Drosophila tissue and organ: Mushroom Bodies

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Mcm3 replicative helicase mutation impairs mushroom body neuroblast proliferation and memory in Drosophila

Blumröder, R., Glunz, A., Dunkelberger, B.S., Serway, C.N., Berger, C., Mentzel, B., de Belle, J.S. and Raabe, T. (2016). Genes Brain Behav [Epub ahead of print]. PubMed ID: 27283469

This study performed the molecular and phenotypic characterization of a structural brain mutant called small mushroom bodies (smu), which was isolated in a screen for mutants with altered brain structure. Focusing on the mushroom body neuroblast lineages, it was shown that failure of neuroblasts to generate the normal number of mushroom body neurons (Kenyon cells) is the major cause of the smu phenotype. In particular, the premature loss of mushroom body neuroblasts causes a pronounced effect on the number of late-born Kenyon cells. Neuroblasts show no obvious defects in processes controlling asymmetric cell division, but generate less ganglion mother cells. Cloning of smu uncovers a single amino acid substitution in an evolutionary conserved protein interaction domain of the Minichromosome maintenance 3 (Mcm3) protein. Mcm3 is part of the multimeric Cdc45/Mcm/GINS (CMG) complex, which functions as a helicase during DNA replication. The study proposes that at least in the case of mushroom body neuroblasts, timely replication is not only required for continuous proliferation but also for their survival. The absence of Kenyon cells in smu reduces learning and early phases of conditioned olfactory memory. Corresponding to the absence of late-born Kenyon cells projecting to α'/β' and α/β lobes, smu is profoundly defective in later phases of persistent memory (Blumröder, 2016).

A requirement for mushroom body signaling during olfactory memory retrieval

McGuire, S. E., Le, P. T. and Davis, R. L. (2001). Science 293: 1330-1333. PubMed ID: 11397912

The mushroom bodies (see Anatomical organization of the olfactory nervous system in Drosophila) of the Drosophila brain are important for olfactory learning and memory. To investigate the requirement for mushroom body signaling during the different phases of memory processing, neurotransmission was transiently inactivated through this region of the brain by expressing a temperature-sensitive allele of the shibire dynamin guanosine triphosphatase, which is required for synaptic transmission. Inactivation of mushroom body signaling through alpha/beta neurons during different phases of memory processing reveal a requirement for mushroom body signaling during memory retrieval, but not during acquisition or consolidation (McGuire, 2001).

Genetic and chemical disruption of the MBs produces flies that are normal for general behaviors but are defective in olfactory learning. Many genes involved in olfactory learning and memory show enriched expression in the MBs, particularly those encoding components of the cyclic adenosine monophosphate signaling pathway. Targeting of a constitutively active G-protein alpha subunit to the MBs disrupts olfactory learning, and restoring the rutabaga-encoded adenylyl cyclase specifically to the MBs of rutabaga mutants is sufficient to restore short-term memory in these flies. The model that has emerged from these experiments posits the MBs as important centers in olfactory associative learning and the likely site of convergence of the conditional (CS) and unconditioned (US) stimuli in classical conditioning (McGuire, 2001 and references therein).

A limitation of the previous experiments is that they all involve permanent alterations to the fly's brain throughout development, leading to the possibility that some of the effects on learning might reflect developmental perturbations rather than modifications of the physiology of these neurons that subserve learning and memory processes. Additionally, the irreversible nature of these interventions has made it impossible to dissect the roles of the MBs at the different stages of memory acquisition, consolidation, and retrieval (McGuire, 2001).

To explore the roles of the MBs in the different phases of memory processing, an approach was used that allows transient inactivativation of synaptic transmission from the MBs by targeting expression of a temperature-sensitive shibirets1 transgene to the MBs by the GAL4/UAS system. The shibire gene encodes a dynamin guanosine triphosphatase (GTPase) that is essential for synaptic vesicle recycling and maintenance of the readily releasable pool of synaptic vesicles. The temperature-sensitive allele shibirets1 bears a mutation in the GTPase domain, which renders the protein inactive at restrictive temperatures (>29°C) and causes a rapid inactivation of synaptic transmission and subsequent paralysis. Restricted expression of the shibirets1 transgene in specific cells produces blindness and paralysis at restrictive temperatures. Recently, the transgene was used to demonstrate the role of the dorsal paired medial neurons in memory formation (McGuire, 2001).

A number of GAL4 lines that exhibited enriched MB expression patterns were screened for 3-min memory performance when driving the UAS-shits1 transgene at both permissive (25°C) and restrictive (32°C) temperatures in an olfactory classical conditioning paradigm. In this assay, flies are conditioned by exposure to one odor paired with electric shock (CS+) and subsequent exposure to a second odor in the absence of electric shock (CS-). Memory is then assayed at predetermined time points after training by forcing the flies to choose between the CS+ and CS-. Several MB GAL4 lines demonstrate significant memory impairment at 3 min when tested at the restrictive temperature. These lines were next analyzed for sensorimotor functions required for the conditioning assay, including locomotion, odor avoidance, and electric shock avoidance, at both the permissive and restrictive temperatures. Subsequently, focus was placed on the GAL4 lines, c739 and 247, which demonstrate intact sensorimotor functions when driving the UAS-shits1 at both permissive and restrictive temperatures. For these MB GAL4 lines, memory at 3 min at the permissive temperature is indistinguishable among flies bearing both the GAL4 element and the UAS-shits1 transgene in combination and control flies bearing the GAL4 element or the UAS-shits1 element alone. At the restrictive temperature, however, the combination of c739 or 247 with the UAS-shits1 transgene results in a significant impairment of performance. The line 201Y; UAS-shits1 shows a slight but nonsignificant decrease in memory performance under these conditions. These data indicate that the inactivation of MB neurotransmission disrupts the processes underlying the encoding, storage, or retrieval of memory tested 3 min after training (McGuire, 2001).

These data were analyzed relative to the expression patterns of the three GAL4 lines to gain insights into possible functional subdivisions of the MBs. The GAL4 line 247, in which GAL4 is under the control of a 247-base pair (bp) enhancer fragment isolated from the D-mef2 gene, drives reporter gene expression in all lobes of the MB. In the line 201Y, the gamma lobe is preferentially marked, along with a small subset of the alpha/beta neurons. In contrast, the GAL4 c739 element drives reporter gene expression preferentially in the alpha/beta lobes. The expression overlap between the two GAL4 lines that disrupt 3-min memory when combined with UAS-shits1 at the restrictive conditions is within the alpha/beta lobes, suggesting the importance of this subset of MB neurons for the expression of memory. At the restrictive temperature, the UAS-shits1 in combination with 201Y, which preferentially drives reporter gene expression principally in the gamma lobes, does not significantly impair 3-min memory. The mild memory impairment in this line could be due to insufficient levels of expression of the UAS-shits1 transgene or rather it could reflect the possibility that the neurons in which this line drives the UAS-shits1 are not necessary for memory expression at this time point (McGuire, 2001).

To determine whether the deficient performance of these flies arises from a defect in memory acquisition, consolidation, or retrieval, memory was examined at a later time point (3 hours). Prior research has shown that most of the memory measured at this time point has been consolidated into an anesthesia-resistant form. The separation of training and testing also allows MB signaling to be reversibly inactivated separately during each phase and then it can be asked whether memory performance is affected. Three-hour memory was examined at the permissive temperature throughout the experiment. Under these conditions, the performance of the c739;UAS-shits1 flies is indistinguishable from flies bearing either the c739 element or the UAS-shits1 element. The lines 247 and 201Y in combination with UAS-shits1 disrupted 3-hour memory at the permissive temperature and were not analyzed further (McGuire, 2001).

To examine the requirement for signaling through the MBs during the retrieval of olfactory memory, training was performed under permissive conditions and the flies were maintained under these conditions until just before testing, at which point they were shifted to the restrictive temperature. When the performance of these flies was examined at 3 hours under these conditions, memory was abolished in the c739;UAS-shits1 flies, whereas the memory of the control groups was intact. Whether the acquisition of olfactory memory shares a similar requirement for MB signaling was examined. Training was performed under the restrictive conditions and immediately the flies were cooled to the permissive temperature. When the performance of these flies was examined at 3 hours under these conditions, a difference was observed between the c739;UAS-shits1 flies and the control line c739 but no difference between c739;UAS-shits1 and the UAS-shits1 control, indicating a general effect of heat on lines carrying the UAS-shits1 element, but no specific disruption of memory when UAS-shits1 is combined with c739. Subsequently it was investigated whether the interval between training and testing, during which memories are consolidated and stored, would require signaling through the MBs to observe normal memory performance at 3 hours. Flies were trained and tested under permissive conditions and given a temperature shift to restrictive conditions during the interval between these events. Under these conditions, a general effect of heat on the performance of all of the lines was observed, but no significant difference between any of the groups was observed (McGuire, 2001).

By transiently blocking synaptic transmission from the MBs during memory formation, consolidation, and retrieval, the temporal requirements of MB signaling during the different phases of memory processing could be examined. The results suggest quite unexpectedly that signaling through the MB alpha/beta neurons is required during olfactory memory retrieval, but not during memory acquisition or storage. It is proposed that, in Drosophila, olfactory memory retrieval requires signaling through the alpha/beta lobes to downstream neurons for expression. This does not preclude, however, a role for other MB lobes in memory formation, consolidation, or retrieval. A recent study demonstrating the sufficiency of rutabaga expression in the MBs for rescue of the short-term memory defect in rutabaga mutants has suggested that the gamma lobes might be of particular importance in the formation of short-term memories. Recent studies have also demonstrated that fasciclinII mutants are defective in memory acquisition and this protein is predominantly expressed in the alpha/beta neurons, although it is expressed at lower levels in the gamma lobe. One hypothesis to explain the combined observations is that memory formation occurs in the gamma neurons, or in both gamma and alpha/beta neurons simultaneously, but that memory retrieval occurs principally through the output of the alpha/beta neurons. Indeed, such a scenario involving a partial redundancy of function can explain why a subset of neurons might be sufficient, but not necessary, for memory expression. However, the observation that rutabaga and fasciclinII flies are only partially impaired in short-term memory indicates the likelihood that other mechanisms and perhaps locations of signal convergence, such as the antennal lobe or the lateral protocerebrum, may additionally mediate memory acquisition or storage. Taken together, these data suggest that acquisition and consolidation occur upstream of the MB synapse upon follower neurons, either in the MB neurons themselves or in upstream circuits. Retrieval of these memories within 3 hours would then engage signaling through a subset of the MB neurons, involving the alpha/beta lobes. It remains to be determined whether long-term memories (>24 hours) are dependent on the MBs (McGuire, 2001).

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Altered representation of the spatial code for odors after olfactory classical conditioning. Memory trace formation by synaptic recruitment

Yu, D., Ponomarev, A. and Davis, R. L. (2004). Neuron 42: 437-449. PubMed ID: 15134640

In the olfactory bulb of vertebrates or the homologous antennal lobe of insects, odor quality is represented by stereotyped patterns of neuronal activity that are reproducible within and between individuals. Using optical imaging to monitor synaptic activity in the Drosophila antennal lobe, classical conditioning is shown to rapidly alter the neural code representing the learned odor by recruiting new synapses into that code. Pairing of an odor-conditioned stimulus with an electric shock-unconditioned stimulus causes new projection neuron synapses to respond to the odor along with those normally activated prior to conditioning. Different odors recruit different groups of projection neurons into the spatial code. The change in odor representation after conditioning appears to be intrinsic to projection neurons. The rapid recruitment by conditioning of new synapses into the representation of sensory information may be a general mechanism underlying many forms of short-term memory (Yu, 2004).

Drosophila can develop a robust association between an odor, the conditioned stimulus (CS), and electric shock, the unconditioned stimulus (US), if the CS and the US are paired. Flies display their memory of this association by avoiding the odor CS during a test, after previously experiencing the pairing of the CS and the US. The number, nature, and the locations of the cellular memory traces that guide this acquired avoidance behavior are unknown, but significant evidence suggests that some cellular memory traces are formed in mushroom body neurons, higher-order neurons that form part of the olfactory nervous system. Furthermore, the evidence indicates that the memory traces are formed in part by the activation of the cyclic AMP signaling system. However, the memory traces that underlie insect odor memory are probably formed in many different areas of the olfactory nervous system and in other areas of the brain as well (Yu, 2004).

Optical imaging of synaptic activity in Drosophila brains coupled with behavioral conditioning has been used to visualize and study a cellular memory trace. This trace is established as new synaptic activity after conditioning in the antennal lobe projection neurons of the olfactory system. A concept established from these results, that may generalize to other forms of memory, is that memories form by the rapid recruitment of relatively inactive synapses into the representation of the sensory information that is learned. In other words, the synaptic representation of the odor CS is changed by learning, with new synaptic activity added to the representation after learning (Yu, 2004).

The anatomical organization of the Drosophila olfactory nervous system shares many fundamental similarities to that of vertebrates, suggesting that the mechanisms for odor perception, discrimination, and learning are shared. Olfactory receptor neurons (ORNs), distributed near the surface of the antenna and maxillary palp on each side of the head, project axons to the antennal lobe, where they terminate in morphologically discrete and synapse-dense areas known as glomeruli. The projection patterns of the ORNs are stereotyped between animals; ORNs that express the same olfactory receptor gene, although distributed across the surface of the antenna and maxillary palps, project their axons to the same glomerular target in the antennal lobe. There they are thought to form excitatory synapses with at least two classes of neurons: the local interneurons (LNs), a large fraction of which are GABAergic inhibitory neurons, and the projection neurons (PNs). A unique feature of the circuitry within the insect antennal lobe is the apparent existence of reciprocal dendrodendritic connections between the PNs and the LNs. The presence of these unique junctions with both transmissive and receptive specializations indicates that each glomerulus processes and makes computations that may underlie odor perception, discrimination, and learning, rather than being a simple transit station for the throughput of olfactory information. Individual PNs generally extend dendrites into a single antennal lobe glomerulus and then convey the processed olfactory information to two higher brain centers: the mushroom bodies and the lateral protocerebrum (Yu, 2004).

The neuroanatomy thus suggests that distinct odors are represented (1) by the stimulation of distinct sets of ORNs; (2) by spatial patterns of glomerulus activation within the antennal lobe, and (3) by a distinct set of synaptic fields activated in the mushroom bodies and the lateral protocerebrum. Functional imaging experiments have suggested the existence of a spatial code for odors within the antennal lobe of insects and the olfactory bulb of vertebrates. Calcium dyes, voltage-sensitive dyes, transgenically supplied fluorescent proteins, and intrinsic optical signals have been used to visualize odor-specific patterns of glomerulus activation in Drosophila, honeybee, zebrafish, salamander, and rat (Yu, 2004 and references therein).

The search for cellular memory traces began by first asking whether synaptic transmission could be detected in antennal lobe glomeruli of intact but immobilized adult flies after stimulation with pure odors that are frequently used as conditioned stimuli in behavioral learning experiments. It is possible to detect olfactory responses with optical reporters in the antennal lobes using reduced preparations of either isolated adult heads or dissected adult brains. Intact Drosophila adults are used, immobilized in a pipette tip, with their heads and antennae exposed. A small square of cuticle is removed from the dorsal head of each animal. Flies are mounted under a laser-scanning confocal microscope to detect basal fluorescence and the change in fluorescence induced with the application of odor. Initially flies were used carrying the GH146-GAL4 transgene to drive expression of a reporter of synaptic transmission; UAS-synapto-pHluorin (UAS-spH) was used to reveal PN presynaptic specializations within antennal lobe glomeruli (Yu, 2004).

A brief application of odor through a glass micropipette directed at the antennae produced a rapid, quantifiable, and stereotypic response in glomeruli between animals. For instance, the odor 3-octanol (OCT) produced a rapid burst of fluorescence in several glomeruli that occurred with the presentation of odor. Responses were quantified as the average percent change in the intensity of the pixels that represent each glomerulus during stimulation. A spatial response observed to OCT was observed as a pseudocolor image over eight glomeruli that were unambigously identified and that formed the focus of this study. Four of the eight glomeruli were activated reproducibly by OCT, whereas four others remained unchanged. These responses were quantitatively similar at two different odor concentrations. The increased responses of the four glomeruli at the higher odor concentration indicated that responses at lower odor concentrations fell well below the dynamic response ceiling for spH. The remarkably small standard errors that were obtained for glomerular responses between flies indicate that the procedures and standards that were employed were highly consistent and accurate. The many variables that could influence reproducibility include fly dissection, fly mounting, odor application, confocal scanning, glomerulus identification, and glomerulus circumscription during data analysis (Yu, 2004).

A stimulus that is used frequently as the unconditioned stimulus for olfactory classical conditioning is mild electric shock. This shock is normally delivered to flies as they stand on an electrified grid while also being in the presence of an odor. This US is effective at conditioning flies when presented along with an odor, although the identity of the neurons within the olfactory pathway that are stimulated by both odor and shock is unknown. Neurons that can function as cellular coincidence detectors must be activated either directly or indirectly by both stimuli (Yu, 2004).

It was therefore asked whether the PNs that responded to the odor CS could also respond to the US of electric shock. Pulses of electric shock were applied (at an intensity and frequency used to behaviorally condition adult Drosophila) to the abdomens of flies that were immobilized under the microscope. Synaptic transmission was activated in all glomeruli that expressed UAS-spH. The synaptic transmission events occurred with a periodicity that matched the 5 s interstimulus interval of the electric shock. When these time-based signals were converted to the frequency domain by Fourier transformation, a major component with a frequency matching the frequency of shock delivery (0.2 Hz) was extracted. These data indicate, therefore, that PNs are activated by electric shock stimuli applied to the abdomen. The neural pathways that carry the electric shock stimulus from the abdomen to the brain and the identity of the neurons immediately presynaptic to the PNs in this pathway have not yet been identified (Yu, 2004).

Since some PNs responded to both OCT and the US of electric shock when presented separately, it was of interest to ask whether these neurons could be conditioned by simultaneously presenting both odor and shock (forward conditioning). To test this, individual flies were conditioned either with OCT paired with electric shock or with one of a series of control protocols, including the odor only, shock only, and odor with shock but separated by 30 s to 2 min (trace conditioning). The optical response of the PNs to an odor test stimulus was then monitored 3 min after these treatments. The delay of 3 min was chosen, since for normal behavioral conditioning experiments it takes 3 min after training flies to test their choice behavior in a T-maze. Focus was placed on the effect of forward conditioning compared to other conditioning protocols, since the protocols of CS only, US only, and trace conditioning failed to produce behavioral conditioning (Yu, 2004).

The responses of most PNs to the test odor of OCT after the various conditioning protocols were similar or identical to the naive response. For instance, PNs innervating glomerulus DM2 responded to OCT with a 6% increase. Conditioning with the CS only, US alone, CS and US paired, or CS + US trace did not significantly alter this response. Similarly, most PNs that failed to respond to the odor CS by itself failed to exhibit any change in response after the conditioning protocols. Surprisingly, however, there was one notable exception. PNs innervating glomerulus D responded after forward conditioning to OCT with a %deltaF/F (fluorescence within each glomerulus relative to the basal fluorescence measured prior to the test with OCT) of 7%, while the responses of these PNs after US only, CS only, or trace conditioning protocols were similar to the naive response, which was not significantly different from zero. These data indicate, therefore, that forward pairing of the odor CS and the shock US rapidly awakens the PN synapses in the D glomerulus within 3 min after conditioning. The failure to observe a conditioning effect on the OCT-responsive glomeruli -- DM6, DM2, DM3, and DL3 -- cannot be due to a ceiling effect, since the odor concentration used for conditioning was well below the ceiling of spH's dynamic range. Thus, additional PN synapses in the antennal lobe are recruited rapidly to represent the odor CS after forward conditioning (Yu, 2004). These conclusions were reproduced and extended with a second type of experimental design. Since the response of the D PNs during the CS test was not affected by prior exposure of the CS when compared between flies, a 'within-animal' design was used for the next set of experiments. Each fly was presented the odor CS for 3 s, during which PN responses were monitored. After a rest of 5 min, the fly was then conditioned, and 3 min after conditioning, the response to a 3 s odor test was again monitored. The response before conditioning was compared with the response after conditioning. As before, the response of the D PNs to OCT alone was undetectable. However, the response after forward conditioning with OCT reached a %deltaF/F of 6% when measured 3 min later (Yu, 2004).

