative modulation (Vogt, 2014).

Random convergence of olfactory inputs in the Drosophila mushroom body
Caron, S. J., Ruta, V., Abbott, L. F. and Axel, R. (2013). Nature 497(7447): 113-117. PubMed ID: 23615618

The mushroom body in the fruitfly Drosophila melanogaster is an associative brain centre that translates odour representations into learned behavioural responses. Kenyon cells, the intrinsic neurons of the mushroom body, integrate input from olfactory glomeruli to encode odours as sparse distributed patterns of neural activity. This study has developed anatomic tracing techniques to identify the glomerular origin of the inputs that converge onto 200 individual Kenyon cells. Each Kenyon cell integrates input from a different and apparently random combination of glomeruli. The glomerular inputs to individual Kenyon cells show no discernible organization with respect to their odour tuning, anatomic features or developmental origins. Moreover, different classes of Kenyon cells do not seem to preferentially integrate inputs from specific combinations of glomeruli. This organization of glomerular connections to the mushroom body could allow the fly to contextualize novel sensory experiences, a feature consistent with the role of this brain centre in mediating learned olfactory associations and behaviours (Caron, 2013).

Olfactory perception in the fly is initiated by the binding of an odorant to an ensemble of olfactory sensory neurons (OSNs) in the antennae, resulting in the activation of a unique and topographically fixed combination of glomeruli in the antennal lobe (AL). The discrimination of odours therefore requires the integration of information from multiple glomeruli in higher olfactory centres. AL projection neurons (PNs) extend dendrites into a single glomerulus and project axons that bifurcate to innervate two distinct brain regions, the lateral horn and the MB. The invariant circuitry of the lateral horn is thought to mediate innate behaviours, whereas the MB translates olfactory sensory information into learned behavioural responses. PN axons that innervate the MB terminate in large boutons. A given KC extends a small number of dendritic “claws”, with each claw receiving information from only one PN bouton. A single bouton connects to multiple KC claws to form a discrete anatomic structure, the microglomerulus. Each KC projects an axon to one of the three different classes of MB lobes, α/β, α’/β’, or γ, where it synapses upon a relatively small number of extrinsic output neurons (Caron, 2013).

Electrophysiological and optical imaging studies show that odorants activate sparse subpopulations of KCs distributed across the MB without spatial preference. Individual KCs could be connected to preferential combinations of glomeruli that are co-ordinately activated by behaviourally relevant odours. Alternatively, KCs may not receive structured input; rather the glomerular inputs may be random, a feature that maximizes the diversity of odour representations in the MB. This study has exploited the specialized structure of the PN-KC synapse to characterize the glomerular origin of the PNs that converge onto individual KCs (Caron, 2013).

Photoactivatable green fluorescent protein (PA-GFP) was expressed in all neurons of the fly and a single KC was photolabelled. It was observed that individual photolabelled KCs elaborate between 2 and 11 dendritic claws restricted to the main olfactory calyx. The axonal projections of a labelled KC can be traced into either the α/β, α’β’, or γ lobes of the MB. Texas red dextran was then electroporated into the centre of a single KC claw, filling the PN bouton innervating that claw. Retrograde transfer of the dye labels a single PN and its associated AL glomerulus, providing further evidence that an individual KC claw receives input from only a single glomerulus (Caron, 2013).

It was verified that this tracing method identifies functional connections between PNs and KCs. Functional imaging was performed on flies that express the calcium indicator GCaMP3 in most KCs to identify the claws activated by the stimulation of a single glomerulus. Electroporation of dye into an activated microglomerulus labels a single PN that innervates the stimulated glomerulus. Thus, the electroporation of dye into a KC claw allows faithful identification of the PN to which it is functionally connected (Caron, 2013).

The strategy of photolabelling a single KC and sequential electroporation of dye into each of its claws was used to define glomerular inputs to an individual KC. In initial experiments, PA-GFP was expressed in all neurons and 100 randomly chosen KCs were photolabelled in 100 different flies. Among the 100 photolabelled KCs, 84 α/β KCs, 14 α’/β’ KCs, but only 2 γ KCs were identified. Each MB contains about 1000 α/β KCs, 370 α’β’ KCs, and 670 γ KCs. γKCs are underrepresented in this initial data set. This is likely to result from the spatial segregation of their cell bodies, which renders γ KCs less accessible to photolabelling. Most α/βKCs, but not the α/β and α’β’ KCs, express Fruitless (Fru). An additional 100 γ KCs were targeted for photoactivation in flies expressing PA-GFP under the control of the Fru promoter (Caron, 2013).

Texas red dextran was sequentially electroporated into different claws of a photolabelled KC. It is technically difficult to fill all the claws of a KC and on average 3 glomerular inputs were identified per KC. In fewer than 5% of the samples, the number of labelled PNs differed from the number of claws filled, reflecting either unsuccessful or imprecise electroporation. Samples with more labelled PNs than expected were discarded. The low frequency of unsuccessful claw fills indicates that claws extending from a given KC were filled with equal efficiency independent of size. Thus the size of a claw was not a selection criterion in these experiments (Caron, 2013).

A total of 683 inputs that synapse on 200 KCs were identified. 654 of these inputs connect to PNs innervating 49 of the 51 AL glomeruli. PNs innervating the DA3 and VL1 are absent from the data set but boutons were identified from these PNs in the MB calyx. 29 of the claws receive input from brain regions other than the AL. Interestingly, 11 of these claws are innervated by PNs that derive from pseudoglomeruli in the proximal antennal protocerebrum, a thermosensing centre in the fly brain that receives input from distinct heat- and cold-sensing neurons in the antennae. The remaining 18 PNs innervated different uncharacterized regions of the brain (Caron, 2013).

It was observe that the distribution of the glomerular inputs to KCs is not uniform. Inputs from the DA1 and DC3 glomeruli are most frequent, with each accounting for 5.1% of the total connections. The non-uniform distribution reflects the fact that the size and number of calycal boutons formed by PNs varies across glomeruli. For instance, the PNs associated with the DA1 and DC3 glomeruli form more numerous boutons in comparison with the PNs of less frequently represented glomeruli. It was also observed that there is a small but significant difference between the inputs to the α/β and γ KCs (p < 0.001). All subsequent statistical analyses were therefore performed separately on both the α/β and γ data sets, but failed to reveal any significant difference between the two data sets. Therefore, only the results obtained from the full data set are shown (Caron, 2013).

Statistical analyses of the 665 connections allowed searching for structure among the connections between glomeruli and KCs. First, it wae determined whether the KCs receiving input from a given glomerulus have a higher probability of receiving additional input from that same glomerulus. Of the 200 KCs in the data set, only 11 receive two inputs from the same glomerulus, and none receive three or more such inputs. It was determined whether the frequency of convergent input from a single glomerulus is significantly above or below chance expectations by randomly shuffling the connections in the data set between the different KCs, while maintaining the number of connections each of them receives. This shuffling maintains the frequency of glomerular connections observed in the experimental data, but eliminates any potential, non-random patterns of inputs onto individual KCs. This shuffling is used in all subsequent statistical analyses. The frequency of multiple connections from the same glomerulus in the observed and shuffled data sets is not significantly different. Thus, no KCs were observed that receive preferential inputs from a single glomerulus. Rather, individual KCs integrate information from multiple different glomeruli (Caron, 2013).

It was next determined whether KCs are connected to any preferential pair, trio, or quartet of glomeruli. Of the 1378 (53*52/2) different pairs of glomeruli that could converge onto an individual KC, 508 distinct pairs appear in the data set. 310 of these pairs connect to only one of the 200 KCs analysed, whereas certain pairs of glomeruli connect to multiple KCs. There are combinations of glomerular trios that connect with two different KCs, and one case in which two KCs receive inputs from the same quartet of glomeruli. However, the observed frequency with which the different pairs, trios and quartets converge onto different KCs is consistent with expectations from the shuffled data set. Thus, the identity of a glomerulus connected to a KC provides no predictive information as to the identity of the remaining glomerular inputs onto that neuron (Caron, 2013).

Glomeruli can be grouped based on biological properties shared by their associated OSNs (sensilla type, odour specificity) and PNs (developmental origin and topography of their axonal projections). KCs might receive preferential input from one or another of these glomerular categories. For example, the OSNs innervating the AL are derived from three sensillar types (basiconic, coeloconic, and trichoid sensilla) that project to three classes of glomeruli tuned to different odour categories. If individual KCs were tuned to a particular class of odours, they might preferentially integrate inputs from one type of sensillum. Statistical analyses, however, reveal that KCs that receive an input from one sensillar type are no more or less likely to receive additional inputs from this or any other type of sensillum than is predicted by chance. Sensillar type, however, provides only a coarse correlate of odour tuning. Therefore, glomeruli were first grouped based on the similarity of their odour response profiles and again no structure was observed in the inputs to a KC that correlated with odour tuning (Caron, 2013).

Glomeruli were classified on the basis of the properties of their PNs. PN axons from different glomeruli project to broad but stereotyped domains in the lateral horn and calyx of the MB. Input to an individual KC could be shaped by the topography of PN projections. Analysis of the distribution of inputs to a given KC, however, fails to reveal any preferential PN connectivity that reflects the organization of their projection in either the MB calyx or lateral horn. KCs do not preferentially integrate information from glomeruli innervated by PNs sharing a developmental origin. In addition, KCs do not select their input based on topographical constraints as suggested by a previous study. Finally, three glomeruli are innervated by Fru-expressing OSNs and PNs. Preferential pairing of inputs from Fru+ PNs onto individual KCs were not observed. Moreover, although most γ KCs express Fru, there is no preferential input from Fru+ glomeruli to γ KCs (Caron, 2013).

Next, an unbiased search was performed for structure by examining correlations within the connectivity matrix between the 53 glomeruli (51 AL glomeruli and 2 pseudoglomeruli) and the 200 KCs. Correlations were extracted by performing a principal component analysis of this matrix. This analysis failed to reveal structure in the input to KCs other than that inherent in the non-uniform distribution of glomerular inputs (Caron, 2013).

These data are consistent with a model in which each KC receives input from a combination of glomeruli randomly chosen from the non-uniform distribution of glomerular projections to the MB. Classification of either glomeruli or KCs on the basis of several shared developmental, anatomic, and functional features fails to reveal structured input onto individual KCs. Members of a given PN class do not preferentially converge onto an individual KC nor do members of a KC class receive specific and distinguishing PN inputs. A given KC can integrate information from glomeruli activated by food odours, pheromones, CO2 and even temperature. Recent data suggests that the extrinsic output neurons of the MB that are responsible for the different forms of learned behaviour are anatomically segregated and synapse with KC axons within a specific MB lobe. Interestingly, similar glomerular inputs are observed for the KCs that innervate the different lobes of the MB. This random input to individual KCs provides a mechanism to contextualize a rich diversity of novel KC responses (Caron, 2013).

It is important to note that the tracing procedure that was developed only allows characterization of the inputs to a single KC per fly. It is therefore possible that the inputs to every KC are determined but this developmental program results in a distribution of glomerular inputs that appears random. However, it is difficult to conceive of a development mechanism that could dictate the identity of inputs to each of the seven claws of the 2000 KCs. Moreover, the logic of employing complex and unlikely identity codes to achieve an uncorrelated distribution of inputs is elusive. Indeed, a previous study examined the electrophysiological response of KCs to different odours in a line of flies that labels only 23 α/β neurons but failed to identify replicate KCs with shared odour response profiles. These observations support the conclusion that the complement of glomerular inputs to KCs differs in different individuals. In addition, it is not possible, from the analysis of the glomerular inputs to 200 KCs, to exclude the existence of small subsets of KCs that received determined inputs from the AL. Nonetheless, the data are most consistent with a model in which the majority of individual KCs receive input from a random collection of glomeruli, a finding with important implications for odour processing in the MB (Caron, 2013).

If the connections from AL to MB are indeed random, a given odour will activate a different ensemble of KCs in different flies. However, in an individual fly, a given odour will consistently activate the same ensemble. This representation must acquire valence through experience or unsupervised activity dependent plasticity to dictate an appropriate behavioural output. Uncorrelated glomerular input to KCs affords the fly with the ability to impart meaning to a diversity of novel and unpredictable sensory stimuli that it may encounter throughout its life. Plasticity at highly convergent synapses between KC axons and MB extrinsic neurons could mediate experience-dependent behavioural output, an elemental feature of MB function. Thus, the fly has evolved an olfactory circuit with a connectivity that optimizes its ability to contextualize and respond appropriately to a rich array of olfactory experiences (Caron, 2013).

Embryonic origin of olfactory circuitry in Drosophila: contact and activity-mediated interactions pattern connectivity in the antennal lobe
Prieto-Godino, L. L., Diegelmann, S. and Bate, M. (2012). PLoS Biol 10: e1001400. PubMed ID: 23055825

Olfactory neuropiles across different phyla organize into glomerular structures where afferents from a single olfactory receptor class synapse with uniglomerular projecting interneurons. In adult Drosophila, olfactory projection interneurons, partially instructed by the larval olfactory system laid down during embryogenesis, pattern the developing antennal lobe prior to the ingrowth of afferents. In vertebrates it is the afferents that initiate and regulate the development of the first olfactory neuropile. This study investigated the embryonic assembly of the Drosophila olfactory network. Dye injection and genetic labelling was used to show that during embryogenesis, afferent ingrowth pioneers the development of the olfactory lobe. With a combination of laser ablation experiments and electrophysiological recording from living embryos, it was shown that olfactory lobe development depends sequentially on contact-mediated and activity-dependent interactions, and an unpredicted degree of similarity was revealed between the olfactory system development of vertebrates and that of the Drosophila embryo. Electrophysiological investigation is also the first systematic study of the onset and developmental maturation of normal patterns of spontaneous activity in olfactory sensory neurons, and some of the mechanisms regulating its dynamics were uncovered. It was found that as development proceeds, activity patterns change, in a way that favours information transfer, and that this change is in part driven by the expression of olfactory receptors. These findings show an unexpected similarity between the early development of olfactory networks in Drosophila and vertebrates and demonstrate developmental mechanisms that can lead to an improved coding capacity in olfactory neurons (Prieto-Godino, 2012).

A striking feature of olfactory system organization is the conserved arrangement of olfactory sensory neuron (OSN) terminals and uniglomerular projections neurons (PNs) into an odotopic glomerular map. Previous studies lead to the conclusion that the sequence of events and developmental mechanisms patterning connectivity among OSNs and PNs in vertebrates and in insects are radically different. However, most studies of the development of the olfactory network in insects have focused on adult development. This study uncovered developmental events and mechanisms leading to the embryonic assembly of the Drosophila olfactory network from the beginning, before contacts are made, until functional maturity at hatching. It was found that afferent ingrowth pioneers AL development and that contact and activity-dependent interactions among the components of the circuit are essential for appropriate patterning of connectivity in the larval AL. This study provides insights into axon-to-dendrite and axon-to-axon interactions in neural circuit assembly and reveals an unexpected degree of similarity with other embryonically developing vertebrate olfactory systems. Furthermore, this paper provides systematic study of the onset and developmental maturation of normal patterns of spontaneous activity in OSNs. The implications of these findings is discussed in the context of general principles of neural network development and more specifically with a focus on the development of connectivity in olfactory circuits (Prieto-Godino, 2012).

A key finding in this study is the interdependence of OSNs and PNs for the proper development of the larval antennal lobe (AL). Although at early stages of embryogenesis OSN and PN axons approach the site of the future AL independently of each other, once PN dendrites penetrate the emerging AL, interactions with OSN regulate the patterning of connectivity (Prieto-Godino, 2012).

Embryonic development of the Drosophila AL begins with OSN terminals targeting distinct territories that probably represent the origins of AL glomeruli. At this stage PN axons turn away from this site and continue growing towards higher brain centres. By the time growth cones of OSN axons contact the proximal region of PNs axons, the PNs have not yet extended any dendrites. Hours later, PN extend dendrites directed towards particular territories within the emerging AL, possibly guided by the same cues that direct OSN terminal targeting. The early arrival of OSNs in the future region of the AL before PN dendrite extension suggested a possible role for OSNs in the development of the AL. Indeed, this study found that PNs require presynaptic innervation for their survival, although innervation does not necessarily have to come from OSNs. Additionally, there is no specific requirement for OSN terminals in promoting sprouting of PN dendrites since in the absence of OSNs, surviving PNs have dendrites. These dendrites are normally longer than controls, suggesting they elongate until they find presynaptic partners, with the implication that OSNs normally give PN dendrites a stop growth signal. This effect is both contact and activity dependent, because PNs in animals where all OSNs had been silenced have overgrown dendrites that do not extend beyond the AL. A similar effect has been found in the dendrites of motorneurons in Drosophila embryos, where the removal of presynaptic terminals induces an overgrowth of postsynaptic motorneuron dendrites that anticipates the dendritic overgrowth induced by the lack of pre-synaptic activity at later developmental stages (Prieto-Godino, 2012).

Independently of whether PNs survive or not, in all cases the AL is lost when OSNs are ablated. Loss of the AL has also occurred on an evolutionary scale in terrestrial isopods, which in the process of colonising the land have secondarily lost their olfactory sensilla in the main olfactory appendage, together with the corresponding olfactory deutocerebral structures (second neuromere of the supraesophageal ganglion where the olfactory lobe is located). Furthermore, in some species the tritocerebrum (posteriorly adjacent neuromere to the deutocerebrum) seems to have acquired additional neuropile structures. The findings show that there is an interdependence in the development of the Drosophila embryonic olfactory system that results in the loss of deutocerebral olfactory structures (the AL) in response to the ablation of OSNs. At the same time the finding of occasional ectopic tritocerebral and subesophageal innervation of PNs indicates a possible developmental route for the evolutionary acquisition of additional tritocerebral structures (Prieto-Godino, 2012).

These results contrast with previous studies in adult Drosophila, which show that PNs pioneer development of the adult AL independently from adult OSN development. Why is development of the olfactory system in Drosophila different during embryogenesis and metamorphosis? Interestingly, experiments in other embryonically developing olfactory systems, in both vertebrates and invertebrates, also demonstrate an essential role for OSN ingrowth in the development of their first olfactory centres. Experiments in Xenopus where OSNs were removed unilaterally at early embryonic stages showed that an olfactory bulb fails to develop on the ablated side, but is present on the control side. Similarly, an experiment in cockroaches where most, but not all, OSNs were unilaterally removed during embryogenesis before they innervate the AL showed that the deafferented lobe was severely disrupted, its characteristic glomeruli were missing, and it was markedly reduced in volume. Furthermore, as with the current findings, PNs in these partially deafferented lobes were sparsely branched and had elongated dendrites instead of their characteristic uniglomerular tufts. In contrast, when OSNs were ablated early in adult development in insects (Manduca and Drosophila adult) an AL still formed, and PN dendrites arborized in their glomerular territories. It is concluded that the differences found in the development of the Drosophila larval and adult olfactory systems probably arise from fundamental differences between embryonic development and metamorphosis. In embryos (vertebrate or Drosophila) there is no preexisting network to guide development, whereas during metamorphosis the adult olfactory system makes use of cues derived from the larval olfactory system. Thus its wiring seems to rely more on external cues and less on interactions among its network components than the wiring of the larval network (Prieto-Godino, 2012).

The method allows spontaneous activity to be recorded from OSNs developing in vivo in the Drosophila embryo. Although it has been assumed that OSNs in mice and insects may be active during development , and there is a previous report of activity recorded from the antennal nerve of Manduca during adult development, this is the first systematic description of the onset and developmental maturation of normal patterns of spontaneous activity in OSNs (Prieto-Godino, 2012).

The results reveal three important features about the development of activity patterns in OSNs:

  • As in other developing systems, the earliest action potentials generated by OSNs are different from mature ones, with smaller amplitude and a longer duration. Such changes in spike shape seem to be a general feature of emerging activity as ionic conductances are acquired and mature (Prieto-Godino, 2012).
  • At early stages, intermittent bursts of activity are recorded in the OSNs. Activity patterns that consist of spontaneous bursts are common to many developing neural networks, including the auditory, visual, motor, and olfactory systems, and their time course is remarkably similar across different neural systems, with inter-burst intervals varying between 0.5 and 2 mi. Such activity may be an inevitable consequence of cells acquiring mature excitable properties, but it is also possible that the generality of these activity patterns, and the diversity of mechanisms by which they are generated and terminated, is an indication of an essential and significant role in the development of neural networks (Prieto-Godino, 2012).
  • As development proceeds, variability of the spike train diminishes, which is predicted according to information theory to increase signal (odour) detectability.
  • A previous in vitro study of locust frontal ganglion neurons showed that there is a transient period during the wiring process when activity is irregular, but as the network matures, regularity increases. This is the first direct statistical analysis of the transition from immature to mature spike-trains in vivo and allows leads to the suggestion that the coding capabilities of the network improve as it develops. It seems likely that a change towards patterns that would be expected to increase signal detectability, and thus network functionality, would be a general feature in neural networks as they mature (Prieto-Godino, 2012).

    The mechanisms by which this immature activity is generated, shaped, and terminated vary from system to system. In the embryonic OSNs, the transition from irregular spike-trains to continuous discharge may require the expression of olfactory receptors (OR), because in larvae mutant for the co-receptor Orco Or83b, necessary for OR function, this transition does not occur normally. Since Orco is expressed before the onset of spontaneous activity, it is suggested that the change in the pattern of OSN spontaneous activity is likely to be driven, at least in part, by the onset and level of expression of specific ORs. However, this might not be the only factor shaping spontaneous activity patterns over development, and other factors such as expression of other ion channels may also play a role. This might explain why 16 h AEL Orco mutants have indistinguishable levels of activity when compared with controls, yet the variability in their spike train is significantly increased (Prieto-Godino, 2012).

    Previous studies have suggested that spontaneous activity is essential for the normal development of vertebrate OSNs, but that there is no such requirement in insects. However, this study found that there is a role for OSN activity in the development of the larval olfactory network. OSN activity regulates the morphology of OSN terminals independently of activity in neighbouring axons, and without activity terminals appear immature and occupy larger territories. This is similar to what has been described in zebrafish and mouse OSN terminals devoid of activity. There is also a report of a similar phenotype found in the AL of third instar Drosophila larvae after synaptic release was blocked in a large subset of OSNs. The results show that while immature terminal morphology is a cell autonomous phenotype that is independent of activity levels in neighbouring OSN axons, the expansion of OSN terminals is limited by interactions among the OSN terminals. Interestingly a similar process has been found to regulate the morphology and terminal expansion of retinotectal axons. Thus the control of axonal terminal extension via activity-dependent interactions may be a general process in the wiring of nervous systems. The nature of inter-axonal interactions that limit terminal growth remains unknown and is one example of how future work using amenable experimental systems such as the one provided by the larval olfactory network in Drosophila larvae may reveal general mechanisms operating during the assembly of neural circuitry (Prieto-Godino, 2012).

    Somatosensory, PNS, nociceptive, proprioceptive, and mechanosensory neurons

    Functional architecture of neural circuits for leg proprioception in Drosophila
    Chen, C., Agrawal, S., Mark, B., Mamiya, A., Sustar, A., Phelps, J. S., Lee, W. A., Dickson, B. J., Card, G. M. and Tuthill, J. C. (2021). Curr Biol. PubMed ID: 34637749

    To effectively control their bodies, animals rely on feedback from proprioceptive mechanosensory neurons. In the Drosophila leg, different proprioceptor subtypes monitor joint position, movement direction, and vibration. This study investigate how these diverse sensory signals are integrated by central proprioceptive circuits. Signals for leg joint position and directional movement converge in second-order neurons, revealing pathways for local feedback control of leg posture. Distinct populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role in detecting external substrate vibration. In each pathway, the flow of sensory information is dynamically gated and sculpted by inhibition. Overall, these results reveal parallel pathways for processing of internal and external mechanosensory signals, which are proposed to mediate feedback control of leg movement and vibration sensing, respectively. The existence of a functional connectivity map also provides a resource for interpreting connectomic reconstruction of neural circuits for leg proprioception (Chen, 2021).

    This study reports the anatomical structure and functional organization of second-order circuits for leg proprioception in Drosophila. Due to the lack of clear hierarchical structure within the VNC leg neuropil, it has been challenging to infer the flow of proprioceptive sensory signals with existing tools. Therefore genetic driver lines were generated that label specific subtypes of leg proprioceptors and classified candidate second-order neurons based on hemilineage identity. Optogenetics and calcium imaging were used to map the functional connectivity between leg proprioceptors and second-order neurons, followed by EM reconstruction to validate synaptic connectivity and in vivo calcium imaging to understand the function of second-order neurons during leg movement. Spatially targeted and subtype-specific optogenetic stimulation were used to analyze integration of FeCO signals within a subset of second-order neuron classes (Chen, 2021).

    Overall, this work reveals the logic of sensory integration in second-order proprioceptive circuits: some populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role for detection of external substrate vibration. Signals for leg joint position and directional movement converge in other second-order neurons, revealing pathways for local feedback control of leg posture. It is anticipated that this functional wiring diagram (see Summary diagram of circuits processing leg proprioceptive signals from the Drosophila FeCO, based on experiments in this study) will also help guide the interpretation of anatomical wiring diagrams determined through EM reconstruction of VNC circuits (Chen, 2021).

    Proprioceptors in the Drosophila FeCO can be classified into three subtypes: club neurons encode bidirectional tibia movement and vibration frequency; claw neurons encode tibia position (flexion or extension); and hook neurons encode the direction of tibia movement.19 Our results show the existence of two distinct central pathways for processing signals from club vs. claw and hook neurons (see Summary diagram of circuits processing leg proprioceptive signals from the Drosophila FeCO, based on experiments in this study). It is proposed that neurons downstream of the club mediate sensing of small mechanical vibrations in the external environment, whereas neurons downstream of the claw and hook provide proprioceptive feedback to motor circuits for controlling the posture and movement of the legs. This division of central pathways for external and internal sensing may be a common motif across limbed animals. Work in a variety of species, including a recent study in mice, has found that many animals can detect low-amplitude, high-frequency, substrate-borne vibrations (Chen, 2021).

    Flies may use vibration sensing to monitor acoustic signals in the environment, such as during courtship behavior, or to detect approaching threats. The distinct anatomical organization of neurons downstream of the club vs claw and hook also supports a segregation of vibration sensing and motor control feedback pathways. 9Ba and 10Ba neurons arborize in the mVAC, a common target of descending neuron axons. In contrast, 13Bb arborize in the IntNp, which contains the dendritic branches of the leg motor neurons and premotor interneurons. Based on these differences, it was hypothesized that vibration-sensing neurons interact with ascending and descending signals to and from the brain, whereas neurons downstream of hook and claw axons contribute to local motor control through direct or indirect connections to motor neurons. Leg motor neurons receive position- and movement-tuned proprioceptive input, consistent with feedback from claw and hook neurons (Chen, 2021).

    Additional connectomic reconstruction is needed to determine which second-order neurons mediate these feedback connections, but 13Bb neurons are promising pre-motor candidates. VNC neurons postsynaptic to claw and hook axons receive only local input, from individual legs. In contrast, second-order neurons postsynaptic to club axons integrate signals across multiple legs. For example, GABAergic 9Bb neurons pool information from left and right legs in a single VNC segment, whereas cholinergic 10Ba neurons receive convergent input from left and right legs across different segments. Integrating club input across legs may improve detection of external vibration signals, while proprioceptive signals from the claw and hook may be initially processed in parallel to support postural control of individual legs. Bilateral integration also occurs in second-order auditory circuits downstream of the Drosophila Johnston's organ: mechanosensory signals from the two antennae are processed in parallel by second-order neurons in the AMMC but then converge in third-order neurons in the wedge (Chen, 2021).

    Although second-order neurons in the vibration pathway integrate club signals across legs, multiple classes of second-order neurons in the motor pathway (13Bb and 8Aa) integrate signals across different FeCO subtypes from the same leg. Using new genetic driver lines that subdivide claw neurons into extension- and flexion-tuned subtypes, it was found that extension-tuned claw and hook neurons converge on 13Bb neurons. These cells are hypothesized to mediate resistance reflexes that stabilize tibia position in response to external perturbations. Prior work in the stick insect has shown that tibia resistance reflexes rely on position and directional movement signals from the FeCO (Chen, 2021).

    In support of this hypothesis, another class of neurons in the 13B hemilineage, 13Ba, also encode tibia extension and drive tibia flexion when optogenetically activated. This functional connectivity map reveals interesting parallels with sensorimotor circuitry in the larval Drosophila VNC. Although fly larvae do not have legs, they do possess body wall proprioceptors (class I sensory neurons) and use chordotonal neurons to sense external vibrations in a manner analogous to club neurons in the adult FeCO. As in the adult, larval neurons belonging to lineage 9 (basin neurons) and lineage 8 (eve lateral interneurons) integrate signals from chordotonal sensory neurons and proprioceptors. These examples suggest that some lineage connectivity motifs are likely conserved across the larval and adult nervous systems, which are already known to possess molecular and general anatomical similarities (Chen, 2021).

    The results identify a prominent role for inhibition in central processing of proprioceptive information from the FeCO. Of the eight identified second-order cell classes, six are putative inhibitory neurons (i.e., release GABA or glutamate). In other sensory circuits, local inhibitory processing contributes to sharpening spatial and temporal dynamics as well as reducing sensory noise through crossover inhibition (Chen, 2021).

    By pharmacologically blocking GABAa and GluCl receptors, we identified a role for inhibition in controlling adaptation within second-order neurons (e.g., 10Ba and 13Bb neurons; Figure 5C). In other cases (20/22Ab or 9Ba; Figure 5A), inhibition was strong enough to completely mask proprioceptive inputs from FeCO axons. We hypothesize that this inhibition may be tuned in certain behavioral contexts, for example, during active movements, to gate the flow of proprioceptive feedback signals in a context-dependent manner. Synaptic transmission in Drosophila can be mediated by chemical synapses, which can be visualized with EM, or electrical gap junctions, which are not typically identifiable at the resolution of current EM volumes. FeCO neurons release acetylcholine but also express gap junction proteins (shakB; data not shown). We therefore used pharmacology to test for the presence of gap junctions between sensory and central neurons. MLA, an effective antagonist of nicotinic acetylcholine receptors in Drosophila eliminated functional connectivity between club and 9Bb neurons but only reduced functional connectivity between club and 10Ba neurons. We observed similar results downstream of the claw: MLA blocked functional connectivity between claw and 13Bb neurons but only reduced functional connectivity between claw and 13Ba neurons (data not shown). These results suggest that second-order proprioceptive circuits receive mixed chemical and electrical input from FeCO neurons. More work is needed to confirm these observations and to investigate the functional significance of why pathways might use one means of signal transmission over the other. One hypothesis is that chemical synapses exhibit adaptation (e.g., synaptic depression), whereas electrical synapses may be more advantageous for sustained synaptic transmission (Chen, 2021).

    Each may provide different advantages for pathways that control behavior on a variety of timescales, from slow postural reflexes to rapid escape behaviors (Chen, 2021).

    Central processing of sensory signals from the FeCO has been previously studied in other insects, especially the locust and stick insect. In both species, second-order interneurons encode combinations of tibia movement and position and also integrate multimodal signals from different proprioceptive organs (Chen, 2021).

    Vibration signals detected by the FeCO appear to be processed by largely segregated populations of VNC interneurons. However, these conclusions were based on mapping of sensory receptive fields, and it was not previously possible to identify specific sources of sensory input, as is done in this study. Overall, comparison of our functional connectivity results in Drosophila with the prior work in other insect species suggests general evolutionary conservation of VNC circuits for leg proprioception and motor control. Although it is currently difficult to identify homologous cell types across insect species, future efforts could leverage conserved developmental programs: the organization of neuroblasts that give rise to the VNC is similar across insect species separated by 350 Ma of evolution (Chen, 2021).

    This is an important advantage of using developmental lineages to define VNC cell classes-locusts and stick insects also possess 9A, 10B, and 13B neurons, which could someday be identified based on molecular markers of lineage identity (Chen, 2021).

    The functional connectivity approach that was employed in this study has both benefits and drawbacks. On the positive side, it allowed screening a large connectivity matrix of genetically identified sensory and central neurons. Compared to other methods for anatomical mapping (e.g., EM), the use of optogenetics and calcium imaging allowed measuring of connection strength and dynamics across multiple individuals. It was found that second-order VNC neurons varied significantly in their functional connectivity strength and temporal dynamics. 5-fold differences were observed in peak calcium signals in response to optogenetic stimulation with the same light intensity. This range could be due to differences in GCaMP expression or intracellular calcium buffering, but could also reflect differences in synaptic strength between pre- and postsynaptic partners (Chen, 2021).

    One limitation of functional connectivity is that it is not possible to measure all possible combinations of pre- and postsynaptic partners. For example, a previous study provided evidence that 9Aa neurons receive input from hook and club neurons, which was not observed in the current screen. This discrepancy could be due to the fact that the driver lines that were used do not label the specific subset of hook and club cells presynaptic to 9Aa neurons. Alternatively, it may be due to differences in signal transmission driven by optogenetic stimulation versus natural tibia movements, as was the case for 9Bb neurons (Chen, 2021).

    Functional connectivity mapping also cannot resolve whether inputs are direct, due to the slow kinetics of GCaMP6. This study therefore used sparse, targeted EM tracing to validate some of the functional connections that were identified between FeCO and VNC neurons. A more detailed comparison of functional and anatomical connectivity will require dense, comprehensive reconstruction of the VNC neuropil. Automated reconstruction and manual proofreading have recently led to draft wiring diagrams of neural circuits in the adult Drosophila central brain (Chen, 2021).

    Identifying neural substrates of competitive interactions and sequence transitions during mechanosensory responses in Drosophila
    Masson, J. B., Laurent, F., Cardona, A., Barre, C., Skatchkovsky, N., Zlatic, M. and Jovanic, T. (2020). Curr Biol 29(6): 935-944. PLoS Genet 16(2): e1008589. PubMed ID: 32059010

    Nervous systems have the ability to select appropriate actions and action sequences in response to sensory cues. The circuit mechanisms by which nervous systems achieve choice, stability and transitions between behaviors are still incompletely understood. To identify neurons and brain areas involved in controlling these processes, a large-scale neuronal inactivation screen was combined with automated action detection in response to a mechanosensory cue in Drosophila larva. Behaviors were analyzed from 2.9x105 larvae, and 66 candidate lines were identified for mechanosensory responses out of which 25 for competitive interactions between actions. The neurons in these lines were further characterized in detail and their connectivity was analyzed using electron microscopy. The neurons in the mechanosensory network were found to be located in different regions of the nervous system consistent with a distributed model of sensorimotor decision-making. These findings provide the basis for understanding how selection and transition between behaviors are controlled by the nervous system (Masson, 2020).

    In order to identify neurons and brain regions underlying competitive interactions and transitions between actions during mechanosensory responses, a high-throughput inactivation screen was performed where individual neurons and groups of neurons were silenced (using tetanus-toxin) in 567 genetic GAL4 lines in Drosophila larva, and the effects of these manipulations on larval behavioral responses to a mechanosensory cue were examined (Masson, 2020).

    The behavioral response of wild-type larvae to the stimulus (air-puff) were characterized and larvae were found to perform a probabilistic sequence of five different actions. An automated approach was developed and used that detects and distinguishes five different discrete behaviors that larvae perform in response to the air-puff. Evidences suggest that the discrete action description is relevant when compared to a continuum approach as parameters associated to larva dynamics tend to naturally cluster. The representation is found to be stable even for large number of larvae while their characteristics (amplitude of actions, duration, size of the larva, shape etc.) can vary significantly. Yet it is pointed out that it does not mean that all behaviors and actions that larvae exhibit are necessarily described as only discrete actions (Masson, 2020).

    This analysis was used to describe phenotypes that result from manipulation of different populations of neurons or single neuron types. Phenotypes were found that are consistent with a specific role of neurons in sensory processing or motor control, competitive interactions, and sequence transitions. Neuronal expression data for all of the GAL4 lines used in this screen have been previously published). The number of neurons that were targeted in the tested lines varies from 1 to 7 pairs on average and smaller number of the GAL4 lines the driver is restricted to a single neuron type. The morphology of top hits were analyzed in more detail using single-cell FLP-out and their connectivity was analyzed using electron-microscopy reconstruction (see Putative pathways in the mechanosensory network)(Masson, 2020).

    A framework was developed for selectively identifying circuit elements underlying competitive interactions and sequence transitions. Sensory-processing, sensorimotor decisions, and sequence generation are intertwined processes as the latter two will depend on how the sensory information is processed, and the sequence production mechanistically might depend on competitive interaction between distinct actions as suggested by models of sequence generation like competitive queuing or chains of disinhibitory loops. Nevertheless, the reasoning described below was used to identify neurons selectively involved in competitive interactions that underlie sensorimotor decisions and sequence generation (Masson, 2020).

    It was reasoned that, if the stimulus cannot be processed and thus perceived accurately the animals might respond less, by performing less of all or some of the actions. If the sensory processing is affected in the opposite way (hypersensitivity), animals might respond more, and perform more of all or some of the actions normally observed. Thus, the neurons that gave such inactivation phenotypes (of less of one or more actions; or more of one or more actions) could be involved in any aspect of sensory processing or motor control. It cannot be excluded that these larvae responded less because the inactivation of the neurons modulates the overall animal state (Masson, 2020).

    However, inactivation of neurons involved in mediating competition between actions is expected to result in increased probability of one action and a decreased probability of one or more other actions (or the converse) as the neuron implementing the competitions will promote one action while inhibiting competing options. Based on this logic, 25 hits (GAL4 lines) were identified that were top candidates for selectively mediating affected competitive interactions. Morphologically the neurons in these lines were characterized using light microscopy of multicolor flip-out and for some of the neurons determined their connectivity by identifying them in the electron microscopy volume. It was found that some of these neurons received input from chordotonal sensory neurons, chordotonal related interneurons or multidendritic class III sensory neurons while others were pre-motor neurons. In addition, other neurons were found that project to or are located in the brain. Taken altogether, the GAL4 lines that were identified as hits drive in neurons that are located in the ventral nerve cord (both abdomen and thorax region), suboesophageal ganglion and brain. This suggests that the networks for competitive interactions between actions that occur in response to air-puff are distributed across the nervous system (Masson, 2020).

    The idea that sensorimotor decisions are made 'through a distributed consensus that emerges in competitive populations' and that interactive behaviors require sensorimotor and selection system to function in parallel have emerged in various fields, but it has been challenging to elucidate the neuronal architecture that would implement such sensorimotor decisions. The Drosophila larva, because of its numerical simplicity, small size and the existence of multiple experimental approaches for structural and functional connectivity studies, behavioral genetics, optogenetics etc. is an ideal system for investigating how the outcomes of these competitive interactions at the different sites are integrated across the nervous system to give rise to coherent sensorimotor behaviors (Masson, 2020).

    The neural architecture that controls the productions of probabilistic action sequences and establishes the order of the individual elements in the sequence is also poorly understood. This study identified a number of hit line phenotypes that were consistent with an implication of the neurons in ensuring proper ordering of individual elements in the sequence. For example, the neurons in the R45D11 line could be inhibiting reversals from Bend to Crawl and promoting transitions from Bend to Back, while neurons in the R69E06 line could be promoting transitions from Bend to Back-up while preventing reversals from Bend to Hunch. In previous work on a two- element Hunch-Bend sequence in response to an air-puff, it was proposed that transitions to the next element in the sequence and reversal to the previous element are controlled through two different motifs: lateral disinhibition from the neuron driving one behavior onto the neuron driving the following behavior and feedback disinhibition that provides a positive feedback that stabilizes the second behavior and prevents reversals back onto the previous actions (Jovanic, 2016).

    It was speculated that chains of such disinhibitory loops could be a general mechanism for generating longer behavioral sequences. In the case of longer sequences (more than two elements) the maintenance of a selected action (through a positive feedback) after the transition from the previous action has occurred would need to be balanced with promoting the transition from the current onto the following action in the sequence. The candidate neurons in the R45D11 and the R69E06 could represent a starting point for investigating these mechanisms as their phenotype are consistent with preventing reversals from Bend to Hunch and Crawl and promoting transitions from Bend to Back-up (that represent nearly 80% of transitions from Bend). Another category of phenotypes, increase in transitions from Hunch to Back-up and decreased from Hunch to Bend, suggests that asymmetric competitive interactions exist between transitions to Bend and Back-up (from Hunches) where the transitions from Hunch to Bend inhibit transitions from Hunch to Back-up but not the other way around. Such a mechanism would allow a progression of a sequence in a probabilistic way where the transitions from Hunch to Bend are more likely (50%) than to Back-up (less than 15%) (Masson, 2020).

    In summary, this screen provides a roadmap for investigating the neural circuit mechanisms underlying the different computations during mechanosensory responses. It also offers a starting point for identifying the mechanisms underlying the competitive interactions between behaviors as well as the transition between individual actions in probabilistic sequences across the nervous system. While the number of neurons that were targeted in the tested lines varies from one to seven pairs on average, and sometimes more, in the case when the lines label multiple neuron types, intersectional strategies can be used to further refine the expression patterns. In the larva, a volume of electron microscope data has been acquired and more than 60% of the nervous system has been reconstructed through collaborative efforts. The synaptic partners of the identified candidate neurons can therefore be further reconstructed in the electron microscopy volume. Combined with EM reconstruction, physiology, and modeling the candidate lists of neurons can be used to relate circuit structure and function across the nervous system and unravel the principles of how the nervous system selects actions and produces action sequences in response to external stimuli (Masson, 2020).

    Characterization of proprioceptive system dynamics in behaving Drosophila larvae using high-speed volumetric microscopy
    Vaadia, R. D., Li, W., Voleti, V., Singhania, A., Hillman, E. M. C. and Grueber, W. B. (2019). Curr Biol 29(6): 935-944. PubMed ID: 30853438

    Proprioceptors provide feedback about body position that is essential for coordinated movement. Proprioceptive sensing of the position of rigid joints has been described in detail in several systems; however, it is not known how animals with a flexible skeleton encode their body positions. Understanding how diverse larval body positions are dynamically encoded requires knowledge of proprioceptor activity patterns in vivo during natural movement. This study used high-speed volumetric swept confocally aligned planar excitation (SCAPE) microscopy in crawling Drosophila larvae to simultaneously track the position, deformation, and intracellular calcium activity of their multidendritic proprioceptors. Most proprioceptive neurons were found to activate during segment contraction, although one subtype was activated by extension. During cycles of segment contraction and extension, different proprioceptor types exhibited sequential activity, providing a continuum of position encoding during all phases of crawling. This sequential activity was related to the dynamics of each neuron's terminal processes, and could endow each proprioceptor with a specific role in monitoring different aspects of body-wall deformation. This study demonstrates this deformation encoding both during progression of contraction waves during locomotion as well as during less stereotyped, asymmetric exploration behavior. The results provide powerful new insights into the body-wide neuronal dynamics of the proprioceptive system in crawling Drosophila, and demonstrate the utility of the SCAPE microscopy approach for characterization of neural encoding throughout the nervous system of a freely behaving animal (Vaadia, 2019).

    This study demonstrates a new approach for live volumetric imaging of sensory activity in behaving animals, leveraging an optimized form of high-speed SCAPE microscopy. This methodology was used to examine the activity patterns of a heterogeneous collection of proprioceptive neurons during crawling, as well as during more complex movements such as head turning and retraction, to determine how larvae sense body-shape dynamics. Imaging revealed 3D distortion of proprioceptive dendrites during movement and GCaMP activity that occurred coincident with dendritic deformations. It is noted that the results are consistent with a complementary study (He, 2019), which examined ddaD and ddaE dorsal proprioceptors and also demonstrated increased activity during dendrite folding. The He study elucidated that this deformation-dependent signaling is reliant on the mechanosensory channel TMC (Vaadia, 2019).

    This survey of the full set of hypothesized multidendritic proprioceptors in behaving larvae revealed that most neurons (all class I neurons, dmd1, and vbd) increase activity during segment contraction. By contrast, dbd neurons showed increased activity during segment stretch, which is consistent with previous electrophysiological recordings of dbd in a dissected preparation. The temporal precision afforded by high-speed SCAPE microscopy further revealed that different proprioceptors exhibit sequential onset of activity during forward crawling. Timing of activity was associated with distinct dendrite morphologies and movement dynamics, suggesting that proprioceptors monitor different features of segment deformation. The complementary sensing of segment contraction versus stretch in class I, dmd1, and vbd versus dbd neurons provides an additional measure of movement that is conceptually similar to the responses of Golgi tendon organs versus muscle spindles in mammals. Combined, these results indicate that this set of proprioceptors function together to provide a continuum of sensory feedback describing the diverse 3D dynamics of the larval body (Vaadia, 2019).

    Prior work suggested that the proprioceptors analyzed in this study have partially redundant functions during forward crawling because silencing different subsets caused similar behavioral deficits, namely slower crawling, whereas silencing both subsets had a more severe effect. Slow locomotion may be a common outcome in a larva that is lacking in part of its sensory feedback circuit, yet the results suggest that each cell type has a unique role. The demonstration of the varying activity dynamics of proprioceptors during crawling and more complex movements indicates that diverse sensory information is available to the larva, and suggests that feedback from a combination of these sensors could be used to infer aspects of speed, angle, restraint, and overall body deformation. This feedback system is likely to be important for a wide range of complex behaviors, such as body bending and nociceptive escape (Vaadia, 2019).

    How can an understanding of proprioceptor activity patterns inform models of sensory feedback during locomotion? Electron microscopic reconstruction has shown that ddaD, vbd, and dmd1 proprioceptors synapse onto inhibitory premotor neurons (period-positive median segmental interneurons, A02b), which promote segment relaxation and anterior wave propagation. Thus, activity of these sensory neurons may signal successful segment contraction and promote forward locomotion, in part by promoting segment relaxation. Furthermore, vpda neurons provide input onto excitatory premotor neurons A27h, which acts through GABAergic dorsolateral (GDL) interneurons to inhibit contraction in neighboring anterior segments, thereby preventing premature wave propagation. In this way, vpda feedback could contribute to proper timing of contraction in anterior segments during forward crawling. In contrast to other proprioceptors, dbd neurons are active during segment stretch. Their connectivity also tends to segregate from contraction-sensing neurons, and understanding how the timing of this input promotes wave propagation is an important future question. This study's dynamic recordings of the function of these neurons during not just crawling but also exploration behavior provide essential new boundary data for testing putative network models derived from this anatomical roadmap (Vaadia, 2019).

    SCAPE's high-speed 3D imaging capabilities enabled 10 VPS imaging of larvae during rapid locomotion. Fast volumetric imaging not only prevented motion artifacts but also revealed both the 3D motion dynamics and cellular activity associated with crawling behavior. SCAPE's large, 1-mm-wide field of view allowed multiple cells along the larva to be monitored at once, while providing sufficient resolution to identify individual dendrite branches. Because SCAPE data are truly 3D, dynamics could be examined in any section or view. Additionally, fast two-color imaging enabled simultaneous 3D tracking of cells, monitoring of GCaMP activity, and correction for motion-related intensity effects. The demonstration that larvae that are compressed during crawling exhibit altered dendrite deformation, and thus altered proprioceptive signaling, underscores the benefit of being able to image unconstrained larvae, volumetrically, in real time. Furthermore, rapid volumetric imaging allowed for the analysis of sensory responses during non-stereotyped, exploratory head movements in 3 dimensions, revealing activity patterns that could be utilized for encoding of complex, simultaneous movements. This finding also demonstrates the quantitative nature of SCAPE data and its high signal to noise, which enabled real-time imaging of neural responses without averaging from multiple neurons (Vaadia, 2019).

    This study provides an example of how high-resolution, high-speed volumetric imaging enabled investigation of the previously intractable question of how different types of proprioceptive neurons encode forward locomotion and exploration behavior during naturalistic movement. Imaging could readily be extended to explore a wider range of locomotor behaviors such as escape behavior, in addition to other sensory modalities such as gustation and olfaction. Detectable signals reveal rich details including the firing dynamics of dendrites and axonal projections during crawling. Waves of activity in central neurons within the ventral nerve cord can also be observed. It is expected that the in vivo SCAPE microscopy platform utilized in this study could ultimately allow complete activity mapping of sensory activity during naturalistic behaviors throughout the larval CNS. Using SCAPE, it is conceivable to assess how activity from proprioceptive neurons modulates central circuits that execute motor outputs, which will provide critical information for a dissection of the neural control of behavior with whole-animal resolution (Vaadia, 2019).

    A neural basis for categorizing sensory stimuli to enhance decision accuracy
    Hu, Y., Wang, C., Yang, L., Pan, G., Liu, H., Yu, G. and Ye, B. (2020). A neural basis for categorizing sensory stimuli to enhance decision accuracy. Curr Biol. PubMed ID: 33065003

    Sensory stimuli with graded intensities often lead to yes-or-no decisions on whether to respond to the stimuli. How this graded-to-binary conversion is implemented in the central nervous system (CNS) remains poorly understood. This study shows that graded encodings of noxious stimuli are categorized in a decision-associated CNS region in the ventral cord of Drosophila larvae, and then decoded by a group of peptidergic neurons for executing binary escape decisions. GABAergic inhibition gates weak nociceptive encodings from being decoded, whereas escalated amplification through the recruitment of second-order neurons boosts nociceptive encodings at intermediate intensities. These two modulations increase the detection accuracy by reducing responses to negligible stimuli whereas enhancing responses to intense stimuli. These findings thus unravel a circuit mechanism that underlies accurate detection of harmful stimuli (Hu, 2020).

    This study identified a neural network that categorizes noxious stimuli of graded intensities to generate binary escape decisions in Drosophila larvae, and a gated amplification mechanism was unraveled that underlies such binary categorization. In responding to the noxious stimuli, whereas failure in prompt responses may cause harm, excessive escape responses to negligible stimuli would lead to the loss of resources for survival. The gated amplification mechanism could reduce the responses to negligible stimuli whereas enhancing the responses to intense stimuli. In this way, the accuracy in deciding whether to escape from the stimuli is enhanced (Hu, 2020).

    Information processing in the nervous system is affected by noise, which may be embedded in external sensory stimuli (e.g., sensory noise) or generated within the nervous system (e.g., electric noise). A recent study in C. elegans shows that activation mediated by electrical synapses and disinhibition mediated by glutamatergic chemical synapses form an AND logic gate to integrate the presentation of the salience of attractive odors. The AND-gate computation in worm AIA interneurons requires multiple sensory neurons to report the presence of attractive odors and, consequently, filters out the noise embedded in the sensory stimuli. Another study on the olfactory system of adult Drosophila reported a mechanism to address the noise that is produced within the nervous system. A three-layered feedforward network averages the noise to enhance peak detection accuracy and then uses coincidence detection to distinguish real signals arrived synchronously from noise caused by spontaneous neural activities. In the nervous system, the noise can be produced at each stage of the sensori-motor transformation. Compared with the two mechanisms mentioned above, which filter out the existing noise, the graded-to-binary conversion through the gated amplification mechanism reported in this study makes the converted signals less vulnerable to the noise produced at later stages of sensori-motor transformation. This is because after the graded signals become binary, the signals are more separated (either suppressed or amplified) according to stimulus intensities and, consequently, the same level of noise is less likely to cause the binary signals to falsely pass the decision threshold than the graded ones. As a result, the ambiguous encoding range of the stimulus intensity is narrowed and the frequency of false decisions is reduced, as demonstrated by computational modeling (Hu, 2020).

    Thresholding of gradually accumulated sensory evidence has been considered to be fundamental for generating yes-or-no decisions. For example, a recent study in mammals has shown that visual evidence of danger can be gradually accumulated by recurrent circuits to overcome the threshold for escape behaviors. Such a mechanism takes time to build up decision-associated activities for decisions with higher accuracy, which leads to the well-known speed-accuracy trade-off in perceptual decision making. However, the current findings add a new dimension to the processing of sensory evidence for perceptual decision making: different from recurrent networks, the recruitment of a number of SONs can instantaneously boost the decision-associated activity to reach the decision threshold, which ensures decision speed. Because the gated amplification mechanism reported here also ensures the detection accuracy, such a mechanism might bypass the speed-accuracy trade-off in sensory signal detection (Hu, 2020).

    An electron microscopy connectome study reported 13 types of second-order neurons (SONs) in the Drosophila larval nociceptive system, each of which has distinct connectivity and functions. For example, Basin-4, DnB, and Wave neurons also receive mechanosensory inputs, whereas A08n does not. Moreover, Wave neurons detect stimulus positions on larval body walls. Furthermore, serotonergic modulation acts on this network during development to adjust the nociceptive responses, providing a mechanism for larvae to adjust the escape threshold according to their developmental environment. However, because at least 5 types of SONs are both required and sufficient for larval escape behaviors, it remains a mystery why there exist so many seemingly redundant neurons at the same level in the network. The nociceptive system is a dedicated protective system that responds to potential tissue-damaging insults, so both speed and accuracy of the perceptual decision-making process are important. This is probably why the nociceptive system uses an amplification network formed by a large number of SONs to dissociate time from accuracy in the perceptual decision-making process and avoid the trade-off between decision speed and accuracy (Hu, 2020).

    Novel unbiased computational toolsets were developed for automatically analyzing the functional connectivity of all neural structures, including both somas and neurites in the larval VNC. Using these toolsets, a decision-associated CNS region, the PMC, was identified that covers the neuropil structure TP. The TP is concentrated with large amounts of neurites, especially those of peptidergic neurons. Although this anatomical structure was identified previously, its function is unknown. The finding of this study of its important function in sensori-motor transformation suggests that this region is possibly a hub for information exchange and integration. The detailed anatomical and functional connectivity of the TP could be a fascinating direction for future studies (Hu, 2020).

    In summary, this study postulates a neural basis for converting graded sensory inputs to yes-or-no behavioral decisions. A previous study showed that neurons in the rat posterior parietal cortex encode a graded value of accumulating evidence whereas those in the prefrontal cortex have a more categorical encoding that indicates the decisions. Thus, the categorization of sensory evidence by making graded encodings binary in perceptual decision making is likely an evolutionarily conserved process. In this study, advantage was taken of the powerful genetic model Drosophila to unravel how such computation might be implemented at the cellular and molecular level. Finally, because whole-CNS functional imaging analysis is a key approach to decipher the neural basis for sensori-motor integration and perceptual decision making, it is anticipated that the computational tools developed in this study will facilitate investigations in these fields (Hu, 2020).

    Comparative connectomics reveals how partner identity, location, and activity specify synaptic connectivity in Drosophila
    Valdes-Aleman, J., Fetter, R. D., Sales, E. C., Heckman, E. L., Venkatasubramanian, L., Doe, C. Q., Landgraf, M., Cardona, A. and Zlatic, M. (2020). Neuron. PubMed ID: 33120017

    The mechanisms by which synaptic partners recognize each other and establish appropriate numbers of connections during embryonic development to form functional neural circuits are poorly understood. This study combined electron microscopy reconstruction, functional imaging of neural activity, and behavioral experiments to elucidate the roles of (1) partner identity, (2) location, and (3) activity in circuit assembly in the embryonic nerve cord of Drosophila. Postsynaptic partners were found to be able to find and connect to their presynaptic partners even when these have been shifted to ectopic locations or silenced. However, orderly positioning of axon terminals by positional cues and synaptic activity is required for appropriate numbers of connections between specific partners, for appropriate balance between excitatory and inhibitory connections, and for appropriate functional connectivity and behavior. This study reveals with unprecedented resolution the fine connectivity effects of multiple factors that work together to control the assembly of neural circuits (Valdes-Aleman, 2020).

    The human nervous system is organized into circuits with specifically matched and tuned cell-to-cell connections essential for proper function. During development, neurons navigate through the nervous system to reach their target location. Surrounded by numerous cells along their trajectories and in their target areas, developing neurons ignore most cells and connect only to specific partners (Valdes-Aleman, 2020).

    The absolute numbers of synapses between specific partners can vary across individuals, hemispheres, or repeated network modules in the same individual. However, recent electron microscopy (EM) reconstructions in multiple Drosophila larvae suggest that, at least in some circuits, the relative numbers of synapses between partners are precisely regulated. Thus, the fraction of inputs a neuron receives from a specific partner, relative to its total number of inputs, is remarkably conserved across individuals, across larval stages, and even between larva and adult. For example, the fraction of input varied by an average factor (fold change; i.e., the ratio of two fractions) of 1.07 ± 0.22 between different first instar larvae (n = 13 homologous connections) and 1.09 ± 0.20 from first to third instar (n = 12 homologous connections). Similarly, the average input a mushroom body output neuron receives from a modulatory neuron in the larva and adult is 3.4% and 3.3%, respectivelyh. These examples of conserved fractions of synaptic input across individuals and life stages raise several key questions: (1) How important are the precise numbers of connections between neurons for normal behavior? (2) How are the precise numbers of connections between partners specified? and (3) How is the appropriate balance between excitatory and inhibitory connections in the circuit achieved (Valdes-Aleman, 2020)?

    The chemoaffinity hypothesis proposes that pre- and postsynaptic partners express specific matching combinations of cell surface molecules that enable them to seek out and recognize each other during development. However, relatively few examples of partner-recognition molecules have been identified, so it is unclear whether their use is a general principle or if they are used only in some systems. It is also unknown if these partner-recognition mechanisms specify precise numbers of synapses between partners, or only instruct two neurons to form synapses, but not how many (Valdes-Aleman, 2020).

    Alternative hypotheses propose that neurons seek out specific locations in the nervous system, rather than specific partners, indiscriminately connecting to whichever neurons are present there. Consistent with this, neurons have been shown to use non-partner-derived positional cues, such as third-party guidepost cells or gradients of repellents, to select their termination and synaptogenesis area independently of their partners. Additionally, activity-dependent mechanisms are thought to refine connections through Hebbian and/or homeostatic plasticity mechanisms. Neurons that fire together preferentially wire together in many areas of the vertebrate nervous system through positive feedback. At the same time, homeostatic mechanisms restore activity toward a specific set point through negative feedback, imposing competition and preventing runaway excitation or complete silencing of the circuit. However, the extent to which activity modulates numbers versus the strength of existing synapses is still an open question (Valdes-Aleman, 2020).

    These questions have been difficult to address because they require manipulating candidate factors that could influence connectivity, visualizing synapses between uniquely identified partners, and relating observed structural changes to effects on functional connectivity and behavior. This study therefore used the tractable Drosophila larva as a model system with the following advantages: (1) excellent genetic tools for selective manipulation of uniquely identified neurons; (2) a compact nervous system amenable to rapid imaging with synaptic resolution, and (3) a rich behavioral repertoire with well-established quantitative assay (Valdes-Aleman, 2020).

    Recently, comprehensive synaptic-resolution connectivity maps of the circuitry downstream of the mechanosensory Chordotonal (hereafter 'mechanosensory') neurons and nociceptive multidendritic class IV (hereafter 'nociceptive') neurons in an abdominal segment of a first instar larva have been generated. Portions of this circuit were also reconstructed in two different abdominal segments (A1 and A3) of two different first instar individuals and at two different life stages: first (A1) and third instar (A3) (Valdes-Aleman, 2020).

    This study selectively altered the location or activity of the mechanosensory neurons and generated new EM volumes of the manipulated samples to investigate the effects on connectivity. These anatomical studies were completed with functional connectivity and behavioral assays. This study reveals that proper location, partner identity, and activity are all required to achieve appropriate connectivity and behavior (Valdes-Aleman, 2020).

    In some systems the position of pre- or postsynaptic terminals is specified by non-partner-derived positional cues. In other systems, molecules have been identified that mediate partner matching. However, it was unclear whether both mechanisms could operate in the same system and whether either mechanism specifies numbers of connections between partners (Valdes-Aleman, 2020).

    Although developing sensory axons use non-partner-derived positional cues to select their final termination area in the Drosophila nerve cord, the current results suggest that position alone does not specify connectivity and that partner recognition also exists. When the location of sensory axons was altered, their postsynaptic partners extended ectopic branches and formed synaptic connections with them. The shifted axons did not gain any new strongly connected partners at their ectopic location, providing further evidence of remarkable partner selectivity. It is hard to imagine which cue, other than the mechanosensory axons themselves, instructed partner dendrites to form these ectopic branches and synapses. Nevertheless, the final proof of the existence of the partner-derived cues will be their identification in the future (Valdes-Aleman, 2020).

    If partner-recognition molecules are sufficient for selective synaptogenesis irrespective of the location of partners, why is the precise location of sensory neuron axon terminals so tightly regulated by non-partner-derived positional cues? Despite partner neurons' connecting in ectopic locations, they did not establish appropriate numbers of synapses, resulting in defective responses to mechanosensory stimuli. This indicates that precise positioning of presynaptic mechanosensory axons is necessary for the formation of appropriate number of synapses (Valdes-Aleman, 2020).

    It is not known why some partners received more synapses from shifted mechanosensory axons and others fewer than in wild-type. One possibility could be the involvement of third-party guidepost cells in synaptogenesis which would not be present in the aberrant location. Another speculation is that some neurons are better than others at finding their misplaced partners. Yet another possibility could be that shifting mechanosensory neurons initially resulted in fewer or weaker synaptic connections. This could have triggered compensatory homeostatic changes in the balance of excitation and inhibition within the circuit by increasing mechanosensory connections onto excitatory interneurons and reducing those onto inhibitory interneurons. This latter possibility could explain why similar connectivity effects were observed when sensory neurons were shifted and when they were inactivated during development (Valdes-Aleman, 2020).

    Finally, in addition to changes in synapse numbers, silencing or shifting presynaptic partners could have also induced changes in synaptic strength and electrical properties (e.g., through changes in ion channel composition) that could account for some of the observed effects in behavior and functional connectivity. Furthermore, changes in the shapes of arbors could potentially affect electrical signal propagation. Future patch-clamp recordings following the same experimental manipulations could reveal the extent to which this occurs (Valdes-Aleman, 2020).

    Activity plays a major role in refining the patterns of neuronal connections during development, especially in vertebrates. However, the effects induced within the network in response to selective silencing of specific neuron types are not fully understood (Valdes-Aleman, 2020).

    The role activity plays in the development of the insect central nervous system is less clear. Some studies have shown that a lack of sensory activity during development does not affect neuron morphology or the capacity to form connections. Other studies have reported neural circuits can adapt their morphology, connectivity, or behavior in response to changes in developmental activity. However, a comprehensive synaptic-resolution analysis of the effects of silencing a specific neuron type on the numbers of connections between partners was lacking (Valdes-Aleman, 2020).

    EM reconstructions revealed that silenced mechanosensory neurons connected to the appropriate partners, but with inappropriate numbers of synapses. Interestingly, excitatory multisensory interneurons (Basin) received a higher fraction of input from silenced mechanosensory neurons than in controls, while inhibitory interneurons (Ladder and Griddle) received a lower fraction. Selective silencing of mechanosensory neurons also increased input from a different sensory modality (nociceptive) onto Basin interneurons and decreased their input from inhibitory interneurons. This overall effect is similar to observations in the cortex, where sensory deprivation induces network-level homeostasis that alters the balance of excitation and inhibition. Synaptic scaling in the cortex is thought to be multiplicative, such that all excitatory connections onto an excitatory neuron are scaled equally when excitatory drive onto that neuron is reduced. In contrast, the inhibitory connections onto excitatory neurons are reduced. Although the majority of studies in the cortex focus on homeostatic plasticity of functional connections, this study demonstrated a drastic plasticity in the number of synaptic connections between partners. This apparent homeostasis of synapse numbers may follow similar multiplicative rules, because this study found that both mechanosensory and nociceptive inputs onto Basin interneurons were increased when mechanosensory neurons were silenced (Valdes-Aleman, 2020).

    It was found that larvae with permanently silenced mechanosensory neurons not only had increased structural connections between nociceptive and Basin neurons but also stronger functional connections and behavioral responses to nociceptive stimuli. This structural and behavioral compensation is reminiscent of findings in mammals, in which if one sensory modality is removed, another modality is restructured and improved (Valdes-Aleman, 2020).

    Interestingly, silencing mechanosensory neurons during development permanently decreased responses to mechanosensory stimuli, even days after restoring activity. This is also reminiscent of findings in mammals, in which deprivation of visual input during an early critical period permanently impairs vision. However, this result appears at odds with the increased structural and functional connections from silenced mechanosensory neurons onto the excitatory Basins. A possible explanation is the reduction of mechanosensory connections onto inhibitory neurons under the same conditions. Unlike nociceptive neurons, the mechanosensory neurons have more inhibitory than excitatory postsynaptic partners, and these inhibitory interneurons play a role in triggering mechanosensory behaviors through disinhibition. Silencing the mechanosensory neurons may therefore result in a permanent reduction in disinhibition in the circuit with permanent consequences on behavior (Valdes-Aleman, 2020).

    In summary, although partner-recognition molecules can ensure neurons recognize and connect only with appropriate partners, they are not sufficient to robustly specify appropriate numbers of synapses. Conversely, although neither precise location of presynaptic terminals nor neuronal activity in presynaptic partners directly instructs partner specificity, both are crucial to achieve appropriate numbers of connections, appropriate strengths of functional connections, appropriate balance of excitation and inhibition, and appropriate behavior. This study reveals with unprecedented resolution how location, identity, and activity work together to give rise to appropriately wired neural circuits and appropriate behaviors (Valdes-Aleman, 2020).

    Mechanism underlying starvation-dependent modulation of olfactory behavior in Drosophila larva
    Slankster, E., Kollala, S., Baria, D., Dailey-Krempel, B., Jain, R., Odell, S. R. and Mathew, D. (2020). Sci Rep 10(1): 3119. PubMed ID: 32080342

    Starvation enhances olfactory sensitivity that encourage animals to search for food. The molecular mechanisms that enable sensory neurons to remain flexible and adapt to a particular internal state remain poorly understood. The roles of GABA and insulin signaling in starvation-dependent modulation of olfactory sensory neuron (OSN) function was studied in the Drosophila larva. The GABAB-receptor and insulin-receptor play important roles during OSN modulation. Using an OSN-specific gene expression analysis, this study explored downstream targets of insulin signaling in OSNs. The results suggest that insulin and GABA signaling pathways interact within OSNs and modulate OSN function by impacting olfactory information processing. It was further shown that manipulating these signaling pathways specifically in the OSNs impact larval feeding behavior and its body weight. These results challenge the prevailing model of OSN modulation and highlight opportunities to better understand OSN modulation mechanisms and their relationship to animal physiology (Slankster, 2020).

    Starvation increases olfactory sensitivity that enhances an animal's search for food. This has been shown in insects, worms, and mammals including humans. However, the mechanisms by which an animal's starved state modulates sensory neuron function remain poorly understood. Understanding of these mechanisms significantly improved in the last decade or so from studies that showed how neuromodulators enable changes in the gain of peripheral sensory inputs. The prevailing mechanistic model for olfactory sensory neuron (OSN) modulation by the animal's starved state is that during the animal's starved-state, lower insulin signaling frees production of the short neuropeptide F receptor (sNPFR1), which increases sNPF signaling. Higher sNPF signaling increases presynaptic facilitation of OSNs, which leads to enhanced responses to odors. Interestingly, insulin and neuropeptide Y (the mammalian ortholog of sNPF) signaling also feature in the vertebrate olfactory bulb (Slankster, 2020).

    However, the above model is incomplete and several questions remain. For instance, the model does not account for the role of GABA signaling, which plays important roles during both starvation and olfactory behavior in flies and mammals. The model also does not account for interactions between GABA and insulin signaling pathways that are known to impact neuromodulation in both fly and mammalian systems: For instance, GABAB-Receptor (GABABR) mediates a GABA signal from fly brain interneurons, which may be involved in the inhibitory control of Drosophila insulin like peptide (DILP) production; In mammalian CNS neurons, insulin increases the expression of GABAAR on the postsynaptic and dendritic membranes; GABA administration to humans resulted in a significant increase in circulating Insulin levels under both fasting and fed conditions. Finally, the model does not account for the ultimate targets of insulin/GABA/sNPF signaling that alter OSN sensitivity to odors and its function (Slankster, 2020).

    The above questions are significant because the mechanisms driving neural circuit modulations are fundamental to understanding of how neural circuits support animal cognition and behavior. If these mechanisms are better understood, it would be possible to learn how flexibility and the ability to adapt to a particular internal state are built into the sensory circuit. Understanding the mechanisms by which the starved state of an animal modulates its olfactory sensitivity and thereby controls its food-search behavior is important for both olfactory and appetite research. Finally, this connection cannot be ignored in light of the obesity epidemic and the demonstration that obese adults have reduced olfactory sensitivity (Slankster, 2020).

    This study builds upon the prevailing model and argue that GABA and insulin signaling pathways interact within OSNs to mediate starvation-dependent modulation of its function and that defects in these signaling pathways impact larval food-search and feeding behaviors, which in turn impact weight gain. The Drosophila larval system is used in this study to demonstrate evidence in support of this argument. Using larval behavior assays, this study shows that GABABR and insulin receptor (InR) are required for starvation dependent increases in larval olfactory behavior. Using a novel OSN-specific gene expression analysis, this study shows that insulin and GABA signaling pathways interact within OSNs and modulate OSN function by impacting odor reception, olfactory information processing, and neurotransmission. Finally, this study shows that manipulating these signaling pathways specifically in the OSNs impact larval feeding behavior and its body weight (Slankster, 2020).

    Insulin and GABA signaling pathways interact within OSNs and likely modulate OSN function by impacting odor reception (Orco), olfactory information processing (Rut), and/or neurotransmission (Syt1). Defects in GABA/insulin signaling pathways impact the animal's feeding behavior and body weight. These findings suggest a hitherto unsuspected role for GABA signaling in starvation-dependent modulation of OSN function, a role that is likely downstream of insulin signaling. They also raise questions about how individual OSNs may be differentially modulated by the animal's starved state. Finally, these findings imply a potential relationship between nutrient sensing and animal physiology (Slankster, 2020).

    GABA and insulin signaling play important roles during both starvation and olfactory behavior. While GABA signaling in different regions of the animal brain is known to mediate starvation-dependent behavior, its role in specific olfactory neurons during starvation is unclear. Similarly, insulin has long been considered as an important mediator of state dependent modulation of feeding behavior. However, its precise role in olfactory neurons during starvation is controversial. According to the prevailing model, insulin signaling decreases upon starvation. However, a previous study showed that there is a three-fold increase in DILP-6 (Drosophila Insulin like Peptide) mRNA expression in larval tissue including fat bodies upon starvation (Slaidina, 2009), which is inconsistent with the model described in this paper. While the significance of DILP-6 increase in larval tissue during starvation is as yet unclear, consistent with the prevailing model, this study shows that InR and DILP-6 expression in larval head samples decrease upon starvation (Slankster, 2020).

    This study also shows that higher insulin signaling increases expression levels of GABABRs in OSNs. This result is in line with several other studies in flies and mammals that have suggested possible interactions between GABA signaling and insulin signaling in different regions of the brain. The most relevant example supporting the current observation is noted in mice where insulin increases the expression of GABAARs on the postsynaptic and dendritic membranes of CNS neurons. Other examples show how GABA signaling might influence insulin signaling. For instance, in flies, GABA signaling from interneurons has been shown to affect insulin signaling by regulating DILP production; In humans, GABA administration significantly increases circulating insulin levels under both fasting and fed conditions; In diabetic rodent models, combined oral administration of GABA and an anti-diabetic drug (Sitagliptin) promoted beta cell regeneration and reduced blood glucose levels. Overall, this study adds to this growing body of literature and strongly suggests that GABA and insulin signaling pathways interact within larval OSNs to mediate OSN modulation (Slankster, 2020).

    It is noted that starvation enhanced larval attraction toward only a subset of the odors tested. A related question in the field is whether starvation enhances an animal's ability to detect food-odors or all odors. Studies are inconclusive so far. Some studies have shown that starvation enhances an animal's ability to detect both food-related odors and nonfood-related odors. While similar results have also been shown in humans, the findings regarding the relevance of odor to feeding are rather mixed. This study along with previous studies raise the possibility that starvation differentially modulates individual OSNs. Indeed, individual OSNs exhibit functional diversity that may lend them to differential modulation by the animal's internal state. This diversity may stem from heterogeneous GABABR levels on the terminals of individual OSNs that determine differential presynaptic gain control. It is reasonable to speculate that heterogeneous GABABR and/or InR levels in individual OSNs could contribute to differential modulation of OSNs by the animal's starved state, which in turn impacts behavior toward only a subset of odors (Slankster, 2020).

    An inability to regulate sensitivity to food odors at appropriate times leads to irregular feeding habits, which in turn leads to weight gain. Obesity researchers will readily acknowledge that while several obvious risk factors for obesity (e.g., genetics, nutrition, metabolism, environment etc.) have been heavily researched, the relationship between nutrient sensing/sensory behavior and obesity remains grossly understudied. The present study sets the stage to further explore this relationship. Interestingly, several of the signaling molecules described in this study that play a role in OSN modulation have also been implicated in hyperphagia and obesity phenotypes. For instance, overexpression of sNPF in Drosophila and NPY injection in the hypothalamus of rats leads to increased food-intake and bigger and heavier phenotypes. Genetically obese rats have low levels of insulin in the brain including in the olfactory bulb and imbalanced insulin signaling via insulin receptors is associated with obesity phenotypes. Adenylyl cyclase (rut) deficient mice were found to be obese and both Adenylyl cyclase and Synaptotagmin have been targeted for anti-obesity drug development. These studies provide added significance to the observation that manipulating mechanisms mediating starvation-dependent modulation of OSNs impact feeding behavior and weight gain in larvae (Slankster, 2020).

    Indeed, food odors can be powerful appetitive cues. A previous study showed that larvae engage in appetitive cue-driven feeding behavior and that this behavior required NPF signaling within dopaminergic neurons in higher-order olfactory processing centers (Wang, 2013). The current studies show that manipulating GABABR signaling in first-order OSNs impact appetitive cue-driven feeding behavior in larvae. While it remains to be seen whether parallel regulations during different stages of olfactory information processing impact feeding behavior, further studies are needed to reveal the mechanistic relationship between GABABR/InR signaling in OSNs, feeding behavior, and changes in body-weight (Slankster, 2020).

    Based on the evidence so far, a motivating model is proposed for future investigations (see Model for OSN modulation). In this model, InR expressed on the terminals of larval OSNs act as sensors for the internal state of the animal. Its concerted activity with GABABR impacts OSN function either at the level of odor reception by affecting the expression of Orco or at the level of olfactory signal transduction by affecting the expression of Rut or at the level of neurotransmission by affecting the expression of Syt1 and sNPFR1. It is acknowledged that more exhaustive gene expression analyses are required to identify other molecular players downstream of InR and GABABR. It would also be valuable to investigate the relationship between InR expression levels on the terminals of individual OSNs and the sensitivity of individual OSNs to modulation by the animal's starved state (Slankster, 2020).

    A valid concern in this study is that an innate attraction of larvae toward an odorant does not necessarily equate to food-search behavior. However, it is argued that attractiveness toward an odor source is a reliable measure of food-search behavior because an animal's ability to efficiently smell and move toward an odor source necessarily predicates most forms of such behavior. Another possibility to be considered is that changes in OSN sensitivity, food-search and/or feeding behaviors are independently regulated. For instance, it has been noted that starvation-induced hyperactivity in adult Drosophila was independently regulated from food consumption behavior in the flies. Blocking octopamine signaling in a small group of octopaminergic neurons located in the subesophageal zone (SEZ) of the fly brain neurons eliminated starvation induced hyperactivity but not the increase in food consumption. While such a possibility cannot be ruled out, the evidence presented in this study support the argument that starvation induced-changes in OSN function is related to the observed changes in food search and feeding behaviors. It is acknowledged that other studies have opted to keep larvae on sucrose with the intention of starving them of amino acids and other nutrients. So, the non-starved conditions in the present study actually represents partial starvation of macronutrients other than sugar. This was done to control the nutrient intake in the non-starved state with the intention of measuring the impact of individual macronutrients on OSN modulation in future studies. Finally, while this study tested the hypothesis that increases in body-weight of mutant genotypes are due to altered food consumption, alternate hypotheses that body-weight increases may be due to altered metabolism or increased fat accumulation haven not been tested(Slankster, 2020).

    Overall, this study conducted in a simple, tractable, and highly conserved model system builds upon the prevailing model of starved-state dependent modulation of OSN function. It highlights and offers unique opportunities that are now possible to address the inadequate understanding of OSN modulation mechanisms at the resolution of single neurons, which in turn would lead to a better understand how flexibility and the ability to adapt to a particular internal state are built into the sensory circuit (Slankster, 2020).

    Glomerulus-selective regulation of a critical period for interneuron plasticity in the Drosophila antennal lobe
    Chodankar, A., Sadanandappa, M. K., VijayRaghavan, K. and Ramaswami, M. (2020). J Neurosci. PubMed ID: 32532889

    Several features of the adult nervous systems develop in a "critical period," (CP) during which high levels of plasticity allow neural circuits to be tuned for optimal performance. Through an analysis of long-term olfactory habituation (LTH) in female Drosophila, this study provides new insight into mechanisms by which CPs are regulated in vivo LTH manifests as a persistently reduced behavioural response to an odorant encountered for four continuous days and occurs together with the growth of specific, odorant-responsive glomeruli in the antennal lobe. The CP for behavioral and structural plasticity induced by ethyl butyrate (EB) or carbon dioxide (CO(2)) closes within 48 hours after eclosion. The elaboration of excitatory projection neuron (PN) processes likely contribute to glomerular volume increases: both occur together and similarly require cAMP signalling in the antennal lobe inhibitory local interneurons (iLNs). Further, the CP for structural plasticity could be extended beyond 48 hours if EB- or CO(2)-responsive olfactory sensory neurons (OSNs) are silenced after eclosion; thus, OSN activity is required for closing the CP. Strikingly, silencing of glomerulus-selective OSNs extends the CP for structural plasticity only in respective target glomeruli. This indicates existence of a local, short-range mechanism for regulating CP closure (Chodankar, 2020).