Is the memory trace in the D PNs specific for OCT as a CS, with other odors recruiting other sets of neurons and synapses, or is the change in D PNs a general property of learning something about any odor? To address this issue, within-animal conditioning experiments were carried out using methylcyclohexanol (MCH) as the CS, a second odor that is used frequently for odor learning in Drosophila (Yu, 2004).

The responses of some PNs to MCH before any conditioning were more variable between flies than for OCT. However, PNs innervating the three glomeruli DM6, DM2, and DM3 exhibited significant responses to MCH alone applied before conditioning. Forward conditioning, however, recruited the activity of glomerulus VA1 (both VA1l and VA1m) into the representation of MCH. Like the D glomerulus for OCT responses, VA1 was insensitive to MCH prior to conditioning. Therefore, different odors recruit normally insensitive PNs into their spatial representation after conditioning (Yu, 2004).

Behavioral memories can be very short or quite enduring, depending on the nature of the task learned, the strength of the training, the saliency of the cues, and undoubtedly the nature and number of the cellular memory traces that underlie the behavioral memory trace. The stability of the cellular memory trace that was established by forward pairing with OCT and shock in the D glomerulus PNs was probed by testing at different times after conditioning. This conditioned response waned rapidly. When tested at 5 min after conditioning, the increased response at 3 min had decayed to 5%, and by 7 min after conditioning the cellular memory trace was not significantly different from zero. Attempts to extend the duration of this memory trace with multiple and spaced conditioning trials have not been successful (Yu, 2004).

The recruitment of PN synapses of the D glomerulus into the representation of OCT and those of the VA1 glomerulus into the representation of MCH after conditioning suggests that synaptic recruitment was odorant specific. Nevertheless, the conditioned animals were conditioned and challenged with only one of the two odorants. To further explore the specificity of synaptic recruitment, a discriminative, within-animal experimental design was employed in which each animal was challenged with both odors prior to and after conditioning with either OCT or MCH (Yu, 2004).

PN synapses innervating glomeruli DM6, DM2, and DM3 showed significant responses to MCH before conditioning, while the remaining glomeruli failed to show significant responses. Most importantly, there were no significant differences in the responses to MCH after conditioning compared to those before conditioning. However, the conditioning recruited the PN synapses of the D glomerulus into the naive representation of OCT, which consisted of significant responses from glomeruli DM6, DM2, DM3, and DL3. In the reciprocal experiment, conditioning with MCH did not alter the representation of OCT by glomeruli DM6, DM2, DM3, and DL3 but selectively recruited PN synapses of VA1 into the MCH representation. These results, obtained with animals that were presented with two different odors in a discriminative protocol, strongly support the contention that the recruitment is odor specific (Yu, 2004).

Since the D PNs receive synaptic inputs from ORNs and LNs, it was of interest to ask whether the memory trace induced by OCT conditioning in D PN synapses was intrinsic to these neurons or whether the trace was established in one of the presynaptic partners so that the increase in D PN synaptic activity was only a reflection of an upstream memory trace. To test whether a synaptic memory trace was established in ORNs, UAS-spH was expressed using the ORN driver OR83b-GAL4. Using imaging conditions that were designed to identify glomerulus D and other glomeruli visible with GH146-GAL4, six glomeruli, along with D, were reproducibly discernable using this driver. Stimulation of flies with OCT produced a synaptic response in three of the six identified glomeruli, but these did not include D. Thus, PNs that innervate D do not receive excitatory input from the OR83b-expressing ORNs that form synapses in D (Yu, 2004).

It was asked, nevertheless, whether the ORNs that project to D responded to the US of electric shock and whether forward conditioning could recruit the OCT-blind D ORNs into being OCT sensitive. Electrical stimulation of flies carrying both OR83b-GAL4 and UAS-spH produced no increase in fluorescence of D or other glomeruli in response to shock pulses. Furthermore, forward pairing failed to produce any detectable change in synaptic activity within the identified glomeruli (Yu, 2004).

A GAD-GAL4 driver was used to direct expression of UAS-spH in LNs to address the same issues for these neurons. LNs that innervate glomeruli DM6, DM2, DM3, and DL3 all responded to the odor CS, whereas those innervating D, DL2, DA1, and VA1 failed to respond. The sets of responding and nonresponding glomeruli matched exactly those observed using the PN GAL4 driver. However, electric shock pulses to the body failed to stimulate synaptic responses in the LNs innervating D, and the synaptic responses of these neurons also could not be conditioned. The failure of the D PN synaptic trace to be transmitted to the LNs, which may be both presynaptic and postsynaptic to PNs, may indicate that the recruited D PNs may synapse on other PNs or interneurons rather than on the GAD-expressing LN or that the threshold for LN activation is simply too high for the memory trace to be transferred from the D glomerulus PNs (Yu, 2004).

Therefore, forward conditioning directly recruits D PNs into the representation of the CS of OCT. This recruitment is not the manifestation of a conditioned memory trace in the presynaptic ORNs or the LNs, since neither the ORNs nor the LNs that are presynaptic to the D PNs responded to the shock US, and neither neuron type exhibited a conditioned response (Yu, 2004).

The forward conditioning protocol used for most of the imaging experiments employed a single odor as the CS, paired with the US of electric shock pulses. Behavioral conditioning experiments, however, have often employed discriminative conditioning protocols with two different odors. The two-odor, discriminative, behavioral conditioning paradigm was modified into a single-odor classical conditioning paradigm to test the behavioral effects of the various conditioning protocols used for imaging. Flies were presented with CS only, US only, CS + US paired, or CS + US with a trace interval of 30 s, 1 min, or 2 min. They were then tested for their avoidance of the odor CS in a T-maze against a second odor to which they were naive and under conditions in which animals naive to any conditioning protocol distribute equally between the two odors (Yu, 2004).

The GH146-GAL4/UAS-spH flies were behaviorally conditioned using the new single-odor conditioning protocol and the effects of this behavioral conditioning was compared at 3 min posttraining to the conditioned synaptic responses of D PNs. The CS only, US only, or trace conditioning protocols produced small or no behavioral changes, similar to the lack of effect at the synaptic level. In contrast, forward conditioning produced a high behavioral performance score, similar to the robust synaptic change observed in D PNs. Therefore, the synaptic changes that were observed in D PNs produced by the conditioning protocols correlate well with the behavioral changes produced by the same protocols at 3 min after conditioning. Although the relative effectiveness of the various conditioning protocols correlated well between the imaged memory trace and behavioral performance, the duration of the behavioral memory after single-odor CS/US coincidence was much more enduring (>2 hr) than the enhanced synaptic activity of the D glomerulus PNs. Therefore, the D glomerulus memory trace would be capable of driving behavior for only the first few minutes after conditioning. Other memory traces of longer duration must be formed for more enduring behavioral performance (Yu, 2004).

The results offer two main conceptual advances. First, it is shown that forward conditioning of living Drosophila alters the representation of the odor CS in the PN synapses in the antennal lobe. Prior studies with the honeybee have suggested that memory traces are laid down in the antennal lobes, but these studies have employed pharmacological manipulations, calcium imaging, or physical insults to the entire antennal lobe without discriminating the roles of individual glomeruli, specific neuron types, or their synapses. In this study the GAL4 system of Drosophila to drive reporter expression in subsets of neurons, which provided resolution between types of neurons, and the reporter synapto-pHluorin, which provided a specific readout of synaptic activity in response to odorants. This approach was extended by imaging living flies before and after conditioning. This extension led to the specific finding that a short-lived cellular memory trace forms in Drosophila PNs after conditioning (Yu, 2004).

The existence of the short-term cellular memory trace in PNs and the correlated behavioral responses lends strong support to the idea that transient olfactory memories are formed in the insect antennal lobe. Much evidence has now accumulated to support the hypothesis that mushroom body neurons are centrally involved in odor learning, using the cAMP signaling cascade, in part, for the integration of sensory information. However, memories are distributed, and neurons other than mushroom body neurons are clearly involved in olfactory learning. The data provide evidence that the distributed memory system in Drosophila includes the antennal lobes. An attractive hypothesis is that the antennal lobes and the mushroom bodies are both sites for memory formation but that the earliest memories are formed in the antennal lobes by altering the representation of the sensory stimulus and that this altered representation is then transferred to and perhaps strengthened by the mushroom bodies (Yu, 2004).

The evidence offers the surprising conclusion that the PNs likely function as integrators of the CS and US. The ORNs, LNs, and PNs that innervate glomeruli recruited by conditioning did not respond to the odor CS. Of the three, only the PNs responded to the US of electrical shock. Thus, the available evidence suggests that PNs are the first point in the CS pathway that intersects functionally with the US pathway, although the possibility cannot be eliminated that ORNs and LNs receive US information via neuromodulatory rather than excitatory inputs, nor can the possibility be eliminated that some unknown neuron presynaptic to the recruited PNs integrates the CS and US. There is no neuroanatomical information about the US pathway from peripheral receptors or the identity of the presynaptic neurons providing US input to the PNs. However, it seems likely that the stimulus of electric shock must itself be processed by higher-order neurons in order to acquire its negative value attribute, which can then be stamped onto the PNs as associated with the CS. The CS pathway to the recruited PNs also remains unknown, since the odor CS (OCT or MCH) does not appear to be conveyed to glomerulus D or VA1 via the OR83b-expressing ORNs. It is possible that some ORNs that fail to express OR83b may project to these glomeruli and convey the CS stimulus. An alternative and more attractive possibility is that some local interneurons may convey the CS information from other glomeruli by synapsing on PNs innervating the recruited glomeruli. Such excitatory, interglomerular local interneurons have been discovered in the vertebrate olfactory bulb (Yu, 2004).

The second major conceptual advance is that the evidence suggests that memory traces are formed by the recruitment of synapses that are relatively silent to the odor CS, within the sensitivity of optical imaging, into the ensemble of synapses whose activity represents the odor CS in naive animals and that the selection of recruited synapses is odor specific. The possibility cannot be excluded, however, that some synaptic activity exists within the recruited PNs that is below the sensitivity of that detectable by optical imaging. Nevertheless, the results and the emerging evidence that cellular synaptic plasticity may occur from the activation of normally silent synapses suggest that some forms of behavioral memory may occur through a large synaptic gain mechanism, perhaps approaching an 'off-on' switch mechanism, rather than through smaller graded changes in synapses that represent the stimuli in naive animals. Thus, memory formation involves the recruitment of synapses to represent the sensory cues that are learned (Yu, 2004).

In addition to these advances, these findings also pose new and intriguing puzzles. Is the short-term memory trace established in the PNs independent of other memory traces, so as to directly guide behavior for a short period after learning, or is it transferred to the mushroom bodies or the lateral protocerebrum, perhaps to be consolidated there into a more enduring trace, with behavior being guided from these higher-ordered brain centers? A related question is whether the PN synaptic memory trace is specific to the connections made in the antennal lobe or whether this occurs on a cell-wide basis, with conditioning also stamping its effects on PN synapses made in the mushroom bodies and the lateral protocerebrum. Do any of the known memory mutants disrupt the formation or stability of the PN memory trace? How is it that the recruitment of new synapses in the antennal lobe produces a new representation of the learned odor? Is it just simply that more activated synapses represent the learned odor, or does the synaptic activation of PNs alter the coding of the odor CS, perhaps by influencing the coherency or timing of PN and LN oscillations that may contribute to odor encoding (Yu, 2004)?

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Drosophila DPM neurons form a delayed and branch-specific memory trace after olfactory classical conditioning

Yu, D., Keene, A. C., Srivatsan, A., Waddell, S. and Davis, R. L. (2005). Cell 123(5): 945-57. PubMed ID: 16325586

Formation of normal olfactory memory requires the expression of the wild-type amnesiac gene in the dorsal paired medial (DPM) neurons. Imaging the activity in the processes of DPM neurons revealed that the neurons respond when the fly is stimulated with electric shock or with any odor that was tested. Pairing odor and electric-shock stimulation increases odor-evoked calcium signals and synaptic release from DPM neurons. These memory traces form in only one of the two branches of the DPM neuron process. Moreover, trace formation requires the expression of the wild-type amnesiac gene in the DPM neurons. The cellular memory traces first appear at 30 min after conditioning and persist for at least 1 hr, a time window during which DPM neuron synaptic transmission is required for normal memory. DPM neurons are therefore 'odor generalists' and form a delayed, branch-specific, and amnesiac-dependent memory trace that may guide behavior after acquisition (Yu, 2005).

Memory traces together represent the memory engram that directs behavior of the organism after learning or conditioning events. Classical conditioning is one form of learning whereby a conditioned stimulus (CS) becomes predictive of an unconditioned stimulus (US) when the two stimuli are paired in an appropriate way. The prototypic example of classical conditioning stems from studies on dogs conducted by Ivan Pavlov in which tone cues (CS) paired with a food reward (US) became predictive of the food reward, shown by the dog's salivation upon hearing the tone cue after conditioning. In Drosophila, olfactory classical conditioning is a robust and well-studied type of learning in which olfactory cues (CS) are usually paired with electric shock (US), such that conditioning leads to learned avoidance behavior of the CS. Learning to associate two forms of sensory information likely involves specific neurons that respond to both sensory cues and can integrate the information to produce learning. Thus, memory traces for olfactory classical conditioning in Drosophila are expected to form in neurons positioned at the intersections of the olfactory nervous system, the pathway that conveys and processes the CS (CS pathway), and the pathways that convey and process the US (US pathway) (Yu, 2005 and references therein).

The insect olfactory nervous system begins with olfactory receptor neurons (ORNs) distributed between the antennae and maxillary palps. The ORNs project axons to the antennal lobe, where they terminate in morphologically discrete and synapse-dense areas known as glomeruli. There, the ORNs are thought to form excitatory synapses with at least two classes of neurons, one of these being the projection neurons. The projection neurons then convey the olfactory information along their axons in the antennal cerebral tract to at least two higher brain centers, the mushroom bodies and the lateral horn. A large body of evidence has accumulated indicating the importance of the mushroom bodies for olfactory learning. Thus, odors are represented first in the olfactory nervous system by the activation of overlapping sets of ORNs; second by the activation of overlapping sets of projection neurons, and third by the activation of mushroom body and lateral horn neurons (Yu, 2005 and references therein).

An olfactory memory trace forms in the projection neurons after olfactory classical conditioning. Synaptic release of neurotransmitter from presynaptic specializations of projection neurons in the antennal lobe was monitored optically using the transgenically supplied indicator of synaptic transmission, synapto-pHluorin (spH). The memory trace was detected in this case by a rapid but short-lived recruitment of new synaptic activity into the representation of the learned odor. More specifically, distinct odors stimulate distinct sets of projection neurons in naive animals. Within 3 min after conditioning, additional sets of projection neurons become activated by the learned odor. This recruitment is odor specific; different odors recruit different sets of projection neurons into the representation of the learned odor. The recruitment of new sets of projection neuron synapses into the representation of the learned odor, however, is short lived, lasting only 5 min before the synaptic release from the recruited sets of projection neurons decays to the undetectable levels observed prior to conditioning. The short-lived memory trace of projection neurons, although potentially important for guiding behavior for a few minutes after conditioning, cannot account for the time course for behavioral memory, which can last for days. Thus, memory traces in other areas of the nervous system must provide for the persistence of behavioral memory (Yu, 2005).

The dorsal paired medial (DPM) neurons are large neurons that express neuropeptides encoded by the amnesiac (amn) gene and are critical for normal memory. The encoded neuropeptides are related to pituitary adenylyl cyclase-activating peptide (PACAP). The DPM neurons have been widely hypothesized to be part of the US pathway through the release of the expressed modulatory neuropeptides, in part because their processes invade the mushroom body neuropil and are thought to intersect the olfactory nervous system. There is also evidence that these neurons release acetylcholine as a co-neurotransmitter along with neuropeptides (Yu, 2005).

The hypothesis that DPM neurons are solely part of a US pathway predicts that the US but not the CS should activate them and that their response properties should not change after olfactory classical conditioning. A change in their response pattern after conditioning would indicate the presence of a memory trace. A surprising observation is reported that not only do DPM neurons respond to the US of electric shock -- predicted by the hypothesis that they are part of the US pathway -- but they are odor generalists, responding to all odors that were tested. Moreover, they form odor-specific memory traces as registered by increased odor-evoked calcium influx and synaptic transmission. In contrast to the memory trace that forms immediately after conditioning in projection neurons, the memory trace that forms in the DPM neurons is delayed, appearing at 30 min after olfactory classical conditioning. Temporally distinct memory traces that form within projection neurons and DPM neurons after classical conditioning may be partly responsible for guiding behavior during different time windows after learning (Yu, 2005).

There are two DPM neurons, each with a large cell body residing in the dorsal aspect of each brain hemisphere. They have no obvious dendritic field and extend a single neurite in an anterior direction toward the neuropil regions (lobes) that contain the axons of the mushroom body neurons. The neurite from each DPM neuron splits, and one branch broadly innervates the vertical mushroom body lobes while the other innervates the horizontal mushroom body lobes. Careful examination of 12 different confocal stacks highlighting the DPM neurons with the DPM neuron driver, c316-GAL4, revealed that all of the fluorescence in the vertical and horizontal lobes of the mushroom bodies in c316-GAL4/UAS-mCD8GFP flies can be traced to the DPM neuron cell bodies rather than other c316-GAL4-expressing neurons in the brain (Yu, 2005).

It was first asked whether DPM neurons respond to electric-shock pulses delivered to the abdomen of living flies. The processes of DPM neurons in the mushroom body lobes of flies carrying c316-GAL4 and the synaptic transmission reporter UAS-synapto-pHluorin (UAS-spH) or the calcium reporter UAS-G-CaMP were visualized before and during the application of electric-shock pulses delivered to the abdomen. Electric-shock pulses were used of the same intensity, duration, and frequency as those used for behavioral conditioning. The calcium influx in the DPM neuron processes innervating the vertical mushroom body lobes that occurs with electric shock was examined. There was a dramatic response in the processes at the distal tip of the vertical lobes as well as at the vertical-lobe stalk. The change in fluorescence (ΔF/Fo) was examined that occurs with 12 shock pulses delivered at a rate of 1 shock pulse every 5 s. There was an increase in ΔF/Fo coincident with each shock pulse in the vertical lobes and the horizontal lobes with both G-CaMP and spH. These data indicate therefore that electric-shock pulses to the abdomen produce both calcium influx into the DPM neuron processes and synaptic release from their terminals, observations consistent with the possibility that DPM neurons provide US input to the mushroom body neurons (Yu, 2005).

The hypothesis that DPM neurons provide US input into the mushroom body neurons for olfactory memory formation predicts that these neurons should not be activated by the CS of an olfactory stimulus. To test this prediction, DPM neuron calcium influx and synaptic transmission was examined in flies presented with odor stimuli to their antennae and maxillary palps. Stimulation with pure odors like 3-octanol (OCT), 4-methylcyclohexanol (MCH), and benzaldehyde (BEN) elicited robust calcium influx into the DPM neuron processes innervating the vertical mushroom body lobes. The magnitude of the response was dependent on the odor concentration; no responses were observed using air blown over mineral oil, which was used as an odorant diluent. Moreover, these pure odors elicited synaptic activity of the DPM neuron as well as increased calcium influx. Odor responses were also observed in the DPM neuron processes innervating the horizontal mushroom body lobes. Finally, the generality of the DPM odor-evoked response was tested using a battery of 17 different odorants, ranging from pure odors to complex odors such as apple, banana, and grape. In all cases, the DPM neurons responded with increased calcium influx into their processes. Therefore, the DPM neurons are odor generalists in the sense that they apparently respond to all odors administered to the fly. However, the circuitry that provides odorant information to the DPM neurons is unknown (Yu, 2005).

Since the DPM neurons responded to both an odor conditioned stimulus and an electric-shock unconditioned stimulus, the possibility was considered that the neurons might form a memory trace and exhibit a changed response to the CS after olfactory classical conditioning. Either calcium influx into the DPM neuron processes or synaptic release after olfactory classical conditioning were measured. For all experiments, each animal was used for only one measurement in order to avoid potential complications produced by odor habituation, adaptation, or generalization that could occur with multiple exposures (Yu, 2005).

A within-animal experimental design was employed in which the response of the DPM neuron processes within each animal was first evaluated with a single, 3 s presentation of odor. This was followed by forward conditioning, in which a 60 s odor stimulus was presented simultaneously with 12 electric-shock pulses or by backward conditioning in which the 60 s odor stimulus was presented after the onset of the electric-shock stimuli. Forward conditioning leads to robust behavioral conditioning, whereas backward conditioning does not. The response of the DPM neuron processes was then tested at various times after conditioning, again within each animal, and the postconditioning response was compared to the preconditioning response (Yu, 2005).