    Local synaptic inputs support opposing, network-specific odor representations in a widely projecting modulatory neuron
    Zhang, X., Coates, K., Dacks, A., Gunay, C., Lauritzen, J. S., Li, F., Calle-Schuler, S. A., Bock, D. and Gaudry, Q. (2019). Elife 8. PubMed ID: 31264962

    Serotonin plays different roles across networks within the same sensory modality. Previous whole-cell electrophysiology in Drosophila has shown that serotonergic neurons innervating the first olfactory relay are inhibited by odorants. This study shows that network-spanning serotonergic neurons segregate information about stimulus features, odor intensity and identity, by using opposing coding schemes in different olfactory neuropil. A pair of serotonergic neurons (the CSDns) innervate the antennal lobe and lateral horn, which are first and second order neuropils. CSDn processes in the antennal lobe are inhibited by odors in an identity independent manner. In the lateral horn, CSDn processes are excited in an odor identity dependent manner. Using functional imaging, modeling, and EM reconstruction, it was demonstrated that antennal lobe derived inhibition arises from local GABAergic inputs and acts as a means of gain control on branch-specific inputs that the CSDns receive within the lateral horn (Zhang, 2019).

    Temporally specific engagement of distinct neuronal circuits regulating olfactory habituation in Drosophila
    Semelidou, O., Acevedo, S. F. and Skoulakis, E. M. (2018). Elife 7 pii: e39569. PubMed ID: 30576281

    Habituation is the process that enables salience filtering, precipitating perceptual changes that alter the value of environmental stimuli. To discern the neuronal circuits underlying habituation to brief inconsequential stimuli, a novel olfactory habituation paradigm was developed, identifying two distinct phases of the response that engage distinct neuronal circuits. Responsiveness to the continuous odor stimulus is maintained initially, a phase termed habituation latency; it requires Rutabaga Adenylyl-Cyclase-depended neurotransmission from GABAergic Antennal Lobe Interneurons and activation of excitatory Projection Neurons (PNs) and the Mushroom Bodies. In contrast, habituation depends on the inhibitory PNs of the middle Antenno-Cerebral Track, requires inner Antenno-Cerebral Track PN activation and defines a temporally distinct phase. Collectively, these data support the involvement of Lateral Horn excitatory and inhibitory stimulation in habituation. These results provide essential cellular substrates for future analyses of the molecular mechanisms that govern the duration and transition between these distinct temporal habituation phases (Semelidou, 2018).

    Drosophila is a premier system for molecular approaches to understand habituation because of its advanced molecular and classical genetics. In fact, it is a well-established model for habituation of various sensory modalities such as taste, vision, mechanosensory and escape responses, reflecting that habituation is apparent in most, if not all, circuits and modalities of the nervous system. However, in most of these paradigms, the circuits engaged to process the stimulus and establish the experimentally measured attenuated behavioral response are unclear. Importantly, the advanced understanding of the Drosophila olfactory circuitry and stimulus processing facilitates exploration of the mechanisms mediating decreased stimulus responsiveness and habituation to inconsequential odors. Such a recently described paradigm of olfactory habituation in Drosophila required 30 min of odor exposure and was mediated entirely by antennal lobe neurons. In contrast, habituation to repetitive 30 s odor pulses required functional Mushroom Bodies, neurons on the central brain also implicated in associative learning and memory in flies (Semelidou, 2018).

    To resolve this paradox, this study focused on the early behavioral dynamics of habituation upon continuous odor stimulation. To that end, a novel habituation paradigm was developed and characterized to rather brief continuous odors. The behavioral responses define two distinct phases, an initial phase termed habituation latency, when stimulus responsiveness is maintained, which is followed by a significant response decrement reflecting habituation. Analogous response dynamics have been reported for footshock habituation. In addition, whether these phases engage and are mediated by distinct neuronal circuits was. The results highlight the stimulus duration-dependent activation of specific neuronal subsets and their distinct roles in securing timely habituation latency and habituation induction (Semelidou, 2018).

    This study describes a novel olfactory habituation paradigm to brief odor stimuli and operationally defines two distinct phases in the response dynamics. The initial period of ~120 s is termed habituation latency and is characterized by maintenance of responsiveness to the odor. This is followed by manifestation of the habituated response, characterized behaviorally by attenuated osmotaxis. Focusing on the behavioral dynamics early in the process complements previous work olfactory habituation to continuous odor stimulation in Drosophila. A number of criteria differentiate these two paradigms from other types of habituation to olfactory stimuli as discussed below (Semelidou, 2018).

    Drosophila habituate equally well to continuous or pulsed olfactory stimuli. This likely reflects the nature of olfactory stimuli, which typically are continuous rather than pulsed. On the other hand, habituation of the startle response to ethanol vapor may specifically require short (30 s) pulses due to its sedative properties and this may also be reflected by the rather long 6 min ITIs compared to the 15 s to 2.5-min intervals used herein for OCT. Short odor pulses are also required for the odor-mediated jump and flight response habituation, suggesting that pulsing may be necessary to evoke the startle response per se (Semelidou, 2018).

    An important property shared with all habituation paradigms in Drosophila and other systems is spontaneous recovery of the response. This is another differentiating parameter among habituation paradigms in Drosophila. For the olfactory habituation paradigms, whereas 6 min suffice for spontaneous recovery after 4 and 30 min continuous odor exposure, 15-30 to surprisingly 60 min are required for recovery in the olfactory startle paradigms. Habituation to mechanosensory stimuli typically also requires shorter spontaneous recovery times, with habituation of the giant fiber-mediated jump-and-flight response requiring a mere 2 min and electric footshock habituation 6 min. Interestingly, other non-mechanosensory habituation paradigms require long spontaneous recovery periods with 30 min for habituation of the proboscis extension reflex (PER), and surprisingly, 2 hr for habituation of odor-induced leg response. It is posited that these differences reflect the engagement of distinct neuronal circuits mediating habituation to these diverse stimuli and the properties and connections of the neuronal types that comprise them (Semelidou, 2018).

    Overall, these data suggest that latency and habituation to brief odor exposure involve modulation of lateral horn (LH) output, a neuropil innately encoding response valence to odor stimuli. It is propose dthat habituation latency involves processes that are not permissive to, or actively prevent stimulus devaluation. Latency duration depends on stimulus strength and is consistent with the notion that it is adaptive not to devalue strong, hence potentially important stimuli, expediently. In fact, it is posited that habituation latency serves to facilitate associations with concurrent stimuli, a requirement for associative learning. Shortened latency leading to premature habituation is predicted to compromise associative learning (Semelidou, 2018).

    Importantly, maintaining responsiveness early upon odorant exposure requires activity of GABAergic inhibitory neurons, which are essential for lateral inhibition of antennal lobe glomeruli. LN activation appears to prevent saturation by strong continuous odors and hence reduce PN activity. Therefore, shortening habituation latency by blocking GABAergic neurotransmission in the antennal lobe may effectively reduce stimulus intensity, expediting habituation as suggested by the dilute odor experiments. This interpretation is further supported by the decreased habituation latency upon silencing the iACT PNs conveying olfactory signals to the MBs and the LH, but not by the mACT neurons innervating only the LH. Since iACT PNs are mainly excitatory, it appears that response maintenance requires excitatory signaling to the LH and the MBs (Semelidou, 2018).

    All MB neuronal types except the γ, are essential for habituation latency. This suggests that at least part of the excitatory signal conveyed by the iACT PNs impinges upon the αβ and α' β' MB neurons, which is consistent with their role in associative learning and the proposal that habituation latency facilitates it. Neurotransmission from the MBs to LH neurons mediating aversive responses likely engages MB output neurons (MBONs), to maintain the valence and intensity of the odor and sustain aversion. Distinct MBONs are known to drive both attraction and aversion to odors and their potentially differential involvement in habituation is currently under investigation (Semelidou, 2018).

    Dishabituation results in stimulus value recovery and apparently resets habituation latency. Clearly it requires neurotransmission via the GH146-marked neurons and MBs because silencing these neurons disables dishabituation, consistent with their role in response maintenance. These results lead to the hypothesis that dishabituating stimuli might converge on the MBs and/or iACT, possibly stimulating excitatory neurotransmission to the LH, to reinstate stimulus aversion. This hypothesis is currently under investigation as well (Semelidou, 2018).

    In contrast, habituation requires prolonged or repeated exposure to the odorant and functional iACT and mACT PNs converging on the LH. Interestingly, the mainly GABAergic mACT PNs receive input both from the olfactory sensory neurons and the excitatory iACT PNs. Their depolarization also activates the excitatory iACT neurons via direct chemical synapses. This apparent feedback loop may be required for mACT activation after prolonged exposure to aversive odors, since these neurons were reported to respond mainly to attractive stimuli. It is proposed that prolonged aversive odor exposure enhances iACT activation, which in turn leads to habituation, while shorter exposure does not activate the iACT neurons, reflected by their dispensability for habituation latency. Importantly, the mACT innervates the LH downstream of the iACT PNs, providing feedforward inhibition. These characteristics likely underlie the necessary and sufficient role of mACT PNs in habituation upon 4-min odor stimulation. Collectively, these results are consistent with the proposal that mACT activation inhibits the innate LH-mediated avoidance response to the aversive odorant, establishing habituation (see A model of the neuronal subsets underlying (A) Habituation Latency and (B) Habituation, after exposure to aversive stimuli.). However, full mACT activation appears to also require iACT neurotransmission, which if abrogated eliminates habituation but is insufficient to establish it on its own (Semelidou, 2018).

    Because the MZ699 Gal4 driver also marks ventrolateral protocerebrum (vlpr) neurons it is possible that they also play a role in habituation. In fact, vlpr neurons function in aversive odor responses, are activated by excitatory iACT PNs, inhibited by the inhibitory PNs, and are afferent to the LH. Thus, they could act in parallel or synergistically to mACT PNs to establish the habituated response. As no specific vlpr driver is available, it is impossible at the moment to address this possibility directly. Briefly then, the current collective results strongly suggest a novel role for the inhibitory PNs innervating the LH, and possibly vlpr neurons, in inhibition of the innate response and habituation. The kinetics of inhibitory projection neuron activation and their output on downstream neurons could serve as a measure of the duration of odor exposure. Upon prolonged exposure, these neurons mediate inhibition of odor avoidance, thus devaluing the stimulus (Semelidou, 2018).

    Analysis of the neuronal subsets underlying habituation has focused on aversive odors. However, considering the neuronal clusters involved in the process, it would be relatively safe to assume that the results extend to attractive odor habituation as well. It is possible that the neuronal circuitry comprised of PNs, the LH and MBs may be mediating habituation independently of odor valence. However, specific neuronal clusters may differ in odor valance-dependent activation or inhibition of other circuit components with opposing effects on the behavioral readout. For example, inhibitory PNs (iPNs) mediate attraction by releasing GABA in the LH to inhibit avoidance. If inhibited themselves, the resultant attenuated attraction will likely drive a behavioral output of habituation to an attractive odor (Semelidou, 2018).

    In accord with this notion, attractive and aversive odors are represented in different AL glomerular clustersand this valence-dependent organization is preserved into higher brain centers. In fact, the posterior-dorsal LH responds to attractive and its ventral complement to aversive odors, while third order neurons convey information from ventral LH to the vlpr and from the dorsal LH to the superior medial protocerebrum. This organization potentially reflects differential recruitment of these neuronal clusters in habituation to aversive and attractive odors. The circuits involved in habituation to attractive odors and their specific contribution to the process will be the focus of future work (Semelidou, 2018).

    Although behaviorally there is significant osmotactic attenuation after both 4 and 30 min aversive odor exposure, the experiments suggest that these represent distinct types of olfactory habituation. Habituation after 4 min of odor exposure does not require the MBs, but rather the projection neurons innervating the LH. Habituation after 30 min of exposure is also independent of MB function, but appears to be entirely mediated by iLNs and reside within the AL. This clear difference suggests that the specific potentiation of inhibitory synapses shown to underlie habituation after 30 min of exposure is not necessary for habituation to the brief 4-min exposure. Additionally, while Rut is required within the iLNs during the latency period upon brief odor exposure, it is surprisingly required within the same neurons for habituation to long odor exposure. Therefore, Rut-driven activity within the iLNs yields opposing time-dependent behavioral outputs in accord with the abovementioned notion that the same circuit components may drive opposing outputs (Semelidou, 2018).

    Furthermore, the fact that mechanosensory stimuli are not effective dishabituators after 30 min of odor exposure as they are after 4 min, augments the conclusion these are different types of olfactory habituation and suggests that distinct dishabituators likely recruit different neuronal subsets to modulate the habituated response. Such neuronal circuits and the effect of different dishabituators in response recovery are currently under investigatio (Semelidou, 2018).

    Altogether, the results indicate different mechanisms for 4 min and 30 min habituation to aversive odors with the former mediated by the interaction between iPNs, ePNs and their targets in the LH, while the latter is based on the inhibition of ePNs by iLNs at the AL level. However, it is possible that the potentiated PN inhibition would decrease their output to the LH to drive reduced avoidance. This argues that the LH could be involved in the behavioral output indicating habituation after 30 min of OCT exposure as well. An AL-mediated reduction in the perceived intensity or valence of a chronically present odor probably serves an adaptive evolutionary role distinct from short exposure to the same stimulus. In fact, filtering away the chronic odor at the antenna, the first olfactory synaptic station, might facilitate evaluation of additional odors at higher order neurons such as the MBs or the LH (Semelidou, 2018).

    Significantly, this interpretation is congruent with timescale habituation in mice, where short-timescale odor habituation is mGluR-dependent and mediated by the anterior piriform cortex while long-timescale habituation requires NMDAR and is mediated by the olfactory bulb. In addition, studies in mice, rats and primates have shown that habituation of the higher order neurons is faster and more prominent than in olfactory bulb neurons. Therefore, temporal and spatial principles for olfactory habituation appear broadly conserved between insects and mammals, despite their evolutionary distance (Semelidou, 2018).

    Neural Circuitry that Evokes Escape Behavior upon Activation of Nociceptive Sensory Neurons in Drosophila Larvae
    Yoshino, J., Morikawa, R. K., Hasegawa, E. and Emoto, K. (2017). Curr Biol 27(16): 2499-2504 e2493. PubMed ID: 28803873 

    Noxious stimuli trigger a stereotyped escape response in animals. In Drosophila larvae, class IV dendrite arborization (C4 da) sensory neurons in the peripheral nervous system are responsible for perception of multiple nociceptive modalities, including noxious heat and harsh mechanical stimulation, through distinct receptors. Silencing or ablation of C4 da neurons largely eliminates larval responses to noxious stimuli, whereas optogenetic activation of C4 da neurons is sufficient to provoke corkscrew-like rolling behavior similar to what is observed when larvae receive noxious stimuli, such as high temperature or harsh mechanical stimulation. How C4 da activation triggers the escape behavior in the circuit level is still incompletely understood. This study identified segmentally arrayed local interneurons (medial clusters of C4 da second-order interneurons [mCSIs]) in the ventral nerve cord that are necessary and sufficient to trigger rolling behavior. GFP reconstitution across synaptic partners (GRASP) analysis indicates that C4 da axons form synapses with mCSI dendrites. Optogenetic activation of mCSIs induces the rolling behavior, whereas silencing mCSIs reduces the probability of rolling behavior upon C4 da activation. Further anatomical and functional studies suggest that the C4 da-mCSI nociceptive circuit evokes rolling behavior at least in part through segmental nerve a (SNa) motor neurons. These findings thus uncover a local circuit that promotes escape behavior upon noxious stimuli in Drosophila larvae and provide mechanistic insights into how noxious stimuli are transduced into the stereotyped escape behavior in the circuit level (Yoshino, 2017).

    Topological and modality-specific representation of somatosensory information in the fly brain
    Tsubouchi, A., Yano, T., Yokoyama, T. K., Murtin, C., Otsuna, H. and Ito, K. (2017). Science 358(6363): 615-623. PubMed ID: 29097543

    Insects and mammals share similarities of neural organization underlying the perception of odors, taste, vision, sound, and gravity. This study observed that insect somatosensation also corresponds to that of mammals. In Drosophila, the projections of all the somatosensory neuron types to the insect's equivalent of the spinal cord segregated into modality-specific layers comparable to those in mammals. Some sensory neurons innervate the ventral brain directly to form modality-specific and topological somatosensory maps. Ascending interneurons with dendrites in matching layers of the nerve cord send axons that converge to respective brain regions. Pathways arising from leg somatosensory neurons encode distinct qualities of leg movement information and play different roles in ground detection. Establishment of the ground pattern and genetic tools for neuronal manipulation should provide the basis for elucidating the mechanisms underlying somatosensation (Tsubouchi, 2017).

    Only three distinct types of sensory information are transmitted directly to the brain by primary neurons [leg gustatory sensilla (gs), chordotonal organs (co), and wing and haltere campaniform sensilla (cs)]. Such connection has also been reported in other insects, suggesting that this might be a general feature across insecta. Whereas only a small portion of leg co neurons project directly to the brain, most wing and haltere cs neurons innervate the brain; these cs neurons are known to detect various aspects of wing-beat force during flight to provide feedback control. Direct projections to the brain would be important for these neurons to enable fast transmission of information about rapidly changing sensory parameters during flight (Tsubouchi, 2017).

    It was found that ground detection for wind-induced suppression of locomotion (WISL), which would require slower temporal resolution than flight control, is mediated by both direct and indirect pathways. Primary neurons and secondary interneurons of the same sensory modality tend to converge in specific subregions of the brain, forming modality-specific somatosensory representation. In spite of the similar axon trajectory in the brain, these neurons convey information about leg movement in different ways (Tsubouchi, 2017).

    Interneurons associated with the leg co and es terminate in neighboring but different regions of the lateral brain, yet some of them have shared roles in WISL control. Because their signals are transmitted to distinct parts of the brain, yet-unidentified higher-order neurons in the brain should converge those signals to the motor control circuitry (Tsubouchi, 2017).

    In this respect, it is important to note that most ascending secondary interneurons identified in this study have presynaptic output sites, not only in the brain but also in the VNC. Local circuitry in the leg neuropil is important for controlling leg movement. Those local neurons are likely candidates that receive output from the ascending interneurons, because axon terminals of sensory neurons hardly have postsynaptic sites. Similar local output has also been found in other sensory modalities; many olfactory and visual projection interneurons have collateral output synapses in the antennal lobe and optic lobes (Tsubouchi, 2017).

    There are three pairs of leg neuropils. Among them, the foreleg neuropil has specialized arborization of the gs neurons that exist only in the foreleg. Other than this, no substantial differences of arborization patterns were found between the fore-, mid-, and hindleg neuropils (Tsubouchi, 2017).

    The present results provide data for a systematic comparison of the insect somatosensory system with its mammalian counterparts. Insects and mammals share similarities of neural organization underlying the perception of odors, taste, vision, sound, and gravity, and the current data also reveal marked similarity for the mechanosensory system. In insects, some primary neurons project directly to distinct parts of the ventral and lateral brain, whereas others terminate within the VNC. Likewise, in mammals, some neurons project directly to the ventral brain at the medulla oblongata, whereas others terminate within the spinal cord. Modality-specific pathways tend to converge in different subregions of the medulla, as well as in the thalamus of the mammalian brain. Similarly, direct and indirect pathways tend to converge in common subregions of the insect brain, and neurons conveying information about different somatosensory modalities tend to terminate in different subregions. As in mammals, these subregions often lie adjacent to each other in certain parts of the brain; for example, the entire terminal arborizations of the leg co and es secondary interneurons are confined in a 40-μm-wide, 150-μm-tall cylindrical volume in the lateral brain (Tsubouchi, 2017).

    Somatosensory signals are sent predominantly to the ipsilateral brain side in insects and contralateral in mammals. Considering that descending neurons tend to project ipsilaterally in insects but contralaterally in mammals, however, somatosensory signals and motor control computation are processed primarily in the same side of the brain in both cases (Tsubouchi, 2017).

    Layers of sensory axon terminals in the insect VNC and mammalian spinal cord are also organized in a similar order. Insect multidendritic neurons and mammalian free nerve endings share various characteristics in common: Their dendrites both have free endings without forming particular sense organs to detect pain, temperature, and other submodalities. The md neurons project to the most ventral layer of the VNC, whereas free nerve endings innervate the most dorsal layer of the spinal cord. Axons from the insect external sensilla and mammalian hair receptors, both of which detect haptic contact to the tips of the bristles and hairs, terminate in the second-ventral and second-dorsal layers, respectively. Insect chordotonal organ and mammalian muscle spindle, as well as insect campaniform sensilla and mammalian Golgi tendon organ, also show similarity with respect to their functions in motor control. These receptor systems supply afferents to the most dorsal and most ventral layers in insects and mammals, respectively. A fly's stretch receptors and mammalian Merkel cell neurites-as well as Meissner, Ruffini, and Pacinian corpuscles-terminate in the third-ventral and third-dorsal layer, respectively. Although correspondence between them is less obvious, they similarly detect deformation of the exoskeleton and skin. Thus, functionally comparable somatosensory terminals are layered in reverse order between the two systems. Considering that the dorsoventral axis of the mammalian body is developmentally upside down compared with the insect one, the corresponding order of sensory arrangements is actually conserved exactly between the two systems (Tsubouchi, 2017).

    Do corresponding somatosensory cell types express common genes? Modality-dependent molecular specialization is not apparent even within insects or mammals, because the same genes are often expressed in multiple cell types and only a few genes share expression in the corresponding cell types across taxa. This might be a rather general feature; receptor molecules as well as developmental origins of the sensory organs are not identical between insects and mammals also in olfactory and auditory systems, yet sensory centers in the brain share architectural similarities (Tsubouchi, 2017).

    With this somatosensory analysis, transphyletic correspondence of neuronal circuitry has been found in all of the sensory modalities. Corresponding organization has been suggested also for associative centers and motor systems. The fact that essentially all important components of the brain system share conserved features across the two evolutionary clades, which have been separated since at least the end of the Ediacaran period more than 550 million years ago, would suggest that basic development programs for the orderly and secrete segregation of those circuits may have evolved before deuterostome-protostome or deuterostomia-ecdysozoa divergence (Tsubouchi, 2017).

    Identified serotonergic modulatory neurons have heterogeneous synaptic connectivity within the olfactory system of Drosophila
    Coates, K. E., Majot, A. T., Zhang, X., Michael, C. T., Spitzer, S. L., Gaudry, Q. and Dacks, A. M. (2017). J Neurosci 37(31):7318-7331. PubMed ID: 28659283

    Modulatory neurons project widely throughout the brain, dynamically altering network processing based on an animal's physiological state. The connectivity of individual modulatory neurons can be complex, as they often receive input from a variety of sources and are diverse in their physiology, structure, and gene expression profiles. To establish basic principles about the connectivity of individual modulatory neurons, a pair of identified neurons was examined, the 'contralaterally projecting, serotonin-immunoreactive deutocerebral neurons' (CSDns), within the olfactory system of Drosophila. Specifically, the neuronal classes were determined providing synaptic input to the CSDns within the antennal lobe (AL), an olfactory network targeted by the CSDns, along with the degree to which CSDn active zones are uniformly distributed across the AL. Using anatomical techniques, the CSDns were found to receive glomerulus-specific input from olfactory receptor neurons (ORNs) and projection neurons (PNs), and network-wide input from local interneurons (LNs). Furthermore, the number of CSDn active zones was quantified in each glomerulus; CSDn output was fount to be not uniform, but rather heterogeneous across glomeruli and stereotyped from animal to animal. Finally, it was demonstrated that the CSDns synapse broadly onto LNs and PNs throughout the AL, but do not synapse upon ORNs. These results demonstrate that modulatory neurons do not necessarily provide purely top-down input, but rather receive neuron class-specific input from the networks that they target, and that even a two cell modulatory network has highly heterogeneous, yet stereotyped pattern of connectivity (Coates, 2017).

    Serotonergic modulation differentially targets distinct network elements within the antennal lobe of Drosophila melanogaster
    Sizemore, T. R. and Dacks, A. M. (2016). Sci Rep 6: 37119. PubMed ID: 27845422

    Neuromodulation confers flexibility to anatomically-restricted neural networks so that animals are able to properly respond to complex internal and external demands. However, determining the mechanisms underlying neuromodulation is challenging without knowledge of the functional class and spatial organization of neurons that express individual neuromodulatory receptors. This study describes the number and functional identities of neurons in the antennal lobe of Drosophila melanogaster that express each of the receptors for one such neuromodulator, serotonin (5-HT). Although 5-HT enhances odor-evoked responses of antennal lobe projection neurons (PNs) and local interneurons (LNs), the receptor basis for this enhancement is unknown. Endogenous reporters of transcription and translation for each of the five 5-HT receptors (5-HTRs) were used to identify neurons, based on cell class and transmitter content, that express each receptor. Specific receptor types are expressed by distinct combinations of functional neuronal classes. For instance, the excitatory PNs express the excitatory 5-HTRs (5-HT2 type and 5-HT7), the 5-HT1 type receptors are generally inhibitory, and distinct classes of LNs each express different 5-HTRs. This study therefore provides a detailed atlas of 5-HT receptor expression within a well-characterized neural network, and enables future dissection of the role of serotonergic modulation of olfactory processing (Sizemore, 2016).

    Neuromodulators often act through diverse sets of receptors expressed by distinct network elements and in this manner, differentially affect specific features of network dynamics. Knowing which network elements express each receptor for a given neuromodulator provides a framework for making predictions about the mechanistic basis by which a neuromodulator alters network activity. This study provides an 'atlas' of 5-HTR expression within the AL of Drosophila, thus revealing network elements subject to the different effects of serotonergic modulation. In summary, different receptors are predominantly expressed by distinct neuronal populations. For example, the 5-HT2B is expressed by ORNs, while the 5-HT2A and 7 are expressed by cholinergic PNs. Additionally, each receptor was found to be expressed by diverse populations of LNs, with the exception the 5-HT1B. For instance, 5-HT1A is expressed by GABAergic and peptidergic (TKK and MIP) LNs, while 5-HT2A and 2B are not expressed by peptidergic LNs. However, the vPNs are the exception to the general observation that distinct neuronal classes differ from each other in the 5-HTRs and the implications of this are discussed below. Together, these results suggest that within the AL, 5-HT differentially modulates distinct populations of neurons that undertake specific tasks in olfactory processing (Sizemore, 2016).

    A recurring theme of neuromodulation is that the expression of distinct receptor types by specific neural populations allows a single modulatory neuron to differentially affect individual coding features. For instance, GABAergic medium spiny neurons (MSNs) in the nucleus accumbens express either the D1 or D2 dopamine receptor allowing dopamine to have opposite effects on different MSNs via coupling to different Galpha subunits (reviewed in56). MSNs that differ in dopamine receptor expression also differ in their synaptic connectivity. Dopamine activates D1-expressing MSNs that directly inhibit dopaminergic neurons in the ventral tegmental area (VTA), and inhibits D2-expressing MSNs that inhibit GABAergic VTA interneurons thus inducing suppression of dopamine release. In this manner, a single neuromodulator differentially affects two populations of principal neurons via different receptors to generate coordinated network output. This principle also holds true for the effects of 5-HT within the olfactory bulb. For instance, 5-HT enhances presynaptic inhibition of olfactory sensory neurons by 5-HT2C-expressing juxtaglomerular cells57, while increasing excitatory drive to mitral/tufted cells and periglomerular cells via 5-HT2A-expressing external tufted cells. Similarly, distinct classes of AL neurons were observed to differ in their expression of 5-HTRs. For instance, ePNs express the 5-HT2A, 5-HT2B and 5-HT7 receptors, while peptidergic LNs predominantly express the 5-HT1A receptor. This suggests that the cumulative effect of 5-HT results from a combination of differential modulation across neuronal populations within the AL. Interestingly, although it was found that 5-HT2B is expressed by ORNs, previous reports found that 5-HT does not directly affect Drosophila ORNs. In this study, ORNs were stimulated using antennal nerve shock in which the antennae were removed in order to place the antennal nerve within a suction electrode. Thus, if 5-HT2B is localized to the ORN cell body, removal of the antennae would eliminate any effect of 5-HT on ORNs. In several insects, 5-HT within the antennal haemolymph modulates ORN odor-evoked responses. Therefore, it is plausible ORNs are modulated by a source of 5-HT other than the CSD neurons within the AL. Serotonergic modulation of LN activity has widespread, and sometimes odor specific, effects on olfactory processing. LNs allow ongoing activity across the AL to shape the activity of individual AL neurons, often in a glomerulus specific manner creating non-reciprocal relationships. It is fairly clear that 5-HT directly modulates LNs, although 5-HT almost certainly affects synaptic input to LNs. Serotonin modulates isolated Manduca sexta LNs in vitro and, consistent with the current results, a small population of GABAergic LNs in the AL of Manduca also express the 5-HT1A receptor. Furthermore, 5-HT has odor-dependent effects on PN odor-evoked activity, suggesting that odor specific sets of lateral interactions are modulated by 5-HT. Different populations of LNs were found to express different sets of 5-HT receptors, however LNs were categorized based on transmitter type, so it is possible that these categories could be even further sub-divided based on morphological type, synaptic connectivity or biophysical characteristics. Regardless, the results suggest that 5-HT modulates lateral interactions within the AL by selectively affecting LN populations that undertake different tasks. For instance, the TKKergic LNs that express the 5-HT1A receptor provide a form of gain control by presynaptically inhibiting ORNs32. The results suggest that 5-HT may affect TKK mediated gain control differently relative to processes undertaken by other LN populations. Furthermore, the expression of the TKK receptor by ORNs is regulated by hunger, allowing the effects of TKK to vary with behavioral state. It would be interesting to determine if the expression of 5-HTRs themselves also vary with behavioral state as a means of regulating neuromodulation within the olfactory system (Sizemore, 2016).

    Although it was primarily found that individual populations of AL neurons chiefly expressed a single or perhaps two 5-HTR types, the vPNs appear to be an exception. As a population, the vPNs express all of the 5-HTRs and the vPNs that express each 5-HTR did not appear to differ in terms of the proportion of those neurons that were GABAergic or cholinergic (roughly 3:2). Unfortunately, the approach does not allow determination of the degree to which individual vPNs co-express 5-HTRs. However, it is estimated that there are ~51 vPNs and even if this is an underestimate, there is likely some overlap of receptor types as a large number of vPNs expressed the 5-HT1A, 1B, 2B and 7 receptors. It is possible that a single vPN expresses one 5-HTR in the AL and a different 5-HTR in the lateral horn. However, the current approach only allows identification of which neurons express a given 5-HTR, not where that receptor is expressed. The CSD neurons ramify throughout both ALs and both lateral horns, thus vPNs could have differential spatial expression of individual 5-HTRs. Individual neurons expressing multiple 5-HTRs has been demonstrated in several neural networks. For instance, pyramidal cells in prefrontal cortex express both the 5-HT1A and 5-HT2A7. This allows 5-HT to have opposing effects that differ in their time course in the same cell. In terms of the vPNs, the results suggest that the current understanding of the diversity of this neuron class is limited. The expression of receptors for different signaling molecules could potentially be a significant component to vPN diversity (Sizemore, 2016).

    Neuromodulators are often released by a small number of neurons within a network, yet they can have extremely diverse effects depending upon patterns of receptor expression. For the most part, individual populations of AL neurons differed in the receptor types that they expressed. This suggests that 5-HT differentially acts on classes of neurons that undertake distinct tasks in olfactory processing. In the case of the vPNs, this differential modulation may be fairly complex due to the diversity within this neuronal class. The goal of this study was to establish a functional atlas of 5-HTR expression in the AL of Drosophila. This dataset therefore provides a mechanistic framework for the effects of 5-HT on olfactory processing in this network (Sizemore, 2016).

    Glutamate is an inhibitory neurotransmitter in the Drosophila olfactory system
    Liu, W. W. and Wilson, R. I. (2013). Proc Natl Acad Sci U S A 110(25): 10294-10299. PubMed ID: 23729809

    Glutamatergic neurons are abundant in the Drosophila central nervous system, but their physiological effects are largely unknown. This study investigated the effects of glutamate in the Drosophila antennal lobe, the first relay in the olfactory system and a model circuit for understanding olfactory processing. In the antennal lobe, one-third of local neurons are glutamatergic. Using in vivo whole-cell patch clamp recordings, this study found that many glutamatergic local neurons are broadly tuned to odors. Iontophoresed glutamate hyperpolarizes all major cell types in the antennal lobe, and this effect is blocked by picrotoxin or by transgenic RNAi-mediated knockdown of the GluClα gene, which encodes a glutamate-gated chloride channel. Moreover, antennal lobe neurons are inhibited by selective activation of glutamatergic local neurons using a nonnative genetically encoded cation channel. Finally, transgenic knockdown of GluClα in principal neurons disinhibits the odor responses of these neurons. Thus, glutamate acts as an inhibitory neurotransmitter in the antennal lobe, broadly similar to the role of GABA in this circuit. However, because glutamate release is concentrated between glomeruli, whereas GABA release is concentrated within glomeruli, these neurotransmitters may act on different spatial and temporal scales. Thus, the existence of two parallel inhibitory transmitter systems may increase the range and flexibility of synaptic inhibition (Liu, 2013).

    Although glutamatergic neurons are abundant in the Drosophila brain, the role of glutamate as a neurotransmitter in the Drosophila CNS has received little study. In the antennal lobe, where approximately one-third of LNs are glutamatergic, the physiological effects of glutamate have never been characterized. This study shows that glutamate is an inhibitory transmitter that shapes the responses of PNs to olfactory stimuli (Liu, 2013).

    In the past, glutamate has been proposed to mediate lateral excitation between olfactory glomeruli. The results of this study demonstrate that the main effect of glutamate is inhibition, not excitation. The possibility cannot be ruled out that glutamate has small excitatory effects, but no evidence was found of excitation even when GluClα was knocked down genetically or inhibited pharmacologically. It is noted that there is in fact lateral excitation in the antennal lobe, which exists in parallel with lateral inhibition. However, lateral excitation is mediated not by glutamate, but by electrical coupling between LNs and PNs (Liu, 2013).

    All of the effects of glutamate on PNs were eliminated by knocking down GluClα. The dominant role for GluClα is notable, given how many other glutamate receptors are in the genome. The results are particularly surprising in light of two recent studies that have reported behavioral effects of knocking down an NMDA receptor subunit (NR1) in PNs. Further experiments will be needed to clarify the role of NR1 (Liu, 2013).

    There is a precedent for the idea that glutamate can be an inhibitory neurotransmitter in the Drosophila brain. Specifically, several studies have reported that bath-applied glutamate inhibits the large ventrolateral neurons of the Drosophila circadian clock circuit. Collectively, these studies suggest roles for both ionotropic and metabotropic glutamate receptors in glutamatergic inhibition. Regardless of which glutamate receptors are involved, these studies are consistent with the conclusion that glutamate is an important mediator of synaptic inhibition (Liu, 2013).

    The idea that glutamate can be inhibitory has important implications for neural coding. One particularly interesting case is the motion vision circuit of the Drosophila optic lobe. Two neuron types, L1 and L2, both receive strong synaptic inputs from photoreceptors, and they respond equally to contrast increments (“on”) and decrements (“off”). However, based on conditional silencing experiments, L1 is thought to provide input to an on pathway, and L2 to an off pathway. Therefore, opponency must arise downstream from L1 and L2. According to recent evidence, L1 is glutamatergic, whereas L2 is cholinergic. In light of the current data, that result suggests that L1 may actually be inhibitory, which would be sufficient to create opponency in the on and off pathways (Liu, 2013).

    Glutamate can act as an inhibitory neurotransmitter in the Caenorhabditis elegans olfactory circuit, and this fact too has implications for neural coding of odors in this organism. In the worm, a specific type of glutamatergic olfactory neuron inhibits one postsynaptic neuron via GluCl, while also exciting another postsynaptic neuron via an AMPA-like receptor. This arrangement creates a pair of opponent neural channels that respond in an anticorrelated fashion to odor presentation or odor removal, analogous to opponent channels in the visual system (Liu, 2013).

    This study has shown that the cellular actions of Glu-LNs are broadly similar to the actions of GABA-LNs. Specifically, both types of LNs inhibit PNs and other LNs. In addition, both GABA and glutamate inhibit neurotransmitter release from ORNs. Thus, both neurotransmitters inhibit all of the major cell types in the antennal lobe circuit. However, Glu-LNs and GABA-LNs are not functionally identical. In particular, it was found that the vesicular glutamate transporter is mainly confined to the spaces between glomeruli, whereas the vesicular GABA transporter is abundant within glomeruli. This finding implies that glutamate and GABA are released in largely distinct spatial locations. Consistent with this implication, no individual synaptic connections from Glu-LNs onto PNs were found, whereas a substantial rate of connections was found from GABA-LNs onto PNs. Nevertheless, PNs were found to be hyperpolarized by coactivation of multiple Glu-LNs, and PNs are disinhibited by knockdown of GluCl specifically in PNs (Liu, 2013).

    These results can be reconciled by a model where the sites of glutamate release are distant from PN glutamate receptors. As a result, glutamate would need to diffuse some distance to inhibit PNs. Coactivation of multiple Glu-LNs would increase extracellular glutamate concentrations, overwhelming uptake mechanisms and allowing glutamate to diffuse further. In this scenario, glutamatergic inhibition should be most important when LN activity is intense and synchronous. By comparison, GABAergic inhibition of PNs does not require LN coactivation, implying a comparatively short distance between presynaptic and postsynaptic sites. There is a precedent in the literature for the idea that different forms of inhibition can be differentially sensitive to LN coactivation, due to the spatial relationship between presynaptic and postsynaptic sites. In the hippocampus, GABAA receptors are closer than GABAB receptors to sites of GABA release, and so activation of individual interneurons produces GABAA but not GABAB currents, whereas coactivation of many interneurons produces both GABAA and GABAB currents (Liu, 2013).

    The pharmacology of glutamate-gated conductances in antennal lobe neurons is similar to the pharmacology of GABAA conductances in these neurons. This result should prompt a reevaluation of studies that used picrotoxin to block inhibition in the antennal lobe. Given the current results, it seems likely that these studies were reducing both glutamatergic and GABAergic inhibition (Liu, 2013).