The postconditioning responses of the DPM neurons to any of three conditioned odors, OCT, MCH, or BEN, did not differ from the preconditioning responses when assayed at 3 min after forward conditioning. This is in marked contrast to the odor-specific memory trace responses that occur in the projection neurons of the antennal lobe within 3 min after conditioning. However, amn mutant flies are only slightly impaired in 3 min memory and have a more pronounced impairment at later times beginning 10-60 min after training. Furthermore, synaptic transmission from DPM neurons is not required for 3 min memory and is dispensable during acquisition and retrieval for robust 3 hr behavioral memory. DPM synaptic transmission is instead required during the interval between training and testing. These observations led to a consideration of the possibility that the DPM neurons might form a memory trace with a delayed onset (Yu, 2005).

The postconditioning responses at 30 min after forward conditioning to three different odors compared to the preconditioning responses revealed that a delayed memory trace registered by increased calcium influx was detectable at this time. The increase in calcium influx was not observed at 30 min after backward conditioning, indicating that the memory trace is dependent on the order in which the CS and US are presented, like behavioral conditioning. Furthermore, the increased calcium influx after forward conditioning was also detectable at 60 min after conditioning but not at 15 or 120 min after forward conditioning. However, the variability of the postconditioning responses at 120 min was larger than at other time points, probably because the physiological state of the flies becomes compromised and more variable from the prolonged immobilization. Thus, the DPM neuron memory trace, detectable first at 30 min postconditioning, extends to at least 1 hr and perhaps 2 hr after conditioning. Moreover, the delayed memory trace registered by increased calcium influx into the DPM neuron processes at 30 min after conditioning was also registered as increased synaptic transmission using spH as a reporter. Therefore, odor evokes both increased calcium influx and increased synaptic transmission from DPM neurons 30 min after forward conditioning (Yu, 2005).

Two general models were considered for the role of the amn gene and the DPM neurons in the process of olfactory memory formation in Drosophila. The first model, the possibility that the amn gene and the DPM neurons provide solely US information for the process of acquisition, is unlikely for several different reasons. (1) amn mutants have normal levels of memory acquisition, shown by memory growth curves with multiple training trials relative to control flies. Impairment in the processing of the US information would likely cause the mutant flies to exhibit performance scores that reach asymptote at levels lower than controls. (2) The parallel nature of the memory growth curves also suggests that the processing of CS information is unimpaired since CS impairment should slow the memory growth rate relative to control flies. (3) These data suggest that the association process itself, or acquisition, is unimpaired since a defect in the association of the CS with the US would also alter the memory growth curve. (4) The discovery of a delayed olfactory memory trace within the DPM neurons themselves, unless fortuitous, is inconsistent with a role specific to US processing. Rather, the data are strongly consistent with a second model alternative envisioning amn and DPM neuron involvement in the formation of intermediate-term memory. The amn mutants exhibit no obvious deficit in acquisition but are impaired in memory. Synaptic transmission is required from the DPM neurons during the interval between training and testing but not at the time of training or testing. The latter observation indicates either that DPM neurons are chronically active or that acquisition itself leads to sustained DPM neuron activity since blocking synaptic activity after acquisition produces a memory impairment at 3 hr. The delayed memory trace formed in DPM neurons that is coincident in time with their requirement for normal memory formation argues for their involvement in an intermediate stage of memory (Yu, 2005).

The delayed olfactory memory trace that forms in the DPM neurons is different from previously observed projection neuron memory trace in several interesting ways. (1) The memory trace formed by antennal-lobe projection neurons occurs by the recruitment of new synaptic activity into the representation of the learned odor. In other words, there is a qualitative change in the brain's representation of the learned odor as represented by projection neuron activity. The memory trace formed by DPM neurons, in contrast, is a quantitative one, being manifest as an increase in calcium influx and synaptic release with CS stimulation after acquisition. Despite this, the trace formed in the DPM neurons is odor specific. (2) The memory trace formed by projection neurons is detectable very early (as little as 3 min) after training, whereas the memory trace formed by DPM neurons is delayed, forming between 15 and 30 min after training. (3) The memory trace formed by projection neurons is very short lived, existing for about 5 min after training. The memory trace established in DPM neurons persists for at least 2 hr after training. The existence of multiple memory traces in distinct areas of the olfactory nervous system with different times of formation and duration leads to the interesting hypothesis that memory of a singular event over time is due to multiple and distinct memory traces that guide behavior during different windows of time after learning, a conclusion also reached from studies with the honeybee (Menzel, 2001; Yu, 2005).

These observations show that the delayed olfactory memory trace is established in the DPM neuron branch that innervates the vertical mushroom body lobes and not in the branch that innervates the horizontal mushroom body lobes. Thus, there exists an intriguing branch specificity to the formation of the delayed olfactory memory trace. The significance of this observation is not yet clear. However, other studies have pointed to the possibility that mushroom body neurons have branch-specific information processing. Some flies mutant for the α lobes absent (ala) gene lack the vertical branch or the horizontal branch of the mushroom body neurons. Intriguingly, mutant animals missing only the vertical branch of the mushroom body neurons have been reported to exhibit normal short-term memory but no long-term memory. Thus, long-term memory may form only in the vertical branch of the mushroom body neurons or be retrieved specifically from this branch. The formation of a delayed olfactory memory trace in the DPM neuron branch that innervates the vertical mushroom body lobes is consistent with the possibility that branch-specific long-term memory processes occurring in the vertical branch of the mushroom body lobes are dependent on the delayed memory trace that forms in this DPM neuron branch (Yu, 2005).

The delayed memory trace that forms in the DPM neurons is dependent on the normal function of the amn gene product since the trace fails to form in amn mutants but can be rescued by expression of the wild-type amn gene in the DPM neurons. This observation raises at least three possibilities for the role of the amn-encoded neuropeptides in the formation of the delayed olfactory memory trace. (1) It is possible that the released neuropeptides exert their effects in an autocrine fashion, interacting with neuropeptide receptors on the DPM neurons themselves in order to initiate the formation of the memory trace. (2) It is also possible that the released neuropeptides interact with receptors on postsynaptic neurons, such as mushroom body neurons, and that this stimulates a retrograde signal that leads to the formation of the DPM neuron memory trace. (3) It is possible that the amn-encoded neuropeptides are not employed for physiological changes in the adult brain but are required in a developmental capacity for DPM neurons to be competent to form the memory trace (Yu, 2005).

There exist at least two broad explanations for the role of the DPM neurons and the amn-encoded neuropeptides in olfactory learning. One possibility is that the DPM neurons integrate CS and US information independently of integration events that occur elsewhere in the nervous system. In this scenario, the CS information may be transmitted to the DPM neurons via unknown interneurons from the antennal lobe or lateral horn, or, alternatively, the DPM neurons might receive CS information from the mushroom body axons. In other words, DPM neurons may be postsynaptic to the mushroom body neurons. This could explain why the DPM neurons are odor generalists since their broad innervation of the mushroom body lobes would allow them to sample the odorant-stimulated activity of many or all mushroom body neurons. This possibility predicts that the DPM neurons should exhibit postsynaptic specializations on some of their processes -- perhaps those that innervate the horizontal lobes, as one possibility. The strengthening of specific mushroom body-DPM neuron synapses after olfactory learning could explain how the DPM neurons form odor-specific memory traces despite being odor generalists. Other DPM neuron processes may be presynaptic to the mushroom bodies such that the CS/US integration events that occur within the DPM neurons might be passed on to the mushroom bodies to reinforce their output. The presynaptic interactions may be through synapses onto the mushroom body fibers in the vertical lobes, reinforcing mushroom body output over the intermediate term and perhaps establishing the permissive signaling events for long-term memories to form in the vertical lobes. The DPM neurons may also receive US information indirectly from the mushroom body neurons or from other neurons. The contributions of the two putative DPM neuron neurotransmitters -- acetylcholine and neuropeptides -- to these processes remain to be clarified. Both acetylcholine and amn neuropeptides are required for behavioral memory (from experiments with Shibire and amn mutants, respectively). The amn neuropeptides are also required autonomously for the formation of the DPM neuron memory trace (Yu, 2005).

The second broad explanation envisions the DPM neurons as maintaining already integrated information through a networked association with the mushroom bodies. The complete integration of CS and US information may occur in the projection neurons and mushroom body neurons. DPM neurons, in a postsynaptic role to the mushroom bodies, would receive integrated information leading to increased excitability. The transfer of the CS/US-integrated information from the mushroom bodies to the DPM neurons may occur immediately after learning, initiating a process intrinsic to the DPM neurons that produces a delayed increase in odor-evoked transmission 30 min later, or the transfer of the integrated information itself from the mushroom bodies to the DPM neurons may occur through a delayed process after learning. In either case, the increased excitability of the DPM neurons would feed back onto and strengthen the output of the mushroom body neurons, leading to robust intermediate-term memory (Yu, 2005).

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Sequential use of mushroom body neuron subsets during Drosophila odor memory processing

Krashes, M. J., et al. (2007). Neuron 53: 103-115. PubMed ID: 17196534

Drosophila mushroom bodies (MB) are bilaterally symmetric multilobed brain structures required for olfactory memory. Previous studies suggested that neurotransmission from MB neurons is only required for memory retrieval. An unexpected observation that Dorsal Paired Medial (DPM) neurons, which project only to MB neurons, are required during memory storage but not during acquisition or retrieval, led to a revisiting of the role of MB neurons in memory processing. Neurotransmission from the α′β′ subset of MB neurons is required to acquire and stabilize aversive and appetitive odor memory, but is dispensable during memory retrieval. In contrast, neurotransmission from MB αβ neurons is only required for memory retrieval. These data suggest a dynamic requirement for the different subsets of MB neurons in memory and are consistent with the notion that recurrent activity in an MB α′β′ neuron-DPM neuron loop is required to stabilize memories formed in the MB αβ neurons (Krashes, 2007).

It is often said that form follows function. According to this postulate, the striking multilobed arrangement of the insect MBs would imply functional differences between the different types of MB neurons: αβ, α′β′, and γ, but very limited data describing the individual function of these anatomical subdivisions exists. Although several complex behaviors in insects appear to require the MBs and a differential role for distinct MB neuron groups has been suggested, most conceptual models of memory treat the MBs as a single unit (Krashes, 2007).

One of the most detailed examinations of MB function has been in the context of Drosophila aversive olfactory memory, where flies are trained to associate specific odors with the negative reinforcement of electric shock. Genetic studies over the last thirty years have suggested that the MBs play an essential role in fly olfactory memory, but the role of the MBs in memory acquisition, storage, and retrieval has only been examined recently. Taking advantage of a dominant, temperature-sensitive dynamin transgene, uas-shits1, a number of laboratories concluded that MB output was required only for recall, but not for acquisition or storage. These and other findings have led to a simple model wherein Drosophila olfactory memory is formed and “stored” at MB output synapses (Krashes, 2007).

Functional studies of DPM neurons, MB extrinsic neurons that ramify throughout the MB lobes, demonstrated they were specifically required during consolidation, but not acquisition or storage. Furthermore, genetically modified DPM neurons that primarily innervate the MB α′β′ lobes retain function, implying that MB α′β′ neurons might also have a similar function in memory consolidation (Krashes, 2007).

Examination of the GAL4 enhancer-trap lines used to express the uas-shits1 transgene in the earlier MB studies revealed that c309, c747, and MB247 only express in a few MB α′β′ neurons compared to αβ and γ neurons, while c739 expresses exclusively in αβ neurons. Thus, it seems likely that prior studies utilizing these drivers did not observe requirements for MB activity during either olfactory memory acquisition or storage because of insufficient expression in α′β′ neurons (Krashes, 2007).

Subsequently two GAL4 enhancer-traps that strongly express in MB α′β′ neurons were identified to test this hypothesis. The expression of c305a appears to be entirely restricted to α′β′ neurons within the MBs whereas c320 expresses in α′β′, αβ, and a few γ neurons. Both of these lines also express in additional non-MB neurons, so MB{GAL80} tool was employed to more rigorously test the requirement for MB activity in these {GAL4} lines. With these reagents the role of MB α′β′ neurons in memory was investigated and it was found that MB α′β′ neuron output during and after training is critical for the formation and consolidation of both appetitive and aversive odor memory from a labile to a more stable state. For comparison the requirements were also examined for MB αβ neurons using c739, confirming previous results. Thus, output from the MB α′β′ neuron subset is required for memory acquisition and stabilization, whereas output from αβ neurons is apparently dispensable during training and consolidation but is required for memory retrieval (Krashes, 2007).

Based on c305a and c739 data, it is recognized that c320 flies, which express in both α′β′ and αβ neurons, might be expected to exhibit memory loss if MB neuron output was blocked during both the consolidation and recall time windows. However, it is possible that a retrieval effect was not observed with c320 because it expresses GAL4 in fewer αβ neurons, or is in a different subset of αβ neurons relative to the c739 driver (Krashes, 2007).

Despite this caveat, these data suggest that different lobes of the MB have different roles in memory and provide a significant shift in the current understanding of the role of the MB in memory. Older models implied that MB αβ, α′β′, and γ neurons were largely interchangeable, and that each of the MB neurons that responded to a particular odor received coincident CS and US input and modified their presynaptic terminals to encode the memory. The data presented in this study suggest that MB αβ and α′β′ neurons are functionally distinct (Krashes, 2007).

In this study, the role of the unbranched γ lobe neurons was not investigated. Previous work with c309, c747, and MB247 suggests that neurotransmission from γ neurons is likely dispensable for acquisition and consolidation. In addition, a prior study indicated that γ neurons are minimally involved in middle-term memory (MTM) and anesthesia-resistant memory (ARM). However, it is possible that experiments to date have not employed odors that require γ neuron activation. The response of γ neurons may be tailored to ethologically relevant odors such as pheromones. It is notable that fruitless, a transcription factor required for male courtship behavior, is expressed in MB γ neurons, and blocking expression of the male-specific fruM transcript in the MB γ neurons impairs courtship conditioning. If the relevant odors can be identified, it will be interesting to determine if MB α′β′ neurons and Dorsal Paired Medial (DPM) neurons are required to stabilize these odor memories in the γ neurons. Recent work is supportive of the idea that odor identity may be a factor in determining the requirement for the subsets of MB neurons in olfactory learning (Krashes, 2007).

Stable aversive and appetitive odor memory requires prolonged DPM neuron output during the first hour after training, and DPM neuron output is dispensable during training and retrieval. DPM neurons ramify throughout the MB lobes, but DPM neurons that have been engineered to project mostly to the MB α′β′ lobes retain wild-type capacity to consolidate both aversive and appetitive odor memory. This study has demonstrated that, similar to wild-type DPM neurons, blocking output from these modified DPM neurons for 1 hr after training abolishes memory. Thus, finding a specific role for both DPM neuron output to MB α′β′ lobes and MB α′β′ neuron output during the first hour after training is consistent with the notion that a direct DPM-MB α′β′ neuron synaptic connection is important for memory stability. It should be reiterated that the focus of this paper has been on protein synthesis-independent memory, and whether or not a similar processing circuit is utilized for protein synthesis-dependent LTM remains an open question (Krashes, 2007).

Beyond simply attributing an additional function to the MBs, when taken in conjunction with work on the role of DPM neurons in memory, the data presented here suggest a new model for how olfactory memories are processed within the MBs. It is proposed that olfactory information received from the second-order projection neurons (PNs) is first processed in parallel by the MB αβ and α′β′ neurons during acquisition. Activity in α′β′ neurons establishes a recurrent α′β′ neuron-DPM neuron loop that is necessary for consolidation of memory in αβ neurons, and subsequently, memories are stored in αβ neurons, whose activity is required during recall. It is plausible that MB α′β′ neurons are directly connected to MB αβ neurons and/or that DPM neurons provide the conduit between MB neurons. However, the finding that DPM neurons that project primarily to MB α′β′ neurons are functional implies that only a few connections from DPM neurons to MB αβ neurons are necessary (Krashes, 2007).

The requirement for α′β′ neuron output during training also potentially provides a source for the activity that drives DPM neurons. DPM neuron activity is not required during training, and the current data are consistent with the idea that olfactory conditioning triggers activity in MB α′β′ neurons, which in turn elicits DPM neuron-dependent activity. It is proposed that after training, recurrent MB α′β′ neuron-DPM neuron activity is self-sustaining for 60-90 min. This recurrent network mechanism is similar to models for working memory in mammals. It is also conceivable that MB α′β′ neurons receive prolonged input after training from the antenna lobes via the PNs. Olfactory conditioning has been reported to alter the odor response of Drosophila PNs in the AL, but the observed effects were short-lived. Nevertheless, AL plasticity for a few minutes after training could contribute to the required MB α′β′ neuron activity. If continued activity from the AL is required for consolidation, blocking PN transmission with shits1 for 1 hr after training should abolish memory. The bee AL and MB are clearly involved in olfactory memory and may function somewhat independently in learning and memory consolidation, respectively. However, biochemical manipulation of the bee AL can also induce LTM, and therefore it is possible that either plasticity in the AL alone can support LTM, or that the AL and MB interact during acquisition and consolidation. A differential role for the AL and MBs has also been suggested from neuronal ablation studies of courtship conditioning in Drosophila. Short-term courtship memory can be supported by the AL, but memory lasting longer than 30 min requires the MBs (Krashes, 2007).

This work also has significant implications for the organization of aversive and appetitive odor memories in the fly brain. Stability of both appetitive and aversive memory is dependent on DPM neurons and MB α′β′ neurons. It therefore appears that processing of aversive and appetitive odor memories may bottleneck in the MBs. It has been demonstrated that aversive memory formation requires dopaminergic neurons whereas appetitive memory relies on octopamine to provide a possible mechanism to distinguish valence (see Tyramine β hydroxylase). However, it was also found that MB output is required to retrieve aversive and appetitive odor memory, suggesting that both forms of memory involve MB neurons and that both US pathways may converge on MB neurons. It will be important to understand how the common circuitry is organized to independently process the different types of memory and to establish if, and how, such memories coexist (Krashes, 2007).

These data imply that stable memory may reside in MB αβ neurons because blocking output from MB αβ neurons impairs retrieval of MTM and ARM (both components of 3 hr memory). It has been proposed that AMN peptide(s) released from DPM neurons cause prolonged cAMP synthesis in MB neurons that is required to stabilize memory. The finding that genetically engineered DPM neurons mostly projecting to the MB α′β′ lobes are functional, taken with the idea that stable memory resides in MB αβ neurons, is somewhat inconsistent with the notion that crucial AMN-dependent memory processes occur in MB αβ neurons. However, it is plausible that AMN, or another DPM product that is released in a shibire-dependent manner, could diffuse locally from the aberrant DPM neurons to MB αβ neurons (Krashes, 2007).

This work demonstrates that MB αβ neurons and α′β′ neurons have different roles in memory. Beyond gross structural and gene expression differences, it will be essential to establish the precise connectivity, relative excitability, and odor responses of the different MB neurons. Future study may also reveal further functional subdivision within the MB lobes, and it should be possible to refine the current MB α′β′ neuron GAL4 lines with appropriate GAL80 transgenes and FLP-out technology (Krashes, 2007).

In the mammalian brain memories that initially depend on the function of the hippocampus lose this dependence when they are consolidated. This transient involvement of the hippocampus has led to the idea that consolidation of memory results in the transfer of memory from the hippocampal circuits to the cortex. An alternate view is that aspects of the memory are always in the cortex but are dependent on the hippocampus because recurrent activity from cortex to hippocampus to cortex is required for consolidation. Hence, disrupting hippocampal activity during consolidation leads to memory loss (Krashes, 2007).

The current data suggest the simpler fruit fly brain similarly employs parallel and sequential use of different regions to process memory. MB α′β′ neuron activity is required to form memory, MB α′β′ neurons and DPM neurons are transiently required to consolidate memory, and output from αβ neurons is exclusively required to retrieve memory. It is therefore propose that aversive and appetitive odor memories are formed in MB αβ neurons and are stabilized there by recurrent activity involving MB α′β′, DPM neurons, and the MB αβ neurons themselves (Krashes, 2007).

It is becoming increasingly apparent that neural circuit analysis will play an important role in understanding how the brain encodes memory. The ease and sophistication with which one can manipulate circuit function in Drosophila, combined with the relative simplicity of insect brain anatomy, should ensure that the fruit fly will make significant contributions to this emerging discipline (Krashes, 2007).