    It is perhaps surprising that knocking down GluClα in PNs had such a substantial effect on PN odor responses, given that picrotoxin alone has comparatively modest effects. The solution to this puzzle may lie in the finding that glutamate regulates not only PNs but also GABA-LNs. Importantly, GABA-LNs are spontaneously active and provide tonic inhibition to PNs. Hence, in the intact circuit, glutamatergic inhibition of GABA-LNs should tend to disinhibit PNs. Picrotoxin prevents Glu-LNs from inhibiting GABA-LNs and should tend to potentiate GABAergic inhibition. The effects of GABA are mediated in part by GABAB receptors, which are not sensitive to picrotoxin. Thus, picrotoxin likely has bidirectional effects on the total level of inhibition in the circuit. By contrast, knockdown of GluClα specifically in PNs should not directly affect GABA-LNs and should not produce these complex effects. These results illustrate how a cell-specific genetic blockade of a neurotransmitter system can have more dramatic effects than a global pharmacological blockade of the same system (Liu, 2013).

    This study reveals that an LN can have push-pull effects on a single population of target cells. For example, Glu-LNs directly inhibit PNs, but they should also disinhibit PNs, via the inhibition of GABA-LNs. This architecture may allow for more robust gain control and rapid transitions between network states and is similar to the wiring of many cortical circuits, where corecruitment of excitation and inhibition is a common motif (Liu, 2013).

    Why might the existence of two parallel inhibitory transmitters be useful? The data argue that GABA and glutamate may act on different spatial and temporal scales. Because these two inhibitory systems comprise different cells, receptors, and transporters, they can be modulated independently. Because their properties are encoded by different genes, they can also evolve independently. This organization should confer increased flexibility in adapting synaptic inhibition to a changing environment (Liu, 2013).

    Identification and analysis of a glutamatergic local interneuron lineage in the adult Drosophila olfactory system
    Das, A., Chiang, A., Davla, S., Priya, R., Reichert, H., Vijayraghavan, K. and Rodrigues, V. (2011). Neural Syst. Circuits 1(1):4. PubMed Citation: 22330097

    The antennal lobe of Drosophila is perhaps one of the best understood neural circuits, because of its well-described anatomical and functional organization and ease of genetic manipulation. Olfactory lobe interneurons - key elements of information processing in this network - are thought to be generated by three identified central brain neuroblasts, all of which generate projection neurons. One of these neuroblasts, located lateral to the antennal lobe, also gives rise to a population of local interneurons, which can either be inhibitory (GABAergic) or excitatory (cholinergic). Recent studies of local interneuron number and diversity suggest that additional populations of this class of neurons exist in the antennal lobe. This implies that other, as yet unidentified, neuroblast lineages may contribute a substantial number of local interneurons to the olfactory circuitry of the antennal lobe. This study identified and characterized a novel glutamatergic local interneuron lineage in the Drosophila antennal lobe. MARCM (mosaic analysis with a repressible cell marker) and dual-MARCM clonal analysis techniques to identify this novel lineage unambiguously, and to characterize interneurons contained in the lineage in terms of structure, neurotransmitter identity, and development. The glutamatergic nature of these interneurons was demonstrated by immunohistochemistry and an enhancer-trap strain was used that reports the expression of the Drosophila vesicular glutamate transporter (DVGLUT). The neuroanatomical features of these local interneurons at single-cell resolution, and the marked diversity in their antennal lobe glomerular innervation patterns was documented. Finally, the development of these dLim-1 and Cut positive interneurons was tracked during larval and pupal stages. This study has identified a novel neuroblast lineage that generates neurons in the antennal lobe of Drosophila. This lineage is remarkably homogeneous in three respects. All of the progeny are local interneurons, which are uniform in their glutamatergic neurotransmitter identity, and form oligoglomerular or multiglomerular innervations within the antennal lobe. The identification of this novel lineage and the elucidation of the innervation patterns of its local interneurons (at single cell resolution) provides a comprehensive cellular framework for emerging studies on the formation and function of potentially excitatory local interactions in the circuitry of the Drosophila antennal lobe (Das, 2011).

    Central synaptic mechanisms underlie short-term olfactory habituation in Drosophila larvae
    Larkin, A., et al. (2010). Learn Mem. 17(12): 645-53. PubMed Citation: 21106688

    Naive Drosophila larvae show vigorous chemotaxis toward many odorants including ethyl acetate (EA). Chemotaxis toward EA is substantially reduced after a 5-min pre-exposure to the odorant and recovers with a half-time of ~20 min. An analogous behavioral decrement can be induced without odorant-receptor activation through channelrhodopsin-based, direct photoexcitation of odorant sensory neurons (OSNs). The neural mechanism of short-term habituation (STH) requires the (1) Rutabaga adenylate cyclase; (2) transmitter release from predominantly GABAergic local interneurons (LNs); (3) GABA-A receptor function in projection neurons (PNs) that receive excitatory inputs from OSNs; and (4) NMDA-receptor function in PNs. These features of STH cannot be explained by simple sensory adaptation and, instead, point to plasticity of olfactory synapses in the antennal lobe as the underlying mechanism. These observations suggest a model in which NMDAR-dependent depression of the OSN-PN synapse and/or NMDAR-dependent facilitation of inhibitory transmission from LNs to PNs contributes substantially to short-term habituation (Larkin, 2010).

    Experience-induced plasticity of synapses is believed to be a fundamental mechanism of learning and memory. However, central synaptic changes that underlie memory have not been clearly defined, even for relatively simple nonassociative learning processes such as habituation (Larkin, 2010).

    During habituation, unreinforced exposure to a repeated or prolonged stimulus results in a reversible decrease in response to that stimulus. Habituation probably serves as an important building block for more complex cognitive function. By allowing unchanging or irrelevant stimuli to be ignored, it allows cognitive resources to be focused on more salient stimuli (Larkin, 2010 and references therein).

    The neural basis of short-term habituation (STH) is best studied in the marine snail, Aplysia californica. In this organism STH (lasting ~30 min) of the defensive gill-withdrawal reflex in response to tactile stimulation of the siphon is thought to arise from presynaptic depression of transmitter release at sensorimotor synapses. However, even here, presynaptic plasticity may not be cell-autonomous, potentially requiring, for instance, activity of yet-to-be-identified interneurons (Larkin, 2010).

    Several forms of habituation have been described in Drosophila and are often shown to require the function of genes that regulate cAMP-dependent forms of associative memory. For instance, habituation of proboscis extension reflex as well as odor-evoked startle reflex in adult Drosophila requires rutabaga (rut)-encoded Ca2+/calmodulin-sensitive adenylyl cyclase. In addition, habituation of the ethanol-induced startle response requires the shaggy/GSK-3 signaling pathway. Despite such pioneering observations, the mechanisms of these various forms of habituation, even whether the primary neuronal changes are purely sensory or involve plasticity of central synapses (involving centrally located interneurons that may integrate various different kinds of modulatory, inhibitory, and excitatory inputs), remain poorly understood (Larkin, 2010).

    Recent advances in understanding the circuitry that underlies Drosophila olfactory behavior, as well as the development of new tools to perturb identified neurons in vivo, has opened the opportunity for understanding mechanisms of olfactory habituation at the level of the underlying neural circuitry (Larkin, 2010).

    In the larval olfactory system, 21 olfactory sensory neurons (OSNs), each expressing a single odorant receptor (together with the broadly expressed Or83b co-receptor), synapse, respectively, onto 21 cognate projection neurons (PNs) within 21 glomeruli in the larval antennal lobe (AL). Local, predominantly GABAergic interneurons (LNs) synapse widely within the antennal lobe, interlinking different glomeruli. Various neuromodulatory synapses also form on the larval antennal lobe and mushroom body. Thus, odorant-stimulated signals in sensory neurons are processed in the antennal lobe, modulated by motivational or emotional states, and relayed through projection neurons to higher brain centers (Larkin, 2010).

    Previous work has shown that in Drosophila larvae, olfactory chemotaxis decreases after odorant pre-exposure. This study shows that this behavioral habituation, alternatively referred to as 'adaptation' by some previous investigators, arises from mechanisms of synaptic plasticity. This study demonstrates that odorant receptor activation is not necessary for olfactory habituation; however, local interneuron activity and projection neuron signaling is necessary. These observations suggest a model in which habituation occurs by a pathway in which NMDA receptors in projection neurons signal depression of OSN-PN synapses and/or facilitation of LN-PN synapses (Larkin, 2010).

    Previous studies have not clearly discriminated between peripheral and central mechanisms. Indeed, the term 'adaptation,' better applied to sensory neuron changes such as receptor desensitization, has often been used interchangeably with the term 'habituation', which is usually restricted to behavioral changes arising from central synaptic mechanisms (Larkin, 2010). .

    The form of larval olfactory STH characterized in this study displays at least some of the defining behavioral characteristics of habituation. First, there is a behavioral decrement in response to repeated or sustained application of a particular stimulus. Second, STH shows spontaneous recovery with time in the absence of the habituating stimulus. And third, STH is susceptible to dishabituation when habituated larvae are presented with of a strong or noxious stimulus. The property of dishabituation is particularly significant, as an important way of distinguishing between habituation and either fatigue or sensory adaptation. Dishabituation shows that the habituated animal retains the capability to respond and suggests that the attenuated behavioral response arises from some form of active suppression. Thus, the behavioral data suggest (1) that the term 'habituation' may be better used in place of 'adaptation,' while referring to the behavioral phenomenon that was studied; and (2) that STH probably arises from central synaptic mechanisms, rather than sensory neuron adaptation (Larkin, 2010).

    Three main lines of data support the conclusion that STH arises from a central synaptic mechanism that resides in the antennal lobe, rather than from adaptation of olfactory receptor signaling in the OSN. First, behavioral decrements similar to STH can be induced by direct depolarization of OSNs, indicating that STH may potentially be induced by processes stimulated by activation action-potential firing in OSNs, independently of olfactory receptor activation. Second, and more striking, STH requires synaptic-vesicle exocytosis from local interneurons during the process of odorant exposure, when STH is being established. This requirement is incompatible with an exclusively sensory mechanism. Third, STH requires the function of NMDA receptors on postsynaptic projection neurons. This last observation also provides a particularly strong argument for a synaptic mechanism, indicating a need for plasticity of OSN and/or LN synapses made onto dendrites of projection neurons in the antennal lobe. Given that OSNs are excitatory and LNs are primarily inhibitory, it appears most likely that NMDAR functions in PNs to depress excitatory OSN-PN synapses and/or to potentiate inhibition by strengthening the LN-PN synapse. It is suggestd that the LN-PN mechanism may be involved because (1) LN transmission seems necessary for both induction and expression of habituation; and (2) the process of dishabituation could be attractively explained as arising from the inhibition of local inhibitory synapses through descending neuromodulation. A requirement for facilitation of the LN-PN synapse would be consistent with previous studies (Sachse, 2007) showing that adult-long-term olfactory habituation is associated with an increase in odor-evoked calcium fluxes in GABAergic processes within the Drosophila antennal lobe (Larkin, 2010).

    Based both on experimental and theoretical arguments, a simple model is suggested for short-term olfactory habituation. Since this is a model, no claim is being made to to having ruled out additional major contributing mechanisms, It is suggested that during initial odorant pre-exposure, dendritic NMDA receptors on projection neurons detect and respond to membrane depolarization occurs coincident with transmitter release from LNs. Calcium entry through dendritic NMDA receptors may trigger a local retrograde signal required for facilitation of transmitter release from the LNs. Although existing data do not rule out functions for rutabaga in higher larval brain centers, it is suggested that either the generation of a retrograde signal in PN dendrites or the presynaptic response of LNs to this signal could be dependent on the rut adenylate cyclase. In habituated animals, facilitation of GABA release would reduce odor-evoked projection neuron outputs to higher brain centers, thereby reducing olfactory behavior. As NMDAR signaling would only occur at active glomeruli, this mechanism can account not only for the observed odor selectivity of habituation, but also the instances of cross-habituation (Larkin, 2010).

    Such a model also naturally suggests a hypothesis for the mechanism of dishabituation: namely, that dishabituating stimuli cause release of neuromodulators that act to reduce GABA release from local inhibitory synapses (Larkin, 2010).

    Given the remarkable similarities in the anatomical organization of insect and mammalian olfactory systems, a significant conservation of olfactory mechanisms would be expected. In rodents, at least two forms of habituation have been described, lasting 2-3 and 30-60 min, respectively: the latter equivalent in timescale to larval STH described in this study. Consistent with a similar underlying mechanism, the more persistent form of olfactory habituation can be blocked by an N-methyl-D-aspartate (NMDA) receptor antagonist in the olfactory bulb, a structure homologous to the insect antennal lobe. Thus, larval STH described in this study has some similarities to a previously characterized form of mammalian olfactory habituation. Analysis of the underlying mechanisms is therefore likely to provide directly transferable insights in mammalian olfaction. The data make the prediction that the activity of mammalian olfactory interneurons, either periglomerular or granule cells, is critical for the establishment and display of at least one timescale of olfactory habituation (Larkin, 2010).

    In addition to providing some insight into mechanisms of olfactory habituation in mammals, it possible that circuit mechanisms of larval olfactory habituation are relevant to other forms of behavioral habituation. In at least three previous instances, increased inhibition has been associated with attenuated behavior. For example, habituation of an escape reflex mediated by the lateral giant fibers in the crayfish has been associated with enhanced GABAergic transmission onto giant fibers. Similarly, LTP of inhibitory synapses controlling excitability of the Mauthner cell has been associated with reduced escape behavior in goldfish. Furthermore, ethanol, a potentiator of GABA synapses, has been shown to enhance habituation of a motor pathway in the frog spinal cord. Could these different instances of habituation all involve circuit mechanisms similar to those used in Drosophila larval olfactory behavior (Larkin, 2010)?

    In all brain regions, principal/projection neurons are subject to inhibitory feedback modulation and a pathway that has been appreciated as potentially essential for neuronal homeostasis. Potentiation of inhibitory feedback triggered by the pattern of principle cell activation would be predicted to preferentially dampen this particular output pattern. Thus, the circuit mechanism suggest in this study is theoretically generalizable to other and more complex forms of habituation. Further experiments will be required to determine the validity of this very testable hypothesis (Larkin, 2010).

    The importance of habituation has been underlined by the fact that deficits in sensory gating and pre-pulse inhibition (PPI), processes with similarities to habituation, have been linked with various neurological problems, including autism and schizophrenia. Indeed, a circuit model for understanding schizophrenia has specifically proposed that altered negative feedback in the hippocampus may underlie both positive and negative symptoms of schizophrenia (Larkin, 2010).

    In addition, defects in habituation or habituation-like processes have been described in Fragile X syndrome and migraines. It has also been shown to have important effects relating to learning disabilities, age-related changes in learning, and substance abuse. If mechanisms of olfactory habituation prove to be general, then studies of olfactory plasticity may prove relevant for other forms of cognition as well as for human neurological disease (Larkin, 2010).

    A presynaptic gain control mechanism fine-tunes olfactory behavior
    Root, C. M., et al. (2008). Neuron 59(2): 311-21. PubMed Citation: 18667158

    Early sensory processing can play a critical role in sensing environmental cues. This study investigated the physiological and behavioral function of gain control at the first synapse of olfactory processing in Drosophila. Olfactory receptor neurons (ORNs) express the GABAB receptor (GABABR) and its expression expands the dynamic range of ORN synaptic transmission that is preserved in projection neuron responses. Strikingly, it was found that different ORN channels have unique baseline levels of GABABR expression. ORNs that sense the aversive odorant CO2 do not express GABABRs nor exhibit any presynaptic inhibition. In contrast, pheromone-sensing ORNs express a high level of GABABRs and exhibit strong presynaptic inhibition. Furthermore, a behavioral significance of presynaptic inhibition was revealed by a courtship behavior in which pheromone-dependent mate localization is impaired in flies that lack GABABRs in specific ORNs. Together, these findings indicate that different olfactory receptor channels may employ heterogeneous presynaptic gain control as a mechanism to allow an animal's innate behavioral responses to match its ecological needs (Root, 2008).

    The stereotypic organization of the Drosophila olfactory system and the identification of the family of odorant receptor genes make the fly an attractive system to study olfactory mechanisms. An adult fly expresses about 50 odorant receptor genes and each ORN typically expresses just one or a few receptor genes. ORNs detect odors in the periphery and send axons to glomeruli in the antennal lobe. Each glomerulus receives axons from about 20 ORNs expressing the same receptor genes and dendrites of a few uniglomerular projection neurons (PNs), which propagate olfactory information to higher brain centers. This numerically simple olfactory system coupled with genetic markers to label most of the input channels provides an opportunity to dissect synaptic function and information processing (Root, 2008).

    The Drosophila antennal lobe is populated with GABAergic local interneurons (LNs) that release GABA in many if not all glomeruli. GABA exerts its modulatory role via two distinct receptor systems, the fast ionotropic GABAA receptor, which is sensitive to the antagonist picrotoxin, and the slow metabotropic GABAB receptor, which is sensitive to the antagonist CGP54626. Pharmacological blockade of the GABA receptors demonstrate that GABA-mediated hyperpolarization suppresses PN response to odor stimulation in a non-uniform fashion. Electron microscopy studies of the insect antennal lobe show that GABAergic LNs synapse with PNs, which support the well established olfactory mechanism of lateral inhibition. GABAergic LNs also synapse onto ORNs and imaging studies in mouse suggest that activation of GABABRs in ORN terminals suppress neurotransmitter release in ORNs (Root, 2008).

    It was hypothesized that setting the appropriate olfactory gain for environmental cues is important for adjusting an organism's sensitivity to its environment. A recent study shows that GABABR mediated presynaptic inhibition provides a mechanism to modulate olfactory gain. Electrical recordings show that interglomerular presynaptic inhibition suppresses the olfactory gain of PNs to potentially increase the dynamic range of the olfactory response. Likewise, gain modulation may not be uniform among different glomeruli, which could reflect a tradeoff between sensitivity and dynamic range in different olfactory channels. For example, high sensitivity may be crucial for some environmental cues, such as those that require an immediate behavioral response, whereas a larger dynamic range may be more advantageous for other odors where precise spatial and temporal information may be critical for optimal performance (Root, 2008).

    This study investigated the physiological and behavioral function of gain control in early olfactory processing. Interneuron-derived GABA was shown to activate GABABRs on ORN terminals, reducing the gain of ORN-to-PN synaptic transmission. Different types of ORNs exhibit different levels of presynaptic inhibition and this heterogeneity in presynaptic inhibition is preserved in antennal lobe output projection neurons. Interestingly, pheromone-sensing ORNs exhibit high levels of GABABR expression and behavioral experiments indicate that GABABR expression in a population of pheromone ORNs is important for mate localization, suggesting that presynaptic gain control is important for the olfactory channel-specific fine-tuning of behavior (Root, 2008).

    Two-photon imaging was used to monitor activity in selective neural populations in the antennal lobe. Specific blockade of GABABRs reveals a scalable presynaptic inhibition to suppress olfactory response at high odor concentrations. Pharmacological and molecular experiments suggest that GABABRs are expressed in primary olfactory receptor neurons. Furthermore, the level of presynaptic inhibition is different in individual glomerular modules, which is tightly linked to the level of GABABR expression. The importance of presynaptic GABABRs in olfactory localization was investigated, and it was found that reduction of GABABR expression in the presynaptic terminal of ORNs impairs the ability of male flies in locating potential mates (Root, 2008).

    Heterogeneity was found in the levels of presynaptic inhibition among different glomeruli. Varying GABABR2 expression level in ORNs with molecular manipulations is sufficient to produce predictable alterations in presynaptic inhibition in specific glomeruli. Together these experiments argue that presynaptic GABABR expression level is a determinant of glomerulus-specific olfactory gains in the antennal lobe. A recent report revealed that there is a non-linear transformation between ORNs and PNs that is heterogeneous between glomeruli. In other words, PNs innervating a given glomerulus have a unique response range for its ORN input. Given that ORNs are the main drivers of PN response, it is plausible that the heterogeneity in presynaptic inhibition contributes to the heterogeneity in ORN to PN transformations observed by Bhandawat and colleagues. Additionally, heterogeneity in GABA release by LNs could also contribute to heterogeneity in presynaptic inhibition. It is interesting to note that when presynaptic inhibition is abolished, heterogeneity remains in the input-output curves of PN response to the four different odors in these experiments, suggesting that other mechanisms such as probability of vesicle release contribute to the heterogeneity as well (Root, 2008).

    Theoretical analysis of antennal lobe coding has recently suggested that the non-linear synaptic amplification in PNs provides an efficient coding mechanism for the olfactory system. According to this model, the optimal distribution of firing rates across a range of odorants should be flat without clusters. Firing rates of a given ORN responses cluster in an uneven distribution. Conversely, PNs exhibit a more equalized firing rate distribution than ORNs. According to the optimum coding theory, the high amplification of ORN to PN transformation generates a more even distribution of PN firing rates that should facilitate odor discrimination. However, this model of olfactory coding poses a potential problem. The high gain in this synaptic amplification reduces the dynamic range of PNs, causing a loss of information about concentration variation that could be important for an animal to localize odor objects. Presynaptic inhibition may provide a mechanism to expand the dynamic range of the olfactory system. For some glomerular modules that mediate innate behaviors such as avoidance of the stress odorant CO2, there is a potential trade off for odor sensitivity and dynamic range. The lack of GABABR in the CO2 sensing ORNs could be important to maintain high sensitivity (Root, 2008).

    Pheromones play an important role in Drosophila mating behaviors and the current results indicate that pheromone sensing ORNs have high levels of GABABR, which is correlated with a high level of presynaptic inhibition in these ORNs. Mate localization is impaired in the absence of presynaptic inhibition in one pheromone sensing glomerulus. It is interesting to note that in addition to the pheromone sensing ORNs, the palpal ORNs also exhibit high GABABR expression level. Although the behavioral role of the palpal ORNs has not been determined, it is possible that they are also important for odor object localization. There are two potential mechanisms for the role of GABABR in olfactory localization. GABABR-mediated activity-dependent suppression of presynaptic transmission on a short time scale provides a mechanism for dynamic range expansion. On a longer time scale, activity-dependent suppression provides a mechanism for adaptation, hence a high pass filter to allow the detection of phasic information. Further experiments will be necessary to determine which property is important for olfactory localization (Root, 2008).

    Intraglomerular and interglomerular presynaptic inhibition mediated by GABABRs have been described in the mammalian olfactory system. Intraglomerular presynaptic inhibition was suggested as a mechanism to control input sensitivity while maintaining the spatial maps of glomerular activity. Interglomerular presynaptic inhibition was proposed as a mechanism to increase the contrast of sensory input. A recent report revealed a similar gain control mechanism by interglomerular presynaptic inhibition in the Drosophila olfactory system where GABABR expression in ORNs was shown to scale the gain of PN responses. Interestingly, most if not all of the presynaptic inhibition was suggested to be lateral. In contrast, this study study does not seek to distinguish between intra- and interglomerular presynaptic inhibition, however evidence was found that the VA1lm glomerulus receives significant intraglomerular presynaptic inhibition. Thus, despite significant differences between the insect and mammalian olfactory systems, the inhibitory circuit in the first olfactory processing center appears remarkably similar (Root, 2008).

    Based on whole cell recordings of PNs in response to ORN stimulation, Olsen (2008) suggests that both GABAAR and GABABR are expressed in ORNs to mediate presynaptic inhibition and that GABAAR signaling is a large component of lateral presynaptic inhibition. In contrast, this study, which employed direct optical measurements of presynaptic calcium and synaptic vesicle release, suggests that GABABRs but not GABAARs are involved in presynaptic inhibition. To resolve these discrepancies further molecular experiments will be important to determine conclusively whether ORNs express GABAAR and whether the receptor contributes to gain control. Furthermore, the antennal lobe is a heterosynaptic system comprised of at least three populations of neurons that include ORNs, LNs and PNs. Therefore, how these different populations of neurons respond to GABA signaling and what contribution they make to olfactory processing in the antennal lobe is a critical question for future investigation (Root, 2008).

    This study has demonstrated differential presynaptic gain control in individual olfactory input channels and its contribution to the fine-tuning of physiological and behavioral responses. Synaptic modulation by the intensity of receptor signaling is reminiscent of the mammalian nervous system where expression levels of AMPA glutamate receptors play an important role in regulating synaptic efficacy. Furthermore, presynaptic regulation of GABABR signaling provides a mechanism to modulate the neural activity of individual input channels without much interference with overall detection sensitivity because this mechanism of presynaptic inhibition would only alter responses to high intensity stimuli. In parallel, it is tempting to speculate that global modulation of interneuron excitability should alter the amount of GABA release across channels, thus providing a multi-channel dial of olfactory gain control that may reflect the internal state of the animal (Root, 2008).

    Metamorphosis of an identified serotonergic neuron in the Drosophila olfactory system
    Singh, R. B., et al. (2007). Neural Dev. 2: 20. PubMed Citation: 17958902

    Odors are detected by sensory neurons that carry information to the olfactory lobe where they connect to projection neurons and local interneurons in glomeruli: anatomically well-characterized structures that collect, integrate and relay information to higher centers. Recent studies have revealed that the sensitivity of such networks can be modulated by wide-field feedback neurons. The connectivity and function of such feedback neurons are themselves subject to alteration by external cues, such as hormones, stress, or experience. Very little is known about how this class of central neurons changes its anatomical properties to perform functions in altered developmental contexts. A mechanistic understanding of how central neurons change their anatomy to meet new functional requirements will benefit greatly from the establishment of a model preparation where cellular and molecular changes can be examined in an identified central neuron. This study examined a wide-field serotonergic neuron in the Drosophila olfactory pathway and mapped the dramatic changes that it undergoes from larva to adult. Expression of a dominant-negative form of the ecdysterone receptor prevents remodeling. Different transgenic constructs were used to silence neuronal activity, and defects are reported in the morphology of the adult-specific dendritic trees. The branching of the presynaptic axonal arbors is regulated by mechanisms that affect axon growth and retrograde transport. The neuron develops its normal morphology in the absence of sensory input to the antennal lobe, or of the mushroom bodies. However, ablation of its presumptive postsynaptic partners, the projection neurons and/or local interneurons, affects the growth and branching of terminal arbors. These studies establish a cellular system for studying remodeling of a central neuromodulatory feedback neuron and also identify key elements in this process. Understanding the morphogenesis of such neurons, which have been shown in other systems to modulate the sensitivity and directionality of response to odors, links anatomy to the development of olfactory behavior (Singh, 2007).

    Changes in the pattern of arborization of a mature neuron can come about as a consequence of removal of its afferent inputs or targets, chronic stress or other environmental inputs, such as delivered during learning or exercise. Many of these changes are effected through the action of growth factors and developmental signals acting in concert with steroid hormones and neuronal activity to modify the cytoskeleton or synaptic properties relevant to an altered functional setting. Metamorphosis in Drosophila (a period during which mature larval neurons are often altered to take on new adult functions) provides a context where the mechanistic underpinnings of such neuronal change can be genetically dissected (Singh, 2007).

    This study used a genetic method to mark the serotonin-immunoreactive deutocerebral interneurons (CSDn), recently identified on the basis of serotonin immunoreactivity. While this preparation identifies a central neuron, it also has an important feature that allows the analysis of mechanisms underlying the changes it undergoes during remodeling. This system, because of the random nature of the RN2-FLP action, results in bilateral, unilateral or no excision of the FRT element in the Tub-FRT-CD2-FRT-Gal4 construct in the CSDn. Thus, it was possible to choose and analyze preparations where the CSDn from only one hemisphere was labeled: this facility is vital as it allows the analysis of contralateral and ipsilateral projections of the CSDn, without this being obscured by projections of the neuron from the other hemisphere to the same target sites. The GFP reporter in the RN2-Flp, Tub-FRT-CD2-FRT-Gal4, UAS mCD8-GFP strain is first detected very late in embryogenesis (stage 20), after the neuron has acquired its mature larval pattern. These features thus provide a preparation where an identified central neuron, whose function is known, can be followed and genetically manipulated as it changes its form in response to external and internal cues during metamorphosis (Singh, 2007).

    The neuron, present during the larval stages, undergoes well-defined changes during pupation to give rise to a more complex adult architecture. What are the factors that regulate the stereotyped pruning and re-growth of arbors in the CSDn during metamorphosis? The results suggest that the interaction of external factors and autonomous properties (some of which could be identified) establish the homeostasis required during branching and establishment of the adult form (Singh, 2007).

    Arbors from the larval neuron are removed by pruning over the first 20 hours of pupation before the adult pattern is elaborated. The EcR-B1 isoform, whose expression is typically seen in neurons that alter their larval form and contribute to the circuitry in the adult, is detected in CSDn. Down-regulating EcR in the CSDn during metamorphosis results in a failure of remodeling and the 'adult' neuron retains a larval morphology. The detailed mechanisms by which EcR signaling acts to bring about sculpting of cell shape are not totally understood and reports on Manduca sexta indicate that steroid-induced modifications in dendritic shape can be regulated by activity-dependent mechanisms (Singh, 2007).

    Studies on the cellular and molecular mechanisms of pruning events during metamorphosis could provide valuable insights into understanding of degeneration in higher systems. These events require ubiquitin-mediated proteolysis, and it is known that local activity of caspases is involved in dendritic pruning in an identified sensory neuron. Degeneration of specific branches is followed by migration of glial cells into the site of activity. The role of these glia in bringing about pruning and in clearing debris from the vicinity requires further study (Singh, 2007).

    The assembly of complex circuits is dependent on a carefully orchestrated interplay of intrinsic and extrinsic cues. Does activity play a role in determining neuronal shape? Spontaneous and evoked activity in the CSDn were silenced using different methods and changes were observed in the dendritic arbors as well as in presynaptic terminals. The effects on the terminals and dendrites are possibly due to distinct mechanisms and will be discussed separately (Singh, 2007).

    The strongest effects on presynaptic terminal branching were produced by expression of TeTxLC, which blocks synaptic release, and a dominant-negative Shi protein, which affects receptor-mediated endocytosis. Apart from blocking neuronal activity by abrogating synaptic vesicle release, both treatments could potentially affect axon growth. Consistent with this is the observation that TeTxLC expression affects re-growth of CSDn terminals during metamorphosis, while pruning occurred normally. Weak anatomical defects have also been described in other, non-modulatory neurons, some of which could be explained by a role in the regulation of levels of cell adhesion molecules (Singh, 2007).

    Increases in size and branching pattern of the dendritic trees is a robust effect occurring notably when neuronal activity was silenced by Kir2.1expression. In the third instar larva, expression of TNT-G leads to an increase in dendritic arbors with no significant effect on the presynaptic terminals. Expression using the RN2-Flp, Tub-FRT-CD2-FRT-Gal4, stock initiates in the fully developed larval neuron; hence, the changes in dendritic branches are likely to be a consequence of lack of neuronal activity, rather than a developmental effect. What are the mechanisms by which neuronal activity can alter morphologies of neurons? It has been demonstrated that tetanus toxin expression in motorneurons not only affects its presynaptic release because of cleavage of synaptobrevin, but also alters synaptic input by an as yet unknown mechanism. The finding of altered dendritic morphology supports the possibility that homeostatic alterations occur to compensate for a lack of activity (Singh, 2007).

    A large body of data provides evidence for retrograde signaling in the development and consolidation of synapses. The observation of expanded dendritic trees upon expression of a dominant negative form of Glued, while intriguing, is difficult to explain in this light. The changes that were seen are in the dendritic (post-synaptic) field when retrograde transport is blocked cell-autonomously. While this needs further investigation, a possible explanation is that these effects are an indirect consequence of physiological alterations at the presynaptic terminals. Local morphological changes in neurons can be effected by sequestration of proteosomes and other molecules at different regions of the cell in response to activity, which could result in sculpting of cellular architecture due to altered protein composition at different cellular regions (Singh, 2007).

    Defects in branching observed by abrogation of vesicle release at the synapse in a serotonergic neuron could implicate this modulator in paracrine or autocrine signaling in regulation of neuronal outgrowth, target selection and synapse formation. Such effects have been demonstrated in the gastropod Helisoma , as well as in Drosophila, where serotonin levels regulate neuronal branching and modulate the development of neuronal varicosities in the central nervous system. In these experiments, no significant changes were detected in the branching pattern of CSDn upon strong reduction of serotonin (and dopamine) using a temperature sensitive allele of dopa decarboxylase. Furthermore, unlike in M. sexta, where afferents are necessary for the formation of glomerular tufts of the serotonergic neuron within the antennal lobe, development of the CSDn occurs normally in the absence of sensory input from the antenna (Singh, 2007).

    The olfactory pathway consists of afferent sensory neurons, local integrating neurons and projection neurons. Circuitry for an additional level of integration exists in the atypical projection neurons (aPNs), the antennal posterior superior protocerebral neuron (APSP), the giant symmetric relay interneurons (GSI) and the bilateral ACT relay interneurons (bACT). The architecture as well as the serotonergic nature of the CSDn closely resembles the S1 neuron in M. sexta, which receives input from bilateral projections in the protocerebrum and terminates in the lobe contralateral to the soma to modulate the activity of interneurons. It is proposed that the ipsilateral dendrites receive input from as-yet unidentified neural elements in the antennal lobe, while some axonal arbors are postsynaptic to interneurons in the calyx of the mushroom bodies and the lateral horn. It is speculated that the targets of the terminal arbors are either the PNs or the LNs since their ablation results in a reduction in branching. This architecture, which needs to be confirmed by electron microscopic analysis, provides circuitry for 'top-down' regulation of the primary olfactory center. It seems very likely that the CSDn, like its counterpart in the moth, responds to mechanosensory stimulation, providing an important role in responses to odor stimulation coupled with airflow, as would be expected in insects during flight. The modulatory effects of this large field neuron on its partners in the antennal lobe needs to be investigated by high-resolution functional imaging (Singh, 2007).

    This study describes a serotonergic neuron whose anatomy suggests feedback integration within the antennal lobe of insects. The neuron undergoes remodeling during pupal life from a simple larval to a more complex adult pattern. These studies suggest that the morphology of the dendritic arbors that terminate in the lobe ipsilateral to the soma is regulated by neuronal activity. The arborization of terminal arbors depends on vesicle recycling, endocytosis and Dynein-dependant retrograde transport. These findings demonstrate a useful identified-neuronal preparation where developmental mechanisms and remodeling can be studied in the context of olfactory behavior (Singh, 2007).

    Role of GABAergic inhibition in shaping odor-evoked spatiotemporal patterns in the Drosophila antennal lobe
    Wilson, R. I. and Laurent, G. (2005). J. Neurosci. 25(40): 9069-79. 16207866

    Drosophila olfactory receptor neurons project to the antennal lobe, the insect analog of the mammalian olfactory bulb. GABAergic synaptic inhibition is thought to play a critical role in olfactory processing in the antennal lobe and olfactory bulb. However, the properties of GABAergic neurons and the cellular effects of GABA have not been described in Drosophila, an important model organism for olfaction research. Whole-cell patch-clamp recording, pharmacology, immunohistochemistry, and genetic markers have been used to investigate how GABAergic inhibition affects olfactory processing in the Drosophila antennal lobe. This study shows that many axonless local neurons (LNs) in the adult antennal lobe are GABAergic. GABA hyperpolarizes antennal lobe projection neurons (PNs) via two distinct conductances, blocked by a GABAA- and a GABAB-type antagonist, respectively. Whereas GABAA receptors shape PN odor responses during the early phase of odor responses, GABAB receptors mediate odor-evoked inhibition on longer time scales. The patterns of odor-evoked GABAB-mediated inhibition differ across glomeruli and across odors. LNs display broad but diverse morphologies and odor preferences, suggesting a cellular basis for odor- and glomerulus-dependent patterns of inhibition. Together, these results are consistent with a model in which odors elicit stimulus-specific spatial patterns of GABA release, and as a result, GABAergic inhibition increases the degree of difference between the neural representations of different odors (Wilson, 2005).

    Smell begins when odor molecules interact with olfactory receptor neurons (ORNs). ORNs then project to the brain following anatomical rules common to species as evolutionarily distant as flies and rodents. Briefly, the odor sensitivity of a particular ORN is specified by the expression of a single olfactory receptor gene. All the ORNs that express a particular receptor send their axons to the same glomeruli in the brain. There, ORNs make synapses with second-order neurons [mitral cells (in vertebrates) or projection neurons (in insects)] (Wilson, 2005).

    What happens when signals reach these second-order olfactory neurons is determined by complex local circuitry. One obstacle to understanding this circuitry is the sheer number of input channels in the mammalian olfactory system. The rat olfactory bulb contains ~1000 glomeruli; in contrast, the Drosophila antennal lobe contains just ~40 glomeruli. This, along with the genetic advantages of Drosophila, makes the fruit fly a useful model for investigating olfactory processing (Wilson, 2005).

    A given odor excites many Drosophila antennal lobe projection neurons (PNs) but inhibits others. These odor-evoked inhibitory epochs can last from ~100 ms to several seconds. Similar odor-evoked inhibition has also been observed in other insects and in olfactory bulb mitral cells. Some odor responses of mitral cells and PNs are purely inhibitory. Other responses are multiphasic, in which an inhibitory epoch follows or precedes an excitatory epoch. These temporal patterns are cell and odor dependent and have been proposed to encode information about the stimulus. However, the mechanism of these 'slow' patterns is not fully understood (Wilson, 2005).

    One possibility is that inhibitory epochs represent periods when principal neurons are synaptically inhibited by GABAergic local neurons (LNs). GABA-immunoreactive LNs are present in the adult antennal lobe of several species and in the larval Drosophila antennal lobe. Antennal lobe LNs can synaptically inhibit PNs, and the antennal lobe is strongly immunoreactive for GABAA receptors). However, GABAA antagonists do not block odor-evoked slow inhibition or slow temporal patterns in PNs. Therefore, these inhibitory epochs have been hypothesized to reflect a metabotropic conductance or the action of a different inhibitory neurotransmitter. Alternatively, inhibition of PNs could be caused by inhibition of ORNs (Wilson, 2005).

    This study investigated the mechanisms of odor-evoked inhibition in PNs. It was confirmed that many Drosophila antennal lobe LNs are GABAergic. GABA receptors contribute to odor-evoked inhibition of PNs on both fast and slow time scales, and GABA-mediated slow inhibition increases the diversity of odor-evoked responses among PNs. This is consistent with models that invoke GABAergic inhibition to increase the discriminability of olfactory representations (Wilson, 2005).