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Mapping olfactory representation in the Drosophila mushroom body

Jefferis, G. S., et al. (2007). Cell 128(6): 1187-203. PubMed ID: 17382886

The first olfactory relay in the brain contains a spatial map. Olfactory receptor neurons (ORNs) expressing a specific odorant receptor (and therefore having precisely defined olfactory tuning properties) send axon projections to discrete and reproducibly positioned glomeruli in the vertebrate olfactory bulb or insect antennal lobe. In Drosophila, most ORN classes express one specific odorant receptor and send axons to one of ~50 glomerular targets (Jefferis, 2007 and references therein).

Persistent spatial organization deep within the brain is a motif in many sensory systems. For example, adjacent regions of the somatosensory cortex respond to stimuli from neighboring body parts. Does the spatial organization evident in the first olfactory relay also persist at deeper levels? In flies, the branching patterns have been described of the axons of second order projection neurons (PNs, equivalent to vertebrate mitral cells) in higher olfactory centers: the mushroom body (MB) and lateral horn (LH) of the protocerebrum. In the LH axon branching patterns of PNs of the same glomerular class were highly stereotyped across animals, while such stereotypy was less evident in the MB. Several putative output neurons of the LH have been described. Understanding how these neurons integrate olfactory information is a key problem in the neural basis of olfactory perception. In mice, the existence of some spatial organization in higher olfactory centers has been reported by following the targets of 2 of the 1000 ORN classes to the olfactory cortex. The integrative properties of olfactory cortical neurons have also been studied. However, the anatomical basis of this integration remains challenging because of the numerical complexity of the rodent olfactory system (Jefferis, 2007 and references therein).

Neuroanatomy is the foundation of both developmental and functional studies of the brain. In order to understand the development of neuronal wiring, it is necessary to describe the degree of wiring precision across individuals. Similarly, high-resolution neuroanatomy makes predictions about information transfer and transformation, constraining models of neural processing. Two anatomical approaches have been particularly influential in constructing wiring diagrams. The first is exemplified by the classic work of Cajal using the Golgi method. A small fraction of the neurons within a piece of tissue are stained to reveal their dendritic and axonal projection patterns; the information from many specimens is compared and integrated to give a global picture of the circuit. While this approach was enormously successful in defining the basic logic of connectivity, it lacks comprehensiveness and precision: comprehensiveness because only a small fraction of the neuronal elements are used to construct the global picture; precision because integrating information across sample brains has allowed only qualitative comparisons. The second method is a complete reconstruction of all the connections in a small number of specimens through serial electron microscopy. While new EM technologies are under development, traditional serial section transmission EM approaches are so labor intensive that this has only been achieved once - the reconstruction of the nervous system of C. elegans hermaphrodites (Jefferis, 2007 and references therein).

This study describes an approach that has merits of both methods. By combining genetic single-cell labeling with state-of-the-art image registration techniques, comprehensive maps have been produced of the LH and MB, the two higher olfactory centers of Drosophila. Projections of individual neuronal classes with their neighbors can be visualized and directly compared. These three dimensional maps directly demonstrate the spatial stereotypy of input to the LH and MB. Probabilistic synaptic density maps have been devised and used to identify and quantify the organizational principles of these two centers. It was found, for example, that fruit odors and pheromones are represented in distinct compartments of the LH. Finally, postsynaptic neurons of the LH have been characterized at the single-cell level and the density maps have been used to predict connectivity with input PNs. All the raw and derived data and the necessary software tools are available on the project website, providing a resource that will be integrated with future anatomical, physiological and behavioral data to understand the neural basis of olfactory perception in Drosophila (Jefferis, 2007).

Previous studies have revealed aspects of the spatial organization of higher olfactory centers - the MB calyx and the LH. Of particular relevance to the principles of olfactory information processing, single PNs of different classes have highly stereotyped LH projections. Using five Gal4 enhancer trap lines each labeling 1-3 PN classes, it has been found that PNs from 9 glomeruli project to 3 corresponding zones in the MB calyx and LH; MB output neurons integrate information from each of these zones whereas 6 groups of putative LH output neurons maintain the segregation of these 3 zones (Jefferis, 2007).

This study contains several advances over previous approaches: (1) the projection patterns of 11 new PN classes are described at single-cell resolution, qualitatively extending previous results; (2) all single neuron tracings were digitized, and transformed onto a common reference brain; (3) at the single neuron level, the distribution was determined of PN presynaptic terminals in the MB and LH. Fourth and most importantly, combining the above information allowed generation of quantitative synaptic density maps for 35 PN classes, representing 32 of ~50 unique olfactory channels defined by the projection of ORN classes to antennal lobe glomeruli. This allowed decomposition of MB and LH input into individual channels and then the reassemblage for most of the olfactory system, providing a global view of these higher order centers. Lastly, projection patterns are described of three groups of LHNs at single-cell resolution, and predictions are made about their physiological properties based on their potential connectivity with specific PN classes (Jefferis, 2007).

The concentric zonal organization of PN input into the MB calyx was quantitatively confirmed. However, LH organization is more complex and cannot simply be described as zonal, with the exception of the segregation of pheromone projections from the rest of the channels. This is evident from the single neuron projections of many classes that send stereotyped and divergent branches to multiple areas of the LH, as well as the synaptic density maps. Together with the extensive branching of individual LHNs, characterizing the LH as providing relatively little integration across glomeruli is now considered inaccurate (Jefferis, 2007).

Comparing PN branching patterns in the LH and MB suggests that the LH is likely to support more stereotyped integration. This proposal is consistent with the view that the LH mediates innate olfactory behaviors while the MB participates in odor-mediated learning. However, a clear stereotypy of PN terminals in the MB calyx has now been demonstrated. This is likely to explain observations that certain odors can evoke spatially stereotyped activity in MB neurons. Thus the MB calyx and LH receive different levels of stereotyped input that can be integrated by third order coincidence detectors that combine information from different input channels (Jefferis, 2007).

The most striking biological insight obtained from this study is the segregation in the LH between putative pheromone representing PNs and almost all other PNs in the apparently homogeneous LH neuropil. Interestingly, the highest degree of LH volumetric sexual dimorphism that was quantified coincides with the presynaptic terminals of the GABAergic vVA1lm and vDA1 PNs. It is important to note that in addition to the PNs that express the GAL4 driver GH146 that were characterized in this study, there may be other PNs that relay pheromone information from VA1lm and DA1 glomeruli to higher brain centers and contribute to the sexual dimorphism that was found in the LH (Jefferis, 2007).

The convergence of excitatory and inhibitory projections from these putative pheromone representing glomeruli at overlapping or adjacent locations may allow postsynaptic neurons to respond to the presence of a signal that activates these two glomeruli in a particular ratio or to allow signals from these two glomeruli to have opposing effects on LH neurons that initiate particular behaviors. Behaviorally, male flies appear to integrate information both from attractive and inhibitory pheromones produced by other males. Furthermore, new data show that Fru+ Or67d ORNs innervating the DA1 glomerulus detect a male sex pheromone that has a negative effect on other males and a positive effect on females. It is speculated that balanced excitation and inhibition in these pathways may regulate LHNs that contribute to the appropriate behavioral alternative. Sex-specific integration in the lateral horn may underlie sex-specific behaviors (Jefferis, 2007).

The spatial segregation of pheromone representation contrasts with the representation of glomeruli that receive input from ORNs of the basiconic sensilla, which are generally activated by fruit odorants. Many of these PN classes have extensive overlap in their LH synaptic density maps. This property, coupled with the fact that many fruit odorants activate multiple classes of basiconic ORNs, makes the representations of different fruit odorants and natural fruit odors quite overlapping. These data thus support the following principles: olfactory information concerning food has extensive structural intermixing at the LH compared to the glomerular organization of the antennal lobe, but rather discrete channels are retained for pheromones all the way from the sensory periphery to the LH. It is proposed that the LH is globally organized according to biological values rather than chemical nature of the odorant information (Jefferis, 2007).

This finding is reminiscent of the male silkworm moth, Bombyx mori, where PNs from the macroglomeruli representing sex pheromones send axon projections to a discrete area in the lateral protocerebrum defined by a high level of anti-cGMP staining. Spatial segregation of the pheromone representation in higher olfactory centers may therefore be a conserved feature in insects. This segregation is exaggerated into two entirely separate pathways in mammals, where the nasal epithelium and main olfactory bulb process general odorants and some pheromones, while the vomeronasal organ and accessory olfactory bulb are more specific to pheromone sensation. Furthermore, mitral cells originating from the main and accessory olfactory bulbs project to distinct areas of the cortex (Jefferis, 2007).

Having generated a comprehensive and quantitative map of PN input to the LH, a future challenge is to identify and characterize third order LHNs: where are their dendritic fields in the LH, with which PNs do they form synapses, where do they send their axonal outputs, and what are their physiological properties and functions in olfactory behavior? This effort has been started by identification of Gal4 lines labeling neurons with projections in the vicinity of the LH. Three groups of LHN were characterized at single-cell resolution and their potential connectivity with different PN classes was predicted. However this is clearly only a beginning. The widespread distribution of LHN cell bodies and their potential output to different parts of the brain along with the difficulty of identifying large groups of LHNs labeled by new Gal4 enhancer traps suggest that LHNs are heterogeneous genetically, anatomically and, in all likelihood, functionally. One tractable avenue will be to find LHNs that send dendrites to DA1/VA1lm PN target areas and may therefore respond to pheromones and instruct mating behavior. Two LHN groups that were characterized project to this LH region, and single-cell and potential synapse analyses indicate that some of these LHNs may form strong connections with pheromone responsive PN channels. Further characterization of these and other LHNs will bring an understanding the neural circuit basis of olfactory perception and behavior (Jefferis, 2007).

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A map of olfactory representation in the Drosophila mushroom body

Lin, H. H., Lai, J. S., Chin, A. L., Chen, Y. C. and Chiang, A. S. (2007). Cell 128(6): 1205-17. PubMed ID: 17382887

Neural coding for olfactory sensory stimuli has been mapped near completion in the Drosophila first-order center, but little is known in the higher brain centers. This study reports that the antenna lobe (AL) spatial map is transformed further in the calyx of the mushroom body (MB), an essential olfactory associated learning center, by stereotypic connections with projection neurons (PNs). Kenyon cell (KC) dendrites are segregated into 17 complementary domains according to their neuroblast clonal origins and birth orders. Aligning the PN axonal map with the KC dendritic map and ultrastructural observation suggest a positional ordering such that inputs from the different AL glomeruli have distinct representations in the MB calyx, and these representations might synapse on functionally distinct KCs. These data suggest that olfactory coding at the AL is decoded in the MB and then transferred via distinct lobes to separate higher brain centers (Lin, 2007).

The greatest challenge facing the field of sensory biology at present is to address how sensory coding is represented from the first-order center to the higher brain centers, where neuronal activity must be computed to elicit appropriate behavior responses. This study reports a spatial map of olfactory representations in the MBs of adult Drosophila brains. It was shown that KC dendrites are segregated into 17 complementary domains defined by both clonal origins and birth orders. When viewed from the posterior, PN axonal termini of DL3/D/DA1/VA1d, of DM2, and of DM1/VA4 form three concentric zones corresponding to KC dendrites from early α/β, late α/β, and α'/β' neurons in the posterior calyx, respectively. The spatial organization of PN-to-KC connectivity suggests that olfactory coding in the AL is maintained in the MB calyx where signal processing is more versatile (Lin, 2007).

One question that now can be addressed is, are odorants carrying similar biological information processed by the same class of KCs? A chemotopic map of OR responses to 110 odorants indicates that excitatory and inhibitory responses are chemical-class dependent. By integrating the PN-to-KC map with existing electrophysiological data, it was observe that KC responses to chemicals are likely also class specific. For example, many aromatic odorants are excitatory to Or10a and many terpenes are inhibitory to Or49b, which connects via DL1 and VA5, respectively, to γ neurons. Since MBs are essential for odor discrimination, it is predicted that a fly will find it more difficult to discriminate two odorants that are relayed by the PNs to the same class(es) of KCs. It has been observed that odors of a particular chemical class are often clustered, as shown by the 'odor space' constructed from the response of 24 ORs to 110 odorants. It was shown that three odorants in different chemical classes mapped to three distinct points in this space: pentyl acetate (an ester) and 2-hepatanone (a ketone) elicited similar patterns of activation maps together, distant and different from that elicited by methyl salicylate (an aromatic compound). Consistently in the anatomical study, it was found that pentyl acetate- and 2-hepatanone-induced signals are likely processed by the same class of KCs (i.e., late α/β neurons), while those induced by methyl salicylate reach other classes of KCs, excluding late α/β neurons. It is noted that this is a working model of odor discrimination, since it does not yet include all PN-to-KC connections in the adult olfactory system and only six ORs have yet been linked with the PN-to-KC map. Additional functional subsets of KCs are expected in each of the five classes. While a more complete PN-to-KC map is needed, the model of odor space versus KC class provides an important advance in the understanding of neural computation underlying behavioral responses to odors (Lin, 2007).

The findings are in congruence with functional imaging studies, which indicate that odor-evoked activity occurs in specific regions in the calyx. As odor concentration increases, more glomeruli are activated in the AL and more KCs are activated in the calyx. The anatomical data suggest that perception of odor identity may require integration among five classes of KCs, while the number of responsive KCs may reflect the perception of odor intensity (Lin, 2007).

Confocal imaging of specific GAL4-driven reporter expression patterns reveals axonal segregation for each of the five KC classes. This topology implies that stereotyped olfactory representation in the AL glomeruli received from OSNs (first order) are further relayed by PNs (second order) to a fixed combination of five KC classes (third order) in the calyx; such an implication is supported by findings on connectivity. It is surmised that information processing is further achieved by segregating axon bundles to different MB lobes, where output neurons (fourth order) diverge the processed information to separate higher brain centers (fifth order). Incomplete as this model may be, the possibility is acknowledged of (1) crosstalk among KCs and (2) modulatory innervation of MB calyx and lobes. Because this study was focused only on a subset of PNs, the possibility cannot be ruled out that further functionally important differences in PNs may yet be discerned. Nonetheless, this anatomical model serves to advance the notion that an olfactory map in the MBs helps to guide olfactory-driven behaviors (Lin, 2007).

All animals are born with a set of innate behavioral responses, 'hardwired' in the nervous system. In Drosophila, innate behaviors such as sleep and courtship require proper functioning of the MBs. It is notable that Fruitless, a transcription factor required for male courtship behavior, is expressed in OSNs and PNs innervating the same set of AL glomeruli (VL2a, DA1, and VA1), suggesting interconnections between these two sets of olfactory neurons. Intriguingly, fruitless expresses also in the MBs of the ? and α/β lobes, and courtship conditioning is impaired when expression of the male-specific fru transcript is disrupted in MB γ neurons. In likelihood connectivity assignment, VL2a- and DA1-PNs connect with γ and early α/β lobes. It is possible that the fru-expressing PNs and KCs also are interconnected in the MB calyx, as are the fru-expressing OSNs and PNs in the AL. These data suggest that stereotyped connectivity in the PN-to-KC map is likely involved in fru-expressing circuits, which are essential for proper behavioral responses to volatile sex pheromones (Lin, 2007).

A central question in olfaction is how the brain discriminates different odors to elicit an appropriate behavioral response. Stereotypic connectivity maps of odorant-to-OR, OSN-to-PN, and PN-to-KC at three consecutive levels allow further construction of a neural computation of odor discrimination in the adult Drosophila brain. Stereotypic PN-to-KC connectivity and functional imaging suggest differential representation of the odors in the AL is maintained in the MB calyx and possibly further processed in the different MB neurons/lobes. If so, how does the same class of KCs discriminate odorants carrying different biological information, such as a sex pheromone and an aggregation pheromone? A single class of KCs might be sufficient to discriminate two different odors in some cases, since Drosophila larvae can discriminate different odors with only γ neurons. Thus, additional spatial and/or temporal complexity for neural computation must exist among KCs of the same birth-order class. Consistent with this notion, the data show that PNs connecting with the same class of KCs may have different projecting patterns among K1-K5 dendritic divisions, suggesting differential functions for each of the four KC clones. Even with the same developmental history of clonal origin and birth order, KCs are likely divided into different identities further based on differential gene expression. For example, Gal4 line G0050 labels the entire α'/β' lobe but c305a labels only the frontal-half α'/β' lobe. Even with such developmental specification, odor discrimination also may require additional integration among different classes of KCs (Lin, 2007).

Although stereotypic connectivity maps from ORNs to PNs to KCs give the impression of a straight and simple path, olfactory coding clearly will be modulated by both stimulatory and inhibitory signals as it makes its way through the brain. A single ORN can exhibit both excitatory and inhibitory responses to different odorants. In the ALs, odor responses of the PNs are reshaped by inhibition from local neurons. In the MBs, KCs may receive both stimulatory and inhibitory stimuli from PNs, since most of them are cholinergic but some of them are GABAergic. Immunohistochemical labeling and GFP expression patterns in Cha-GAL4 and GAD-GAL4 lines indicate that KCs are also composed of both cholinergic and GABAergic neurons. The distribution of odor responses across different classes of KCs and the imposition of odor-sensitive excitatory and inhibitory responses both appear to enhance distinct neural representations of different odors. Such complexity of odor representations greatly reduces the possibility of overlap between spatiotemporal patterns elicited by two different odorants, making them easier to discriminate or to memorize and recall (Lin, 2007).

In conclusion, the data offer specific and testable hypotheses that olfactory coding at the ALs is likely further represented and decoded in the MBs and then transferred via distinct lobes to separate higher brain centers. It would be important now to complete the PN-to-KC map, to identify further subclasses within each of the five KC classes, and to answer how different classes of KCs communicate with each other during olfactory neural computation (Lin, 2007).

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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. (2014b). 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, 2014b: 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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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 we have 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, 2014b).

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, 2014b).

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, 2014b).

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, 2014b).

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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).

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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

The complete connectome of a learning and memory centre in an insect brain

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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Long-term memory requires sequential protein synthesis in three subsets of mushroom body output neurons in Drosophila

Wu, J. K., Tai, C. Y., Feng, K. L., Chen, S. L., Chen, C. C. and Chiang, A. S. (2017). . Sci Rep 7(1): 7112. PubMed ID: 28769066

Creating long-term memory (LTM) requires new protein synthesis to stabilize learning-induced synaptic changes in the brain. In the fruit fly, Drosophila melanogaster, aversive olfactory learning forms several phases of labile memory to associate an odor with coincident punishment in the mushroom body (MB). It remains unclear how the brain consolidates early labile memory into LTM. This study surveyed 183 Gal4 lines containing almost all 21 distinct types of MB output neurons (MBONs) and showed that sequential synthesis of learning-induced proteins occurs at three types of MBONs. Downregulation of oo18 RNA-binding proteins (ORBs) in any of these MBONs impaired LTM. And, neurotransmission outputs from these MBONs are all required during LTM retrieval. Together, these results suggest an LTM consolidation model in which transient neural activities of early labile memory in the MB are consolidated into stable LTM at a few postsynaptic MBONs through sequential ORB-regulated local protein synthesis (Wu, 2017).

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Two components of aversive memory in Drosophila, anesthesia-sensitive and anesthesia-resistant memory, require distinct domains within the Rgk1 small GTPase

Murakami, S., Minami-Ohtsubo, M., Nakato, R., Shirahige, K. and Tabata, T. (2017). J Neurosci [Epub ahead of print]. PubMed ID: 28416593

For aversive olfactory memory in Drosophila, multiple components have been identified that exhibit different stabilities. Intermediate-term memory generated after single cycle conditioning is divided into anesthesia-sensitive memory (ASM) and anesthesia-resistant memory (ARM), with the latter being more stable. This study determined that the ASM and ARM pathways converged on the Rgk1 small GTPase and that the N-terminal domain-deleted Rgk1 was sufficient for ASM formation, whereas the full-length form was required for ARM formation. Rgk1 is specifically accumulated at the synaptic site of the Kenyon cells (KCs), the intrinsic neurons of the mushroom bodies (MBs), which play a pivotal role in olfactory memory formation. A higher than normal Rgk1 level enhanced memory retention, which is consistent with the result that Rgk1 suppressed Rac-dependent memory decay; these findings suggest that rgk1 bolsters ASM via the suppression of forgetting. It is proposed that Rgk1 plays a pivotal role in the regulation of memory stabilization by serving as a molecular node that resides at KC synapses, where the ASM and ARM pathway may interact (Murakami, 2017).

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Activity of defined mushroom body output neurons underlies learned olfactory behavior in Drosophila

Owald, D., Felsenberg, J., Talbot, C. B., Das, G., Perisse, E., Huetteroth, W. and Waddell, S. (2015). Neuron 86: 417-427. PubMed ID: 25864636

During olfactory learning in fruit flies, dopaminergic neurons assign value to odor representations in the mushroom body Kenyon cells. This study identified a class of downstream glutamatergic mushroom body output neurons (MBONs) called M4/6, or MBON-β2β'2a, MBON-β'2mp, and MBON-γ5β'2a, whose dendritic fields overlap with dopaminergic neuron projections in the tips of the β, β', and γ lobes. This anatomy and their odor tuning suggests that M4/6 neurons pool odor-driven Kenyon cell synaptic outputs. Like that of mushroom body neurons, M4/6 output is required for expression of appetitive and aversive memory performance. Moreover, appetitive and aversive olfactory conditioning bidirectionally alters the relative odor-drive of M4β' neurons (MBON-β'2mp). Direct block of M4/6 neurons in naive flies mimics appetitive conditioning, being sufficient to convert odor-driven avoidance into apprroach, while optogenetically activating these neurons induces avoidance behavior. It is therefore proposed that drive to the M4/6 neurons reflects odor-directed behavioral choice. See Three Pairs of Glutamatergic Output Neurons Innervate the Tips of the Horizontal Mushroom Body Lobes (Owald, 2015).

Many prior studies have concluded that mushroom body neurons are dispensable for naive odor-driven behavior and subsets are either required or are dispensable for particular memory functions. However, these experiments simultaneously blocked all the outputs from a given population of KCs using cell-wide expression of shits1. The current results suggest that these models should be reconsidered. Blocking the specific M4β/MBON-β2β'2a, M4β'/MBON-β'2mp, and M6/MBON-γ5β'2a output from the mushroom body, as opposed to blocking all outputs, has a radical effect on naive odor-driven behavior. It is proposed that ordinarily, in naive flies, the multiple mushroom body output channels are ultimately pooled and contribute a net zero to odor-driven behavior. Therefore, if one uses a mushroom body neuron-driven UAS-shits1 that simultaneously blocks all outputs, there is no apparent effect on naive behavior. If, however, one blocks only one channel, or alters its efficacy by learning, the odor-driven behavior can be changed. A similar logic could also account for why clear memory retrieval defects are seen when blocking M4β'/MBON-β'2mp and M6/MBON-γ5β'2a neurons that presumably pool outputs from the tip of the γ and β' lobe, yet blocking all α'β' neuron outputs did not demonstrably disrupt later memory retrieval. Others have shown a role for α'β' neuron output to retrieve earlier forms of memory (Owald, 2015).

Both the physiological and behavioral results are consistent with a depression of the M4β'/MBON-β'2mp and M6/MBON-γ5β'2a output being sufficient to code learned approach. Learning-related plasticity has been reported at the β-lobe outputs in both bees and locusts, although the importance of these synaptic connections in the behavior of these insects is not known. At this stage it is not certain that the observed decrease in the relative odor drive reflects plasticity of the synapses between odor-specific KCs and the M4/6 neurons. However, it seems plausible, because this synaptic junction is addressed by the relevant rewarding dopaminergic neurons. Given that blocking M4β'/MBON-β'2mp and M6/MBON-γ5β'2a neurons converts avoidance to approach, other mushroom body output channels, perhaps some of which lie on the vertical α-lobe projection, must drive the approach behavior. It is therefore conceivable that a similar plasticity of odor drive to these putative approach outputs could be critical for aversive conditioning. Such an idea is consistent with several prior reports of aversive memory traces that are specific to the vertical α-branch of the mushroom body. In addition, aversive learning has been reported to depress odor drive in the vertical lobe of downstream MB-V2α/MBON-α2sc and MB-V2α'/MBON-α'3 neurons and to potentiate odor drive of MB-V3/MBON-α3 output neurons. However, it is notable that blocking either the MB-V2α/MBON-α2sc and MB-V2α'/MBON-α'3 neurons or MB-V3/MBON-α3 neurons did not affect naive odor avoidance behavior in the current experiments or those of others. Therefore, although MB-V2α/MBON-α2sc, MB-V2α'/MBON-α'3, and MB-V3/MBON-α3 neurons are required for memory expression, it is not currently known which reinforcing neurons address MB-V2α/MBON-α2sc, MB-V2α'/MBON-α'3, and MB-V3/MBON-α3 connections and how these outputs specifically contribute to odor-guided behavior (Owald, 2015).

The physiological analyses suggest bidirectional plasticity of odor-evoked responses, with aversive learning increasing the relative conditioned odor drive to the M4β'/MBON-β'2mp neurons. This could account for why output from M4/6 neurons is also required for expression of aversive memory. Moreover, whereas blocking the M4β/MBON-β2β'2a, M4β'/MBON-β'2mp, and M6/MBON-γ5β'2a neurons converts odor avoidance into approach, activation of M4β/MBON-β2β'2a, M4β'/MBON-β'2mp, and M6/MBON-γ5β'2a neurons drives avoidance. It therefore seems likely that plasticity of the relative odor drive to M4β'/MBON-β'2mp neurons is also part of the aversive memory engram. Again, it is not known that the increased odor drive after training reflects synaptic potentiation between odor-specific KCs and the M4β'/MBON-β'2mp neurons. Increased odor drive to M4β'/MBON-β'2mp neurons could, for example, also result from plasticity elsewhere in the KCs that enhances signal propagation along the horizontal KC arbor. Nevertheless, the MB-M3 dopaminergic neurons that are required to reinforce aversive memory also innervate the tips of the β and β' lobe. In addition, a recent study reported that aversive learning specifically decreased unconditioned odor-evoked neurotransmission from the γ neurons, a result that presumably would mirror a relative increase in the response to the reinforced odor. Lastly, aversive conditioning using relative shock intensity utilizes the rewarding dopaminergic neurons that occupy the same zones on the mushroom body as the M4β'/MBON-β'2mp and M6/MBON-γ5β'2a neuron dendrites. With the caveat that GRASP is only an indicator of proximity, the anatomical studies suggest that dendrites of rewarding dopaminergic neurons may connect to the M4β'/MBON-β'2mp and M6/MBON-γ5β'2a neuron presynaptic terminals, forming a potential feedback or forward loop that could serve such a relative-judgment function (Owald, 2015).

It is perhaps noteworthy that KC outputs in the vertical lobe are onto excitatory cholinergic MB-V2α/MBON-α2sc and MB-V2α'/MBON-α'3 neurons, whereas the horizontal outputs are onto glutamatergic, potentially inhibitory, M4β/MBON-β2β'2a, M4β'/MBON-β'2mp, and M6/MBON-γ5β'2a neurons. This suggests that distinct signaling modes may be driven from the bifurcated collaterals of KCs. It will be crucial to understand how these outputs from the different branches, and those from discrete lobes, are ultimately pooled to guide appropriate behavior (Owald, 2015).

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Memory-relevant mushroom body output synapses are cholinergic

Barnstedt, O., Owald, D., Felsenberg, J., Brain, R., Moszynski, J. P., Talbot, C. B., Perrat, P. N. and Waddell, S. (2016). Neuron 89: 1237-1247. PubMed ID: 26948892

Memories are stored in the fan-out fan-in neural architectures of the mammalian cerebellum and hippocampus and the insect mushroom bodies. However, whereas key plasticity occurs at glutamatergic synapses in mammals, the neurochemistry of the memory-storing mushroom body Kenyon cell output synapses is unknown. This study demonstrates a role for acetylcholine (ACh) in Drosophila. Kenyon cells express the ACh-processing proteins ChAT and VAChT, and reducing their expression impairs learned olfactory-driven behavior. Local ACh application, or direct Kenyon cell activation, evokes activity in mushroom body output neurons (MBONs). MBON activation depends on VAChT expression in Kenyon cells and is blocked by ACh receptor antagonism. Furthermore, reducing nicotinic ACh receptor subunit expression in MBONs compromises odor-evoked activation and redirects odor-driven behavior. Lastly, peptidergic corelease enhances ACh-evoked responses in MBONs, suggesting an interaction between the fast- and slow-acting transmitters. Therefore, olfactory memories in Drosophila are likely stored as plasticity of cholinergic synapses (Barnstedt, 2016).

Despite decades of work on learning and memory and other functions of the MB, the identity of the fast-acting neurotransmitter that is released from the KCs has remained elusive. Much of the insect brain was considered to be cholinergic, but the MB was thought to be unique. Histological studies concluded that the MB did not express ChAT but that subsets of KCs contained glutamate, aspartate, or taurine. However, conclusive evidence that these molecules are released as neurotransmitters has not materialized (Barnstedt, 2016).

This study presents multiple lines of evidence that ACh is a KC transmitter. (1) KCs express the ChAT and VAChT proteins that synthesize and package ACh into synaptic vesicles, and the expression of these genes is required for MB-dependent learned behavior. (2) Stimulation of KCs triggers responses in MBONs that are similar to those evoked by direct ACh application. (3) Reducing ACh processing in KCs impairs KC-evoked responses in MBONs. (4) ACh- and KC-evoked responses in MBONs are both sensitive to antagonism of nicotinic ACh receptors. (5) Odor-evoked responses in MBONs are attenuated by reducing the expression of several nicotinic ACh receptor subunits. Taken together, these data provide compelling support that ACh is a major neurotransmitter released from Drosophila KCs (Barnstedt, 2016).

The anatomy of ACh-responsive MBONs suggests that many αβ, α'β', and γ lobe KCs are likely to be cholinergic. Calcium imaging may miss subtle or inhibitory effects, so it remains possible that subclasses of KC might also release or corelease other small molecule transmitters. It is, for example, notable that the MB neurons express an atypical putative vesicular transporter. Furthermore, taurine histology specifically labels the αβ core neurons. Anatomy suggests that αβ core and αβ surface outputs are pooled by MBONs with dendrites in the α lobe tip and throughout the β lobe, but that the dendrites of MBONs in the α lobe stalk preferentially innervate αβ surface neurons. It will be important to understand how ACh signals from different KCs are integrated by MBONs. The αβ and γ, but not α'β', KCs can corelease ACh with the sNPF neuropeptide. The current data raise the possibility that coreleased sNPF may facilitate ACh-evoked responses. sNPF drives autocrine presynaptic facilitation of certain olfactory sensory neurons in the adult fly. Conversely, sNPF decreased the resting membrane potential of larval motor neurons that ectopically express sNPFR. MBONs with dendrites in certain lobes therefore receive different combinations of transmitters and may vary in responding to sNPF (Barnstedt, 2016).

Finding that ACh is the KC transmitter has important implications for learning-relevant plasticity at KC-MBON synapses. Current models suggest that valence-specific and anatomically restricted reinforcing dopaminergic neurons drive presynaptically expressed plasticity between KCs and particular MBONs. Reward learning skews KC-MBON outputs toward driving approach by depressing the odor drive to MBONs that direct avoidance, whereas aversive learning enhances drive to avoidance by reducing drive to approach MBONs and increasing drive to avoidance pathways. The results here indicate that learning is represented as dopaminergic tuning of excitatory cholinergic KC-MBON synapses (Barnstedt, 2016).

Learning requires dopamine receptor function in the KCs, which implies a presynaptic mechanism of plasticity at the KC-MBON junction. Presynaptic plasticity of odor-activated KCs provides a simple means to retain odor specificity of memory in the highly convergent anatomy of the MB-where 2,000 KCs converge onto single or very few MBONs per zone on the MB lobes. The anatomically analogous mammalian cerebellar circuits, to which the insect MBs have been compared, exhibit presynaptic glutamatergic plasticity that is cAMP dependent. Finding that the KC transmitter is ACh suggests that cAMP-dependent mechanisms can modulate synaptic connections, regardless of transmitter identity. The MB KCs appear to be strikingly similar to the large parallel ensemble of cholinergic amacrine cells in the vertical lobe of the cuttlefish. These Cephalopod amacrine cells also share the same fan-out input and fan-in efferent anatomy of the Drosophila KCs, and plasticity occurs at the cholinergic connection between amacrine cells and downstream large efferent neurons (Barnstedt, 2016).

Work in the locust suggested that spike-timing-dependent plasticity (STDP) marks the relevant conditioned odor-activated KC-MBON synapses so that they are susceptible to reinforcing modulation. STDP relies on coincidence of pre- and postsynaptic activity and influx of postsynaptic Ca2+ through NMDA-type glutamate receptors. Recent work in Drosophila pairing odor presentation with dopaminergic neuron activation reported odor-specific synaptic depression at a KC-MBON junction that did not require postsynaptic MBON depolarization. It will be important to determine whether this holds for all DAN-MBON compartments or whether some learning-induced plasticity involves synaptic Ca2+ influx through an ACh-triggered nAChR, rather than the more traditional glutamate-gated NMDA receptors (Barnstedt, 2016).

This study identified roles for the Dα1, Dα4, Dα5, and Dα6 nAChR subunits in M4/6 MBONs. Reducing the expression of these subunits lowered odor-evoked signals in MBONs and converted naive odor avoidance into approach behavior. Dα5 and Dα6 subunits can form functional heteromeric channels in vitro. Different MBONs may express unique combinations of AChRs and therefore have characteristic physiological responses to KC-released ACh, as well as perhaps different learning rules and magnitudes of plasticity. Pre- or postsynaptically localized muscarinic AChRs could provide additional memory-relevant modulation (Barnstedt, 2016).

Beyond important roles in memory formation, consolidation, and expression, the MB- and DAN-directed modulation of specific MBON pathways has also been implicated in controlling hunger, thirst, temperature, and sleep/wake state-dependent locomotor behaviors. It will therefore be important to understand how plasticity of cholinergic KC transmission serves these discrete functions (Barnstedt, 2016).

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Suppression of a single pair of mushroom body output neurons in Drosophila triggers aversive associations

Ueoka, Y., Hiroi, M., Abe, T. and Tabata, T. (2017). FEBS Open Bio 7(4): 562-576. PubMed ID: 28396840

Memory includes the processes of acquisition, consolidation and retrieval. In the study of aversive olfactory memory in Drosophila melanogaster, flies are first exposed to an odor (conditioned stimulus, CS+) that is associated with an electric shock (unconditioned stimulus, US), then to another odor (CS-) without the US, before allowing the flies to choose to avoid one of the two odors. The center for memory formation is the mushroom body which consists of Kenyon cells (KCs), dopaminergic neurons (DANs) and mushroom body output neurons (MBONs). However, the roles of individual neurons are not fully understood. This study focused on the role of a single pair of GABAergic neurons (MBON-gamma1pedc) and found that it could inhibit the effects of DANs, resulting in the suppression of aversive memory acquisition during the CS- odor presentation, but not during the CS+ odor presentation. It is proposed that MBON-gamma1pedc suppresses the DAN-dependent effect that can convey the aversive US during the CS- odor presentation, and thereby prevents an insignificant stimulus from becoming an aversive US (Ueoka, 2017).

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Propagation of homeostatic sleep signals by segregated synaptic microcircuits of the Drosophila mushroom body

Sitaraman, D., Aso, Y., Jin, X., Chen, N., Felix, M., Rubin, G. M. and Nitabach, M. N. (2015). Curr Biol 25: 2915-2927. PubMed ID: 26455303.

The Drosophila mushroom body (MB) is an associative learning network that is important for the control of sleep. Particular intrinsic MB Kenyon cell (KC) classes have been identified that regulate sleep through synaptic activation of particular MB output neurons (MBONs) whose axons convey sleep control signals out of the MB to downstream target regions. Specifically, it was found that sleep-promoting KCs increase sleep by preferentially activating cholinergic sleep-promoting MBONs, while wake-promoting KCs decrease sleep by preferentially activating glutamatergic wake-promoting MBONs. By using a combination of genetic and physiological approaches to identify wake-promoting dopaminergic neurons (DANs) that innervate the MB, it was shown that they activate wake-promoting MBONs. These studies reveal a dopaminergic sleep control mechanism that likely operates by modulation of KC-MBON microcircuits (Sitaraman, 2015).

This study used a combination of sophisticated cell-specific genetic manipulations with behavioral sleep analysis and optical electrophysiology to identify compartment-specific wake-promoting MB DANs that activate wake-promoting microcircuits. Previous studies have implicated DANs innervating the central complex (CX) - a brain region involved in locomotor control - in regulating sleep, and other non-dopamingeric CX neurons have been implicated in homeostatic control of sleep. In addition, it has recently been shown that manipulations of dopamine signaling in the MB alter sleep, although the precise DANs involved remains unclear. This study has now identified specific wake-promoting MB DANs and shown that they innervate lobe compartments also innervated by wake-promoting KCs and MBONs. Importantly, this study has also shown that dopamine secretion by DANs innervating a particular MB lobe compartment acts through D1 subtype receptors to activate the wake-promoting microcircuit specific to that compartment to a much greater extent than it activates the sleep-promoting microcircuit residing in different compartments. This provides direct physiological evidence for compartment-specific dopamine signaling in the regulation of sleep by the MB, and is consistent with a previous study in the context of learning and memory. Future studies are required to determine additional cellular and molecular details of how dopamine signals modulate sleep-regulating microcircuits (Sitaraman, 2015).

On the basis of recently published studies of MB control of sleep and the results presented in this study, a unified mechanistic model is proposed for homeostatic control of sleep by excitatory microcircuits in the Drosophila MB. Wake-promoting MBON-γ5β'2a/β'2mp/β'2mp_bilateral and sleep-promoting γ2α'1 each receive anatomical inputs from both wake-promoting γm and α'/β' KCs KCs and sleep-promoting γd KCs. However, segregation of sleep control information into separate microcircuits is enforced by greater synaptic weights between γ and γm and α'/β' KCs and MBON-γ5β'2a/β'2mp/β'2mp_bilateral, and between γm and α/β' KCs and MBON-γ5β'2a/β'2mp/β'2mp_bilateral, and between γd KCs and MBON-γ2α'1 (Sitaraman, 2015). Thus it is hypothesize that compartment-specific dopamine signals from MB DANs could potentially determine these differences in synaptic weight. Future studies will test this hypothesis (Sitaraman, 2015).

Interestingly, other fly behaviors have recently been found to be regulated by sleep-controlling compartment-specific MB microcircuits. For example, the integration of food odor to suppress innate avoidance of CO2 is mediated by MBON-γ5β'2a/β'2mp/β'2mp_bilateral and PAM DANs that innervate the β'2 compartment. Optogenetic activation experiments reveal that wake-promoting γ5β'2a/β'2mp/β'2mp_bilateral mediates innate avoidance, while MBON-γ2α'1 mediates attraction. However, thermogenetic inactivation studies reveal that both MBON-γ5β'2a/β'2mp/β'2mp_bilateral and MBON-γ2α'1 are important for various forms of associative memory formation. These diverse waking behaviors that involve the activity of sleep-regulating neurons raises the interesting question whether such roles are independent, or causally linked, which future studies can address (Sitaraman, 2015).

Importantly, this study has provided for the first time a cellular and molecular mechanism for for dopaminergic control of sleep through modulation of an associative network. While dopaminergic projections to cerebral cortex are known to be important for regulating sleep and arousal in mammals, underlying cellular and molecular mechanisms remain poorly understood, although D2 subtype dopamine receptors have been implicated in the control of REM sleep. Because of the possible evolutionary relationship between the MB and vertebrate forebrain associative networks (such as mammalian cerebral cortex), these studies thus provide a framework for the design of analogous experiments in genetically tractable vertebrate model systems such as zebrafish and mice (Sitaraman, 2015)

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Control of sleep by dopaminergic inputs to the Drosophila mushroom body

Sitaraman, D., Aso, Y., Jin, X., Chen, N., Felix, M., Rubin, G. M. and Nitabach, M. N. (2015). Curr Biol 25: 2915-2927. PubMed ID: 26455303.

The Drosophila mushroom body (MB) is an associative learning network that is important for the control of sleep. Particular intrinsic MB Kenyon cell (KC) classes have been identified that regulate sleep through synaptic activation of particular MB output neurons (MBONs) whose axons convey sleep control signals out of the MB to downstream target regions. Specifically, it was found that sleep-promoting KCs increase sleep by preferentially activating cholinergic sleep-promoting MBONs, while wake-promoting KCs decrease sleep by preferentially activating glutamatergic wake-promoting MBONs. By using a combination of genetic and physiological approaches to identify wake-promoting dopaminergic neurons (DANs) that innervate the MB, it was shown that they activate wake-promoting MBONs. These studies reveal a dopaminergic sleep control mechanism that likely operates by modulation of KC-MBON microcircuits.