    As in the olfactory bulb, each glomerulus in the Drosophila antennal lobe contains four main classes of neurons: (1) the axon terminals of ORNs, (2) the dendrites of PNs that convey information from ORNs to higher brain centers, (3) neurites from LNs that interconnect glomeruli, and (4) the centrifugal axonal projections of neurons that relay information to the antennal lobe from higher brain centers. Recent studies have illuminated the development, morphology, and physiology of Drosophila ORNs and PNs. Drosophila LNs, in contrast, have not received much attention. LNs have been noted in Golgi-impregnated antennal lobes, but remarkably little is known about the number, morphology, and connectivity of these cells or about their impact on other antennal lobe neurons. If adult LNs are also GABAergic, and if GABA is inhibitory (as it is in other insects), then LNs could participate in sculpting the inhibitory epochs prominent in many PN odor responses. In the larval Drosophila antennal lobe, many LNs are immunopositive for GABA. In the adult, it has been shown that many somata around the antennal lobes express the GABA biosynthetic enzyme glutamic acid decarboxylase (Wilson, 2005).

    This study confirms that many adult Drosophila antennal LNs are GABAergic. Using confocal immunofluorescence microscopy with an anti-GABA antibody, many GABA-positive somata were observed in the vicinity of the antennal lobe neuropil. To identify LNs, flies were used in which a large subpopulation of these cells were genetically labeled. In these flies (GAL4 enhancer trap line GH298), reporter gene activity labels a cluster of somata lateral to the antennal lobe neuropils. The neurites of these neurons collectively fill the antennal lobes, reminiscent of the morphology of LNs identified in Golgi impregnations. When whole-cell patch-clamp recordings were made from the somata of GFP-positive cells in GH298-GAL4, UAS-CD8GFP flies, intrinsic properties characteristic of LNs were observed, namely high input resistances and action potentials with amplitude >40 mV. It was also confirmed with single-cell biocytin fills that these GFP-positive neurons were indeed LNs. When GH298-GAL4,UAS-CD8GFP brains stained for GABA were visualized using dual-channel confocal microscopy, it was found that most GFP-positive somata were also GABA positive. About one-fifth of the GFP-positive somata did not stain for GABA. These neurons may contain a different neurotransmitter, or the staining may not have been sensitive enough to detect low levels of GABA. The possibility cannot be excluded that these GABA-negative neurons are not LNs (Wilson, 2005).

    It was then confirmed that GABA hyperpolarizes antennal lobe neurons. In LNs, these results imply that inhibition is mediated entirely by GABAA receptors. In contrast, GABAergic inhibition of PNs is mediated by both GABAA and GABAB receptors. Thus, synaptic inhibition onto PNs and LNs is functionally specialized (Wilson, 2005).

    How might GABAergic inhibition contribute to olfactory processing in the Drosophila antennal lobe? Recent studies using optical measurements of neural activity have concluded that ORN and PN odor responses are very similar and that the antennal lobe is merely a relay station that faithfully transmits ORN signals to PNs without alteration. These conclusions imply that synaptic inhibition in the antennal lobe may exist merely to control global excitability and may not play an important role in representing information about the stimulus. However, the optical reporters used in these studies lack temporal resolution, have limited dynamic range, and may not be sensitive to inhibitory events. Whole-cell patch-clamp recordings from Drosophila PNs show prominent inhibitory epochs in many odor responses, generating odor-dependent spatiotemporal response patterns. Such complex temporal patterns are not present in the responses of ORNs, implying that they arise in the antennal lobe and thus represent a transformation of the olfactory code between the first and second layers of olfactory processing. These temporal patterns are reminiscent of those seen in olfactory bulb mitral cells and in other insects (Wilson, 2005).

    A common notion in olfaction is that such spatiotemporal patterns represent lateral interactions, the net effect of which is to amplify contrast. This idea has taken two main forms. The first proposes a contrast-enhancement mechanism akin to that seen in the retina. According to this model, specific mutual inhibitory interactions exist between principal neurons in nearby glomeruli with similarly tuned ORN inputs. When a principal neuron is activated strongly by an odor, it will trigger lateral inhibition of its neighbors to suppress weak responses to that odor, sharpening the difference between their tuning curves. A different hypothesis is that lateral interactions exist in a more distributed manner. Odors are represented as stimulus-specific sequences of neuronal ensembles. The stimulus is represented both by the identity of the active neurons and the time when they are active. According to this model, the net effect of interglomerular interactions is not to prune away weak responses. Rather, inhibitory interactions may coexist with excitatory interactions (or relief-of-inhibition mechanisms), such that new principal neuron responses appear as others disappear. Because each stimulus is represented by an evolving neural ensemble, the available coding space is expanded. Again, the outcome of this process is thought to be a progressive decorrelation, such that overlap is reduced between stimulus representations (Wilson, 2005).

    Both these models predict that eliminating odor-evoked inhibitory epochs in second-order olfactory neurons will increase the similarity between the spatiotemporal activity patterns produced in these neurons by different odors. This study reports that odor-evoked inhibitory epochs in Drosophila PNs are mostly suppressed by a GABAB receptor antagonist and that blocking GABAB receptors decreases the coefficient of variation among PN peristimulus-time histograms. These results are consistent with models in which lateral interactions between principal and local neurons increase the degree of difference between the neural representations of different odors (Wilson, 2005).

    It is important to point out that the effect of the GABAB antagonist on PN odor responses may be mediated partly by presynaptic effects on ORN axon terminals or by indirect effects via other excitatory inputs to PNs. Determining the locus of this effect will require additional experiments using cell type-specific genetic manipulations. However, because GABAB receptors mediate much of the direct effect of GABA on PNs, it seems likely that the effect of CGP54626, a compound that blocks the late inhibitory epoch in a PN odor response, on odor-evoked PN activity is attributable at least in part to postsynaptic GABAB receptors (Wilson, 2005).

    Finally, it should be noteed that two conceptually distinct kinds of temporal patterns can in principle coexist among second-order olfactory neurons. Slow temporal patterns are punctuated by inhibitory epochs on the timescale of tens to thousands of milliseconds. In this study, it was shown that these slow patterns in the Drosophila antennal lobe are sensitive to a GABAB antagonist. Distinct from this is fast inhibition, which synchronizes the firing of principal neurons on time scales of several milliseconds and is sensitive to picrotoxin. Fast, odor-evoked synchronous oscillations occur in the olfactory systems of many organisms and are required for fine olfactory discrimination in the honeybee. There is little evidence for such oscillatory synchronization among Drosophila PNs. These observations deserve additional investigation but suggest that different organisms may emphasize different strategies for olfactory processing (Wilson, 2005).

    Theoretical models of olfactory processing that invoke synaptic inhibition to increase the contrast between different stimulus representations presume nonuniform connectivity between inhibitory and principal neurons. In insects, a GABAergic LN can arborize across the entire antennal lobe, and so it is not obvious that single LNs will make connections preferentially with particular glomeruli. In this study, it was found that the neurites of single LNs form spatially heterogeneous patterns in the antennal lobe. This finding alone does not prove that individual LNs make connections preferentially in the glomeruli in which their dendrites are most dense; for example, average synaptic strength could be higher in glomeruli with fewer neurites. However, individual LNs also displayed specific odor preferences. This supports the idea that the odor tuning of individual LNs might be correlated with which glomeruli were preferentially innervated by that LN. According to this model, LN odor tuning would be biased toward the tuning of the excitatory neurons innervating those glomeruli. Drosophila LNs receive excitatory input from PNs. In other insect species, LNs are also known to receive direct input from ORNs (Wilson, 2005).

    Consistent with these conclusions, a functional imaging study of the Drosophila antennal lobe has found that each odor stimulus evokes GABA release in some glomeruli more than others. Furthermore, these spatial patterns of GABA release are odor dependent (Ng, 2002). That study measured synaptic release from all GABAergic neurons simultaneously. This investigation has now been extended to single LNs, the morphological and functional diversity of which suggests a cellular mechanism for how the pattern of GABA release can be nonuniform and odor dependent. Ultimately, a test of this idea should come from correlating the morphology of single LNs with their odor preferences. Recent studies have reported the odor tuning of a large subset of Drosophila olfactory receptors and the mapping of each receptor to a specific ORN type. Once it is know which ORN type corresponds to each glomerulus, it should be possible to design experiments of this type more systematically (Wilson, 2005).

    Developmentally programmed remodeling of the Drosophila olfactory circuit
    Marin, E. C., Watts, R. J., Tanaka, N. K., Ito, K. and Luo. L. (2005). Development 132(4): 725-37. 15659487

    Neural circuits are often remodeled after initial connections are established. The mechanisms by which remodeling occurs, in particular whether and how synaptically connected neurons coordinate their reorganization, are poorly understood. In Drosophila, olfactory projection neurons (PNs) receive input; their dendrites synapse with olfactory receptor neurons in the antennal lobe and relay information to the mushroom body (MB) calyx and lateral horn. Embryonic-born PNs participate in both the larval and adult olfactory circuits. In the larva, these neurons generally innervate a single glomerulus in the antennal lobe and one or two glomerulus-like substructures in the MB calyx. They persist in the adult olfactory circuit and are prespecified by birth order to receive input from a subset of glomeruli distinct from larval-born PNs. Developmental studies indicate that these neurons undergo stereotyped pruning of their dendrites and axon terminal branches locally during early metamorphosis. Electron microscopy analysis reveals that these PNs synapse with MB gamma neurons in the larval calyx and that these synaptic profiles are engulfed by glia during early metamorphosis. As with MB gamma neurons, PN pruning requires cell-autonomous reception of the nuclear hormone ecdysone. Thus, these synaptic partners are independently programmed to prune their dendrites and axons (Marin, 2005).

    One of the best-studied examples of neuronal reorganization in an insect brain is the gamma neuron of Drosophila mushroom bodies (MBs). MB gamma neurons are born during embryonic and early larval stages. They send dendrites into the MB calyx and axons into larval medial and dorsal MB axon lobes. During early metamorphosis, gamma neurons prune their larva-specific dendrites and axon branches before re-extending adult-specific processes. What happens to their synaptic partners while MB gamma neurons reorganize their dendrites and axons? In this study, it was shown that a subset of olfactory projection neurons -- the major presynaptic partners of MB gamma neurons -- are also morphologically differentiated to function in both larva and adult. The reorganization of these neurons during metamorphosis is independently controlled by some of the same molecular mechanisms as that of the MB gamma neurons (Marin, 2005).

    In the adult fly, odors are detected by olfactory receptors (ORs) on the dendrites of about 1300 olfactory receptor neurons (ORNs) in the antennae and maxillary palps. In general, each ORN appears to express one of ~45 possible OR types, and the axons of all ORNs expressing a given OR converge to one of ~45 stereotypical glomeruli in the antennal lobe (AL), the equivalent of the mammalian olfactory bulb. From there, 150-200 projection neurons (PNs) relay olfactory activity to higher brain centers, the MB calyx and the lateral horn (LH) of the protocerebrum. Systematic clonal analysis using the MARCM method to label single and clonally related clusters of PNs that express the GAL4 driver GH146 revealed that these PNs are prespecified by lineage and birth order to receive input via their dentrites from particular glomeruli in the adult AL. Moreover, each glomerular class of PNs exhibits a characteristic axon branching pattern in the LH, suggesting stereotyped targets in at least one higher olfactory center (Marin, 2005).

    The Drosophila larval olfactory system is much smaller and simpler by comparison, shown to consist of only 21 ORNs in the dorsal organ and believed to include ~50 PNs relaying information to the larval MB and LH. Developmental analysis has shown that the PNs born during larval stages exhibit only a single unbranched process from the cell body to the MB calyx until early metamorphosis, when dendrites and axon terminal branches start to elaborate. Thus, larval-born PNs do not participate in the larval olfactory circuit (Marin, 2005).

    What, then, is the origin of the relay interneurons that connect the larval AL to higher olfactory centers? Do they contribute to the adult olfactory system as well? This study shows that, in contrast to the larval-born PNs, PNs generated during embryogenesis exhibit morphologically differentiated dendrites and axons in both larva and adult. These neurons prune their processes locally during the first few hours of metamorphosis and later re-extend them to innervate developing adult structures. This pruning process is regulated by ecdysone and TGFß signaling, as has been demonstrated previously for MB gamma neurons. Thus, developmentally programmed remodeling allows these embryonic-born PNs to participate in two distinct olfactory circuits at two different stages in the Drosophila life cycle (Marin, 2005).

    The MARCM method allows the labeling of a single neuron, or all neurons born from the same neuroblast, that express a particular GAL4 driver. These studies focus on the ~90 (out of an estimated total 150-200) PNs that express GAL4-GH146. A heatshock-promoter-driven FLP recombinase was used to control the timing of the mitotic recombination that results in labeled MARCM clones. In a previous study (Jefferis, 2004), at least one GAL4-GH146-positive PN was identified that could only be labeled by heatshock-induced mitotic recombination during embryogenesis. This embryonic-born PN specifically targeted its dendrites to glomerulus VA2, one of many glomeruli innervated when labeling the entire population of GH146 PNs, yet never by PN single-cell or neuroblast clones labeled by heatshock during larval stages. This discrepancy in the number of innervated glomeruli suggested that a fraction of adult AL glomeruli were being targeted by a subset of PNs born during embryogenesis (Marin, 2005).

    To study the embryonic-born neurons labeled by the GH146 driver, MARCM clones were systematically generated by heatshock induction at embryonic stages. Large anterodorsal neuroblast clones labeled by heatshock early in embryogenesis innervated at least 15 glomeruli not targeted by either the anterodorsal or lateral neuroblast clones labeled by heatshocking newly hatched larvae. MARCM single-cell clones were used to characterize embryonic-born PNs that innervate eight different landmark glomeruli in the adult AL. The gross morphology of these PNs in the adult brain is quite similar to that of the larval-born PNs previously described: each PN generally innervates a single glomerulus in the antennal lobe (distinct from those innervated by larval-born PNs), then sends its axon via the inner antennocerebral tract to display a characteristic terminal branching pattern in the LH according to its glomerular class, along with a number of collaterals in the MB calyx that end in prominent boutons (Marin, 2005).

    By comparing the specific glomeruli innervated in each partial anterodorsal neuroblast clone generated by heatshock at different times during embryogenesis, it was ascertained that: (1) these embryonic-born PNs were generated in the order DP1m, VL2p, VA6, VA2, DL5, DM3, VM3 and finally DL6, and (2) every clone labeled by embryonic heatshock included all of the larval-born anterodorsal PNs analyzed in the previous study, indicating that both PN subsets originate from the same neuroblast. Upon generation of the DL6 PN(s), the anterodorsal neuroblast apparently arrests, producing additional projection neurons later only in larval life (as indicated by heatshock-induced labeling of just a single anterodorsal glomerular class, DL1, until about 36 hours after larval hatching) (Marin, 2005).

    In summary, embryonic-born PNs look just like larval-born PNs with regard to both their dendritic and axonal projections in the adult brain. Moreover, since their dendrites target a distinct subset of AL glomeruli and their axons exhibit characteristic terminal branching patterns in the LH according to their glomerular classes, these embryonic-born PNs serve to expand the repertoire of odor representation in adults beyond the larval-born PNs previously characterized (Marin, 2005).

    Given their early origin, these GH146-positive embryonic-born PNs may participate in the larval olfactory circuit as well. Indeed, examining third instar larval brains reveals that GH146 is strongly expressed in presumptive projection neurons that appear to innervate the larval AL and to send axons up to the MB calyx and larval equivalent of the adult LH. These projections appear to be contributed by about 16 to 18 clustered neurons that are presumably derived from the anterodorsal neuroblast (Marin, 2005).

    To examine the morphology and connectivity of these PNs in the larval olfactory system with greater resolution, the MARCM method was used to specifically label PNs generated prior to larval hatching and brains were dissected from wandering third instar larvae. In contrast to the larval-born PNs analyzed in earlier studies (Jefferis, 2004), all anterodorsal embryonic-born PNs exhibited densely branched dendrites in the larval AL and axons with large synaptic structures targeting glomerulus-like subregions in the MB calyx as well as branches in the presumptive LH. The large majority of the anterodorsal embryonic-born PNs each targeted a single glomerulus in the LAL and/or in the MB. In some cases, individual PNs targeted two glomeruli in one or both structures (Marin, 2005).

    Several lines of evidence suggest that the embryonic-born PNs observed in the larval olfactory system are the same cells as the PNs that contribute to the much larger and more complex adult circuit. (1) The frequencies of labeled single-cell clones are comparable between the two stages, arguing against the possibilities that embryonic-born PNs are either dying off during metamorphosis or remaining quiescent and undetected through larval life. (2) The numbers of GH146-positive PNs observed at the time of puparium formation and in the adult are similar. (3) Most importantly, each embryonic-born PN undergoes characteristic morphological changes during metamorphosis. Therefore, the PNs labeled by embryonic heatshock are referred to as persistent projection neurons (PPNs). However, at this point, the methods do not allow correlation of specific glomerular classes in larva with those observed later in adulthood (Marin, 2005).

    Prior studies have used MB gamma neurons as a model system to study the molecular mechanisms of axon pruning. γ neuron pruning depends on cell-autonomous reception of the steroid hormone ecdysone; single neurons that are homozygous mutant for the ecdysone co-receptor ultraspiracle (usp) in an otherwise heterozygous brain fail to reorganize their processes and retain both dorsal and medial axon lobes in the adult brain. In addition, gamma neurons must upregulate the expression of ecdysone receptor isoform B1 (EcRB1) prior to axon pruning. This upregulation requires TGFß signaling; MB gamma neurons that are mutant for the TGFß/Activin Type I receptor baboon (babo) or its downstream effector mad do not upregulate EcRB1 expression and consequently fail to prune (Marin, 2005 and references therein).

    It was asked whether a similar molecular pathway is utilized during PPN reorganization. To ascertain whether the pruning of PPNs is also regulated by ecdysone, EcRB1 expression patterns were analzyed. At puparium formation, only 20 of the ~90 GH146+ projection neurons present were strongly positive for EcRB1. These strongly stained PNs, ~18 of which belonged to the anterodorsal cluster, also had noticeably larger and brighter cell bodies than surrounding PNs, which were probably immature larval-born PNs. Single-cell MARCM clones generated by embryonic heatshock were also strongly positive for EcRB1 at puparium formation. Thus, it is concluded that EcRB1 expression is highly expressed in PPNs at the onset of metamorphosis (Marin, 2005).

    Is TGFβ signaling generally required to regulate expression of EcRB1 for neuronal pruning during metamorphosis? MARCM was used to label cells that were homozygous for the strongest baboon allele, baboFd4, in a heterozygous background to test whether PPNs also require TGFß reception for normal pruning. At the wandering third instar stage, PPNs homozygous for baboFd4 appeared to have normal dendritic and axonal projections. However, baboFd4 PPNs failed to show high-level expression of EcRB1 by the onset of puparium formation. This result indicates that, as for the MB gamma neurons, high-level expression of EcRB1 in remodeling PPNs depends on TGFß signaling (Marin, 2005).

    Consistent with the loss of EcRB1 expression, baboFd4 PPNs fail to reorganize their processes normally during the first few hours of metamorphosis. For wild-type PPNs at 8 hours APF, approximately 95% of dendrites, 80% of MB calyx processes, and 85% of LH processes are in the final two stages of pruning. However, most of the embryonic-born baboFd4 PPNs still retain dendrites and axons with larval morphology at this time. Dense dendritic processes were visible in the larval AL for 100% of PN clones examined, and only 14% of axon branches in the LH appeared to resemble the final two stages of pruning. The degree of pruning in the calyx was more difficult to estimate, due to the concurrent degeneration of gamma MB neuron dendrites and loss of glomerular organization, but disappearance of synaptic boutons still seemed inhibited (Marin, 2005).

    To confirm that this failure to prune resulted from loss of ecdysone signal reception, MARCM was used to label PPNs that were homozygous for a well-characterized mutant allele of the ecdysone co-receptor, usp3. At the wandering third instar stage, usp3 PPNs exhibit normal morphology, and, as expected, EcRB1 was expressed at wild-type levels at the time of puparium formation (Marin, 2005).

    However, when these brains were examined at 8 hours APF, a significant defect in dendrite and axon pruning was observed. In the majority of cases, both dendritic densities in the location of the larval antennal lobe and axon branches in the MB calyx and LH had been retained. Taken together, these mosaic experiments suggest that PPN dendritic and axonal pruning require cell-autonomous function of EcRB1/USP, as has been shown previously for MB gamma neurons (Marin, 2005).

    What are the consequences for the adult olfactory circuit when larval circuits fail to prune? PPNs homozygous for usp3 or baboFd4 that failed to prune their dendrites and axons during metamorphosis allowed investigation of this question. When examined in adults, wild-type PPN dendrites were confined to a single glomerulus in the adult AL with the exception of the VL2p+ class. Dendrites of single-cell PPN clones homozygous for usp3 generally appeared to target glomeruli in the adult AL appropriate for PPNs; however, ectopic processes in additional areas of the AL, which could be interpreted as persisting larval dendrites, were often present. In a few cases, usp3 PPN dendrites were sparser and less specifically targeted to particular glomeruli, but still remained somewhat confined to certain regions of the AL. Likewise, whereas wild-type PPNs always exhibit terminal swellings on short side branches, about 40% of usp3 PPNs retained larval-like boutons directly on their main trunks in the MB calyx; however, they always had side branches with terminal swellings as well, implying that re-extension and adult-specific outgrowth were not completely impaired. In addition, the main axon trunk often diverted conspicuously from the inner antennocerebral tract in the MB calyx, presumably to maintain contact with the larval boutons. Nearly all usp3 PPN axons exhibited grossly wild-type morphologies in adult LH; only one usp3 PPN axon in the sample failed to enter the LH. In summary, usp3 PPNs display ectopic processes in AL and MB that appear to be due to defects in pruning during early metamorphosis; these pruning defects do not seem to interfere with the growth or even targeting (in the case of AL) of adult-specific processes (Marin, 2005).

    In comparison, baboFd4 PPNs exhibited more severe dendritic and axonal phenotypes in the adult brain. In a few cases, these PPNs had targeted an appropriate glomerulus but also featured ectopic processes. More commonly, sparse diffuse processes were observed in the AL that were somewhat localized but did not appear to target any specific glomerulus. Processes also occasionally strayed to arborize outside the ventral AL. In the most severe cases, sparse dendrites were distributed broadly throughout the AL. In the MB calyx, all baboFd4 PPN axons appeared to have retained large larval-like boutons directly on their main trunks, rather than exclusively terminal swellings on short side branches as in wild type; in 64% of cases, there were no MB collaterals with wild-type adult appearance at all. The main axon trunk often diverged dramatically from the inner antennocerebral tract in the MB calyx. Finally, in the LH, the majority of baboFd4 PPNs featured significant aberrations including unusually profuse swellings along the branches, failure to enter the LH and/or failure to elaborate higher order branches in the LH. These phenotypes imply an axon re-extension, pathfinding and/or targeting defect in addition to the impaired pruning observed at 8 hours APF (Marin, 2005).

    In summary, both usp3 and baboFd4 PPNs exhibit phenotypes in the adult brain consistent with blockage of pruning during early metamorphosis, including extraglomerular processes in the AL as well as large larval-like boutons on the main trunk and diversion from the inner antennocerebral tract as the axon passes through the MB calyx. However, baboFd4 PPNs also feature more severe phenotypes, particularly a complete lack of glomerular innervation and of adult-like axon collaterals with terminal swellings in the MB calyx, as well as failure to enter the LH and/or to elaborate higher order terminal branches. These latter phenotypes appear to be qualitatively different from those attributable to a simple loss of pruning, suggesting that TGFß signaling via baboon may have an additional role in re-extension and/or adult-specific targeting during metamorphosis (Marin, 2005).

    In this study, the PPNs of the Drosophila olfactory system have been shown to play analogous functions in two neural circuits at different life stages. They do so by developmentally programmed disassembly and reassembly of synaptic connections during metamorphosis. The implications of these findings for the larval and adult olfactory systems and to neural circuit reorganization are discussed below (Marin, 2005).

    Therefore, PPNs serve as relay interneurons connecting the antennal lobe to the MB calyx and the presumptive LH in larvae, just as previously characterized larval-born projection neurons do in adults. Each PPN generally targets its dendrites to one glomerular substructure in the larval AL, probably receiving input from one of the 21 olfactory receptor neurons of the dorsal organ. From there, the PPN's axon extends to higher brain centers, forming one or two large synaptic structures en passant on its way through the MB calyx to the LH. Electron microscopy studies with genetically encoded markers expressed separately in PPNs or in MB gamma neurons established that PPNs form functional synapses in the larval circuit and that MB gamma neurons are among their postsynaptic partners (Marin, 2005).

    This analysis of these PPNs in the adult olfactory circuit confirmed and extended the developmental and wiring logic derived from previous analysis of larval-born PNs. Just like larval-born PNs, embryonic-born PPNs are prespecified to target their dendrites to particular glomeruli according to their birth order. Specifically, most PPNs are derived from the same anterodorsal neuroblast that later gives rise to about half the GH146-positive PNs. Like the larval-born PNs, PPNs exhibit stereotyped terminal arborization patterns in the LH. Interestingly, in the adult AL, PPNs innervate a distinct subset of glomeruli from either their larval-born anterodorsal cousins or the projection neurons generated by the lateral neuroblast. This indicates that, in addition to relaying activity from larva-specific olfactory receptor neurons earlier in development, PPNs expand the olfactory repertoire of the adult circuit (Marin, 2005).

    In addition to serving larval-specific functions, one proposed function for larval circuits is to provide a foundation upon which adult circuits can be built. In the case of the olfactory circuit, however, previous analysis indicates that the adult-specific antennal lobes form adjacent to, but spatially distinct from, the larval antennal lobe. Analysis of PPN remodeling supports the notion that the adult circuit is constructed de novo rather than upon the larval circuit. A developmental timecourse analysis revealed that PPNs prune their dendrites and axon branches during early metamorphosis, so that only the main unbranched process from the cell body to the distal edge of the calyx remains by 12 hours APF. By contrast, the larval-born PNs begin to elaborate dendrites at the onset of puparium formation and restrict their processes to specific regions of the developing AL between 6 and 12 hours APF. Persistent projection neurons start exhibiting this type of localized dendritic outgrowth in the adjacent but distinct adult AL site only at 18 hours APF, around the time that adult-specific ORN axons arrive but prior to their invasion of the AL. This strongly implies that, far from providing contact-mediated cues for differentiating larval-born PNs, PPNs target glomeruli in the developing AL only after the larval-born PNs have established their dendritic target domains. The finding that PPN-specific glomeruli are intercalated with those targeted by dendrites of larval-born PNs, rather than occupying a spatially segregated domain in the adult antennal lobe, implies complex targeting rules in the establishment of wiring specificity of the adult circuit (Marin, 2005).

    The fact that PPNs have clearly identifiable addresses for their dendritic targeting in the adult circuit suggested an interesting question: does assembly of the adult circuit depend on the disassembly of the larval circuit? The data suggest that neuronal reorganization appears to be separable into two at least partially independent events, pruning and re-extension. Even usp3 PPNs whose larva-specific dendrites and axons appear unpruned still exhibit the random fine filopodial extensions characteristic of wild-type neurons at 8-12 hours APF, and moreover target their new dendrites to appropriate adult antennal lobe glomeruli, as well as exhibiting adult-specific axon collaterals in the MB calyx and grossly wild-type terminal branches in the LH (Marin, 2005).

    The fact that most usp3 persistent PNs still innervate appropriate glomeruli in the adult antennal lobe and have axons with adult characteristics would suggest that ultraspiracle-mediated execution of ecdysone signaling is required for pruning but not for responding to re-extension and/or targeting cues in the developing brain. However, most baboFd4 PPNs failed to target appropriately in the adult olfactory system. This difference in phenotypes may be due to differential perdurance of wild-type Usp versus Babo protein in single-cell MARCM clones and/or to differences in the severity of the alleles examined, consistent with the observation that baboFd4 PPNs show slightly more homogeneous pruning phenotypes at 8 hours APF. However, usp3 carries a missense mutation that alters an invariant arginine in the DNA-binding domain and blocks MB gamma neuron pruning completely. Thus, the possibility is favored that baboon is required for additional ultraspiracle-independent functions during metamorphosis, in the initiation of pruning, re-extension and/or targeting of adult olfactory structures (Marin, 2005).

    Ventral Cord: Walking, Flying and the Neurohormone system

    Extracting temporal relationships between weakly coupled peptidergic and motoneuronal signaling: Application to Drosophila ecdysis behavior
    Mark, B., Lai, S. L., Zarin, A. A., Manning, L., Pollington, H. Q., Litwin-Kumar, A., Cardona, A., Truman, J. W. and Doe, C. Q. (2021). Elife 10. PubMed ID: 33973523

    Neuromodulators, such as neuropeptides, can regulate and reconfigure neural circuits to alter their output, affecting in this way animal physiology and behavior. This study presents a quantitative framework to study the relationships between the temporal pattern of activity of peptidergic neurons and of motoneurons during Drosophila ecdysis behavior, a highly stereotyped motor sequence that is critical for insect growth. This study analyzed, in the time and frequency domains, simultaneous intracellular calcium recordings of peptidergic CCAP (crustacean cardioactive peptide) neurons and motoneurons obtained from isolated central nervous systems throughout fictive ecdysis behavior induced ex vivo by Ecdysis triggering hormone. The activity of both neuronal populations was found to be tightly coupled in a cross-frequency manner, suggesting that CCAP neurons modulate the frequency of motoneuron firing. To explore this idea further, a probabilistic logistic model was used to show that calcium dynamics in CCAP neurons can predict the oscillation of motoneurons, both in a simple model and in a conductance-based model capable of simulating many features of the observed neural dynamics. Finally, an algorithm was developed to quantify the motor behavior observed in videos of pupal ecdysis, and their features were compared to the patterns of neuronal calcium activity recorded ex vivo. The motor activity of the intact animal was found to be more regular than the motoneuronal activity recorded from ex vivo preparations during fictive ecdysis behavior; the analysis of the patterns of movement also allowed to identification of a new post-ecdysis phase (Pineiro, 2021).

    Temporal cohorts of lineage-related neurons perform analogous functions in distinct sensorimotor circuits
    Mark, B., Lai, S. L., Zarin, A. A., Manning, L., Pollington, H. Q., Litwin-Kumar, A., Cardona, A., Truman, J. W. and Doe, C. Q. (2021). Elife 10. PubMed ID: 33973523

    The mechanisms specifying neuronal diversity are well-characterized, yet it remains unclear how or if these mechanisms regulate neural circuit assembly. To address this, the developmental origin was mapped of 160 interneurons from seven bilateral neural progenitors (neuroblasts), and they were identified in a synapse-scale TEM reconstruction of the Drosophila larval CNS. Lineages were found to concurrently build the sensory and motor neuropils by generating sensory and motor hemilineages in a Notch-dependent manner. Neurons in a hemilineage share common synaptic targeting within the neuropil, which is further refined based on neuronal temporal identity. Connectome analysis shows that hemilineage-temporal cohorts share common connectivity. Finally, this study showed that proximity alone cannot explain the observed connectivity structure, suggesting hemilineage/temporal identity confers an added layer of specificity. Thus, this study demonstrated that the mechanisms specifying neuronal diversity also govern circuit formation and function, and that these principles are broadly applicable throughout the nervous system (Mark, 2021).

    Tremendous progress has been made in understanding the molecular mechanisms generating neuronal diversity in both vertebrate and invertebrate model systems. In mammals, spatial cues generate distinct pools of progenitors, which generate neuronal diversity in each spatial domain. The same process occurs in invertebrates like Drosophila, but with a smaller number of cells, and this process is particularly well understood. The first step occurs when spatial patterning genes act combinatorially to establish single, unique progenitor (neuroblast) identities. These patterning genes endow each neuroblast with a unique spatial identity (Mark, 2021).

    The second step is temporal patterning -- the specification of neuronal identity based on birth-order, an evolutionarily conserved mechanism for generating neuronal diversity. This study focused on Drosophila embryonic neuroblasts, which undergo a cascade of temporal transcription factors: Hunchback (Hb), Krüppel (Kr), Pdm, and Castor (Cas). Each temporal transcription factor is inherited by ganglion mother cells (GMCs) born during each expression window. The combination of spatial and temporal factors endows each GMC with a unique identity (Mark, 2021).

    The third step is hemilineage specification, which was initially characterized in Drosophila larval and adult neurogenesis, and may also be used in vertebrate neurogenesis. Hemilineages are formed by GMC asymmetric division into a pair of post-mitotic neurons; during this division, the Notch inhibitor Numb (Nb) is partitioned into one neuron (NotchOFF neuron), whereas the other sibling neuron receives active Notch signaling (NotchON neuron), thereby establishing NotchON and NotchOFF hemilineages. In summary, three mechanisms generate neuronal diversity within the embryonic central nervous system (CNS): neuroblast spatial identity, GMC temporal identity, and neuronal hemilineage identity (Mark, 2021).

    A great deal of progress has also been made in understanding neural circuit formation in both vertebrates and invertebrate model systems, revealing a multi-step mechanism. Neurons initially target their axons to broad regions (e.g., thalamus/cortex), followed by targeting to a neuropil domain (glomeruli/layer), and finally forming highly specific synapses within the targeted domain (Mark, 2021).

    Despite the progress in understanding the generation of neuronal diversity and the mechanisms governing axon guidance and neuropil targeting, how these two developmental processes are coordinated remains largely unknown. While it is accepted that the identity of a neuron is linked to its connectivity, the developmental mechanisms involved are unclear. For example, do clonally related neurons target similar regions of the neuropil due to the expression of similar guidance cues? Do temporal cohorts born at similar times show preferential connectivity? This study addressed the question of whether any of the three developmental mechanisms (spatial, temporal, hemilineage identity) are correlated with any of the three circuit-wiring mechanisms (neurite targeting, synapse localization, connectivity). This study mapped the developmental origin for 80 bilateral pairs of interneurons in abdominal segment 1 (A1) by identifying and reconstructing these neurons within a full CNS TEM volume -- this is over a quarter of the ~300 neurons per hemisegment. The unexpected observation was made that hemilineage identity determines neuronal projection to sensory or motor neuropils; thus, neuroblast lineages coordinately produce sensory and motor circuitry. In addition, it was shown that neurons with shared hemilineage-temporal identity target pre- and post-synapse localization to similar positions in the neuropil, and that hemilineage-temporal cohorts share more common synaptic partners than that produced by neuropil proximity alone. Thus, temporal and hemilineage identity plays essential roles in establishing neuronal connectivity (Mark, 2021).

    This study determined the relationship between developmental mechanisms (spatial, temporal, and hemilineage identity) and circuit assembly mechanisms (projections, synapse localization, and connectivity). To do this, both developmental and circuit features were mapped for 160 neuronal progeny of 14 neuroblast lineages in a serial section TEM reconstruction - this allows characterization neurons that share a developmental feature at single synapse resolution. It is important to note that the seven neuroblasts in this study were chosen based on successful clone generation and availability of single neuroblast Gal4 lines, and thus there should be no bias towards a particular pattern of neurite projections, synapse localization, or connectivity. The results show that individual neuroblast lineages have unique but broad axon and dendrite projections to both motor and sensory neuropil; hemilineages restrict projections and synapse localization to either motor or sensory neuropil; and distinct temporal identities within hemilineages provide additional specificity in synapse localization and connectivity. Thus, all three developmental mechanisms act combinatorially to progressively refine neurite projections, synapse localization, and connectivity (Mark, 2021).

    In mammals, clonally related neurons often have a similar location, morphology, and connectivity. In contrast, this study found that clonally related neurons project widely in the neuropil, to both sensory and motor domains, and thus lack shared morphology. Perhaps as brain size expands to contain an increasing number of progenitors, each clone takes on a more uniform structure and function. Yet the observation that each neuroblast clone had highly stereotyped projections suggests that neuroblast identity (determined by the spatial position of the neuroblast) determines neuroblast-specific projection patterns. Testing this functionally would require manipulating spatial patterning cues to duplicate a neuroblast and assay both duplicate lineages for similar projections and connectivity (Mark, 2021).

    This study found that hemilineages produce sensory and motor processing units via a Notch-dependent mechanism. Pioneering work on Drosophila third instar larval neuroblast lineages showed that each neuroblast lineage is composed of two hemilineages with different projection patterns and neurotransmitter expression. These studies were extended to embryonic neuroblasts and showed that Notch signaling determines motor versus sensory neuropil projections in all lineages examined. Surprisingly, the NotchON hemilineage always projected to the dorsal/motor neuropil, whereas the NotchOFF hemilineage always projected to the ventral/sensory neuropil. The relationship between the NotchON hemilineage projecting to the motor neuropil may be a common feature of all 30 segmental neuroblasts or it could be that the NotchON/NotchOFF provides a switch to allow each hemilineage to respond differently to dorsoventral guidance cues, with some projecting dorsally and some projecting ventrally. Analysis of additional neuroblast lineages will resolve this question. Another point to consider is the potential role of Notch in post-mitotic neurons as these experiments generated Notchintra misexpression in both newborn sibling neurons as well as mature post-mitotic neurons. Future work manipulating Notch levels specifically in mature post-mitotic neurons undergoing process outgrowth will be needed to identify the role of Notch in mature neurons, if any (Mark, 2021).

    Elegant work has identified neuropil gradients of Slit and Netrin along the mediolateral axis, Semaphorins along the dorsoventral axis, and Wnt5 along the anteroposterior axis. The finding that neurons in a hemilineage project to a common region of the neuropil strongly suggests that all neurons within a hemilineage respond in the same way to these global pathfinding cues. Conversely, the finding that neurons in different hemilineages target distinct regions of the neuropil suggests that each hemilineage expresses a different palette of guidance receptors, which enable them to respond differentially to the same global cues. For example, neurons in ventral hemilineages may express Plexin receptors to repel them from high Semaphorins in the dorsal neuropil (Mark, 2021).

    Hemilineages have not been well described in vertebrate neurogenesis. Notch signaling within the Vsx1 + V2 progenitor lineage generates NotchOFF V2a excitatory interneurons and NotchON V2b inhibitory interneurons, which may be distinct hemilineages. Interestingly, both V2a and V2b putative hemilineages contain molecularly distinct subclasses; this study raises the possibility that these subtypes arise from temporal patterning within the V2 lineage. In addition, NotchON/NotchOFF hemilineages may exist in the pineal photoreceptor lineage, where NotchON and NotchOFF populations specify cell-type identity (Mark, 2021).