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Heterosynaptic plasticity underlies aversive olfactory learning in Drosophila

Hige, T., Aso, Y., Modi, M. N., Rubin, G. M. and Turner, G. C. (2015). Neuron 88: 985-998. PubMed ID: 26637800

Although associative learning has been localized to specific brain areas in many animals, identifying the underlying synaptic processes in vivo has been difficult. This study provides the first demonstration of long-term synaptic plasticity at the output site of the Drosophila mushroom body. Pairing an odor with activation of specific dopamine neurons induces both learning and odor-specific synaptic depression. The plasticity induction strictly depends on the temporal order of the two stimuli, replicating the logical requirement for associative learning. Furthermore, dopamine action was shown to be confined to and distinct across different anatomical compartments of the mushroom body lobes. Finally, overlap between sparse representations of different odors defines both stimulus specificity of the plasticity and generalizability of associative memories across odors. Thus, the plasticity found in this study not only manifests important features of associative learning but also provides general insights into how a sparse sensory code is read out (Hige, 2015).

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Re-evaluation of learned information in Drosophila

Felsenberg, J., Barnstedt, O., Cognigni, P., Lin, S. and Waddell, S. (2017). Nature 544(7649): 240-244. PubMed ID: 28379939

Animals constantly assess the reliability of learned information to optimize their behaviour. On retrieval, consolidated long-term memory can be neutralized by extinction if the learned prediction was inaccurate. Alternatively, retrieved memory can be maintained, following a period of reconsolidation during which it is labile. Although extinction and reconsolidation provide opportunities to alleviate problematic human memories, a detailed mechanistic understanding of memory updating is lacking. This study identified neural operations underpinning the re-evaluation of memory in Drosophila. Reactivation of reward-reinforced olfactory memory can lead to either extinction or reconsolidation, depending on prediction accuracy. Each process recruits activity in specific parts of the mushroom body output network and distinct subsets of reinforcing dopaminergic neurons. Memory extinction requires output neurons with dendrites in the α and α' lobes of the mushroom body, which drive negatively reinforcing dopaminergic neurons that innervate neighbouring zones. The aversive valence of these new extinction memories neutralizes previously learned odour preference. Memory reconsolidation requires the γ2α'1 mushroom body output neurons. This pathway recruits negatively reinforcing dopaminergic neurons innervating the same compartment and re-engages positively reinforcing dopaminergic neurons to reconsolidate the original reward memory. These data establish that recurrent and hierarchical connectivity between mushroom body output neurons and dopaminergic neurons enables memory re-evaluation driven by reward-prediction error (Felsenberg, 2017).

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Coincident postsynaptic activity gates presynaptic dopamine release to induce plasticity in Drosophila mushroom bodies

Ueno, K., Suzuki, E., Naganos, S., Ofusa, K., Horiuchi, J. and Saitoe, M. (2017). Elife 6. PubMed ID: 28117664

Simultaneous stimulation of the antennal lobes (ALs) and the ascending fibers of the ventral nerve cord (AFV), two sensory inputs to the mushroom bodies (MBs), induces long-term enhancement (LTE) of subsequent AL-evoked MB responses. LTE induction requires activation of at least three signaling pathways to the MBs, mediated by nicotinic acetylcholine receptors (nAChRs), NMDA receptors (NRs), and D1 dopamine receptors (D1Rs). This study demonstrates that inputs from the AL are transmitted to the MBs through nAChRs, and inputs from the AFV are transmitted by NRs. Dopamine signaling occurs downstream of both nAChR and NR activation, and requires simultaneous stimulation of both pathways. Dopamine release requires the activity of the rutabaga adenylyl cyclase in postsynaptic MB neurons, and release is restricted to MB neurons that receive coincident stimulation. These results indicate that postsynaptic activity can gate presynaptic dopamine release to regulate plasticity (Ueno, 2017).

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Presynapses in Kenyon cell dendrites in the mushroom body calyx of Drosophila

Christiansen, F., et al. (2011). J. Neurosci. 31(26): 9696-707. PubMed ID: 21715635

Plastic changes at the presynaptic sites of the mushroom body (MB) principal neurons called Kenyon cells (KCs) are considered to represent a neuronal substrate underlying olfactory learning and memory. It is generally believed that presynaptic and postsynaptic sites of KCs are spatially segregated. In the MB calyx, KCs receive olfactory input from projection neurons (PNs) on their dendrites. Their presynaptic sites, however, are thought to be restricted to the axonal projections within the MB lobes. This study shows that KCs also form presynapses along their calycal dendrites, by using novel transgenic tools for visualizing presynaptic active zones and postsynaptic densities. At these presynapses, vesicle release following stimulation could be observed. They reside at a distance from the PN input into the KC dendrites, suggesting that regions of presynaptic and postsynaptic differentiation are segregated along individual KC dendrites. KC presynapses are present in γ-type KCs that support short- and long-term memory in adult flies and larvae. They can also be observed in α/β-type KCs, which are involved in memory retrieval, but not in α'/β'-type KCs, which are implicated in memory acquisition and consolidation. It is hypothesized that, as in mammals, recurrent activity loops might operate for memory retrieval in the fly olfactory system. The newly identified KC-derived presynapses in the calyx are, inter alia, candidate sites for the formation of memory traces during olfactory learning (Christiansen, 2011).

This study used several approaches to provide evidence that the KC dendrites within the calyx of larval and adult Drosophila are not exclusively postsynaptic. They also form presynaptic active zones (AZs), which was named KCACs. These findings are supported by data from two previous studies, which reported the presence of a presynaptic vesicle protein, Synaptobrevin, in KCs within the calyx. This study used a functional imaging approach to show that KCACs are able to release SVs. Furthermore, which different KC subtypes form KCACs was examined and a detailed description of the KCAC location within the calyx is provided. The presence of these previously undescribed KC-intrinsic presynaptic elements adds a new layer of complexity to the MB microcircuitry (Christiansen, 2011).

Within KC dendrites, AZs and PSDs are clearly organized into discrete subdomains. Here, the question emerges whether a given KC dendrite is either exclusively presynaptic or postsynaptic, or whether both presynaptic and postsynaptic domains can be present within the same KC dendrite in a consecutive fashion. MARCM identified single KCs, which showed Bruchpilot (BRP) puncta spatially segregated from claw-like regions that are thought to harbor the postsynaptic specializations of cholinergic PN::KC synapses. In parallel experiments, these claws were shown clustered the acetylcholine receptor Dα7. Thus, it appears likely that presynaptic and postsynaptic domains can be present within the same KC dendrite (Christiansen, 2011).

Based on BRP-RNAi analysis, it is estimated that ~20%-30% of all presynapses in the calyx are KCACs, in both adults and larvae. These synapses are apparently part of the general calyx microcircuitry. They might synapse onto PNs, KCs themselves, the anterior paired lateral (APL) neuron, modulatory neurons, or so-far-undescribed cells. From this analysis, it appears unlikely that PN boutons are direct postsynaptic partners of the KCACs, as the KCACs appear to be clearly physically segregated from the PN boutons. KCACs might, however, project onto PN axons (Christiansen, 2011).

It appears well possible that KCACs project onto the GABAergic APL neuron, which arborizes in the whole calyx. Within the insect antennal lobe, reciprocal dendrodendritic connections between the PNs and the partially GABAergic local interneurons (LNs) have been described. The PN neurites and the LNs are both transmissive and receptive in the antennal lobe, suggesting a computation between them. KCACs might be involved into similar computations in the calyx. This would be in accordance with EM studies in crickets that suggest presynapses in KCs that connect to GABAergic fibers in the MB calyx (Christiansen, 2011).

KCACs might also mediate KC::KC communication. In fact, dendritic segments of KCs that harbor presynapses appear to run in a parallel fashion. This arrangement could promote the communication between dendritic segments of KCs via dendrodendritic synapses. Such KC::KC synapses could therefore modulate signals originating from the distal segments of the arborizations, which carry odor-evoked signals. By these means, an effective computation between KCs could be accomplished before they transmit their input signals downstream (Christiansen, 2011).

Unfortunately, at the moment no general PSD markers are available in Drosophila. Moreover, the neurotransmitter used by KCs remains unknown. With a general postsynaptic marker or knowledge about the KC transmitter, it would have been possible to generated tools to identify the postsynaptic partners of KCACs. Yet currently, despite efforts, it is only possible to speculate about the postsynaptic partners of KCs in the calyx (Christiansen, 2011).

Memory traces are typically thought to be manifested as plastic changes in neuronal anatomy and physiology that occur in specific brain regions. Several lines of evidence indicate that MBs are causally involved in associative learning of olfactory stimuli. Flies with chemically ablated KCs or mutants lacking the MBs are deficient in olfactory learning. Learning was investigated in flies mutant for the adenylyl cyclase rutabaga (rut), which is suggested to act as a coincidence detector between conditioned stimulus (odor) and unconditioned stimulus (e.g., electric shock). Reexpression of a rut cDNA in a rut- background within a subpopulation of KCs sufficed to restore odor learning. For appetitive learning, reexpression of rut in either PNs or KCs is sufficient to restore the mutant defect, whereas aversive learning is rescued only by rut reexpression in KCs. Reversible disruption of transmitter release in Drosophila KCs, using a temperature-sensitive dynamin transgene, UAS-shibirets1, was shown to block memory retrieval in α/β neurons and acquisition and stabilization of memory in α'/β' neurons. Together, these data imply that MBs play a major role in learning and memory. To form, stabilize, and retrieve memory, KCs use their presynapses. The KC presynapses are so far believed to reside in the lobes (Christiansen, 2011 and references therein).

The biogenic amines octopamine and dopamine are thought to mediate the unconditioned stimulus signal for learning olfactory associations, with octopamine representing appetitive stimuli and dopamine representing aversive stimuli. It has been shown that, in honeybees, sugar can be replaced by octopamine application to the calyx to trigger the conditioned proboscis-extension reflex. In the fruit fly, the amines octopamine and dopamine are released onto MB lobes and calyx. This holds also true for the larva. Therefore, the KCACs might be involved in appetitive learning as well as in aversive learning in fly and larva (Christiansen, 2011).

Notably, this study found that the KC subpopulations α and α/β, but not α'/β', form KCACs. This dichotomy correlates with functional differences in learning and memory that have been assigned to these KC classes in previous studies. For example, α'/β' KCs were reported to be required during and after training to acquire and stabilize olfactory memory, whereas output from α/β neurons was postulated to be required to retrieve memory. It has been proposed that, during acquisition, olfactory information received from PNs is first processed in parallel by the α/β and α'/β' KCs. Notably, activity in α'/β' KCs (which do not form KCACs) is supposed to trigger a recurrent loop between α'/β' KCs and dorsal paired medial neurons, which project to the MB lobes. This loop, in turn, might be necessary for memory consolidation in α/β neurons. Subsequently, memories could be stored in α/β neurons, whose activity is required during recall. As α'/β' neurons are devoid of KCACs, KCACs cannot be involved in the circuit described above. Instead, it is likely that additional, similar recurrent loops exist, which are mediated via KCACs. However, it remains unresolved how exactly KC::KC communication is organized anatomically and functionally. This study now proposes a newly discovered synapse population as candidate sites for KC::KC communication (Christiansen, 2011).

In the mammalian olfactory system, major feedback pathways exist, which project onto neurons one level lower in hierarchy. It has been shown that likewise in Drosophila activation of KCs induced a depolarization in cell bodies of PNs and LNs within the antennal lobes. It was thus suggested that MB lobes provide feedback to the ALs. Moreover, an additional memory trace appears to exist in the antennal lobe, in the PNs. It may therefore well be the case that KCs project onto PNs or onto feedback neurons via their KCACs (Christiansen, 2011).

An urgent question of the field concerns the identification of the postsynaptic partner cells of KC presynapses, which harbor memory traces during olfactory conditioning. It is generally assumed that MB-extrinsic downstream neurons involved in behavioral execution of learned behavior serve as postsynaptic partners here. The current findings raise the possibility that microcircuits inside the MB could be places for further modulation and computation of olfactory processing and/or memory formation and modulation. As a consequence, not only the communication to downstream neurons but also the representation of sensory information within the MB circuitry might be changed by experience. Future analysis using optophysiological tools at the KCACs, together with further anatomical work, should provide answers to these questions (Christiansen, 2011).

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Integration of the olfactory code across dendritic claws of single mushroom body neurons

Gruntman, E. and Turner, G. C. (2013). Nat Neurosci. 16: 1821-1829. PubMed ID: 24141312

In the olfactory system, sensory inputs are arranged in different glomerular channels, which respond in combinatorial ensembles to the various chemical features of an odor. This study investigated where and how this combinatorial code is read out deeper in the brain. The unique morphology was exploited of neurons in the Drosophila mushroom body, which receive input on large dendritic claws. Imaging odor responses of these dendritic claws revealed that input channels with distinct odor tuning converge on individual mushroom body neurons. How these inputs interact to drive the cell to spike threshold was determined using intracellular recordings to examine mushroom body responses to optogenetically controlled input. The results provide an elegant explanation for the characteristic selectivity of mushroom body neurons: these cells receive different types of input and require those inputs to be coactive to spike. These results establish the mushroom body as an important site of integration in the fly olfactory system (Gruntman, 2013).

There are two basic requirements that must be fulfilled to show that neurons read the combinatorial code of the early olfactory layers: they receive convergent input from functionally distinct glomerular channels and require activation of multiple inputs to respond. Using in vivo imaging of the individual synaptic inputs, this study found that Kenyon cells receive inputs with functionally distinct odor response properties. By optogenetically stimulating a defined subset of projection neurons and intracellularly recording from postsynaptically connected Kenyon cells, it was found that several of those inputs must be activated to evoke a spiking response in a downstream Kenyon cell. These results indicate that Kenyon cells respond to specific combinations of coactive glomerular channels. This is likely the basis for their highly stimulus-specific response properties. Notably, this study found that synaptic summation is essentially linear in Kenyon cells, and multiple lines of evidence suggest that Kenyon cell dendrites have purely passive cable properties. Using patterned photostimulation, others have shown that neurons in olfactory cortex respond selectively to particular patterns of glomerular activation. Thus, the integration of different channels is likely to be a fundamental aspect of the transformation at the third layer of the olfactory system. (Gruntman, 2013).

Anatomical studies originally suggested that the mushroom body might be an important site for the convergence of different glomerular channels. Projection neurons send wide-ranging projections in the calyx of the mushroom body, and the synaptic terminals of different projection neuron types intermingle in this area. Moreover, single-cell labeling suggests that the dendrites of individual Kenyon cells extend rather widely in the mushroom body calyx, suggesting they could collect input from different projection neuron types. Retrogradely tracing the inputs to individual Kenyon cells showed that projection neurons of different glomerular origin converge onto individual Kenyon cells. This study found no statistical structure in the probability of different projection neurons converging onto the same Kenyon cell, suggesting that connectivity at this layer is random. This result contrasts somewhat with earlier anatomical studies that found that different projection neuron types show coarsely regionalized projections, although there was extensive overlap between different projection zones. It has also been shown that different subtypes of Kenyon cells tend to innervate particular regions of the mushroom body calyx. Consistent with this loose regionalization, one study reported a correlation in the projection patterns of particular types of projection neurons and Kenyon cells. Altogether, the evidence from these global mapping studies supports a model in which projection neuron-Kenyon cell connectivity is probabilistic and regionally biased rather than completely random (Gruntman, 2013).

This study took a functional approach to the question of convergence by directly imaging odor responses of individual synaptic sites. The results indicate that functionally distinct inputs converge onto the dendritic trees of individual Kenyon cells. When the similarity of odor response profiles was examined for the claws of a given Kenyon cell, it was found that they were more similar to one another than they were to claws from different cells. This suggests that projection neurons with similar tuning properties have a tendency to converge onto the same Kenyon cells. In addition, when ChR2 stimulation was used to examine the relationship between anatomical and functional connectivity, the levels of connectivity that were observed were significantly different from that predicted by random convergence. Overall, the results were more consistent with the model of regionalized, probabilistic connectivity derived from global mapping of projection neuron and Kenyon cell projections than that of entirely random convergence supported by retrograde labeling. The functional approach may have proved more sensitive to detecting correlations in connectivity than a purely anatomical one; correlated response properties are important determinants of wiring in many neural circuits. Nevertheless, the dominant theme of the current results was that functionally distinct inputs converge onto the dendrites of individual Kenyon cells. Convergence is likely a core feature of this layer of the olfactory circuit, as trans-synaptic tracing has shown that neurons in the piriform cortex receive mitral cell input originating from several different glomeruli (Gruntman, 2013).

A recent study investigated the input-output transformation of Kenyon cells by imaging activity in projection neuron boutons and Kenyon cell axons (Li, 2013). Examining odor-evoked activity in these different cells, the authors found that the summed activity of the projection neuron inputs correlates well with the likelihood of an axonal response in a postsynaptic Kenyon cell. In contrast, this study used an electrophysiological approach to examine synaptic responses to optogenetically controlled projection neuron inputs, enabling investigation of the integration of inputs from the dendritic claws. By recording from randomly selected Kenyon cells and reconstructing their morphology post hoc, both functional and anatomical measures of connectivity were establised for each cell recorded. Comparing responses of Kenyon cells with different levels of connectivity allowed determinination of how different synaptic inputs interact and allowed establishment of the relationship between synaptic input and spiking in these cells (Gruntman, 2013).

Dendritic inputs from different sites could interact synergistically; for example, by summating to activate voltage-gated channels that boost the synaptic response. Such synergistic interactions have been observed in mammalian barrel cortex, where coordinated input to different dendritic sites from different sensory modalities elicits a distinct bursting response mode in these cells. Synergistic interactions could make it easier for Kenyon cells to respond selectively to particular input patterns; they could enable a clear distinction between activation of a small set of inputs that is not sufficient to bring the cell to spike and activation of a larger, supra-threshold number of inputs. Electrical stimulation experiments in locust Kenyon cells have shown that synaptic responses are amplified and temporally sharpened by a voltage-dependent mechanism. In contrast, the current results with Drosophila Kenyon cells revealed that claws interact linearly when small numbers are coactive, and sublinearly when larger numbers are stimulated, likely as a result of shunting effects on the dendritic tree. Note that the stimulation conditions were designed to deliver high-frequency projection neuron input in a narrow time window, conditions that are well-suited to reveal synergistic interactions between coincident input. In separate experiments, the interaction between two precisely timed inputs was examined: synaptic stimulation at the dendrites and current injection at the soma. The additivity of these inputs was examined at a variety of different relative timings, and again no evidence was found for synergistic effects that would indicate heightened sensitivity to coincident input. Rather, the results are consistent with a model in which Kenyon cell dendrites serve as passive cables that convey and integrate synaptic input. Notably, this may enable Kenyon cells to take advantage of the format of projection neuron population activity. The antennal lobe transforms olfactory signals so that population representations are more linearly separable in the projection neurons than in the ORNs. By acting as linear integrators, the Kenyon cell dendrites would be well-suited to separate distinct projection neuron activity patterns (Gruntman, 2013).

The results are reminiscent of findings from third-order neurons in vertebrates. A recent study of cells in the dorsal telencephalon of zebrafish showed that these cells exhibit no special sensitivity to synchronous mitral cell inputs. Rather, input synchronization was important to control the precise timing of dorsal telencephalon spikes. Similarly, in mammalian olfactory cortex, synaptic inputs arrive in alternating waves of excitation and inhibition, which enforce temporally precise spiking, phase-locked to this oscillation cycle. In the case of the dorsal telencephalon neurons, the main factor driving cells to spike threshold is a large, slow depolarization, whereas the oscillatory synaptic drive governs the timing of spikes. This is very similar to intracellular recordings of Kenyon cell odor responses: large depolarizations are observed, with high-frequency (although non-periodic) fluctuations riding on top. As such, it seems likely that the main factor driving Kenyon cells to spike threshold in Drosophila, similar to dorsal telencephalon neurons, is the slow wave of depolarization that arises from the summation of projection neuron input from several dendritic claws (Gruntman, 2013).

The linear and sublinear additivity of claws is likely an important factor contributing to the sparsity of Kenyon cell spikes. When examining synaptic responses, only a few cases were found in which projection neuron stimulation evoked a response that was consistently above spike threshold in the postsynaptic Kenyon cell. These Kenyon cells were connected via several claws: three claws for one cell, five for the other. To characterize the relationship between connectivity and spiking, an extensive series of recordings was carried out in which Kenyon cells that spike in response to photostimulation were searched for specifically. A range of connectivity was found in the set of responding cells. Comparison was made across these different cells to examine the effects of increasing connectivity on spiking characteristics of Kenyon cells. Surprisingly, no correlation was found between the number of contacted claws and the magnitude of the spiking response. Kenyon cells tended to either respond or not, similar to the odor-evoked responses of these cells, which also do not span a wide range of spike rates. However, when the likelihood of Kenyon cell responses was examined as a function of the number connected claws, a strong relationship was observed. This analysis revealed that there was a marked increase in the proportion of responding cells receiving input on four or more claws. Kenyon cells typically have five to seven claws, so this suggests that the majority of a Kenyon cell's claws need to be coactive to evoke an odor-like response (Gruntman, 2013).

This requirement was not absolute, however, as cells with reliable spiking responses with lower levels of connectivity were found, and even a very small number of Kenyon cells were found that spiked when connected via only a single claw (2 of 191 total recorded Kenyon cells). Although it is possible that some Kenyon cells require activation of all their claws, it seems likely that most Kenyon cells require only a subset of their inputs to be active to spike. As there are many different projection neuron input patterns that could activate a subset of the Kenyon cells claws, these results indicate that Kenyon cells encode input patterns in a degenerate manner and that several different input patterns could effectively drive the cell. This is consistent with the odor response properties of Kenyon cells; although these cells are much more odor-selective than projection neurons, they do occasionally respond to multiple odors. Thus, although Kenyon cells' requirement for multiple coactive inputs certainly contributes to their stimulus selectivity, that selectivity is not absolute. Moreover, inhibitory circuit elements could potentially be important for controlling this selectivity, a possibility that was not addressed in this study. Together, these considerations indicate that Kenyon cells are likely to be degenerate decoders that respond to several related projection neuron response patterns (Gruntman, 2013).

It was found that Kenyon cells derive their highly specific response properties by integrating over diverse input channels, effectively reading the combinatorial odor code. Why would such selective responses be constructed from synaptic inputs with widely divergent tuning? One possibility is that it gives the mushroom body the flexibility to support olfactory learning. Given that each Kenyon cell is connected to inputs with very different odor tuning, adjusting the synaptic strength of one of the inputs could markedly alter the cell's response properties. In addition, this convergent connectivity is likely important for diversifying the odor response properties of the Kenyon cells relative to the projection neurons. This diversification could enable the network to transition from broadly tuned projection neurons to narrowly tuned Kenyon cells while maintaining the capacity to represent many different odors (Gruntman, 2013).

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Presynaptic inhibition of γ lobe neurons is required for olfactory learning in Drosophila

Zhang, J., Tanenhaus, A. K., Davis, J. C., Hanlon, B. M. and Yin, J. C. (2014). Neurobiol Learn Mem 118C: 80-88. PubMed ID: 25460038

The loss of heterotrimeric Go signaling through the expression of pertussis toxin (PTX) within either the α/β or γ lobe mushroom body neurons of Drosophila results in the impaired aversive olfactory associative memory formation. This study focused on the cellular effects of Go signaling in the γ lobe mushroom body neurons during memory formation. Expression of PTX in the γ lobes specifically inhibits Go activation, leading to poor olfactory learning and an increase in odor-elicited synaptic vesicle release. In the γ lobe neurons, training decreases synaptic vesicle release elicited by the unpaired conditioned stimulus minus, while leaving presynaptic activation by the paired conditioned stimulus plus unchanged. PTX expression in γ lobe neurons inhibits the generation of this differential synaptic activation by conditioned stimuli after negative reinforcement. Hyperpolarization of the γ lobe neurons or the inhibition of presynaptic activity through the expression of dominant negative dynamin transgenes ameliorated the memory impairment caused by PTX, indicating that the disinhibition of these neurons by PTX was responsible for the poor memory formation. The role for γ lobe inhibition, carried out by Go activation, indicates that an inhibitory circuit involving these neurons plays a positive role in memory acquisition. This newly uncovered requirement for inhibition of odor-elicited activity within the γ lobes is consistent with these neurons serving as comparators during learning, perhaps as part of an odor salience modification mechanism (Zhang, 2013).

Activation of Go is inhibited by the expression of PTX. The inhibition of Go activation by the expression of PTX within the γ lobe neurons of the mushroom bodies leads to a significant decrease in short term aversive memories. This study has now shown that this memory defect is caused by the disinhibition of the γ lobe neurons. Inhibition of Go increases odor-induced presynaptic activity. The inhibition of γ lobe neurons by either hyperpolarization or synaptic vesicle depletion reverses the PTX learning phenotype. It is proposed that the Go-mediated presynaptic inhibition of γ lobe neurons is required to generate differential conditioned stimulus salience during discriminative leaning (Zhang, 2013).

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Activity-dependent plasticity in an olfactory circuit

Sachse, S., Rueckert, E., Keller, A., Okada, R., Tanaka, N. K., Ito, K. and Vosshall, L. B. (2007). Neuron 56: 838-850. PubMed ID: 18054860

Olfactory sensory neurons (OSNs) form synapses with local interneurons and second-order projection neurons to form stereotyped olfactory glomeruli. This primary olfactory circuit is hard-wired through the action of genetic cues. It was asked whether individual glomeruli have the capacity for stimulus-evoked plasticity by focusing on the carbon dioxide (CO2) circuit in Drosophila. Specialized OSNs detect this gas and relay the information to a dedicated circuit in the brain. Prolonged exposure to CO2 induced a reversible volume increase in the CO2-specific glomerulus. OSNs showed neither altered morphology nor function after chronic exposure, but one class of inhibitory local interneurons showed significantly increased responses to CO2. Two-photon imaging of the axon terminals of a single PN innervating the CO2 glomerulus showed significantly decreased functional output following CO2 exposure. Behavioral responses to CO2 were also reduced after such exposure. It is suggested that activity-dependent functional plasticity may be a general feature of the Drosophila olfactory system (Sachse, 2007).

Neuroanatomical, functional, and behavioral analysis suggests that the Drosophila olfactory system has the capacity for reversible activity-dependent plasticity. Evidence of this plasticity is readily seen by measuring the volume of the V glomerulus. Because the volume increase can be induced by odor activation of ORs ectopically expressed in the CO2-activated OSNs, it is concluded that persistent stimulus-evoked activity in these neurons underlies these anatomical changes. It has been shown that stimulus-evoked plasticity is a general feature of the Drosophila olfactory system and not a peculiarity of the CO2 circuit. For instance, the volume of DM2 is increased by chronic exposure to ethyl butyrate, a ligand for the Or22a-expressing neurons that target DM2 (Sachse, 2007).

Drosophila, CO2 is detected by a population of approximately 25-30 OSNs in the antenna that express the chemosensory receptor Gr21a, which along with Gr63a comprises the Drosophila CO2 receptor. These OSNs project axons that terminate in the V glomerulus in the ventral antennal lobe. The Drosophila CO2 circuit is ideal for studying odor-evoked plasticity because Gr21a-expressing OSNs are the only neurons in the fly that respond to CO2, and they do not respond to any other stimuli. In this work, stimulus-evoked changes in the anatomy and function were examined of the Drosophila CO2 circuit. The results provide functional evidence that a primary olfactory center is capable of activity-dependent plasticity (Sachse, 2007).

The data are consistent with a model in which one class of inhibitory LNs and the output of the V glomerulus are the major targets of plasticity induced by sensory exposure. Under conditions of ambient CO2, the Gr21a circuit forms normally and small amounts of CO2 produce robust behavioral responses. When flies are exposed to elevated CO2 early in life, it is postulated that chronic activation of Gr21a neurons promotes functional changes in the LN2 subtype of inhibitory local interneurons without affecting either the functional properties of the OSNs or the CO2-evoked response of the LN1 neurons. It is suggested that the volume increases seen with CO2 exposure may result from neuroanatomical changes in the LNs, although their extensive glomerular arborization made this hypothesis difficult to test experimentally. Since a majority of the LN2 population in Drosophila has been shown to be GAD1 positive and thus to release GABA, as known for antennal lobe LNs in other insects, greater CO2-evoked activity of LN2s may lead to an increased inhibition of the PN postsynaptic to Gr21a OSNs. The finding of reduced activity in the output region of the PN innervating the V glomerulus supports this hypothesis. Thus, CO2-evoked activity would be attenuated in the antennal lobe circuit in these animals, producing a corresponding decrease in the intensity of the behavioral response (Sachse, 2007).

It has recently been shown that LNs are not only inhibitory, as has been assumed so far. A newly described population of excitatory cholinergic LNs forms a dense network of lateral excitatory connections between different glomeruli that may boost antennal lobe output (Olsen, 2007; Shang, 2007). Future studies are necessary to investigate if excitatory LNs are also subject to activity-dependent plasticity (Sachse, 2007).

Stimulus-dependent plasticity can be induced and reversed in a critical period early in the life of a fly. Similar critical periods have been documented in selective deafferentation periods in mammalian somatosensory and visual cortex. In all these model systems, the critical period likely allows the animal to compare the genetically determined network template with external conditions and make activity-dependent adjustments that reflect the external environment. For instance, visual cortex 'expects' binocular input when it is wired in utero. If monocular input is experimentally imposed, the system is rewired to reflect this. The same rewiring occurs in the barrel cortex, in which the receptive fields of missing whiskers are invaded by neighboring whiskers, allowing the animal to maintain a continuous representation of external somatosensory space. Drosophila pupae have no sensory input during development and develop an olfactory system that relies neither on evoked activity nor the expression of ORs. The time following adult eclosion may represent a period in which the functional set point of the Drosophila olfactory system is evaluated and adapted to the local environment (Sachse, 2007).

What elements of the antennal lobe circuit are responsible for the stimulus-dependent volume increases seen here? No evidence was found that OSNs modulate their number, morphology, branching pattern, or functional properties in response to CO2 exposure. The same neuroanatomical properties of single LNs or PNs could not be assayed due to the dense processes of these neurons in a given glomerulus. Since the observed net increase in volume cannot be ascribed to anatomical changes in OSNs, morphological plasticity is most likely occurring either at the level of LN or PN. A model is favored in which changes in the LNs underlie the observed volume increases because clear functional differences were found in LN2 responsivity in CO2-exposed animals and because PN dendrites and axons have been shown to be extremely stable in size and morphology when deprived of OSN input. Similar stability in mitral/tufted cells has been shown in rodent olfactory bulb. The possibility that other cells, such as glia, contribute to these activity-dependent volume changes cannot be excluded (Sachse, 2007).

This work suggests that antennal lobe LNs marked with two different Gal4 enhancer traps, Gal4-LN1 and Gal4-LN2, are functionally distinct. The arborization of LN1 and LN2 processes in the V glomerulus suggests that they interact differentially with the antennal lobe circuitry. LN1 processes appear to innervate the core of a given glomerulus, while LN2 processes innervate the glomerulus more uniformly. Both LN1 and LN2 neurons show weakly concentration-dependent tuning to odor stimuli. Thus, compared to the OSNs or PNs, which transmit a precise spike-timing code that reflects absolute CO2 concentration, these LNs appear to respond in a binary fashion, showing similar levels of activity regardless of stimulus concentration (Sachse, 2007).

There is a clear difference in how the responses of these two LN populations are modulated by CO2 exposure. While the activity of LN1 neurons was not significantly affected by CO2 exposure, LN2 neurons exhibited robust and significant increases in CO2-evoked activity after CO2 exposure. It will be of interest to examine the functional properties of these neurons in greater detail using electrophysiological approaches. It is plausible that circuit plasticity as evidenced in the LN2 neurons can be detected with electrophysiology at even lower CO2 concentrations for shorter exposure periods (Sachse, 2007).

How might chronic activation of CO2-sensitive OSNs specifically affect the physiology of LN2 neurons? It is speculated that due to the broader innervation of LN2 processes, these neurons would receive greater presynaptic innervation from Gr21a-expressing OSNs. Thus, with chronic CO2 exposure, the LN2 neurons would be chronically activated. This might cause long-term plasticity leading to greater GABA release from LN2 neurons. In cerebellar stellate cells, such an increase in inhibitory transmitter release has been documented and coined 'inhibitory-long term potentiation' (I-LTP). I-LTP is induced in stellate cells by glutamate released from parallel fibers acting on presynaptic NMDA receptors in these inhibitory interneurons and producing a long-lasting increase in the release of GABA from these cells. Like stellate neurons, at least one population of Drosophila LNs is pharmacologically GABAergic (Sachse, 2007).

How might alterations in LN2 pharmacology affect downstream circuit elements and ultimately CO2-evoked behavior? Drawing on the same cerebellar analogy discussed above, it is plausible that PNs exhibit a type of 'rebound potentiation' that has been observed in Purkinje cells responding to inhibitory input. GABA released from LNs would regulate the excitability of PNs, such that greater GABA release from LN2 would tend to decrease the excitability of CO2-specific PNs. The finding that the output from the V glomerulus to the lateral horn is reduced following CO2 exposure supports the idea that downstream activity in higher processing centers is modulated by the antennal lobe network. However, it still needs to be shown that LN2 neurons form direct inhibitory synapses onto PNs in the V glomerulus. Reduced PN activity in the lateral horn in turn may produce a reduced behavioral sensitivity to this stimulus. Future experiments that examine this stimulus-dependent plasticity at the cellular level using pharmacology and electrophysiology will be necessary to test this model (Sachse, 2007).

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AKAPs act in a two-step mechanism of memory acquisition

Scheunemann, L., Skroblin, P., Hundsrucker, C., Klussmann, E., Efetova, M. and Schwarzel, M. (2013). J Neurosci 33: 17422-17428. PubMed ID: 24174675

Defining the molecular and neuronal basis of associative memories is based upon behavioral preparations that yield high performance due to selection of salient stimuli, strong reinforcement, and repeated conditioning trials. One of those preparations is the Drosophila aversive olfactory conditioning procedure where animals initiate multiple memory components after experience of a single cycle training procedure. This study explored the analysis of acquisition dynamics as a means to define memory components and revealed strong correlations between particular chronologies of shock impact and number experienced during the associative training situation and subsequent performance of conditioned avoidance. Analyzing acquisition dynamics in Drosophila memory mutants revealed that rutabaga (rut)-dependent cAMP signals couple in a divergent fashion for support of different memory components. In case of anesthesia-sensitive memory (ASM) this study identified a characteristic two-step mechanism that links rut-AC1 to A-kinase anchoring proteins (AKAP)-sequestered protein kinase A at the level of Kenyon cells, a recognized center of olfactory learning within the fly brain. It is proposed that integration of rut-derived cAMP signals at level of AKAPs might serve as counting register that accounts for the two-step mechanism of ASM acquisition (Scheunemann, 2013).

Conditioned odor avoidance is subject to a general dichotomy since multiple memory components are engaged in control of behavior. This is usually analyzed at two time points, i.e., 3 min and 3 h after training. At 3 min, basal and dynamic STM are separable by genetic means as revealed by opposing phenotypes of rut1 and dnc1 mutants. Moreover, those components are also separable due to characteristic differences in their acquisition dynamics as revealed by different effects of shock number. A similar dichotomy applied to 3 h memory when ASM and ARM were separable by means of amnestic treatment. It was striking that basal STM and consolidated ARM were instantaneously acquired, resulting in a front line of protection by eliciting conditioned avoidance after a singular experience of a CS/US pairing. Interestingly, consolidated ARM (as defined by means of resisting amnestic treatment) was installed quickly after training. However, it remains to be addressed at the genetic and molecular level, whether 3 h ARM linearly results from the functionally similar basal SMT component (Scheunemann, 2013).

In contrast, the two components of dynamic STM and labile ASM acquire in a dynamic fashion but are clearly dissociated from each other by characteristic chronologies of CS/US pairings required for their acquisition. However, either component contributes to behavioral performance in addition to the appropriate instantaneous component, and hence, increases avoidance probability during the test situation. Considering a potential benefit from avoiding aversive situations this overall dichotomy of behavioral control seems plausible and is also reflected at the genetic level since rut-dependent cAMP signals are limited to support of dynamic but not instantaneous memory components. Rut-dependent STM and ASM, however, are dissociated by means of shock impact and discontinuous formation of ASM is limited to situations where animals repeatedly experience high-impact CS/US pairings within a predefined time window. Experience that does not meet this criterion, however, is not discounted but adds to continuously acquired dynamic STM. By functional means these two components are thus clearly separated but commonly dependent on rut-derived cAMP signals within the KC layer, forming ties between genetically and functionally defined memory components (Scheunemann, 2013).

Genetic dissection of memory has a long-standing history in Drosophila and provided a powerful means to define molecular, cellular, and neuronal networks involved in regulation of conditioned odor avoidance. Among others, the cAMP-signaling cascade has been identified as one central tenet of aversive odor memory foremost by means of two single-gene mutants affecting either a Ca2+-sensitive type 1 adenylyl cyclase (AC1) and/or a cAMP-specific type 4 phosphodiesterase (PDE4) affected in the Drosophila learning mutants rutabaga (rut-AC1) and dunce (dnc-PDE4). Although originally isolated due to poor performance in the aversive odor learning paradigm, a general dichotomy has been recently revealed that separates memory components by their dependency on either rut-AC1 or dnc-PDE4 function, and the view was established that two different types of cAMP signals are engaged during the single-cycle training procedure (Scheunemann, 2012). A similar dichotomy is observed at level of acquisition dynamics and suggests that rut-dependent cAMP signals are limited to formation of dynamically acquired memory components, i.e., dynamic STM and ASM. Interestingly, rut-dependent cAMP is also required for long-term memory (LTM), which acquires after spaced and repeated training sessions. Downstream the signaling cascade, however, appropriate cAMP signals are differently channeled to either support LTM in a CREB-dependent manner, ASM via tomosyn-dependent plasticity, or basal STM via synapsin-dependent regulation of synaptic efficacy. It appears that the chronology of CS/US pairings is an important determinant of which downstream effect is triggered and hence molecular mechanisms must be installed that are sensitive to the temporal order of training (Scheunemann, 2013).

At the level of molecular scaffolds, literature suggests that AKAPs serve the integration of cAMP with other signaling processes and are crucially involved in the control of a plethora of cellular functions in any organ. For example, AKAP79 coordinates cAMP and Ca2+ signaling in neurons to control ion channel activities. The recognized design principle of AKAPs to serve as molecular switch is well in line with the recognized two-step register mechanism involved in ASM formation. An increasing body of evidence shows that AKAPs are involved in memory processing across phyla and accordantly those studies revealed a contribution for support of matured, but not immediate memories. Communality among all those AKAP-dependent memories is the need for repeated and temporally organized training sessions, i.e., only spaced training sessions are effective to induce protein synthesis-dependent LTM in flies and mammals. Similarly, ASM requires the precise timing of two training sessions and mechanistically acts via an 'activated' state generated by the initial CS/US pairing that persists within the brain for ~5 min. Such temporal integration might well take place at level of AKAPs within the KC layer to operate rut-AC1-dependent cAMP signals finally onto phosphorylation of tomosyn. Identification of the particular AKAPs involved in two-step ASM formation will require further analysis of appropriate mutants. To date, only four Drosophila AKAPs are characterized, i.e., rugose, a 550 kDa protein that impacts on STM performance probably via molecular domains other than its AKAP function; yu/spoonbill that supports LTM; and Nervy and AKAP200 have not been tested for their impact on aversive odor memory (Scheunemann, 2013).

Together, the benchmarking of Drosophila aversive odor memory performance by means of acquisition dynamics that were demonstrated in this study will provide a valuable tool since dynamic aspects of acquisition are obviously informative and add to the steady-state condition determined by the single-cycle training procedure (Scheunemann, 2013).

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Hebbian STDP in mushroom bodies facilitates the synchronous flow of olfactory information in locusts

Cassenaer, S. and Laurent, G. (2007). Nature 448: 709-713. PubMed ID: 17581587

Odour representations in insects undergo progressive transformations and decorrelation from the receptor array to the presumed site of odour learning, the mushroom body. There, odours are represented by sparse assemblies of Kenyon cells in a large population. Using intracellular recordings in vivo, this study examined transmission and plasticity at the synapse made by Kenyon cells onto downstream targets in locusts. It was found that these individual synapses are excitatory and undergo hebbian spike-timing dependent plasticity (STDP) on a +-25 ms timescale. STDP is a phenomenon in which the gain of a connection can be changed according to the temporal relationship between pre- and post-synaptic spikes. When placed in the context of odour-evoked Kenyon cell activity (a 20-Hz oscillatory population discharge), this form of STDP enhances the synchronization of the Kenyon cells' targets and thus helps preserve the propagation of the odour-specific codes through the olfactory system (Cassenaer, 2007).