    Only recently have the role of hemilineages been tested for their functional properties. In adults, activation of each larval hemilineage from NB5-2 showed similar behavioral output, whereas each hemilineage from NB6-1 elicited different behaviors. Previous work showed that the Eve+, Saaghi, and Jaam neurons are part of a proprioceptive circuit; this study shows that each class of neurons represents a hemilineage-temporal cohort. Note that the Jaam neurons process sensory input and are in a NotchOFF hemilineage, supporting the conclusion that NotchOFF hemilineages are devoted to sensory processing; the Saaghi premotor neurons are in a NotchON hemilineage consistent with their role in motor processing. Interestingly, both input and output neurons in this circuit arise from a common progenitor (NB5-2), which may generate late-born Jaam/Saaghi sibling neurons. In the future, it would be interesting to determine if other sibling hemilineages are in a common circuit to generate a specific behavior (Mark, 2021).

    The hemilineage results have several implications. First, the results reveal that sensory and motor processing components of the neuropil are being built in parallel, with one half of every GMC division contributing to either sensory or motor networks. This would be an efficient mechanism to maintain sensory/motor balance as lineage lengths are modified over evolutionary time. Second, the results suggest that looking for molecular or morphological similarities in full neuroblast clones may be misleading due to the full neuroblast clone comprising two different hemilineages. For example, performing bulk RNAseq on all neurons in a neuroblast lineage is unlikely to reveal key regulators of pathfinding or synaptic connectivity due to the mixture of disparate neurons from the two hemilineages (Mark, 2021).

    The cortex neurite length of neurons was used as a proxy for birth-order and shared temporal identity. This is thought to be a good approximation, but it clearly does not precisely identify neurons born during each of the Hb, Kr, Pdm, Cas temporal transcription factor windows. Nevertheless, there was sufficient resolution to observe that neurons with the same temporal identity clustered their pre- or postsynapses, rather than localizing them uniformly through the hemilineage neuropil domain. Interestingly, the three-dimensional location of each hemilineage temporal cohort synaptic cluster is identical on the left and right side of A1, ruling out the mechanism of stochastic self-avoidance. Other possible mechanisms include hemilineage-temporal cohorts expressing different levels of the presynapse spacing cue Sequoia or hemilineage-temporal cohorts exhibiting different responses to global patterning cues. Testing the function of temporal identity factors in synaptic tiling will require hemilineage-specific alteration of temporal identity, followed by assaying synapse localization within the neuropil (Mark, 2021).

    The results strongly suggest that hemilineage identity and temporal identity act combinatorially to allow small pools of neurons to target pre- and postsynapses to highly precise regions of the neuropil, thereby restricting synaptic partner choice. Yet precise neuropil targeting is not sufficient to explain connectivity as many similarly positioned axons and dendrites fail to form connections. The model is favored that hemilineages direct gross neurite targeting to motor or sensory neuropil, whereas temporal identity acts combinatorially with each hemilineage to direct more precise neurite targeting and synaptic connectivity. Thus, the same temporal cue (e.g., Hb) could promote targeting of one pool of neurons in one hemilineage and another pool of neurons in an adjacent hemilineage. This limits the number of regulatory mechanisms needed to generate precise neuropil targeting and connectivity for all ~600 neurons in a segment of the larval CNS (Mark, 2021).

    In conclusion, this study demonstrates how developmental information can be integrated with connectomic data. Lineage information, hemilineage identity, and temporal identity can all be accurately predicted using morphological features (e.g., number of fascicles entering the neuropil for neuroblast clones and radial position for temporal cohorts). This both greatly accelerates the ability to identify neurons in a large EM volume as well as sets up a framework in which to study development using data typically intended for studying connectivity and function. This framework is used to relate developmental mechanism to neuronal projections, synapse localization, and connectivity. Lineage, hemilineage, and temporal identity were found act sequentially to progressively refine neuronal projections, synapse localization, and connectivity, and the data supports a model where hemilineage-temporal cohorts are units of connectivity for assembling motor circuits (Mark, 2021).

    Reconstruction of motor control circuits in adult Drosophila using automated transmission electron microscopy
    Phelps, J. S., Hildebrand, D. G. C., Graham, B. J., Kuan, A. T., Thomas, L. A., Nguyen, T. M., Buhmann, J., Azevedo, A. W., Sustar, A., Agrawal, S., Liu, M., Shanny, B. L., Funke, J., Tuthill, J. C. and Lee, W. A. (2021). Cell. PubMed ID: 33400916

    To investigate circuit mechanisms underlying locomotor behavior, this study used serial-section electron microscopy (EM) to acquire a synapse-resolution dataset containing the ventral nerve cord (VNC) of an adult female Drosophila melanogaster. To generate this dataset, GridTape, a technology that combines automated serial-section collection with automated high-throughput transmission EM, was developed. Using this dataset, neuronal networks were studied that control leg and wing movements by reconstructing all 507 motor neurons that control the limbs. A specific class of leg sensory neurons was shown to synapse directly onto motor neurons with the largest-caliber axons on both sides of the body, representing a unique pathway for fast limb control. Open access is provided to the dataset and reconstructions registered to a standard atlas to permit matching of cells between EM and light microscopy data. GridTape instrumentation designs and software are provided to make large-scale EM more accessible and affordable to the scientific community (Phelps, 2021).

    Large-scale neuronal wiring diagrams at synapse resolution will be a crucial element of future progress in neuroscience. This paper presents GridTape, a technology for accelerating large-scale electron microscopy (EM) data acquisition. The power of this approach is demonstrated by acquiring a dataset encompassing an adult female Drosophila ventral nerve cord (VNC). This dataset was used to identify a monosynaptic circuit that directly links a specialized proprioceptive cell type, the bilateral campaniform sensillum (bCS) neurons, with specific motor neurons (MNs). The results highlight how EM datasets can be used to characterize cell types and guide development of cell type-specific driver lines. The public release of this dataset provides a resource for studying the circuit connectivity underlying motor control and demonstrates the rapid advances that can be powered by the GridTape approach (Phelps, 2021).

    Data acquisition remains a rate-limiting step in generating EM connectomics datasets. Manual sectioning for TEM is slow, imprecise, and unreliable. Meanwhile, SEM approaches that circumvent the need for manual sectioning have slow imaging speeds or require massive parallelization of expensive electron optics to acquire comparable datasets. GridTape builds on previous efforts toward TEM parallelization and automation, but overcomes the need for manual sectioning, allowing faster and more consistent section collection and imaging. Because imaging is nondestructive, GridTape is compatible with enhancement by post-section labeling and allows for re-imaging. By eliminating the need to separately handle thousands of fragile sections, GridTape reduces data loss and artifact frequency. This results in better alignment of sections into a coherent, high signal-to-noise image volume, leading to efficient and accurate reconstructions (Phelps, 2021).

    GridTape is also less expensive than high-throughput SEM platforms. For the current price of one commercial multi-beam SEM system, ten TEMCA-GTs can be built, and samples collected on GridTape can be distributed across microscopes for simultaneous imaging. The fixed microscope hardware costs are accompanied by consumable costs associated with support film coating (∼USD$4 per slot, or ∼$18,000 for this study), but this cost is expected to decrease due to technological improvements and economies of scale (Phelps, 2021).

    In the future, GridTape acquisition rates will increase as cameras and imaging sensors improve. Because TEM imaging is a widefield technique, imaging throughput can be increased by using larger camera arrays and brighter electron sources. Moreover, sections larger than current slot dimensions could be accommodated with wider tape and larger slots, although custom microscopes may be necessary for very large samples and slot size will depend on material properties of the support film (Phelps, 2021).

    The EM dataset presented in this study provides a public resource for understanding how the Drosophila nervous system generates behavior. An adult Drosophila VNC was chosen because it is an ideal test case for generating and validating a connectomic dataset. The circuit is genetically and electrophysiologically accessible and neurons are identifiable across individuals. The VNC is compact, containing approximately a third of the neurons in the adult CNS, but contains neuronal networks for executing complex motor behaviors. Because the brain controls behavior via descending projections to the VNC, it is critical to be able to study neuronal circuits in both the brain and the VNC at synaptic resolution. Notably, this VNC dataset complements the recent release of an EM dataset comprising the complete adult female Drosophila brain (Phelps, 2021).

    The VNC dataset was validated by automatically mapping its synapses with high accuracy, successfully registering the predicted synapse density map to a standard atlas and finding a high degree of similarity between EM and LM reconstructed neurons. A pipeline is demonstrated for identifying cells of interest in the dataset by comparing EM reconstructions to LM data. Finally, as a foundation for future work, >1,000 neuron reconstructions and their connectivity are made publicly available. Although these reconstructions were generated manually, advances in automated segmentation approaches are dramatically accelerating analysis of serial-section TEM data (Phelps, 2021).

    Flexible motor control relies heavily on feedback from proprioceptors, a class of sensory neurons that measure body position, velocity, and load. In both vertebrates and invertebrates, proprioceptive feedback is processed by the central nervous system to tune motor output. In insects, morphologically distinct subclasses of chordotonal neurons encode different features of leg movement such as position, velocity, and vibration. Campaniform sensilla encode load signals similar to mammalian Golgi tendon organs. Althoughthe main proprioceptor types are known and the signals they encode, it is now an opportune time to understand how motor circuits integrate proprioceptive inputs to control the body by mapping the complete wiring diagram of an adult Drosophila VNC (Phelps, 2021).

    EM datasets also enable the discovery of cell types and synaptic connections that may be overlooked by other methods. For instance, targeted reconstruction of sensory afferents revealed that the leg sensory neurons with the largest-caliber axons are the bCS neurons, which make direct synapses onto large-caliber leg MNs. This connection is monosynaptic and bCS inputs are specifically located near the putative MN spike initiation zone, suggesting that speed and reliability are essential for the function of these connections (Phelps, 2021).

    The unique bilateral and intersegmental projections of bCS neurons suggests that they directly influence multiple limbs on both sides of the body. This leads to several hypotheses about their function. Prior work suggested that campaniform sensilla encode information about step timing that could drive the transition between stance and swing phases of walking. However, this study observed that bCS neurons synapse onto the same MNs on both sides of the bod, suggesting they drive symmetric movements of left and right legs. This makes it unlikely that bCS neurons contribute to walking, which involves antiphase movement of contralateral legs. Instead, bCS neurons may underlie a fast reflex where multiple legs flex in response to bCS activation. CS can signal either increases or decreases in load, depending on the sensillum's placement and orientation on the leg. Therefore, bCS neuron activation could forcefully stabilize posture in response to additional weight (e.g., to prevent the body from being crushed) or to grip a surface in response to a loss of load (e.g., to prevent being blown away by a gust of wind). The genetic tools that were created to target bCS neurons will enable future analyses of their function (Phelps, 2021).

    Monosynaptic sensory-to-motor neuron connectivity is infrequent in larval Drosophila, but has been observed in other adult insects. Direct sensory feedback may be key in adults for precise control of their segmented limbs. The absence of such connections in larvae may indicate that controlling a limbless body relies less on sensory feedback and more on feedforward processing. As adult flies move much faster than larvae, another possibility is that fast monosynaptic sensory feedback is crucial for fast-moving animals. Indeed, research on escape responses has demonstrated that high-velocity movements are often controlled by the fastest neuronal pathways (Phelps, 2021).

    MNs have diverse but stereotyped functions, reflecting the array of muscles and muscle fibers they innervate. Some MNs have unique and reproducible transcription factor signatures that underlie their physiological properties and axonal morphology. These unique transcription factor patterns specify morphologies that are fairly stereotyped across animals. The results extend these findings by quantitatively demonstrating that most dendritic arborizations of leg MNs are sufficiently stereotyped to be individually identifiable by structure alone. Because the complete population of MNs controlling the two front legs was reconstructed, it was possible to show that mirror symmetry in primary neurite number and position is a systematic principle of MN populations. In contrast, sensory neurons have more redundant copies and variable copy numbers (Phelps, 2021).

    Previously, comprehensive neuronal connectivity maps were acquired for the nerve cords of other organisms including C. elegans, leeches, lampreys, and Drosophila larvae. These maps enabled a more complete understanding of how the nervous system controls locomotor rhythms underlying swimming and crawling. Less is known about the connectivity underlying motor control in limbed animals. The EM dataset presented in this study as a public resource will enable complete connectivity mapping for the circuits that control the legs and wings of an adult Drosophila. Combined with recent advances in recording activity from genetically identified VNC neurons during behavior, adult Drosophila is emerging as a powerful system for studying motor control. With these tools, it is expected that a deeper understanding of the circuit basis for complex motor control is within reach (Phelps, 2021).

    Regulation of coordinated muscular relaxation in Drosophila larvae by a pattern-regulating intersegmental circuit
    Hiramoto, A., Jonaitis, J., Niki, S., Kohsaka, H., Fetter, R. D., Cardona, A., Pulver, S. R. and Nose, A. (2021). Nat Commun 12(1): 2943. PubMed ID: 34011945

    Typical patterned movements in animals are achieved through combinations of contraction and delayed relaxation of groups of muscles. However, how intersegmentally coordinated patterns of muscular relaxation are regulated by the neural circuits remains poorly understood. This study identified Canon, a class of higher-order premotor interneurons, that regulates muscular relaxation during backward locomotion of Drosophila larvae. Canon neurons are cholinergic interneurons present in each abdominal neuromere and show wave-like activity during fictive backward locomotion. Optogenetic activation of Canon neurons induces relaxation of body wall muscles, whereas inhibition of these neurons disrupts timely muscle relaxation. Canon neurons provide excitatory outputs to inhibitory premotor interneurons. Canon neurons also connect with each other to form an intersegmental circuit and regulate their own wave-like activities. Thus, these results demonstrate how coordinated muscle relaxation can be realized by an intersegmental circuit that regulates its own patterned activity and sequentially terminates motor activities along the anterior-posterior axis (Hiramoto, 2021).

    Unc-4 acts to promote neuronal identity and development of the take-off circuit in the Drosophila CNS
    Lacin, H., Williamson, W. R., Card, G. M., Skeath, J. B. and Truman, J. W. (2020). Elife 9. PubMed ID: 32216875

    The Drosophila ventral nerve cord (VNC) is composed of thousands of neurons born from a set of individually identifiable stem cells. The VNC harbors neuronal circuits required to execute key behaviors, such as flying and walking. Leveraging the lineage-based functional organization of the VNC, this study investigated the developmental and molecular basis of behavior by focusing on lineage-specific functions of the homeodomain transcription factor, Unc-4. Unc-4 was found to function in lineage 11A to promote cholinergic neurotransmitter identity and suppress the GABA fate. In lineage 7B, Unc-4 promotes proper neuronal projections to the leg neuropil and a specific flight-related take-off behavior. It was also uncovered that Unc-4 acts peripherally to promote proprioceptive sensory organ development and the execution of specific leg-related behaviors. Through time-dependent conditional knock-out of Unc-4, it was found that its function is required during development, but not in the adult, to regulate the above events (Lacin, 2020).

    How does a complex nervous system arise during development? Millions to billions of neurons, each one essentially unique, precisely interconnect to create a functional central nervous system (CNS) that drives animal behavior. Work over several decades shows that developmentally established layers of spatial and temporal organization underlie the genesis of a complex CNS. For example, during spinal cord development in vertebrates, different types of progenitor cells arise across the dorso-ventral axis and generate distinct neuronal lineages in a precise spatial and temporal order. The pMN progenitors are located in a narrow layer in the ventral spinal cord and generate all motor neurons. Similarly, twelve distinct pools of progenitors that arise in distinct dorso-ventral domains generate at least 22 distinct interneuronal lineages. Within each lineage, neurons appear to acquire similar identities: they express similar sets of transcription factors, use the same neurotransmitter, extend processes in a similar manner and participate in circuits executing a specific behavior (Lacin, 2020).

    The adult Drosophila ventral nerve cord (VNC), like the vertebrate spinal cord, also manifests a lineage-based organization. The cellular complexity of the VNC arises from a set of segmentally repeated set of 30 paired and one unpaired neural stem cells (Neuroblasts [NBs]), which arise at stereotypic locations during early development. These individually identifiable NBs undergo two major phases of proliferation: the embryonic phase generates the functional neurons of the larval CNS, some of which are remodeled to function in the adult, and the post-embryonic phase generates most of the adult neurons. The division mode within NB lineages adds another layer to the lineage-based organization of the VNC. Each NB generates a secondary precursor cell, which divides via Notch-mediated asymmetric cell division to generate two neurons with distinct identities. After many rounds of such cell divisions, each NB ends up producing two distinct hemilineages of neurons, termed Notch-ON or the 'A' and Notch-OFF or the 'B' hemilineage. This paper focuses only on postembryonic hemilineages, which from this point on in the paper are refered to as hemilineages for simplicity. Within a hemilineage, neurons acquire similar fates based on transcription factor expression, neurotransmitter usage, and axonal projection. Moreover, neurons of each hemilineage appear dedicated for specific behaviors. For example, artificial neuronal activation of the glutamatergic hemilineage 2A neurons elicit specifically high frequency wing beating, while the same treatment of the cholinergic hemilineage 7B neurons leads to a specific take-off behavior. Thus, hemilineages represent the fundamental developmental and functional unit of the VNC (Lacin, 2020).

    Previous work has mapped the embryonic origin, axonal projection pattern, transcription factor expression, and neurotransmitter usage of essentially all hemilineages in the adult Drosophila VNC (see Lacin, 2019; Shepherd, 2019). This study leveraged this information to elucidate how a specific transcription factor, Unc-4, acts within individual hemilineages during adult nervous system development to regulate neuronal connectivity and function, and animal behavior. Unc-4, an evolutionarily conserved transcriptional repressor, is expressed post-mitotically in seven of the 14 cholinergic hemilineages in the VNC: three 'A' -Notch-ON- hemilineages (11A, 12A, and 17A) and four 'B' -Notch-OFF- hemilineages (7B, 18B, 19B, and 23B). For four of the Unc-4+ hemilineages (7B, 17A, 18B, and 23B), the neurons of the sibling hemilineage undergo cell death. For the remaining three (11A, 12A, and 19B), the neurons of the sibling hemilineage are GABAergic (Lacin, 2019). Unc-4 expression in these hemilineages is restricted to postmitotic neurons and it appears to mark uniformly all neurons within a hemilineage during development and adult life (Lacin, 2014; Lacin, 2016; Lacin, 2020 and references therein).

    This study generated a set of precise genetic tools that allowed uncovering of lineage-specific functions for Unc-4: in the 11A hemilineage, Unc-4 drives the cholinergic identity and suppresses the GABAergic fate; in the 7B hemilineage, Unc-4 promotes correct axonal projection patterns and the ability of flies to execute a stereotyped flight take-off behavior. It was also found that Unc-4 is expressed in the precursors of chordotonal sensory neurons and required for the development of these sensory organs, with functional data indicating Unc-4 functions in this lineage to promote climbing, walking, and grooming activities (Lacin, 2020).

    Using precise genetic tools, this study dissected the function of the Unc-4 transcription factor in a lineage-specific manner. Within the PNS, Unc-4 function is needed for the proper development of the leg chordotonal organ and walking behavior; whereas in the CNS, Unc-4 dictates neurotransmitter usage within lineage 11A and regulates axonal projection and flight take-off behavior in lineage 7B. Below, are discussed three themes arising from this work: lineage-specific functions of individual transcription factors, an association of Unc4+ lineages with flight, and the lineage-based functional organization of the CNS in flies and vertebrates (Lacin, 2020).

    Seven neuronal hemilineages express Unc-4 in the adult VNC, but the phenotypic studies revealed a function for Unc-4 in only two of them: in the 11A hemilineage, Unc-4 promotes the cholinergic fate and inhibits the GABAergic fate, while in the 7B hemilineage, Unc-4 ensures proper flight take-off behavior likely by promoting the proper projection patterns of the 7B interneurons into the leg neuropil. Why was no loss-of-function phenotype detected for Unc4 in most of the hemilineages in which it is expressed? A few reasons may explain this failure. First, the phenotypic analysis was limited: Neuronal projection patterns and neurotransmitter fate were detected, but not other molecular, cellular, or functional phenotypes. Unc-4 may function in other lineages to regulate other neuronal properties that were not assayed, such as neurotransmitter receptor expression, channel composition, synaptic partner choice, and/or neuronal activity. In addition, as this analysis assayed all cells within the lineage, it would have missed defects that occur in single cells or small groups of cells within the entire hemilineage. Second, Unc-4 may act redundantly with other transcription factors to regulate the differentiation of distinct sets of neurons. Genetic redundancy among transcription factors regulating neuronal differentiation is commonly observed in the fly VNC. Thus, while the research clearly identifies a role for Unc-4 in two hemilineages, it does not exclude Unc-4 regulating more subtle cellular and molecular phenotypes in the other hemilineages in which it is expressed. Similarly, pan-neuronal deletion of Unc-4 specifically in the adult did not lead to any apparent behavioral defect even though Unc-4 expression is maintained in all Unc-4+ lineages throughout adult life, suggesting that Unc-4 function is dispensable in mature neurons after eclosion under standard lab conditions. Future work will be required to ascertain whether Unc-4 functions during adult life or in more than two of its expressing hemilineages during development. Nonetheless, this work shows that Unc-4 executes distinct functions in the 7B and 11A lineages. The Hox transcription factors, Ubx, Dfd, Scr, and Antp, have also been shown to execute distinct functions in different lineages in the fly CNS, suggesting transcription factors may commonly drive distinct cellular outcomes in the context of different lineages. What underlies this ability of one transcription factor to regulate distinct cellular events in different neuronal lineages? The ancient nature of the lineage-specific mode of CNS development likely holds clues to this question. The CNS of all insects arises via the repeated divisions of a segmentally repeated array of neural stem cells whose number, ~30 pairs per hemisegment, has changed little over the course of insect evolution. Within this pattern, each stem cell possessing a unique identity based on its position and time of formation. Each stem cell lineage has then evolved independently of the others since at least the last common ancestor of insects, approximately 500 million years ago. Thus, if during evolution an individual transcription factor became expressed in multiple neuronal lineages after this time, it would not be surprising that it would execute distinct functions in different neuronal lineages. The lineage-specific evolution of the CNS development in flies, worms, and vertebrates may explain why neurons of different lineages that share specific properties, for example, neurotransmitter expression, may employ distinct transcriptional programs to promote this trait (Lacin, 2020).

    Although Unc-4 appears to have distinct functions in different lineages, this study found that an association with flight is a unifying feature among most Unc4+ interneuron lineages and motor neurons. All Unc-4+ hemilineages in the adult VNC except the 23B hemilineage heavily innervate the dorsal neuropils of the VNC, which are responsible for flight motor control and wing/haltere related behaviors, including wing-leg coordination. For example, hemilineages 7B, 11A, and 18B regulate flight take-off behavior and 12A neurons control wing-based courtship singing. In addition, most Unc-4+ motor neurons are also involved with flight - these include MN1-5, which innervate the indirect flight muscles, as well as motor neurons that innervate the haltere and neck muscles, which provide flight stabilization. Since Unc-4 is conserved from worms to humans, it is likely that Ametabolous insects, like silverfish, which are primitively wingless, also have unc-4. It has yet to be determined, though, whether in such ametabolous insects the same hemilineages express Unc-4, and hence this pattern was in place prior to the evolution of flight. This would suggest that there was some underlying association amongst this set of hemilineages that may have been exploited in the evolution of flight. Alternatively, Unc-4 may be lacking in these hemilineages prior to the evolution of flight but then its expression may have been acquired by these hemilineages as they were co-opted into a unified set of wing-related behaviors (Lacin, 2020).

    The adult fly VNC is composed of 34 segmentally repeated hemilineages, which are groups of lineally related neurons with similar features for example, axonal projection and neurotransmitter expression. These hemilineages also appear to function as modular units, each unit appears responsible for regulating particular behaviors, indicating the VNC is assembled via a lineage-based functional organization. The vertebrate spinal cord exhibits similar organization: lineally-related neurons acquire similar fates ('cardinal classes') and function in the same or parallel circuits. The similarity of the lineage-based organization in insect and vertebrate nerve/spinal cords raises the question whether they evolved from a common ground plan or are an example of convergent evolution. Molecular similarities in CNS development between flies and vertebrates support both CNS's arise from a common ground plan. For example, motor neuron identity in both flies and vertebrates, use the same set of transcription factors: Nkx6, Isl, and Lim3. Moreover, homologs of many transcription factors expressed in fly VNC interneurons, such as Eve and Lim1, also function in interneurons of the vertebrate spinal cord. Whether any functional/molecular homology is present between fly and vertebrate neuronal classes awaits comparative genome-wide transcriptome analysis and functional characterization of neuronal classes in the insect VNC and vertebrate spinal cord (Lacin, 2020).

    Electrophysiological validation of premotor interneurons monosynaptically connected to the aCC motoneuron in the Drosophila larval CNS
    Giachello, C. N. G. Zarin, A. A., Kohsaka, H., Fan, Y. N., Nose, A., Landgraf, M. and Baines, R. A. (2020). bioRxiv

    Mapping the wired connectivity of a nervous system is a prerequisite for full understanding of function. In this respect, such endeavours can be likened to genome sequencing projects. These projects similarly produce impressive amounts of data which, whilst a technical tour-de-force, remain under-utilised without validation. Validation of neuron synaptic connectivity requires electrophysiology which has the necessary temporal and spatial resolution to map synaptic connectivity. However, this technique is not common and requires extensive equipment and training to master, particularly when applied to the small CNS of the Drosophila larva. Thus, validation of connectivity in this CNS has been more reliant on behavioural analyses and, in particular, activity imaging using the calcium-sensor GCaMP. Whilst both techniques are powerful, they each have significant limitations for this purpose. This study use electrophysiology to validate an array of driver lines reported to label specific premotor interneurons that the Drosophila connectome project suggests are monosynaptically connected to an identified motoneuron termed the anterior corner cell (aCC). These results validate this proposition for four selected lines. Thus, in addition to validating the connectome with respect to these four premotor interneurons, this study highlights the need to functionally validate driver lines prior to use (Giachello, 2020).

    This approach was validated using the A27h neuron, a well-characterised cholinergic premotor interneuron that the connectome indicates is synaptically connected to aCC. Two additional cholinergic pre-motor interneurons termed A18a and A18b3. The connectome identifies A23a as a GABAergic interneuron directly presynaptic to aCC, involved in locomotion and activated in both forward and backward peristaltic waves. The connectome also identified A31k as a GABAergic interneuron, synaptically connected to aCC, which delivers proprioceptive feedback to motoneurons (Giachello, 2020).

    Regulation of subcellular dendritic synapse specificity by axon guidance cues
    Sales, E. C., Heckman, E. L., Warren, T. L. and Doe, C. Q. (2019). Elife 8. PubMed ID: 31012844

    Neural circuit assembly occurs with subcellular precision, yet the mechanisms underlying this precision remain largely unknown. Subcellular synaptic specificity could be achieved by molecularly distinct subcellular domains that locally regulate synapse formation, or by axon guidance cues restricting access to one of several acceptable targets. These models have been addressed using two Drosophila neurons: the dbd sensory neuron and the A08a interneuron. In wild-type larvae, dbd synapses with the A08a medial dendrite but not the A08a lateral dendrite. dbd-specific overexpression of the guidance receptors Unc-5 or Robo-2 results in lateralization of the dbd axon, which forms anatomical and functional monosynaptic connections with the A08a lateral dendrite. It is concluded that axon guidance cues, not molecularly distinct dendritic arbors, are a major determinant of dbd-A08a subcellular synapse specificity.

    A GABAergic Maf-expressing interneuron subset regulates the speed of locomotion in Drosophila
    Babski, H., Jovanic, T., Surel, C., Yoshikawa, S., Zwart, M. F., Valmier, J., Thomas, J. B., Enriquez, J., Carroll, P. and Garces, A. (2019). Nat Commun 10(1): 4796. PubMed ID: 31641138

    Interneurons (INs) coordinate motoneuron activity to generate appropriate patterns of muscle contractions, providing animals with the ability to adjust their body posture and to move over a range of speeds. In Drosophila larvae several IN subtypes have been morphologically described and their function well documented. However, the general lack of molecular characterization of those INs prevents the identification of evolutionary counterparts in other animals, limiting the understanding of the principles underlying neuronal circuit organization and function. This study characterized a restricted subset of neurons in the nerve cord expressing the Maf transcription factor Traffic Jam (TJ). TJ(+) neurons were found to be highly diverse and selective activation of these different subtypes disrupts larval body posture and induces specific locomotor behaviors. Finally, this study shows that a small subset of TJ(+) GABAergic INs, singled out by the expression of a unique transcription factors code, controls larval crawling speed (Babski, 2019).

    Regulation of forward and backward locomotion through intersegmental feedback circuits in Drosophila larvae
    Kohsaka, H., Zwart, M. F., Fushiki, A., Fetter, R. D., Truman, J. W., Cardona, A. and Nose, A. (2019). Nat Commun 10(1): 2654. PubMed ID: 31201326

    Animal locomotion requires spatiotemporally coordinated contraction of muscles throughout the body. This study investigate how contractions of antagonistic groups of muscles are intersegmentally coordinated during bidirectional crawling of Drosophila larvae. Two pairs of higher-order premotor excitatory interneurons present in each abdominal neuromere were identified that intersegmentally provide feedback to the adjacent neuromere during motor propagation. The two feedback neuron pairs are differentially active during either forward or backward locomotion but commonly target a group of premotor interneurons that together provide excitatory inputs to transverse muscles and inhibitory inputs to the antagonistic longitudinal muscles. Inhibition of either feedback neuron pair compromises contraction of transverse muscles in a direction-specific manner. These results suggest that the intersegmental feedback neurons coordinate contraction of synergistic muscles by acting as delay circuits representing the phase lag between segments. The identified circuit architecture also shows how bidirectional motor networks could be economically embedded in the nervous system.

    A Drosophila larval premotor/motor neuron connectome generating two behaviors via distinct spatio-temporal muscle activity
    Zarin, A. Z., Mark, B., Cardona, A., Litwin-Kumar, A. Doe, C. Q. (2019a). BioRXiv 617977

    A multilayer circuit architecture for the generation of distinct locomotor behaviors in Drosophila
    Zarin, A. A., Mark, B., Cardona, A., Litwin-Kumar, A. and Doe, C. Q. (2019b). Elife 8. PubMed ID: 31868582

    Animals generate diverse motor behaviors, yet how the same motor neurons (MNs) generate two distinct or antagonistic behaviors remains an open question. This study characterized Drosophila larval muscle activity patterns and premotor/motor circuits to understand how they generate forward and backward locomotion. All body wall MNs are activated during both behaviors, but a subset of MNs change recruitment timing for each behavior. TEM was used to reconstruct a full segment of all 60 MNs and 236 premotor neurons (PMNs), including differentially-recruited MNs. Analysis of this comprehensive connectome identified PMN-MN ‘labeled line’ connectivity; PMN-MN combinatorial connectivity; asymmetric neuronal morphology; and PMN-MN circuit motifs that could all contribute to generating distinct behaviors. A recurrent network model was generated that reproduced the observed behaviors, and used functional optogenetics to validate selected model predictions. This PMN-MN connectome will provide a foundation for analyzing the full suite of larval behaviors (Zarin, 2019a and b).

    This study reports a comprehensive larval proprioceptor-PMN-MN connectome and describes individual muscle/MN phase activity during both forward and backward locomotor behaviors. PMN-MN connectivity motifs were identified that could generate muscle activity phase relationships, and selected experimental validation was performed. Proprioceptor-PMN connectivity was identified that provides an anatomical explanation for the role of proprioception in promoting locomotor velocity, and it identifies a new candidate escape motor circuit. Finally, a recurrent network model was generated that produces the observed sequence of motor activity, showing that the identified pool of premotor neurons is sufficient to generate two distinct larval behaviors. It is concluded that different locomotor behaviors can be generated by a specific group of premotor neurons generating behavior-specific motor rhythms (Zarin, 2019a and b).

    Locomotion is a rhythmic and flexible motor behavior that enables animals to explore and interact with their environment. Birds and insects fly, fish swim, limbed animals walk and run, and soft-body invertebrates crawl. In all cases, locomotion results from coordinated activity of muscles with different biomechanical output. This precisely regulated task is mediated by neural circuits composed of motor neurons (MNs), premotor interneurons (PMNs), proprioceptors, and descending command-like neurons. A partial map of neurons and circuits regulating rhythmic locomotion have been made in mouse, cat, fish, tadpole, lamprey, leech, crayfish, and worm. These pioneering studies have provided a wealth of information on motor circuits, but with the exception of C. elegans, there has been no system where all MNs and PMNs have been identified and characterized. Thus, a comprehensive picture of how an ensemble of interconnected neurons generate diverse locomotor behaviors is missing (Zarin, 2019a and b).

    How does the Drosophila larva executes multiple behaviors, in particular forward versus backward locomotion. Are there different motor neurons used in each behavior? Are the same motor neurons used but with distinct patterns of activity determined by premotor inputs? How does the ensemble of premotor and motor neurons generate additional behaviors, such as escape behavior via lateral rolling? A rigorous answer to these questions requires both comprehensive anatomical information -- i.e., a premotor/motor neuron connectome -- and the ability to measure rhythmic neuronal activity and perform functional experiments. All of these tools are currently available in Drosophila, and this study used them to characterize the neuronal circuitry used to generate forward and backward locomotion, and how proprioception is integrated by the PMN ensemble (Zarin, 2019a and b).

    The Drosophila larva is composed of 3 thoracic (T1-T3) and 9 abdominal segments (A1-A9), with sensory neurons extending from the periphery into the CNS, and motor neurons extending out of the CNS to innervate body wall muscles. Most segments contain 30 bilateral body wall muscles that are grouped by spatial location and orientation: dorsal longitudinal (DL; includes previously described DA and some DO muscles), dorsal oblique (DO), ventral longitudinal (VL), ventral oblique (VO), ventral acute (VA) and lateral transverse (LT). Using these muscles, the larval nervous system can generate forward locomotion, backward locomotion, turning, hunching, digging, self-righting, and escape. This study focused on forward and backward locomotion. Forward crawling behavior in larvae involves a peristaltic contraction wave from posterior to anterior segments; backward crawling entails a posterior propagation of the contraction wave (Zarin, 2019a and b).

    Body wall muscles are innervated by approximately 60 MNs per segment, consisting of 28 left/right pairs that typically each innervate one muscle, and whose neuromuscular junctions have big boutons, therefore also called type-Ib MNs; two pairs of type-Is (small bouton) MNs that innervate large groups of dorsal or ventral muscles; three type II ventral unpaired median MNs that provide octopaminergic innervation to most muscles; and one or two type III insulinergic MNs innervating muscle 12. All MNs in segment A1 have been identified by backfills from their target muscles, and several have been shown to be rhythmically active during larval locomotion, but only a few of their premotor inputs have been described. Some excitatory PMNs are involved in initiating activity in their target MNs, while some inhibitory PMNs limit the duration of MN activity or produce intrasegmental activity offsets. Interestingly, some PMNs are active specifically during forward locomotion or backward locomotion. In addition, there are six pair of proprioceptor neurons in each abdominal segment (ddaE, ddaD, vpda, dmd1, dbd and vbd). They are important for promoting locomotor velocity and posture, and some of their CNS targets have been identified, but to date little is known about how or if they are directly connected to the PMN/MN circuits (Zarin, 2019a and b).

    It is a major goal of neuroscience to comprehensively reconstruct neuronal circuits that generate specific behaviors, but to date this has been done only in C. elegans. Recent studies in mice and zebrafish have shed light on the overall distribution of PMNs and their connections to several well-defined MN pools. However, it remains unknown if there are additional PMNs that have yet to be characterized, nor are their any insights into potential connections between PMNs themselves, which would be important for understanding the network properties that produce coordinated motor output. In the locomotor central pattern generator circuitry of leech, lamprey, and crayfish, the synaptic connectivity between PMNs or between PMNs and other interneurons are known to play critical roles in regulating the swimming behavior. However, it is difficult to be certain that all the neural components and connections of these circuits have been identified. Thus, the comprehensive anatomical circuitry reconstructed in this study provides an anatomical constraint on the functional connectivity used to drive larval locomotion; all synaptically-connected neurons may not be relevant, but at least no highly connected local PMN is absent from this analysis (Zarin, 2019a and b).

    The current results confirm and significantly extend previous studies of Drosophila larval locomotion. For example, a recent study has shown that the GABAergic A14a inhibitory PMN (also called iIN1) selectively inhibits MNs innervating muscle 22/LT2 (CMuG F4; CMuG refers to Co-active Muscle Group), thereby delaying muscle contraction relative to muscle 5/LO1 (CMuG F2). This study was extended by showing that A14a also disinhibits MNs in early CMuGs F1/2 via the inhibitory PMN A02e. Thus, A14a both inhibits late CMuGs and disinhibits early CMuGs. In addition, previous work has suggested that all MNs receive simultaneous excitatory inputs from different cholinergic PMNs. However, dual calcium imaging data of the A27h excitatory PMN shows that it is active during CMuG F4 and not earlier. Therefore, MNs may receive temporally distinct excitatory inputs, in addition to the previously reported temporally distinct inhibitory inputs. This study has identified dozens of new PMNs that are candidates for regulating motor rhythms; functional analysis of all of these PMNs is beyond the scope of this paper, particularly due to the additional work required to screen and identify Gal4/LexA lines selectively targeting these PMNs, but the predictions of this paper are clear and testable when reagents become available (Zarin, 2019a and b).

    MNs innervating a single Spatial Muscle Group (SMuG) belong to more than one CMuG, therefore SMuGs do not generally match CMuGs. This could be due to the several reasons: (1) MNs in each SMuGs receive inputs from overlapping but not identical array of PMNs. (2) Different MNs in the same SMuG receive a different number of synapses from the same PMN. (3) MNs in the same SMuG vary in overall dendritic size and total number of post-synapses, thereby resulting in MNs of the same SMuGs fall into different CMuGs (Zarin, 2019a and b).

    This study demonstrates that during both forward and backward crawling, most of longitudinal and transverse muscles of a given segment contract as early and late groups, respectively. In contrast, muscles with oblique or acute orientation often show different phase relationships during forward and backward crawling. Future studies will be needed to provide a biomechanical explanation for why oblique muscles -- but not longitudinal or transverse muscles -- need to be recruited differentially during forward or backward crawling. Also, it will be interesting to determine which spatial muscle groups (e.g., either or both VOs and VLs) are responsible for elevating cuticular denticles during propagation of the peristaltic wave in forward and backward crawling; if the VOs, it would mean that lifting the denticles occurs at different phases of the crawl cycle in forward and backward locomotion. Finally, understanding how the premotor-motor circuits described in this study are used to generate diverse larval motor behaviors will shed light on mechanisms underlying the multi-functionality of neuronal circuits (Zarin, 2019a and b).

    A recent study has reported that proprioceptive sensory neurons (dbd, vbd, vpda, dmd1, ddaE, and ddaD) show sequential activity during forward crawling. dbd responds to stretching and whereas the other five classes are activated by muscle contraction (Vaadia, 2019). All proprioceptors show connectivity to the tier of PMNs described in this study, and this study has identified circuit motifs that are consistent with the observed timing and excitatory function of each proprioceptor neuron. It will be of great interest perform functional experiments to test these anatomical circuit motifs for functional relevance (Zarin, 2019a and b).

    A recurrent network model accurately predicts the order of activation of specific PMNs, yet many of its parameters remain unconstrained, and some PMNs may have biological activity inconsistent with activity predicted by this model. Sources of uncertainty in the model include incomplete reconstruction of inter-segmental connectivity and descending command inputs, the potential role of gap junctions (which are not resolved in the TEM reconstruction), as well as incomplete characterization of PMN and MN biophysical properties. Recent studies have suggested that models constrained by TEM reconstructions of neuronal connectivity are capable of predicting features of neuronal activity and function in the Drosophila olfactory and visual systems, despite the unavoidable uncertainty in some model parameters. Similarly, for the locomotor circuit described in this study, it is anticipated that the addition of model constraints from future experiments will lead to progressively more accurate models of PMN and MN dynamics. Despite it's limitations, the ability for the PMN network to generate appropriate muscle timing for two distinct behaviors in the absence of any third-layer or command-like interneurons suggests that a single layer of recurrent circuitry is sufficient to generate multiple behavioral outputs, and provides insight into the network architecture of multifunctional pattern generating circuits (Zarin, 2019a and b).

    Previous work in other animal models have identified multifunctional muscles involved in more than one motor behavior: swimming and crawling in C. elegans and leech; walking and flight in locust; respiratory and non-respiratory functions of mammalian diaphragm muscle unifunctional muscles which are only active in one specific behavior in the lobster Homarus americanus; swimming in the marine mollusk Tritonia diomedea; and muscles in different regions of crab and lobster stomach. Single-muscle calcium imaging data indicates that all imaged larval body wall muscles are bifunctional and are activated during both forward and backward locomotion. It will be interesting to determine if all imaged muscles are also involved in other larval behaviors, such as escape rolling, self-righting, turning, or digging. It is likely that there are different CMuGs for each behavior, as this study has \ seen for forward and backward locomotion, raising the question of how different CMuGs are generated for each distinct behavior (Zarin, 2019a and b).

    Newly identified electrically coupled neurons support development of the Drosophila giant fiber model circuit
    Kennedy, T. and Broadie, K. (2018). eNeuro 5(6). PubMed ID: 30627638

    The Drosophila giant fiber (GF) escape circuit is an extensively studied model for neuron connectivity and function. Researchers have long taken advantage of the simple linear neuronal pathway, which begins at peripheral sensory modalities, travels through the central GF interneuron (GFI) to motor neurons, and terminates on wing/leg muscles. This circuit is more complex than it seems, however, as there exists a complex web of coupled neurons connected to the GFI that widely innervates the thoracic ganglion. This study defines four new neuron clusters dye coupled to the central GFI, which were named GF coupled (GFC) 1-4. New transgenic Gal4 drivers were identified that express specifically in these neurons, and both neuronal architecture and synaptic polarity were mapped. GFC1-4 share a central site of GFI connectivity, the inframedial bridge, where the neurons each form electrical synapses. Targeted apoptotic ablation of GFC1 reveals a key role for the proper development of the GF circuit, including the maintenance of GFI connectivity with upstream and downstream synaptic partners. GFC1 ablation frequently results in the loss of one GFI, which is always compensated for by contralateral innervation from a branch of the persisting GFI axon. Overall, this work reveals extensively coupled interconnectivity within the GF circuit, and the requirement of coupled neurons for circuit development. Identification of this large population of electrically coupled neurons in this classic model, and the ability to genetically manipulate these electrically synapsed neurons, expands the GF system capabilities for the nuanced, sophisticated circuit dissection necessary for deeper investigations into brain formation (Kennedy, 2018).

    Nociceptive interneurons control modular motor pathways to promote escape behavior in Drosophila
    Burgos, A., Honjo, K., Ohyama, T., Qian, C. S., Shin, G. J., Gohl, D. M., Silies, M., Tracey, W. D., Zlatic, M., Cardona, A. and Grueber, W. B. (2018). Elife 7. PubMed ID: 29528286

    Rapid and efficient escape behaviors in response to noxious sensory stimuli are essential for protection and survival. Yet, how noxious stimuli are transformed to coordinated escape behaviors remains poorly understood. In Drosophila larvae, noxious stimuli trigger sequential body bending and corkscrew-like rolling behavior. A population of interneurons in the nerve cord of Drosophila, termed Down-and-Back (DnB) neurons, was identified that are activated by noxious heat, promote nociceptive behavior, and are required for robust escape responses to noxious stimuli. Electron microscopic circuit reconstruction shows that DnBs are targets of nociceptive and mechanosensory neurons, are directly presynaptic to pre-motor circuits, and link indirectly to Goro rolling command-like neurons. DnB activation promotes activity in Goro neurons, and coincident inactivation of Goro neurons prevents the rolling sequence but leaves intact body bending motor responses. Thus, activity from nociceptors to DnB interneurons coordinates modular elements of nociceptive escape behavior (Burgos, 2018).

    Nocifensive escape behavior in Drosophila larvae consists of C-shaped body bending and rolling, followed by rapid forward crawling. Recent studies have begun to identify circuits that mediate nocifensive behaviors. Prior work identified Basin neurons as multisensory interneurons that drive rolling behavior in response to vibration and noxious stimuli, and identified downstream Goro as command-like neurons for rolling. This study has identified and characterized DnB interneurons that are essential for nocifensive behavior in Drosophila larvae (see Summary model for DnB neurons controlling nocifensive escape). DnB neurons are direct targets of nociceptive cIV neurons and multiple mechanosensory cell types, including cII and cIII gentle touch da neurons and es neurons. Thus, DnBs provide a potential node for multisensory integration of tactile and noxious stimuli. The convergence of input from cIII gentle-touch receptors and cIV nociceptors onto DnB neurons is reminiscent of vertebrate interneurons that receive direct excitatory input from C-fiber/A∂ nociceptors and Aβ mechanoreceptors. Based on these studies nociceptive inputs appear to be integrated with multiple mechanosensory submodalities by Basin and DnB interneurons (Burgos, 2018).

    EM reconstruction of DnB targets supported divergent major downstream circuitry. Output synapses on DnB axons converge on premotor neurons, at least some of which promote peristaltic wave propagation during locomotion. Other downstream neurons receive input from presynaptic sites on the DnB dendrite, and lead to Goro rolling command-like neurons. The spatial segregation of DnB output sites may mirror a functional segregation of downstream circuitry into bending and rolling modules. It is still unclear which muscle groups are recruited and how segments coordinate during body bending and rolling. This study provides evidence that silencing the period-positive median segmental interneuron (PMSI) cohort, which includes direct DnB targets A02g and A02e, reduces rolling behavior. PMSIs are glutamatergic inhibitory premotor neurons that terminate motor neuron bursting to regulate crawling speed. Future work to selectively silence groups of premotor neurons will help to elucidate their role in nocifensive escape downstream of DnBs. Although silencing DnB neurons slightly increased the speed of forward locomotion, overall, forward crawling remained intact. Given that peristaltic waves also consist of segmental contractions, links to premotor neurons provide candidate neurons for dual control of crawling and C-shape bending behavior. Notably, DnB neurons target motor neurons innervating LT1 muscles, which have been implicated in larval self-righting behaviors. Self-righting consists of a C-shape type body bend, and 180° turn, so it is possible that LT1 muscles facilitate curved body bends that underlie both self-righting and rolling behavior. It is noted that the impact of DnB neurons on nociceptive circuits is likely to be more broad than indicated by synaptic connections, since EM and marker expression suggest that DnB neurons are peptidergic. Identification of the putative neuropeptide expressed by DnB neurons, and physiological effects, will be an important future direction, particularly given the important role of neuropeptides in vertebrate pain pathways, and recent evidence that mechanical nociception in larvae is under peptidergic control (Burgos, 2018).

    Prior data showed that rolling is directional and is advantageous for dislodging attacking parasitoid wasps. Efficient rolling occurs coincident with deep C-shaped body bends, but the significance of these body bends for escape behavior has not been determined. DnB neural circuitry appears to be critically important for evoking body bend behavior prior to and during nocifensive rolling. Bending may provide the initial, most rapid, form of withdrawal from a noxious stimulus, and may subsequently support rolling locomotion by orienting and focusing the energy of muscle contraction into lateral thrusts. Re-orientation of denticle belts, triangle-shaped extensions of the cuticle, may also aid rapid lateral locomotion by providing substrate traction. Compromised escape rolling upon DnB inactivation may therefore arise both from weakened Goro activation and decreases in body bend angle. Understanding the circuit mechanisms that promote bending downstream of DnB neurons, and the muscle activities and physical mechanisms that underlie rolling behavior are important future aims (Burgos, 2018).

    Analysis of DnB function revealed modular control of nocifensive escape behavior, consistent with EM reconstruction data. When DnB neurons were ectopically activated C-shaped body bending was observed that was often, but not always, associated with rolling. Other, non-rolling, animals bent with minimal crawling, or bent persistently while attempting to crawl forward. These observations provided initial evidence that C-shaped bending and rolling control circuits are separable, and that nocifensive bending could be combined with other behaviors, like pausing or crawling. Loss of function data supported bending as a primary motor output of DnB activity, with probabilistic activation of rolling motor programs. These behaviors could conceivably be linked, such that reduction in bending compromises rolling ability, or could arise from parallel influence of DnB activity on bending and rolling as suggested by EM reconstruction. Consistent with an important role for DnBs in promoting rolling, silencing Goro while activating DnB neurons promoted persistent bending without rolling, and uncoordinated snake-like forward crawling. This result further implicates a separate premotor circuitry in nocifensive body bending. These data further suggest that the bend-roll sequence must be tightly regulated by interactions between the parallel bend-roll premotor circuits, such that bending occurs first to facilitate rolling, which occurs second. However, bending can occur without being followed by rolling, indicating C-shaped bending itself is not sufficient to trigger rolling. Such independent, but sequentially regulated behavioral modules are consistent with hierarchical models of sequence generation as in fly grooming, human speech, roll-crawl sequence, and hunch-bend sequence. It is noted however, that although bending and rolling are sequential, they co-occur for much of the defensive behavior sequence, in contrast to such sequential and non-overlapping behavioral sequences. Elucidating the mechanisms of timing and interaction between the different circuit modules (bend vs roll) identified therefore promises to shed light on the general mechanisms of circuit implementation of sequence generation and co-ordination between different motor modules (Burgos, 2018).

    The functional organization of descending sensory-motor pathways in Drosophila
    Namiki, S., Dickinson, M. H., Wong, A. M., Korff, W. and Card, G. M. (2018). Elife 7. PubMed ID: 29943730

    In most animals, the brain controls the body via a set of descending neurons (DNs) that traverse the neck. DN activity activates, maintains or modulates locomotion and other behaviors. Individual DNs have been well-studied in species from insects to primates, but little is known about overall connectivity patterns across the DN population. This study systematically investigated DN anatomy in Drosophila melanogaster and created over 100 transgenic lines targeting individual cell types. Roughly half of all Drosophila DNs were identified and connectivity between sensory and motor neuropils in the brain and nerve cord, respectively, were comprehensively mapped. The nerve cord was found to be a layered system of neuropils reflecting the fly's capability for two largely independent means of locomotion -- walking and flight -- using distinct sets of appendages. These results reveal the basic functional map of descending pathways in flies and provide tools for systematic interrogation of neural circuits (Namiki, 2018).

    This study systematically characterized the organization of DNs, a population of interneurons that conduct information from the brain of a fly to motor centers in the VNC. This analysis was based on the morphologies of 98 DN cell types, covering 190 bilateral pairs of neurons. To discern DN morphologies, individual neurons from driver lines targeting many cells were segmented, and also a library of 133 split-GAL4 lines were generated that sparsely target 54 DN types. By registering the morphology of all the DNs with standardized maps of the brain and VNC, three major sensory-motor pathways. One pathway links two neuropils on the posterior slope of the brain (IPS and SPS) to dorsal neuropils associated with the neck, wing, and haltere motor systems, and a second carries neurons with dendrites in the gnathal ganglion (GNG) to the leg neuromeres. The third pathway consists of DNs originating from an array of brain neuropils that converge to innervate the tectulum, a long thin region of the VNC sandwiched between the wing and leg motor neuropils (Namiki, 2018).

    The simple, tripartite anatomical pattern that was observed may reflect both the functional organization of the DNs as well as the evolutionary history of Drosophila. With the notable exception of insects (and the mythical horse, Pegasus), all flying animals use a modified foreleg as a wing. That is, an appendage originally evolved for walking was coopted for flight in pterosaurs, birds, and bats - a fact supported by the fossil record, comparative morphology, and the organization of the underlying motor circuitry. The evolution of flight was quite different in insects, because their wings and associated muscles, did not arise via sacrifice of an entire ancestral leg, and thus the novel aerial mode of locomotion did not strongly compromise the more ancient, terrestrial mode. As a result, insects are unique in possessing two somewhat independent motor systems, a fact that is elegantly manifest in the organization of the VNC and the pattern of DN innervation that was observed: the ventral leg neuromeres of flies resemble those of apterygote hexapods from which they derived, whereas the more recent wing neuropil sits atop the VNC like icing on a cake. It is speculated that the GNG-to-leg neuromere descending pathway represents a very ancient pathway and some of its member DNs may have deep homologies with other arthropod taxa, whereas the pathway linking the posterior slope neuropils to the dorsal motor neuropils of the neck, wing, and haltere are more recently evolved within insects (Namiki, 2018).

    Many behaviors such as grooming, courtship, take-off, and landing require the simultaneous use of both legs and wings. Thus, insects must have a means of coordinating activity across the two motor systems, a need that arose during or after the evolution of flight. As described more fully below, it is speculated that the teculum, and possibly the lower teculum, are neuropils that mediate this functional integration of motor actions between the two systems. The convergence of DNs into the tectulum from such a broad array of brain nuclei may reflect the high degree of sensory integration required to trigger and regulate these more complex, multi-appendage behaviors (Namiki, 2018).

    Based on PA-GFP labeling of neurons in the neck connective, ~350 DN pairs were counted. This is within the range of 200-500 DN pairs estimated in other insect species, but smaller than a value of ~550 pairs estimated in Drosophila based on backfills using a dextran dye. Part of this discrepancy can be explained by the fact that the current count excluded several specialized cell populations that were included in a previous study. These include a set of ~19 pairs of neck motor neurons, whose axons exit the neck connective posterior to the region illuminated for PA-GFP photoconversion, as well as 16 neurons selectively innervating the retrocerebral complex. One of these cells (DNd01), which innervates both the VNC and retrocerebral complex, was included. The current analysis is also likely an underestimate of the total because the nsyb-LexA driver line used to pan-neuronally express PA-GFP, may not label all neurons. For example, this line does not label the Giant Fiber. It is also possible that certain cells are harder to label using the PA-GFP approach as opposed to dextran backfills. The estimates from the two studies agree quite closely for DNs with cell bodies in the cerebral ganglia (172 in this study). Most of the discrepancy with previous studies concerns DNs in the GNG group; this study counted 180 pairs, only 51% of the number by a previous study. Taking the estimate of 350 as a lower bound and 550 an upper bound, it is estimated that the DNs described in this study represent between one third and one half of the entire population (Namiki, 2018).

    Identification of particular DN types in this study relied on the existence of a GAL4-line in the Rubin or Vienna (BrainBase) collection with sparse enough expression to recognize individual DN morphology. Additionally, most of the expression patterns that were screened were from female flies, thus the analysis would not include any potential male-specific DNs. As a result, some DNs were not found that have been reported in other studies, including the Moonwalker Descending Neuron (MDN), which controls backwards walking in flies, and pIP10/p2b, which are involved in the male courtship sequence (Namiki, 2018).

    A direct pathway was found linking the posterior slope of the brain to dorsal VNC neuropils. The posterior slope is innervated by lobula plate tangential cells (LPTCs) projecting from the optic lobe, which are excited by patterns of optic flow resulting from self-rotation. These optic flow patterns are especially relevant during flight, when the fly is able to move freely about all six degrees of freedom, and it has been suggested that LPTCs mediate both corrective steering maneuvers of the wings as well as gaze stabilization of the head. Most of the DNs in this pathway targeted all three segmental dorsal VNC neuropils, which contain neck (T1), wing (T2), or haltere (T3) motor neurons, sensory neuron projections from associated mechanoreceptors, and premotor interneurons. DN innervation of all three segmental dorsal neuropils is consistent with recent studies showing that neck and wing movements are highly correlated and suggests that the DNs of this major posterior slope-to-dorsal neuropil pathway are involved in flight control. This notion is confirmed by recent whole cell recordings from tethered flying flies showing that three members of this population are strongly correlated with compensatory visual responses, and another is involved with spontaneous turns and collision avoidance (Namiki, 2018).

    A similar pathway, in which DNs receiving inputs in the posterior slope target flight neuropil, has been observed in blowflies and flesh flies. These have been contrasted with other DNs in the protocerebrum that have anterior dendrites near the outputs of the lobula that project to ventral leg neuropils. They suggested that the posterior and anterior DN protocerebral pathways are parallel systems linked to separate photoreceptor channels that process different features of the visual scene (e.g. color vs. motion) and may be loosely analogous to the dorsal and ventral streams of the mammalian visual system. The dataset allowed evaluation of this hypothesis in Drosophila by examining the subset of 42 DNs with dendrites in the protocerebrum. In keeping with the observations from large fly species, examples were found in which a DN with more posterior dendrites (e.g. DNg02) projected to the dorsal part of the VNC, whereas a DN with anterior dendrites (e.g. DNg13) projected to the ventral leg neuropils. It was also found that the median location of a DN's dendrites along anterior-posterior axis largely predicted whether its axons targeted dorsal or ventral leg neuropil (although see exceptions DNb01, DNb06, DNp07, and DNp18). However, the dendritic locations of DNs projecting to the dorsal and leg neuropils of the VNC were not segregated into separable, parallel groups, but instead form a continuous pattern of innervation in the protocerebrum. That is, the DN representation is graded in the protocerebrum, at least at the level of resolution of the analysis. Furthermore, the dendritic arbors of many DNs are broad enough that they sample from both anterior and posterior regions of the protocerebrum, suggesting that many DNs integrate information from both the lobula and lobula plate. Rather than the two separate parallel pathways suggested previously - one carrying visual information from the lobula plate to the wing neuropil and the other carrying information from the lobula to the leg neuropil - it is proposed that there is a mixing of this visual information in the protocerebrum, possibly in a graded manner along the anterior-posterior axis. A similar divergence and convergence of connectivity has been described in the brainstem of mice. Brainstem nuclei differentially address spinal circuits, forming exclusive connections either with forelimbs, hindlimbs, or both with differing connection strength (Namiki, 2018).

    Among all DNs targeting the wing neuropil, evidence was found for at least two distinct control systems, one entering the neuropil from a dorsal tract and targeting the dorsal and medial portion of the wing neuropil layer, where power muscle motor neuron dendrites reside, and one entering the neuropil from a more ventral tract and invading primarily the ventral and medial wing neuropil, where many steering muscle motor neurons dendrites reside. In Drosophila, the power muscles comprise two sets of stretch activated muscles attached across the thorax orthogonally. Alternate deformation of the thoracic cavity by these muscles drives the wing stroke indirectly, powering both flight and courtship song. In contrast, the smaller steering muscles attach to the base of the wing hinge and act directly to coordinate the wing movements that change flight course, or actuate finer movement, such as the timing of song pulses. The results suggest separate descending control of the power and steering muscle systems. Outside of flight and song, flies perform a wide range of different behaviors with their wings, including grooming, aggressive displays, and preparation for takeoff. Although this study found that the posterior slope had the largest number of DNs innervating wing neuropil, a wide range of other brain neuropils, including the gnathal ganglia (GNG), VES, lobula plate (PLP), anterior mechanosensory motor center (AMMC), SAD, superior medial protocerebrum (SMP), and lateral accessory lobe (LAL), are also connected to the wing neuropil, albeit via a smaller number of DNs (see Anatomical compartments of the brain and VNC in Drosophila). These sparser pathways may be important for coordinating wing motion when the flies are not flying (Namiki, 2018).

    Despite the trend described in the previous section, in which DNs with more anterior dendrites in the protocerebrum tend to target leg neuropil, this analysis found that a different brain region, the GNG, had the strongest DN connectivity to the six ventral neuromeres of the VNC. This was true even after excluding the many DNs whose neurites are presynaptic in the GNG. Indeed, 90% (88/98) of the DN types have processes in the GNG, most of which are varicose terminals containing synaptogagmin, and thus likely output terminals. Only one-third (29/88) of DNs with processes in the GNG had dendrites in that region, two-thirds of which (18/29) target leg neuropil without any terminals in the dorsal wing, neck, or haltere neuropils (Namiki, 2018).

    Given the GNG's evolutionary history as a separate anterior segmental ganglion, it is perhaps not surprising that this neuropil is strongly connected to more posterior motor centers. The suboesophageal ganglion, which includes the GNG, is involved in a variety of behaviors, including walking, stridulation, flight initiation, head movement, and respiration. However, the GNG has been most specifically implicated in the temporal patterning of walking. For example, both supra- and subesophageal DNs are recruited in the preparatory phase before walking, whereas the activity of subesophageal DNs become predominant during the walking phase (Namiki, 2018).

    The terminals of DNs targeting the same layers of the VNC clustered together within the GNG. One intriguing possibility is that these foci represent regions in which efferent copies of descending commands to leg and wing motor centers are available to cephalic sensory circuits. This information could then be integrated directly with other descending commands within the GNG, or reciprocal connections could feed the information back to the cerebral ganglia. The GNG also receives ascending inputs from the leg neuropil, allowing further integration within this region of information regarding locomotor state or mechanosensory input. Given that the cerebral ganglia are known to have a strong inhibitory effect on walking in insects, another possibility is that some DN terminals in the GNG are inhibitory. Indeed, a recent study found that 37% of DNs express the inhibitory neurotransmitter GABA, compared to 38% that are cholinergic, and just such an inhibitory pathway from the cerebral ganglia to the GNG has been suggested based on prior behavioral experiments. For example, lesion studies have shown that walking persists when the cerebral ganglia are removed and spontaneous bouts are prolonged. In contrast, removal of the GNG reduces spontaneous walking, but prolongs flight duration. Thus it is possible that the DN pathway identified, linking the posterior slope to wing neuropil, maintains flight and inhibits walking, whereas the pathway linking the GNG to the leg neuropils maintains walking and inhibits flight. Thus, the connections within the GNG may play a critical role in action selection, at least at a coarse level (Namiki, 2018).

    DN terminals in the leg neuropils could be sorted into two major types: DNs projecting to the dorso-medial part of each neuromere (type-I) and DNs penetrating through the neuromeres via the oblique tract (type-II). Their terminal locations suggest that type-I and type-II leg DNs may have different access to leg motor neurons because the dendrites are known to form a rough myotopic map across the leg neuromere, with more proximal leg muscles having more proximal dendrites. Based on this arrangement, one possible function of the type-I leg DNs is to coordinate the direction of walking, which depends critically on the control of coxal muscles that protract and retract of the entire leg. Indeed, inverse activation of the thoraco-coxal muscle is required for switching from forward to backward walking in stick insects. In Drosophila, moonwalker DNs (MDNs) innervate the dorso-medial part of the leg neuropil and thus are classified as type-I. Activation of bilateral MDNs cause backward locomotion, whereas the unilateral activation cause backward turning toward the contralateral side. Type-II DNs running through the oblique tract have the opportunity to contact with the entire array of proximal and distal motor neurons and thus may be important for coordinated action of all leg segments. For example, the jumping part of escape takeoffs may require tension in all leg segments, even though the extrinsic muscle extending the trochanter is the primary actor for the fast takeoff mode. Consistent with this idea, type-II DNs are abundant in mesothoracic leg neuropil (DNp02, p05, p06 and p11), and it is the middle legs that flies extend during a jump. Similarly, in locust, the descending contralateral movement detector (DCMD), which is important for escape behavior, has terminals that resemble type-II and synapses directly on the motor neurons in the neuropil associated with the jumping legs (Namiki, 2018).

    A small population of nine DNs specifically project to an intermediate zone of the VNC, the lower tectulum, which occupies a volume distinct from wing and leg neuropils and which this study suggests can be distinguished from the other intermediate neuropil, the tectulum, that sits above it. Neuronal connectivity is not well described in this region, and its function is unknown. However, the observations suggest that, like the tectulum, it is an integrative area involved in both leg and wing control. For example, this region includes dendrites from both the tergotrochanteral leg motor neuron (TTMn) and a branch of a wing motor neuron that has been tentatively identified as III1. The lower teculum also contains the peripheral synapsing interneuron (PSI), which is presynaptic to motor neurons for the wing depressor muscles. The giant fiber (GF) descending neurons that drive a looming-evoked escape takeoff terminate with unbranched axons within the lower tectulum and form gap junctions with the TTMn and PSI. It was surmising that the lower tectulum may play a role during takeoff, which requires coordinated actions of the wings and legs. It is known that there are parallel pathways for take-off behavior in Drosophila, although the anatomical source has not yet been identified. A group of eight unique type DNs, in addition to the GF, were identified whose dendrites overlap with the terminals of visual projection neurons that detect looming. Most of these invade the lower tectulum and their axon terminals share some anatomical features with the GF. This population are candidates for parallel pathways for takeoff, as well as other looming-evoked evasive behaviors, and could represent circuits for wing-leg coordination (Namiki, 2018).

    No DNs were found that originate in the central complex (CX), consistent with studies in other insect species. Thus, information from the CX must be relayed to motor centers via other brain regions. A prime candidate is the the lateral accessory lobe (LAL), which has dense mutual connections with the CX and, together with the bulb (BU), is considered the CX primary output. However, many fewer DNs from the LAL were found than from other regions such as PS, PVLP or AMMC. In other insects such as silk moths, connections between the LAL and the PS are well documented. In Drosophila, connectivity between the LAL and PS is suggested by connectomics studies and the morphology of individual neurons connecting these regions has been recently described. Thus, it is suggested that information processed in the CX may descend to the VNC via a CX-LAL-PS pathway (Namiki, 2018).

    No DNs were found originating from the mushroom bodies (MB), important processing areas for olfactory and visual memory. However, there are 11 DN types innervating the superior medial protocerebrum (SMP), a major target of MB output neurons. The SMP is also well connected with the LAL, which suggests MB output also uses the major descending pathway from the posterior slope via the LAL (Namiki, 2018).

    Prior studies in insects have focused on DN function at the single neuron level. Thus, how DNs operate as a population is still unclear. Evidence in insects and other species suggests that motor directives are likely encoded across the DN population rather than in the activity of individual command neurons. For example, many DNs are active, albeit with different firing patterns, at the same time during walking in locusts, and there are multiple brain locations where electrical stimulation can trigger walking behavior in cockroaches. Also, population vector coding for object direction has been observed in the DNs of dragonflies. Zebrafish have also been shown to utilize population coding in the control of locomotion, despite having only ~220 DNs -- even fewer than Drosophila. In fact, there are very few neurons that fit the rigorous requirements of command neuron (i.e. necessary and sufficient). Even the giant fibers (a.k.a. DNp01), whose activation drives a stereotyped escape jump in response to looming stimuli, are necessary only for a particular 'fast mode' of takeoff, and the behavioral effect of their activation to naturalistic looming stimuli has been shown to depend on the timing of their spike relative to activity in other descending neurons (Namiki, 2018).

    This study found that the VNC areas receiving the largest number of DNs are the dorsal neuropils associated with flight control (neck, wing, haltere neuropils and tectulum). It has been suggested that the number of DNs engaged during a behavior might relate to the precision of the control. In mammals, for example, the number of activated corticospinal tract neurons corresponds to the degree of digital dexterity. It is possible a large DN population target flight neuropils because flight requires a high level of precise control. For example, flies can execute sophisticated rapid aerial turns to evade a looming predator, movements that are controlled by a combination of adjustments in firing phase of tonically active motor neurons and recruitment of phasically active cells (Namiki, 2018).

    In addition to the number of DNs putatively assigned to wing control, this study found that the organization of wing DNs is different than that of the DNs targeting leg neuropil. Several distinct clusters of DNs were identified with nearly identical morphologies and highly overlapped input and output projections, which are referred to as population type DNs because their similar morphology suggests they may function as a group (e.g. DNg01, g02, g03, g05 and g06). In most cases, these population DNs project to the wing neuropil or tectulum and are thus likely involved in flight. In contrast, only unique type DNs (identifiable single bilateral pairs) projecting to leg neuropil were found. This suggests that the strategy for controlling flight and walking may be fundamentally different. Because of the physics involved, even very small changes in wing motion during flight can result in large aerodynamic forces and moments. The necessity for fine control might account for the greater dependence on population coding in flight as compared to walking. Another difference between flight and walking is the temporal scale required for control. For example, wingbeat frequency is much faster than leg stepping frequency. The control of force generation by wing steering muscles depends on the precise timing of motor neuron spikes. The descending input during flight must have the capacity to regulate motor neuron firing phase on a precise temporal scale, a functionality that might be achieved via population coding. Another possibility is that the number of active DNs encodes the magnitude of a command signal to regulate continuous locomotor parameters such as speed. In larval zebrafish and lamprey, for example, more reticulospinal DNs are recruited with increasing swimming frequency. Further functional studies will be required to test whether DN encoding of flight and walking commands operates by different principles (Namiki, 2018).

    This study has analyzed the neuronal organization of descending motor pathways in Drosophila, with single-cell resolution. The wiring diagram revealed, in a genetically accessible model system, creates a framework for understanding of how the brain controls behavior. In combination with the Drosophila genetic toolkit, the driver lines created in the present study open up the possibility to directly probe the function of individual DNs during natural behavior (Namiki, 2018).

    Neuronal cell fate specification by the molecular convergence of different spatio-temporal cues on a common initiator terminal selector gene
    Stratmann, J. and Thor, S. (2017). PLoS Genet 13(4): e1006729. PubMed ID: 28414802

    The extensive genetic regulatory flows underlying specification of different neuronal subtypes are not well understood at the molecular level. The Nplp1 neuropeptide neurons in the developing Drosophila nerve cord belong to two sub-classes; Tv1 and dAp neurons, generated by two distinct progenitors. Nplp1 neurons are specified by spatial cues; the Hox homeotic network and GATA factor grn, and temporal cues; the hb -> Kr -> Pdm -> cas -> grh temporal cascade. These spatio-temporal cues combine into two distinct codes; one for Tv1 and one for dAp neurons that activate a common terminal selector feedforward cascade of col -> ap/eya -> dimm -> Nplp1. This study molecularly decodes the specification of Nplp1 neurons, and finds that the cis-regulatory organization of col functions as an integratory node for the different spatio-temporal combinatorial codes. These findings may provide a logical framework for addressing spatio-temporal control of neuronal sub-type specification in other systems (Stratmann, 2017).

    The Drosophila ventral nerve cord (VNC; defined in this study as thoracic segments T1-T3 and abdominal A1-A10) contains ~10,000 cells at the end of embryogenesis, which are generated by a defined set of ~800 neuroblasts (NBs). The Apterous neurons constitute a small sub-group of interneurons, identifiable by the selective expression of the Apterous (Ap) LIM-homeodomain factor, as well as the Eyes absent (Eya) transcriptional co-factor and nuclear phosphatase. A subset of Ap neurons express the Nplp1 neuropeptide, but can be sub-divided into the lateral thoracic Tv1 neurons, part of the thoracic Ap cluster of four cells, and the dorsal medial row of dAp neurons. In line with the distinct location of the Tv1 and dAp neurons, studies have revealed that they are generated by distinct NBs; NB5-6T and NB4-3, respectively. A number of studies have addressed the genetic mechanisms underlying the specification of the Tv1 and dAp neurons, and the regulation of the Nplp1 neuropeptide. These have revealed that two distinct spatio-temporal combinatorial transcription factor codes, one acting in NB5-6T and the other in NB4-3, converge on a common initiator terminal selector gene; collier, encoding a COE/EBF transcription factor. Col in turn is necessary and sufficient to trigger a feed forward loop (FFL) consisting of Ap, Eya and the Dimmed (Dimm) bHLH transcription factor, which ultimately activates the Nplp1 gene. Strikingly, the combinatorial coding selectivity of the spatio-temporal cues combined with the information-coding capacity of the FFL results in the selective activation of Nplp1 in only 28 out of the ~10,000 cells within the VNC. While these genetic studies have helped resolve the regulatory logic of this cell specification event, they have not addressed the molecular mechanisms by which the two different spatio-temporal combinatorial codes intersect upon the col initiator terminal selector, to trigger a common terminal FFL, or the molecular nature of the FFL (Stratmann, 2017).

    To address this issue, this study has identified enhancers for Tv and dAp neuron expression for the genes in the common Tv1/dAp FFL: col, ap, eya, dimm and Nplp1. Transgenic reporters were generated for these enhancers, both wildtype and mutant for specific transcription factor binding sites, to test their regulation in mutant and misexpression backgrounds. CRISPR/Cas9 technology was used to delete these enhancers in their normal genomic location to test their necessity for gene regulation. Strikingly, this study found that the distinct upstream spatio-temporal combinatorial codes, which trigger col expression in Tv1 versus dAp neurons, converge onto different enhancer elements in the col gene. Hence, the col Tv1 neuron enhancer is triggered by Antp, hth, exd, lbe and cas, while the dAp enhancer is triggered by Kr, pdm and grn. In contrast to this subset-specific enhancer set-up for col activation, the subsequent, col-driven Nplp1 FFL feeds onto common enhancers in each downstream gene. These findings reveal that distinct spatio-temporal cues, acting in different neural progenitors, can trigger the same FFL by converging on discrete enhancer elements in an initiator terminal selector, to thereby dictate the same ultimate neuronal subtype cell fate (Stratmann, 2017).

    This study has been able to molecularly decode the Tv1/dAp genetic FFL cascades, bolstering evidence for a complex molecular FFL, based upon sequential transcription factor binding to the downstream genes. The NB4-3 and NB5-6T neuroblasts are born in different regions of the VNC, and express different spatial determinants i.e., Antp, Lbe, Hth, Exd and Gr. As lineage progression commences, they undergo a programmed cascade of transcription factor expression; the temporal cascade. Early temporal factors Kr and Pdm integrate with Grn in NB4-3, while the late temporal factor Cas integrates with Antp, Lbe, Hth and Exd in NB5-6T, to create two distinct combinatorial spatio-temporal codes. These two codes converge on two different enhancers in the col gene, triggering Col expression, and hence the Nplp1 FFL. The FFL, in this case a so-called coherent FFL, where regulators act positively at one or several steps of a cascade, was first identified in E.coli and yeast regulatory networks, but have also been identified in C.elegans and Drosophila. Coherent FFLs can act as regulatory timing devices, exemplified by the action of col in NB5-6T: The initial expression of col in Ap cluster cells triggers a generic Ap/Eya interneuron fate in all four cells, while its downregulation in Tv2-4 and maintenance in Tv1 helps propagate the FFL leading to Nplp1 expression (Stratmann, 2017).

    This study has found that the two different spatio-temporal programs converge on col, but on different enhancer elements. However, neither enhancer element gave complete null effects when deleted. Specifically, the 6.3kb col-Tv-CRM shows robust reporter expression, overlaps with endogenous col expression, responds to the upstream mutants, and is affected by TFBS mutations. However, when deleted (generating the colΔTv-CRM mutant), it had weak effects upon endogenous col expression in NB5-6T, and no effect upon Eya and Nplp1 expression. Deletion of the col-dAp-CRM (generating the colΔdAp-CRM mutant), gave more robust effects with reduction of Col, Eya and Nplp1 in dAp cells, although the expression was not lost completely (Stratmann, 2017).

    Early developmental genes, which often are dynamically expressed, may be controlled by multiple enhancer modules, to thereby ensure robust onset of gene expression. This has been reported previously in studies of early mesodermal and neuro-ectodermal development, in which several genes i.e., twist, sog, snail are controlled by multiple distal enhancer fragments, so called 'shadow enhancers', in order to ensure reliable onset of gene expression. The shadow enhancer principle is also supported by recent findings on the Kr gene. Moreover, extensive CRM transgenic analysis, scoring thousands of fragments in transgenic flies, has also supported the shadow enhancer idea, revealing that a number of early regulators, several of which encode for transcription factors, indeed have shadow enhancers. The dichotomy between the col transgenic reporter results and the partial impact on col expression upon deletion of its Tv1 and dAp enhancers, gives reason to speculate that col may be under control of additional enhancers, some of which may be referred to as shadow enhancers (Stratmann, 2017).

    The results on the eya, ap, dimm and Nplp1 enhancer mutants stand in stark contrast to the col CRMs findings. For these four genes, the enhancer deletion resulted in robust, near null effects, on expression. It is tempting to speculate that the current findings, combined with previous studies, points to a different logic for early regulators, with highly dynamic patterns, requiring several functionally overlapping enhancers for fidelity, and late regulators and terminal differentiation genes, which may operate with one enhancer that is inactive until the pertinent combinatorial TF codes have been established (Stratmann, 2017).

    Analysis of the ap and eya enhancers indicates that Col directly interacts with these enhancers. Both of these enhancer-reporter transgenes are affected in col mutants, and can be activated by ectopic col. Moreover, mutation of one Col binding site in the ap enhancer and two sites in the eya enhancer, was enough to dramatically reduce enhancer activity. Direct action of Col on ap and eya is furthermore supported by recent data on Col genome-wide binding, using ChIP, which demonstrated direct binding of Col to these regions of ap and eya in the embryo. The regulation of ap is an excellent example of the complexity of gene regulation, and studies have identified additional enhancers controlling ap expression in the wing, muscle and brain (Stratmann, 2017).

    In contrast to regulation of ap and eya, a direct action of Col on dimm and Nplp1 is less clear. Analysis of the dimm and Nplp1 enhancers did not reveal perfectly conserved Col binding sites. Mutation of multiple non-perfect Col binding sites in the dimm enhancer did not affect reporter expression in the Ap cluster, but did however reduce levels in the dorsal Ap cells. Mutation of non-perfect Col binding sites in the Nplp1 enhancer had no impact on enhancer activity, neither in Tv1 nor dAp. These findings support a model where Col is crucial for directly activating ap and eya, which in turn directly activate dimm and Nplp1, with some involvement of Col on dimm. However, support for a direct role for Col on Nplp1 comes from RNAi studies in larvae or adult flies, showing that knockdown of col resulted in loss of Nplp1, while Ap, Eya and Dimm expression was unaffected (Stratmann, 2017).

    It is tempting to speculate that Col regulates Nplp1 not via direct interaction with its enhancer, but rather as a chromatin state modulator, keeping the chromatin around the Nplp1 locus in an accessible state, in order for Dimm, Ap and Eya to be able to access the Nplp1 gene. Support for this notion comes from studies on the mammalian Col orthologue EBF, which is connected to the chromatin remodeling complex SWI/SNF during EBF-mediated gene regulation in lymphocytes. Moreover, the central SWI/SNF component Brahma was recently identified in a genetic screen for Ap cluster neurons, and found to affect FMRFa neuropeptide expression in Tv4 without affecting Eya expression, indicating a late role in Ap cluster differentiation. Alternatively, Col may activate Nplp1 via unidentified, low affinity sites, similar to the mechanism by which Ubx regulates some of its embryonic target genes (Stratmann, 2017).

    ap encodes a LIM-HD protein, a family of transcription factors well known to control multiple aspects of terminal neuronal subtype fate, including neurotransmitter identity, axon pathfinding and ion channel expression. The current results indicate that Ap in turn acts upon dimm, and subsequently with Dimm on Nplp1. eya encodes an evolutionary well-conserved phosphatase and does not bind DNA directly, instead acting as a transcriptional co-factor. Eya (and its orthologues) have been found to interact with several transcription factors in different systems, but whether it forms complexes with Col and Ap is not known (Stratmann, 2017).

    The final transcription factor in the FFL is Dimm, a bHLH protein. Dimm is selectively expressed by the majority of neuropeptide neurons in Drosophila, and is important for expression of many neuropeptides. Intriguingly, Dimm is also both necessary and sufficient to establish the dense-core secretory machinery, found in neuropeptide neurons. Based upon these findings Dimm has been viewed as a cell type selector gene, acting to up-regulate the secretory machinery. This study found evidence for that Dimm acts directly on the Nplp1 enhancer, and this raises the possibility that Dimm is both a selector gene for the dense-core secretory machinery, and can act in some neuropeptide neurons to directly regulate specific neuropeptide gene expression (Stratmann, 2017).

    Temporal cohorts of lineage-related neurons perform analogous functions in distinct sensorimotor circuits
    Wreden, C. C., Meng, J. L., Feng, W., Chi, W., Marshall, Z. D. and Heckscher, E. S. (2017). Curr Biol 27(10): 1521-1528. PubMed ID: 28502656

    An important, but unaddressed question is whether temporal information that diversifies neuronal progeny within a single lineage also impacts circuit assembly. Circuits in the sensorimotor system (e.g., spinal cord) are thought to be assembled sequentially, making this an ideal brain region for investigating the circuit-level impact of temporal patterning within a lineage. This study used intersectional genetics, optogenetics, high-throughput behavioral analysis, single-neuron labeling, connectomics, and calcium imaging to determine how a set of bona fide lineage-related interneurons in the ventral cord contribute to sensorimotor circuitry in the Drosophila larva. Even-skipped lateral interneurons (ELs) are sensory processing interneurons. Late-born ELs contribute to a proprioceptive body posture circuit, whereas early-born ELs contribute to a mechanosensitive escape circuit. These data support a model in which a single neuronal stem cell can produce a large number of interneurons with similar functional capacity that are distributed into different circuits based on birth timing. In summary, these data establish a link between temporal specification of neuronal identity and circuit assembly at the single-cell level (Wreden, 2017).

    This study took advantage of the extremely well-characterized neuronal stem cells (neuroblasts) and their lineages in the Drosophila larval nerve cord to study lineage-circuitry relationships in a sensorimotor system. The Drosophila larval nerve cord is subdivided into a series of bilaterally symmetric segments, each of which contains 30 pairs of neuroblasts that give rise to all nerve cord neurons. This study focused on one class of bona fide sibling neurons-Even-skipped (Eve)-expressing interneurons with lateral cell body positions (ELs), a morphologically diverse set of excitatory interneurons from Neuroblast 3-3 (NB3-3) (Wreden, 2017).

    The first abdominal segment consists of left/right clusters of ten ELs that can be subdivided into two groups based on the expression of the enhancer 'R11F02'. R11F02 expresses in the lateral-most ELs and a few other cells. During neurogenesis, newly born neurons displace their older siblings away from the parent neuroblast-generating an early-to-late, medial-to-lateral spatial pattern. Thus, it was hypothesized that R11F02(+) ELs were late born. Using a panel of transcription factors to assess birth order, R11F02(+) ELs were found to express the late-born marker Nab, but not early-born markers Kruppel/Pdm2. Thus, expression of R11F02 subdivides ELs into early-born and late-born temporal cohorts. However, the functional significance of this subdivision is unknown (Wreden, 2017).

    To investigate early-born and late-born ELs, lines were used that specifically target each temporal cohort of neurons. For this study, R11F02-GAL80 were generated, that, when used with EL-GAL4, allows GAL4 to remain functional only in early-born, medial ELs. In addition, the split GAL4 lines R11F02-DBD and EL-AD was used to generate functional GAL4 in late-born, lateral ELs. Thus, the activity of each temporal cohort can be selectively manipulated (Wreden, 2017).

    The behavioral response to acute stimulation of late-born ELs was examined. Previous work (Heckscher, 2015) showed that chronic stimulation of R11F02(+) ELs caused larvae to crawl with abnormal left/right body posture, but that study did not monitor initial responses of larvae to activation. Thus, it was unknown to what extent acute activation of late-born ELs slows larval motion, as would be expected if late-born ELs process proprioceptive information. In this study a behavior rig was build to monitor behavior before, during, and after optogenetic stimulation. Larval speed was measured by calculating the distance traveled by the larval centroid over time without regard to whether the direction of movement aligned with the body axis. Immediately upon stimulation of late-born ELs, body movements became left/right uncoordinated and speed was significantly reduced. Thus, the normal activity of late-born ELs is required for normal crawling, consistent with the idea that late-born ELs process proprioceptive information (Wreden, 2017).

    It was asked whether stimulation of early-born and late-born ELs elicit similar or distinctive behavioral responses. Surprisingly, during optogenetic stimulation of early-born ELs speed transiently increased. Furthermore, all ELs were simultaneously stimulated and a transient increase was found followed by a sustained reduction in speed, which extended a previous finding that measured the later, but not initial, responses of larvae to activation of all ELs. Thus, it is likely that late-born and early-born ELs operate in distinct circuits (Wreden, 2017).

    Increases in speed upon stimulation of early-born ELs could be due either to faster crawling or to larvae initiating a distinct movement-escape rolling. Escape rolling is the fastest larval movement and can be identified both because trachea on the dorsal side of the larva disappear beneath the body and because the direction of movement is lateral to the body axis. Higher resolution imaging showed that stimulation of early-born ELs frequently elicited multiple rolls, whereas stimulation of late-born ELs rarely elicited rolling. It was asked whether stimulation of early-born ELs triggered other escape-related behaviors -- hunching, fast crawling, reversals, body bending -- and an increase in body bending was found. Thus, activation of early-born ELs robustly triggers some, but not all, escape-related behaviors (Wreden, 2017).

    Next, it was asked whether any early-born EL could be part of an escape circuit. Recently, an escape circuit has been characterized, which contains a set of roll-inducing 'Basin' interneurons (Ohyama, 2015). Furthermore, the neurons downstream of Basins have been identified in a transmission electron microscopic (TEM) volume that contains the entire larval CNS. In the current study it was asked whether any neurons that receive synapses from Basins are early-born ELs. Single-cell clones were generated of early-born ELs, and single-neuron morphology was imaged with fluorescent microscopy. Then, collection of early-born EL morphologies, as determined by light microscopy, was compared to the morphologies of neurons downstream of Basins, as determined by TEM. Three early-born ELs were found receive inputs from Basins. Thus, early-born ELs contribute functionally, and anatomically, to an escape circuit (Wreden, 2017).

    This is the first time that single-cell morphology and connectivity have been identified for a majority of lineage-related interneurons within a Drosophila larval segment. This was accomplished by determining the spatiotemporal origin of neurons that were recently annotated in a Drosophila larval brain TEM volume. Within each segment, each neuroblast gives rise to a unique set of neurons, so this study asked what features are shared among ELs because these features are excellent candidates to be encoded at the stem cell level. First, late-born ELs contribute to a proprioceptive processing circuit. All TEM-annotated, late-born ELs in segment A1 receive direct synaptic input from proprioceptors, and some also receive direct synaptic inputs from Jaam interneurons, which themselves receive a large amount of direct proprioceptive input (Heckscher, 2015). Late-born ELs and Jaams get little input from other sensory neurons (Heckscher, 2015). Second, early-born ELs contribute to a mechanosensitive circuit. The TEM-annotated, early-born ELs in segment A1 receive direct synaptic input from mechanosensitive chordotonal sensory neurons and receive direct synaptic input from Basins 1 and 3, which themselves receive a large amount of direct mechanosensory chordotonal input. These early-born ELs, Basin1, and Basin 3 receive little known input from other sensory neurons. Currently, the inputs on to the remaining early-born ELs in segment A1 are unknown. Nonetheless, a majority of ELs in segment A1 are first-order sensory processing interneurons, directly receiving sensory neuron input, and many ELs are second-order sensory processing interneurons, indirectly receiving sensory neuron input. Notably, ELs are largely silent in the absence of sensory input and are therefore likely to encode sensory information. Taken together, these functional and anatomical data suggest that NB3-3 produces many sensory processing neurons (Wreden, 2017).

    Anatomically, early-born ELs receive synapses from mechanosensitive, chordotonal sensory neurons (Mechano CHOs), whereas late-born ELs receive synapses from other sensory neurons. Thus, early-born versus late-born ELs are likely to process different stimuli. This study tested this idea by monitoring EL responses to a sound that activates chordotonals (Wreden, 2017).

    First, it was shown that sound/vibration stimulus specifically activates chordotonals. In response to sound/vibration, Drosophila larvae perform an avoidance hunch. Hunching can be identified because larvae rapidly reduce crawling speed and shorten their body. A new sound stimulus was generated using a composite of known stimuli. To validate the stimulus, the behavioral rig was adapted by adding a speaker and amplifier, the stimulus was played to larvae, and speed and body perimeter was measured over time. In response to stimulation, control larvae robustly hunched, whereas larvae lacking chordotonals did not hunch. Thus, the sound/vibration stimulus can be sensed by larvae, and the response depends on mechanosensitive chordotonal sensory neurons (Wreden, 2017).

    Next, it was asked to what extent do chordotonals and early-born and late-born ELs respond to sound/vibration. A previously described, head-fixed preparation was adapted, in which the anterior portion of the larva that contains the CNS is flattened and nearly immobilized, but the posterior is untouched. Calcium imaging monitored neuronal activity before, during, and after stimulation, and ΔF/F measured fluorescence intensity. As expected, chordotonals robustly responded to stimulation. Early-born ELs responded to stimulation with a smaller amplitude, but with a similar percentage responding in comparison to chordotonals. In contrast, late-born ELs showed little to no response. Thus, early-born versus late-born ELs differentially respond to sensory input. Furthermore, these data strongly suggest that the chordotonal-to-early-born EL connections seen in the TEM are functional, present in multiple larvae, and present in multiple segments along the anterior-posterior axis of the nerve cord (Wreden, 2017).

    This work contributes an additional concept, showing that within a temporal cohort interneurons are similar. Furthermore, in the Drosophila motor system there may be many temporal cohorts-for example, Basins, Jaams, as well as another group of neurons that contact ELs, Saaghis, may be temporal cohorts. These interneurons are morphologically similar to each other, and Basins have been explicitly hypothesized to be lineage related. Thus, the observed link between temporal patterning and functional circuit assembly may be representative of a widely occurring phenomenon (Wreden, 2017).

    How lineages contribute to neuronal circuits has been investigated in a few brain regions, none of which are sensorimotor. These studies have demonstrated that different brain regions have different lineage-circuitry relationships, which are likely to be critical for establishing region-specific functional differences. Sensorimotor systems perform a unique series of computations-sensing multiple kinds of stimuli, such as self-movement or pain, and producing adaptive motor outputs, such as locomotion or escape. This study used the Drosophila sensorimotor system to show that late-born, lineage-related ELs contribute to a proprioceptive circuit and that early-born, lineage-related ELs contribute to a mechanosensitive circuit. In both circuits, ELs are sensory processing interneurons. Thus, it appears that the NB3-3 lineage endows ELs with the capacity to processes sensory information regardless of circuit identity, and birth-timing segregates ELs into different circuits. Assembling circuitry according to these rules elucidates the developmental mechanisms that generate sensorimotor systems with the ability to process different types of sensory information in parallel (Wreden, 2017).

    Depending on context, Basin interneurons can promote multiple types of escape responses, such as rolling, hunching, and bending. Some, but not all, of these escape behaviors occur upon stimulation of early-born ELs, which are downstream of Basins. These findings raise the questions: do other members of the NB3-3 lineage promote other escape responses? Do early-born neurons from other lineages promote other escape responses? Addressing these questions will be important for the field (Wreden, 2017).

    The data support the idea that a developmental strategy for assembling sensorimotor circuits is as follows: a given neuronal stem cell can produce many neurons with similar functional capacity, which are distributed into different circuits based on birth timing. This developmental strategy may be used in other sensorimotor systems. Although the exact lineage-circuit relationship is unclear, the mammalian spinal cord provides additional examples of temporal cohorts of developmentally related neurons performing analogous functions in different circuits. For example, Renshaw cells and Ia interneurons are sequentially produced by p1 progenitors. Renshaw cells contribute to a motor neuron feedback circuit, whereas Ia interneurons contribute to a stretch reflex circuit. Despite participation in distinct circuits, Renshaw cells and Ia interneurons perform analogous functions-directly synapsing onto motor neurons and terminating firing. In addition, for extensor and flexor premotor interneurons, many of which originate from the same progenitor domain, time of neurogenesis is correlated with spatial, and inferred functional, segregation. Thus, temporal segregation of lineage-related neurons with similar functional capacities is likely to occur in evolutionarily distant species, suggesting the fundamental importance of this developmental strategy (Wreden, 2017).

    Furthermore, the data reveal a correspondence between vertebrate and Drosophila sensorimotor development. In zebrafish, early-born neurons contribute to circuits for fast escape, whereas later-born neurons contribute to circuits for refined movements. These observations led the hypothesis-circuits for fast/gross movements and neurons in these circuits develop early, whereas circuits for slow/refined movements and neurons in these circuits develop later. However, it is unclear how broadly this hypothesis applies. This study shows that similar to zebrafish, in Drosophila, early-born neurons contribute to circuits for fast escape, whereas later-born neurons contribute to circuits for proprioceptive refinement of movements. Thus, this developmental principle guiding sensorimotor circuit assembly may be conserved across species despite separation by hundreds of millions of years of evolution (Wreden, 2017).

    Takagi, S., Cocanougher, B. T., Niki, S., Miyamoto, D., Kohsaka, H., Kazama, H., Fetter, R. D., Truman, J. W., Zlatic, M., Cardona, A. and Nose, A. (2017). Divergent Connectivity of Homologous Command-like Neurons Mediates Segment-Specific Touch Responses in Drosophila. Neuron 96(6): 1373-1387 e1376. PubMed ID: 29198754 Animals adaptively respond to a tactile stimulus by choosing an ethologically relevant behavior depending on the location of the stimuli. This study investigated how somatosensory inputs on different body segments are linked to distinct motor outputs in Drosophila larvae. Larvae escape by backward locomotion when touched on the head, while they crawl forward when touched on the tail. A class of segmentally repeated second-order somatosensory interneurons, that was named Wave, was identified whose activation in anterior and posterior segments elicit backward and forward locomotion, respectively. Anterior and posterior Wave neurons extend their dendrites in opposite directions to receive somatosensory inputs from the head and tail, respectively. Downstream of anterior Wave neurons, premotor circuits were identified including the neuron A03a5, which together with Wave, is necessary for the backward locomotion touch response. Thus, Wave neurons match their receptive field to appropriate motor programs by participating in different circuits in different segments (Takagi, 2017).

    Identification of excitatory premotor interneurons which regulate local muscle contraction during Drosophila larval locomotion
    Hasegawa, E., Truman, J. W. and Nose, A. (2016). Sci Rep 6: 30806. PubMed ID: 27470675 

    Drosophila larval locomotion was used as a model to elucidate the working principles of motor circuits. Larval locomotion is generated by rhythmic and sequential contractions of body-wall muscles from the posterior to anterior segments, which in turn are regulated by motor neurons present in the corresponding neuromeres. Motor neurons are known to receive both excitatory and inhibitory inputs, combined action of which likely regulates patterned motor activity during locomotion. Although recent studies identified candidate inhibitory premotor interneurons, the identity of premotor interneurons that provide excitatory drive to motor neurons during locomotion remains unknown. This study searched for and identified two putative excitatory premotor interneurons in this system, termed CLI1 and CLI2 (cholinergic lateral interneuron 1 and 2). These neurons were segmentally arrayed and activated sequentially from the posterior to anterior segments during peristalsis. Consistent with their being excitatory premotor interneurons, the CLIs formed (GFP Reconstruction Across Synaptic Partners) (GRASP)- and ChAT-positive putative synapses with motoneurons and were active just prior to motoneuronal firing in each segment. Moreover, local activation of CLI1s induced contraction of muscles in the corresponding body segments. Taken together, these results suggest that the CLIs directly activate motoneurons sequentially along the segments during larval locomotion (Hasegawa, 2016).

    Animals perform various types of rhythmic movements such as respiration, chewing and locomotion for their survival. These rhythmic movements are thought to be regulated by neuronal circuits termed central pattern generators (CPGs). CPGs consist of interneurons and motoneurons whose rhythmic activities induce coordinated patterns of muscle contraction. Although CPGs are regulated by descending and sensory inputs, rhythms very similar to those seen in the intact animal can be generated without these inputs. Because CPGs of invertebrates and vertebrates share many characteristics, CPGs in one animal could be a model for other animals. Moreover, because CPGs show many characteristics common to other neuronal systems, CPGs could be a general model linking neuronal circuits to behaviour. Despite the efforts to elucidate the function of CPGs, their identities and functional mechanisms are not completely understood, in particular in animals with a large central nervous system (CNS). This is partly because manipulating the function of specific neurons in the neural circuits is often difficult, especially in animals with vast numbers of neurons such as mammals (Hasegawa, 2016).

    The Drosophila larva is emerging as an excellent model system for studies of CPGs because one can use sophisticated genetic methods, such as the Gal4-UAS system, to manipulate and visualize the activity of specific component neurons in a moderately sized CNS consisting of ~10,000 neurons. Larval forward locomotion is executed by the sequential contraction of muscles from the posterior to the anterior segments. Motoneurons in the ventral nerve cord (VNC) actualize the sequential muscle contraction by being activated from the posterior to the anterior segments during forward locomotion. CPGs responsible for the locomotion seem to be present in the VNC, since neuronal circuits in the thoracic and abdominal segments have been shown to be sufficient for generating the behavior. Calcium imaging of the entire CNS has visualized neurons that are active during larval locomotion including those in the brain, sub-oesophageal zone (SEZ), and the VNC16. However, the identities of these neurons are only beginning to be characterized (Hasegawa, 2016).

    Previous studies showed that motor neurons in the VNC receive both excitatory and inhibitory inputs. It is therefore likely that specific patterns of motoneuron activation are regulated by the balance and the timing of excitatory and inhibitory inputs as shown in other systems. Recently, two types of inhibitory premotor interneurons that regulate larval locomotion have been identified. PMSIs (period-positive median segmental interneurons) are glutamatergic inhibitory premotor interneurons that regulate the speed of larval locomotion. Another glutamatergic interneuron, GVLIs (glutamatergic ventro-lateral interneurons) seem to function as premotor inhibitory neurons to terminate motor bursting. In contrast, premotor interneurons that provide excitatory inputs to motor neurons during locomotion remain to be identified, although they are known to be cholinergic. A recent study identified two cholinergic descending interneurons that form putative synaptic contacts with segmental motoneurons. However, whether they are active and play roles during locomotion remains unknown (Hasegawa, 2016).

    This study sought and identified putative excitatory premotor interneurons that activate motoneurons during locomotion. These neurons, termed CLI1 and CLI2 (cholinergic lateral interneuron), are segmental interneurons that show wave-like activity during locomotion concurrent with the activity propagation of motoneurons. Consistent with CLIs being excitatory premotor neurons, these neurons form GRASP- and ChAT-positive synaptic contacts with motor neurons and are activated just before the activation of motoneurons in each segment. In addition, forced activation of these neurons locally induces the contraction of muscles. These results suggest that wave-like activity of CLIs activates motoneurons sequentially along the segments during forward locomotion (Hasegawa, 2016).

    What are the circuit mechanisms that regulate Drosophila larval locomotion? To answer this question, it is necessary first to identify the neuronal components of the circuits. Excitatory inputs are critical for the generation of locomotor rhythms in various animals. However, identities and roles of excitatory interneurons that regulate Drosophila larval locomotion are unknown. The present study sought such excitatory interneurons using calcium imaging and identified CLI1s and CLI2s as candidate interneurons that excite motor neurons. Anatomical and behavioural studies suggest that these neurons directly activate motoneurons locally in each segment during larval locomotion (Hasegawa, 2016).

    The following four lines of evidence suggest that CLIs are excitatory premotor interneurons: (i) CLIs are activated just before the activation of motoneurons in each segment during fictive locomotion, consistent with their providing excitatory drive to motoneurons. (ii) CLIs express ChAT, which synthesizes acetylcholine, a neurotransmitter known to excite motor neurons in this system. (iii) CLIs form GRASP-positive contacts with motoneurons. (iv) Local activation of CLIs results in the contraction of muscles in the corresponding body segments. Although these data are consistent with direct connection between CLIs and motoneurons, it remains possible that CLIs also excite motor neurons indirectly via other interneurons (Hasegawa, 2016).

    CLI1s and CLI2s share many morphological and functional characteristics. i) They are neighboring neurons that send axons along a common path to reach the neuropile. This suggests that they are sibling neurons derived from the same neuroblast. Consistent with this notion, they also share the expression of R47E12-Gal4. ii) They both project axons along the same fascicle in the anterior commissure and locally innervate motor neurons in the contralateral side of the CNS. iii) They both are cholinergic premotor interneurons and are activated simultaneously during forward locomotion. iv) Activation of these neurons elicits muscle contraction. Taken together, these observations suggest that CLI1s and CLI2s belong to a class of interneurons that fulfill common function(s). There are also distinct features between these two neurons. i) CLI1s innervate the medial neuropile while CLI2s innervate a lateral region, suggesting that they target distinct neurons. ii) CLI1s but not CLI2s project to the next anterior segment. iii) CLI2s are active both during forward and backward locomotion, whereas CLI1s are active only during forward locomotion. Thus, CLI1s only participate in forward locomotion and may activate motor neurons not only in the same segment but also in the next anterior segment, and thus contribute to feed-forward propagation of motor excitation. In contrast, CLI2s may act locally to excite motoneurons only in the same segment and do so both during forward and backward locomotion (Hasegawa, 2016).

    It is currently unknown what motor neurons are the targets of CLI1/2s. Dendrites of motoneurons that innervate different muscle domains form myotopic map along both antero-posterior and medio-lateral axes. The axon terminals of CLI1s are located in the medial neuropile, a region occupied by the dendrites of motoneurons innervating ventral muscles. Thus, CLI1s may form synaptic contacts with the ventral motoneurons. Similarly, candidate targets of CLI2s are dorsal motoneurons, since axon terminals of CLI2s are located in a lateral region occupied by these motoneurons. Consistent with this, it was observed that lifting of the tail, which is likely caused by dorsal muscle contraction when CLI2s but not CLI1s is activated. Moreover, CLI1s and CLI2s are activated at a similar timing as aCC in the same segment, a motor neuron that innervates a dorsal muscle and is activated simultaneously with other motor neurons innervating dorsal/ventral internal muscles. Future studies such as connectomic analyses using serial EM will determine more precisely the downstream circuits of the CLIs (Hasegawa, 2016).

    It is also important to determine in the future the upstream circuits of the CLIs. Since dendritic region of CLI1s and CLI2s partially overlap, these neurons may share common upstream neurons. In particular, because the wave-like activity of CLIs was observed in the isolated CNS that receives no sensory inputs, the activity of CLIs must be regulated by the central circuits that generate a rhythm in an autonomous manner. However, it is also possible that CLIs are activated in response to specific sensory stimulation. Recently, neuronal circuits regulating larval behavior in response to specific sensory stimuli have been identified. It will be interesting to study the link between these circuits and CLIs (Hasegawa, 2016).

    The wave-like activity of CLIs that occurs concomitant with motor activation strongly suggests that these neurons contribute to sequential activation of motor neurons along the segments during locomotion. Since these neurons are commissural neurons, they may also play a role in left-right coordination, as has been proposed for Dbx1-positive neurons in vertebrates and recently identified EL neurons in Drosophila. However, loss-of-function analyses thus far failed to reveal roles of CLIs in larval behaviors. Shibirets, tetanus toxin light chain, Kir2.1, hid and reaper, and ChAT-RNAi were used to inhibit the function of CLIs but no obvious phenotypes were observed. This could be due to insufficient silencing of these neurons by the activity manipulations. It could also be due to the redundancy in the circuit function. It should be noted in this regard that there are likely more CLIs-like neurons present in each segment. The axon terminals of CLI1 and CLI2 only cover part of the motor dendritic region, suggesting other neurons excite motor neurons not targeted by CLIs. Indeed, preliminary results obtained by the ongoing EM reconstruction of the larval CNS suggest that about 10 neurons, in the same neuroblast lineage as CLIs, send their axons locally and contralaterally to the motor region along the common path as CLI1s and CLI2s. It is likely that a group of CLIs-like neurons function in a similar manner and together excite the entire motor system. Unfortunately, direct testing of this possibility is not currently feasible due to the unavailability of Gal4 lines specific to this lineage (Hasegawa, 2016).

    Recently, research has identified two classes of segmental premotor inhibitory interneurons PMSIs and GVLIs. These neurons are activated slightly later than the motor neurons and appear to inhibit the activity of motoneurons at distinct timings during the motor cycle: PMSIs at an early phase and GVLIs at a final phase of motoneuronal activation (Kohsaka, 2014; Itakura, 2015). This study identified CLIs that are activated prior to motor neurons and appear to provide an excitatory drive to the motoneurons. These three classes of premotor interneurons likely help shape the pattern of motor activity by providing excitatory and inhibitory inputs to motoneurons at distinct phases of the motor cycle. Since there are only ~400 interneurons per hemisegment in the larval ventral nerve cord, whose connectivity is being reconstructed, it is hoped that all major classes of premotor interneurons in this system will be identified in the near future. Systematic analyses of CLIs, PMSIs, GVLIs and other premotor neurons will elucidate how the motor patterns generating distinct behaviors are shaped by the combinatorial action of premotor interneurons (Hasegawa, 2016).

    Functional genetic screen to identify interneurons governing behaviorally distinct aspects of Drosophila larval motor programs
    Clark, M. Q., McCumsey, S. J., Lopez-Darwin, S., Heckscher, E. S. and Doe, C. Q. (2016). G3 (Bethesda) 6(7): 2023-2031. PubMed ID: 27172197 

    Drosophila larval crawling is an attractive system to study patterned motor output at the level of animal behavior. Larval crawling consists of waves of muscle contractions generating forward or reverse locomotion. In addition, larvae undergo additional behaviors including head casts, turning, and feeding. It is likely that some neurons are used in all these behaviors (e.g. motor neurons), but the identity (or even existence) of neurons dedicated to specific aspects of behavior is unclear. To identify neurons that regulate specific aspects of larval locomotion, a genetic screen was performed to identify neurons that, when activated, could elicit distinct motor programs. 165 Janelia CRM-Gal4 lines--chosen for sparse neuronal expression--were used to express the warmth-inducible neuronal activator TrpA1, and a screen was carried out for locomotor defects. The primary screen measured forward locomotion velocity, and 63 lines were identified that had locomotion velocities significantly slower than controls following TrpA1 activation (28 ° C). A secondary screen was performed on these lines, revealing multiple discrete behavioral phenotypes including slow forward locomotion, excessive reverse locomotion, excessive turning, excessive feeding, immobile, rigid paralysis, and delayed paralysis. While many of the Gal4 lines had motor, sensory, or muscle expression that may account for some or all of the phenotype, some lines showed specific expression in a sparse pattern of interneurons. These results show that distinct motor programs utilize distinct subsets of interneurons, and provide an entry point for characterizing interneurons governing different elements of the larval motor program (Clark, 2016).

    A circuit mechanism for the propagation of waves of muscle contraction in Drosophila
    Fushiki, A., Zwart, M. F., Kohsaka, H., Fetter, R. D., Cardona, A. and Nose, A. (2016). Elife 5. PubMed ID: 26880545

    Animals move by adaptively coordinating the sequential activation of muscles. The circuit mechanisms underlying coordinated locomotion are poorly understood. This study reports on a novel circuit for propagation of waves of muscle contraction, using the peristaltic locomotion of Drosophila larvae as a model system. An intersegmental chain of synaptically connected neurons, alternating excitatory and inhibitory, was found to be necessary for wave propagation and active in phase with the wave. The excitatory neurons (A27h) are premotor and necessary only for forward locomotion, and are modulated by stretch receptors and descending inputs. The inhibitory neurons (GDL) are necessary for both forward and backward locomotion, suggestive of different yet coupled central pattern generators, and its inhibition is necessary for wave propagation. The circuit structure and functional imaging indicated that the commands to contract one segment promote the relaxation of the next segment, revealing a mechanism for wave propagation in peristaltic locomotion (Fushiki, 2016).

    This study discovered a circuit whose structure and function provides a mechanism for understanding forward wave propagation in peristaltic locomotion. This circuit consists of a chain of alternating excitatory and inhibitory neurons spanning all abdominal segments. The core elements of the chain include just one excitatory and one inhibitory neuron per hemisegment. The inhibitory neuron (GDL) is demonstrated to be sufficient to halt the peristalsis and to relax muscles in all segments, suggesting it is a point of coordination between forward and backward locomotion. It was further demonstrated that the excitatory neuron (A27h) is active during forward but not backward peristalsis, suggesting the existence of another excitatory circuit component critical for backward peristalsis among the synaptic partners of the GDL inhibitory neuron. This circuit defines a backbone of repeating, connected, modules for excitation and inhibition similar to those postulated in a computational model for peristalsis on the basis of behavioral observations that predicted the existence of central pattern generators (Fushiki, 2016).

    This study found that the excitatory neuron (A27h) is premotor, directly synapsing onto motor neurons of its own segment only and that control both dorsal and ventral longitudinal muscles. This suggests an explanation for the observation that in forward crawling, dorsal and ventral longitudinal muscles contract simultaneously. In backward peristalsis, however, a phase gap has been observed in the timing of dorsal and ventral muscle contraction. This decoupling could require a more complex circuit structure for backward wave propagation, and therefore suggests an explanation for the lack of an equivalent excitatory neuron in the circuit chain for backward peristalsis. This study found, however, neurons postsynaptic to the inhibitory neuron (GDL) whose anatomy and position in the circuit suggest a role in backward peristalsis. In contrast, the inhibitory neuron (GDL) itself does not synapse onto motor neurons, and therefore occupies a higher-order position in the circuit that allows its participation in both forward and backward wave propagation in peristalsis. Furthermore, the GDL axon targets the intermediate lateral neuropil, which is neither in the domain of motor neuron dendrites nor in the somatosensory domain, suggestive of a role higher-order motor coordination. Relevant for forward peristalsis, GDL disinhibits the excitation of its anterior homologs, by removing inhibition from a glutamatergic interneurons (A02j) implicated in the regulation of peristaltic speed (one of the PMSIs). A02j is presynaptic to GDLs in anterior segments (Fushiki, 2016).

    A model of peristaltic locomotion must consider the coordination of left and right hemisegments. Though this study found that the chain of alternating inhibitory and excitatory neurons runs independently on the left and right sides of the body, the excitatory neuron (A27h) presents a bilateral arbor and drives motor neurons bilaterally. The wiring diagram best supports a model of left-right coordination where excitatory neurons communicate with each other, but with the caveat that this synergy takes place by the simultaneous co-activation of the target motor neurons rather than reciprocal excitation. This model has been shown to support longer contraction episodes at the front of the wave, consistent with observations of muscle contraction in peristalsis. Independently of the timing, the fine-tuning in the intensity of left-right contractions has been shown to be under control of Even-skipped+ evolutionarily conserved neurons, which integrate both proprioceptive inputs and motor commands (Fushiki, 2016).

    The dissected larval CNS undergoes spontaneous waves of motor neuron activation at about 1/10th the normal speed. These waves occur in the absence of sensory feedback, indicating the presence of CPGs and also suggesting a role for sensory feedback in speeding up the peristaltic wave. The circuit chain of excitatory and inhibitory neurons described in this study could be a part of the CPG, and this study additionally found these neurons are modulated by proprioceptive inputs (from vpda class I dendritic arborization neuron). Given that the vpda is a stretch receptor, it would be active in the segment ahead of the wave of contraction, which is being stretched by the pull exerted by the contracting segment. Proprioceptive feedback action onto the excitatory neuron of the circuit chain could then have two simultaneous effects: promotion of the contraction in the segment ahead of the wave (via activation of A27h), and relaxation of the segment twice removed (via activation of GDL, which acts on the segment anterior to it). Two somatosensory neurons (vdaA and vdaC) were found to synapse axo-dendritically onto the premotor excitatory neuron (A27h) and axo-axonically onto the inhibitory neuron (GDL) in their own segment. Although the function of these two sensory neurons remains unclear, it is speculated that this axo-axonic, likely depolarizing, connection onto GDL reduces the membrane action potential of its axon, reducing synaptic release of GABA onto A27h in the same segment. This model refines a previous model where the proprioceptive feedback was thought to signal the successful contraction of a segment. It is suggested that, in addition, at least some of the proprioceptive feedback (vpda) facilitates wave propagation and, therefore, may underlie the reduction in speed observed in fictive crawling (Fushiki, 2016).

    In addition to the excitatory premotor interneuron A27h, this study found two other interneurons that receive direct synaptic inputs from a GDL (A02d and A08e3) and that, like A27h, also integrate inputs from stretch receptors (vpda, dbd and vbd). One interneuron (A08e3) is an Even-Skipped+ neuron that maintains left-right symmetric muscle contraction amplitude. The other (A02d) is a glutamatergic interneuron that belongs to a lineage of neurons thought to mediate speed of locomotion (one of the PMSIs). While A02d is a segment-local interneuron, proprioceptive axons span multiple segments, suggesting that a GDL can suppresses the effect of proprioceptive feedback specifically within its own segment without affecting the relay of proprioception to adjacent segments. Furthermore, A02d synapses onto a glutamatergic interneuron (A08a) thought to contribute to muscle relaxation in the wake of the peristaltic wave, which could be mediated via putative GABAergic premotor neurons (A31d). Taken together, it is suggested that one of the functions of the inhibitory neuron GDL is to gate proprioceptive feedback within its segment which has implications for the control of both speed and posture (Fushiki, 2016).

    Finally, a descending neuron from the SEZ was observed that synapses onto the excitatory neuron (A27h) of the circuit chain in all segments. This motif has been observed and modeled in the leech and crayfish, where it enables the modulation of wave propagation speed. The brain and SEZ have been deemed non-essential for wave propagation. Speed of wave propagation, therefore, may be controlled in at least two ways: by proprioceptive feedback and by descending inputs. The existence of a circuit chain formed by excitatory and inhibitory neurons might be all that remains when both sensory feedback and the brain are absent, explaining the existence of wave propagation in decerebrated animals, and even for a small set of isolated abdominal segments (Fushiki, 2016).

    Competitive disinhibition mediates behavioral choice and sequences in Drosophila
    Jovanic, T., Schneider-Mizell, C. M., Shao, M., Masson, J. B., Denisov, G., Fetter, R. D., Mensh, B. D., Truman, J. W., Cardona, A. and Zlatic, M. (2016). Cell 167(3): 858-870 e819. PubMed ID: 27720450

    Even a simple sensory stimulus can elicit distinct innate behaviors and sequences. During sensorimotor decisions, competitive interactions among neurons that promote distinct behaviors must ensure the selection and maintenance of one behavior, while suppressing others. The circuit implementation of these competitive interactions is still an open question. By combining comprehensive electron microscopy reconstruction of inhibitory interneuron networks, modeling, electrophysiology, and behavioral studies, this study determined the circuit mechanisms that contribute to the Drosophila larval sensorimotor decision to startle, explore, or perform a sequence of the two in response to a mechanosensory stimulus. Together, these studies reveal that, early in sensory processing, (1) reciprocally connected feedforward inhibitory interneurons implement behavioral choice, (2) local feedback disinhibition provides positive feedback that consolidates and maintains the chosen behavior, and (3) lateral disinhibition promotes sequence transitions. The combination of these interconnected circuit motifs can implement both behavior selection and the serial organization of behaviors into a sequence (Jovanic, 2016).

    A circuit mechanism for the propagation of waves of muscle contraction in Drosophila
    Fushiki, A., Zwart, M. F., Kohsaka, H., Fetter, R. D., Cardona, A. and Nose, A. (2016). Elife 5. PubMed ID: 26880545

    Animals move by adaptively coordinating the sequential activation of muscles. The circuit mechanisms underlying coordinated locomotion are poorly understood. This paper reports on a novel circuit for the propagation of waves of muscle contraction, using the peristaltic locomotion of Drosophila larvae as a model system. This study found an intersegmental chain of synaptically connected neurons, alternating excitatory and inhibitory, necessary for wave propagation and active in phase with the wave. The excitatory neurons (A27h) are premotor and necessary only for forward locomotion, and are modulated by stretch receptors and descending inputs. The inhibitory interneurons (GDL) are necessary for both forward and backward locomotion, suggestive of different yet coupled central pattern generators, and its inhibition is necessary for wave propagation. The circuit structure and functional imaging indicated that the commands to contract one segment promote the relaxation of the next segment, revealing a mechanism for wave propagation in peristaltic locomotion (Fushiki, 2016).

    This study has discovered a circuit whose structure and function provides a mechanism for understanding forward wave propagation in peristaltic locomotion. This circuit consists of a chain of alternating excitatory and inhibitory neurons spanning all abdominal segments. The core elements of the chain include just one excitatory and one inhibitory neuron per hemisegment. The inhibitory neuron (GDL) is sufficient to halt the peristalsis and to relax muscles in all segments, suggesting it is a point of coordination between forward and backward locomotion. It was further demonstrated that the excitatory neuron (A27h) is active during forward but not backward peristalsis, suggesting the existence of another excitatory circuit component critical for backward peristalsis among the synaptic partners of the GDL inhibitory neuron. This circuit defines a backbone of repeating, connected, modules for excitation and inhibition similar to those pos