Olfactory processing in insects begins in an array of receptor neurons that express collectively many tens of olfactory receptor genes (~60 in Drosophila; ~150 in honeybees). The representations of general odours are then decorrelated by local circuits of projection neurons and local neurons in the antennal lobe. In locusts and other insects, the antennal lobe output is distributed in space and time and can be described as stimulus-specific time-series of projection-neuron activity vectors, updated at each cycle of a 20-Hz collective oscillation. Distributed projection-neuron activity is then projected to Kenyon cells, the intrinsic neurons of the mushroom body. In contrast to projection neurons, Kenyon cells respond very specifically and fire extremely rarely. The mechanisms underlying this sparsening are starting to be understood. Such sparse representations are advantageous for memory and recall, consistent with established roles of the mushroom bodies in learning. In Drosophila, experiments combining molecular inactivation with behaviour indicate that synaptic output from Kenyon cells in the lobes is required for memory retrieval. Little is known, however, about the electrophysiological properties of these synapses (Cassenaer, 2007).

The connections made by Kenyon cells onto a small population of extrinsic neurons have been studied in the β-lobe of the locust mushroom body, using an intact, in vivo preparation. β-lobe neurons (β-LNs) respond to odours; their responses are odour-specific and their tuning is sensitive to input synchrony. This study recorded intracellularly from pairs of Kenyon cells and β-LNs: randomly selected Kenyon cells were impaled in their soma; β-LNs were impaled in a dendrite in the β-lobe. Focused was placed on one β-LN anatomical subtype, which comprises many individual neurons. Neurons of this subtype, called β-LNs here, could be recognized also by their physiological characteristics. Each β-LN has extensive dendrites that intersect many of 50,000 Kenyon cell axons. Monosynaptic connections were found in ~2% of tested Kenyon cell (KC)-β-LN pairs. All were excitatory. The delay between Kenyon cell spike and β-LN-excitatory post-synaptic potential (EPSP) onset was 6.5 +- 0.70 ms, including 5.4 +- 0.25 ms for spike propagation from Kenyon cell soma to the β-lobe. The remaining (synaptic) delay (~1 ms) is similar to that at another chemical synapse in the locust brain. Unitary EPSPs were large (1.58 mV +- 1.11), in contrast to those generated in Kenyon cells by individual projection neurons (86 microV +- 44). The fact that Kenyon cell outputs are powerful is consistent with Kenyon cell spikes being rare and therefore highly informative. EPSP amplitude varied greatly across connected pairs (0.55-4 mV). This could reflect a distribution of electrotonic distances between synapses and recording sites. Simultaneous impalements of different dendrites in the same β-LN, however, show that the amplitudes of most events were the same across recording sites. Consistent with this, unitary EPSP kinetics (10-90% rise time, 8.3 ms +- 2.3; time to 1-(1/e) of peak, 13.2 ms +- 4.4) were independent of the β-LN recorded and, thus, of the impalement site. Simultaneous dendritic recordings of different β-LNs, however, revealed that their synaptic backgrounds overlapped only partly. Common EPSPs rarely had the same amplitude. Hence, β-LNs may each receive inputs from hundreds to thousands (~2% of 50,000 Kenyon cells) of Kenyon cells, in overlapping subsets; KC-β-LN connections are strong on average, with target-specific strength (Cassenaer, 2007).

Odour-evoked activity in projection neurons and Kenyon cells consists principally of sequential volleys of synchronized spikes-generally, one spike per responding neuron per oscillation cycle. β-LN responses to odours also consisted typically of sequences of single phase-locked spikes, timed around the trough of several local field potential (LFP) oscillation cycles. The cycles when a spike was produced (usually with probability <1) depended on β-LN and stimulus identity. It is concluded that, to each oscillation cycle corresponds a particular activity vector in the projection neuron, Kenyon cell and β-LN populations. By recording from pairs of β-LNs simultaneously during odour trials, it was also observed that, when the two β-LNs fired one action potential during the same oscillation cycle, those action potentials were tightly synchronized (+-2 ms) (Cassenaer, 2007).

A fortuitous observation provided hints of plasticity at the KC-β-LN synapse. At trial 4 of a Kenyon cell stimulus sequence intended to explore β-LN integration, the β-LN fired a spontaneous action potential roughly at the time of the first (of 2) Kenyon-cell-evoked EPSP. At trial 5, 10 seconds after this single fortuitous pairing, the first EPSP of the pair was greatly enhanced. This suggested the possibility of spike-timing-dependent plasticity (STDP), a phenomenon thus far unknown in invertebrates but well characterized in vertebrates, in which the gain of a connection can be changed according to the temporal relationship between pre- and post-synaptic spikes. The consequence of pre-post temporal relationships was explored on the KC-β-LN synapse. A β-LN was impaled and stimulated alternately by two independent Kenyon cell pathways-one for pairing, one for unpaired control. Each stimulus was repeated every 10 s, with a 5-s delay between pairing and control stimuli. Pairing consisted of a single Kenyon cell (pre) stimulus and a 5-ms supra-threshold β-LN (post) current pulse, timed such that the delay (dt = tpost-tpre) between pre- and post-synaptic spikes varied between -60 and +50 ms. Test trials, used to measure connection strength before and after pairing, were identical to the pairing trials in all respects except in the temporal relationship between pre- and post-synaptic spike times (2.5 s apart). Two examples (for dt = 10 ms and -4 ms, 25 pairings each) are given. For dt = 10 ms, the paired input underwent potentiation; for dt = -4 ms, it underwent depression. For both conditions, the control pathway (same β-LN, different Kenyon cell input) remained unchanged. The changes were thus input-specific; they were often detectable after a single pairing, and could be maintained for up to 25 min. 26 values of dt between -60 and +50 ms were tested. The resulting changes define a classical hebbian profile: the synapse is potentiated when pre- precedes post-, and depressed when post- precedes pre-, with symmetrical profiles. The changes could be fitted well with two exponential decays flanking a narrow linear range around t = +4 ms. Several connections were tested successively with two (or more) values of dt (some positive, others negative): the same connections could undergo both depression and potentiation, depending on the value of dt. The STDP profile thus seems to be a property of each connection and not only a collective one (Cassenaer, 2007).

It was observed that the values of dt over which synaptic weights change correspond to the period of single odour-evoked oscillation cycles; hence, only within-cycle 'coincidences' may modify the connections between a Kenyon cell and its targets. The features of the STDP curve, when considered together with the timing of Kenyon cells and β-LNs during odour-evoked activity, have interesting consequences. Consider the phases of Kenyon cell and β-LN spikes. Owing to propagation delays, Kenyon cell spikes reach their targets just before the trough of the LFP, a little before β-LN firing. Consider a cycle in which a β-LN spikes early: some KC-β-LN connections will undergo depression; at the next trial, β-LN spike time at this cycle should be delayed. If, in contrast, a β-LN spikes late, STDP should potentiate Kenyon cell drive to it, and thus advance spike time for that cycle. In short, the cycle-by-cycle action of STDP suggests adaptive control of β-LN spike phase. The need for such regulation is not unique to this system: models of cortical networks indicate that, as activity propagates through successive 'layers', accumulating noise can rapidly smear the temporal structure that may exist. Modelling studies predict that STDP, given appropriate parameters, could preserve the temporal discretization of activity through such layers (Cassenaer, 2007).

A reduced model was generated of the KC-β-LN circuit, and the STDP rule derived from these experiments was introduced. To control the relative phases of Kenyon cells and β-LNs, Kenyon cell spike phases were drawn from experiments and input weights from uniform distributions with different means: with low weights, β-LN spikes tended to occur late (dt > 0); with larger weights, they occurred early (dt < 0). After several trials (each with a random draw of inputs from the same distribution), STDP was allowed to modify synaptic weights for the following trials: when β-LN spikes occurred late (dt > 0), Kenyon cell outputs became potentiated and β-LN spikes were advanced; for dt < 0, time shifts were inverted. The histograms shown represent spike-time distributions for 1,000 trials before and after STDP, for each of three conditions. These simulations were repeated 200 times (50 trials each), with 11 different Kenyon cell input distributions. Once STDP was turned on (trial 1), the evolution was systematic and rapid, leading to the adaptive up- or downregulation of input weights, firing phase and response intensity. Given that the model is entirely constrained by experiments, it is noteworthy that the mean phase of the first β-LN spike at steady state, matches precisely that measured experimentally (Cassenaer, 2007).

To test directly the effect of STDP on β-LN output, β-LN spike timing was manipulated during responses to odours in vivo: if the model is correct, such manipulations should change the output of the odour-activated Kenyon cells onto that β-LN and, thus, generate predictable shifts in its spike phase. During odour stimuli, short current pulses locked to selected cycles of the LFP were injected in a β-LN: a negative pulse was injected during the cycles and phase when the β-LN would naturally fire (to prevent stimulus-evoked spikes), and a positive pulse was injected at a desired phase, for those same cycles (that is, at an abnormal time relative to the Kenyon cell inputs that would normally drive the recorded β-LN). An example is shown for four consecutive cycles. After several such pairing trials, current injection was terminated and β-LN-firing phase over the next trials was compared to that before pairing. The effects of one such manipulation (dt > 0) were plotted: as predicted, an artificial phase-delay caused a corrective phase-advance. Twenty distinct experiments were carried out in six β-LNs; the expected phase shifts were observed in 16 of those 20. This is consistent with an adaptive role for STDP in the fine-tuning of β-LN spike-phase, and may explain the tight synchronization of β-LNs. Hence, STDP helps preserve the discrete and periodic structure of olfactory representations as they flow through the mushroom bodies (Cassenaer, 2007).

This study showed that the connections made by Kenyon cells to β-LNs are excitatory, strong on average, variable across pairs, and plastic. Plasticity follows time-sensitive hebbian associativity rules and is constrained to within-cycle interactions between pre-and post-synaptic neurons. STDP is therefore not specific to vertebrates or cortical architectures. The molecular underpinnings of STDP in this system, or whether STDP might confer the associative features usually ascribed to mushroom bodies, are not known. The fly and honeybee genomes both reveal coding sequences for N-methyl-D-aspartate (NMDA) receptor subunits and some Drosophila behavioural results are compatible with STDP learning rules. One hypothesis, readily testable, is that STDP provides associativity by tagging transiently the subset of synapses activated simultaneously by the odour, before the conditional arrival of a slower, non-specific reward signal (Cassenaer, 2007).

The results reinforce the proposed importance of spike timing for this, and possibly other, olfactory system(s): Kenyon cells act as coincidence detectors for synchronized projection neuron input, β-LNs act as coincidence detectors for Kenyon cell input; because STDP helps enhance β-LN synchronization, it is inferred that spike timing must be relevant also for the processing of β-LN output. These results indicate that the oscillation cycle-a temporal unit of processing first defined by negative feedback in the antennal lobe-is actively preserved in at least three successive layers of processing (projection neurons, Kenyon cells and β-LNs). It will be interesting to assess whether all Kenyon cell outputs obey the same STDP rules, and if these rules are themselves subject to learning-related modifications. Indeed, Kenyon cells seem to communicate with one another through axo-axonal chemical synapses. Given the dynamics of projection neuron/Kenyon cell activity vectors in response to odours, the possibility that Kenyon cell-Kenyon cell synapses also undergo STDP suggests a mechanism for sequence learning, similar to principles proposed for spatial map formation in rodents; in this study, however, the learned sequences have no relation to movement in physical space. The existence of such similarities (synaptic learning rules, and synchronized and sequential neural activity patterns) may bring us closer to understanding the relationships between circuit dynamics, architecture and learning in the brain (Cassenaer, 2007).

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A fly-inspired mushroom bodies model for sensory-motor control through sequence and subsequence learning

Arena, P., Cali, M., Patane, L., Portera, A. and Strauss, R. (2016). Int J Neural Syst: 1650035. PubMed ID: 27354193

Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies neuropile. The network devoted to context formation is able to reconstruct the learned sequence and also to trace the subsequences present in the provided input. A sensitivity analysis to parameter variation and noise is reported. Experiments on a roving robot are reported to show the capabilities of the architecture used as a neural controller (Arena, 2016).

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The GABAergic anterior paired lateral neuron suppresses and is suppressed by olfactory learning

Liu, X. and Davis, R. L. (2009). Nat. Neurosci. 12(1): 53-59. PubMed ID: 19043409

GABAergic neurotransmitter systems are important for many cognitive processes, including learning and memory. A single neuron was identified in each hemisphere of the Drosophila brain, the anterior paired lateral (APL) neuron, as a GABAergic neuron that broadly innervated the mushroom bodies. Reducing GABA synthesis in the APL neuron enhanced olfactory learning, suggesting that the APL neuron suppressed learning by releasing the inhibitory neurotransmitter GABA. Functional optical-imaging experiments revealed that the APL neuron responded to both odor and electric-shock stimuli that was presented to the fly with increases of intracellular calcium and released neurotransmitter. Notably, a memory trace formed in the APL neuron by pairing odor with electric shock. This trace was detected as a reduced calcium response in the APL neuron after conditioning specifically to the trained odor. These results demonstrate a mutual suppression between the GABAergic APL neuron and olfactory learning, and emphasize the functional neuroplasticity of the GABAergic system as a result of learning (Liu, 2009).

Using single neuron labeling techniques and immunohistochemistry, the APL within the GH146-Gal4 expression domain neuron was identified as the first GABAergic neuron that innervated the mushroom bodies of Drosophila. The innervation was surprisingly broad, with this single neuron accounting for GABAergic processes that extend across the complete three-dimensional volume of the calyx, peduncle, and lobes. Knocking down GABA synthesis in the APL neuron enhanced olfactory learning, indicating that the role of APL was to suppress olfactory learning by releasing the inhibitory neurotransmitter GABA. Functional optical imaging revealed that the APL neuron responded to both CS and US stimuli used for training. It was further demonstrated that a memory trace registered as a reduced response specifically to the trained odor formed in the APL neuron after conditioning, suggesting that olfactory learning somehow suppressed the activity of this inhibitory neuron (Liu, 2009).

These observations meshed well with observations made from altering the expression level of the RDL receptor in the mushroom bodies. It was discovered that overexpression of RDL in the mushroom bodies inhibits learning, whereas reducing RDL expression in the mushroom bodies enhances learning, similar to the effect of reducing GABA synthesis in the APL neuron. Furthermore, the calcium responses to odor observed in the mushroom body neurons of flies that overexpress RDL are reduced, whereas the responses observed in flies with reduced expression of RDL are increased. Thus, increased learning is observed by either reducing RDL expression in the mushroom body neurons, or by decreasing GABA synthesis in the APL neuron that innervates the mushroom body neuropil. The logical conclusion is that the APL neuron provides the GABAergic input to the RDL receptor expressed on the mushroom body neurons, and that this neurotransmitter:receptor dynamic establishes the probability for learning to occur (Liu, 2009).

GABAergic feedback neurons projecting to the mushroom bodies have been reported in the honeybees. The morphology of these feedback neurons and their innervation patterns in the mushroom bodies are similar to the Drosophila APL neuron described in this study. Pairing an odor with a sucrose reward induces a decreased spike activity in the GABAergic feedback neurons towards the trained odor shortly after training, similar to the decreased response observed by optical imaging in the APL neuron after training. These observations suggest that the APL neuron in Drosophila might be the equivalent of the honeybee GABAergic feedback neurons. The processes of the GABAergic feedback neurons in the mushroom body lobes of the honeybee are considered to be postsynaptic and their processes in the mushroom body calyces are considered to be presynaptic. However, the processes of the APL neuron in the mushroom body lobes of Drosophila clearly contained presynaptic specializations, since synaptic vesicle release was observed from these processes by functional imaging. Thus, the functional relationship between the Drosophila APL neuron and the Apis GABAergic feedback neurons remains uncertain (Liu, 2009).

Functional optical imaging experiments have revealed multiple memory traces formed after olfactory conditioning in different areas of the Drosophila brain. The APL neuron memory trace was unique compared to previously described traces, since it was registered as a decrease rather than an increase of neuronal activity. This is not surprising given that the APL neuron releases the inhibitory neurotransmitter GABA. However, an important issue is raised by the combined observations. Is the increased activity in the mushroom bodies after training inducing the decreased activity in the APL neuron, or is the later serving as a permissive event for the former to take place? Temporally, the APL memory trace observed in this study forms within a similar time window as the early memory trace recently reported to form in the α'/β' mushroom body neurons, so these two scenarios remain equally possible. Another more complicated scenario is that these memory traces could form synergistically and in parallel rather than sequentially, since many insect neurons have mixed axons and dendrites and communicate bi-directionally with connected neurons (Liu, 2009).

The APL neuron exhibited a depression in activity after training that was specific to the trained odor compared to a control odor. The mechanism underlying this specificity is unclear. One of the simpler possibilities is that the APL neuron is both pre- and post-synaptic to mushroom body neurons, similar to models proposed for the dorsal paired medial (DPM) neuron. Training may produce a synaptic depression at the synapses between mushroom body neurons conveying the information about the trained odor and the postsynaptic APL neuron, but not at synapses between mushroom body neurons conveying information about other odors and the postsynaptic APL neuron. Such depression would reduce the activity of the APL neuron specifically to the trained odor. This depression of APL activity to the trained odor would also be registered as increased activity in the mushroom body neurons representing the trained odor, since the mushroom body neurons would then receive reduced inhibitory signals from the APL neuron acting presyaptically. A second possibility is that the increased activity of the mushroom body neurons conveying information about the trained odor might induce retrograde signaling causing a depression in specific APL presynaptic, inhibitory fibers. Recent studies of endocannabinoid-mediated hippocampal metaplasticity have revealed that focal stimulation of CA1 pyramidal neurons triggers a long-term depression at inhibitory synapses (I-LTD) restricted to a very small dendritic area (~10 microm), mediated by the postsynaptic release of endocannabinoid that binds to the presynaptic CB-1 receptor on the inhibitory neuron presynaptic terminals31. It remains unknown whether a similar retrograde signaling system exists in flies to mediate a similar effect, although a Ca2+ and synaptotagmin 4 dependent retrograde signaling mechanism has been discovered at the Drosophila neuromuscular junction that functions in a synapse-specific fashion. If selective suppression of inhibitory inputs exists in the central nervous system of Drosophila, then it may serve as a novel mechanism to code and store information in the brain (Liu, 2009).

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Parallel processing of appetitive short- and long-term memories in Drosophila

Trannoy, S., Redt-Clouet, C., Dura, J. M. and Preat, T. (2011). Curr Biol 21: 1647-1653. PubMed ID: 21962716

It is broadly accepted that long-term memory (LTM) is formed sequentially after learning and short-term memory (STM) formation, but the nature of the relationship between early and late memory traces remains heavily debated. To shed light on this issue, this study used an olfactory appetitive conditioning in Drosophila, wherein starved flies learned to associate an odor with the presence of sugar. Advantage was taken of the fact that both STM and LTM are generated after a unique conditioning cycle to demonstrate that appetitive LTM is able to form independently of STM. More specifically, it was shown that (1) STM retrieval involves output from γ neurons of the mushroom body (MB), i.e., the olfactory memory center, whereas LTM retrieval involves output from αβ MB neurons; (2) STM information is not transferred from γ neurons to αβ neurons for LTM formation; and (3) the adenylyl cyclase RUT, which is thought to operate as a coincidence detector between the olfactory stimulus and the sugar stimulus, is required independently in γ neurons to form appetitive STM and in αβ neurons to form LTM. Taken together, these results demonstrate that appetitive short- and long-term memories are formed and processed in parallel (Trannoy, 2011).

Short-term memory (STM) forms right after learning and is based on transient molecular and cellular events lasting from a few minutes to a few hours, whereas long-term memory (LTM) forms later on and involves gene expression and de novo protein synthesis following conditioning. The nature of the links between STM and LTM has long been debated, but there is consensus that STM and LTM are sequential processes and that LTM formation is built on the short-term trace. However, other studies have led to the conclusion that the mechanisms underpinning STM and LTM in vertebrates are at least partially independent (Trannoy, 2011).

Studies in insects have highlighted that mushroom bodies (MBs) play a major role in learning and memory. In particular, in Drosophila, MBs play a key role in olfactory learning and memory. The MBs in each brain hemisphere of Drosophila consist of approximately 2,000 neurons called Kenyon cells that can be classified into three major types: αβ, whose axons branch to form a vertical (α) and a medial (β) lobe, α'β', which also form a vertical (α') and a medial (β') lobe, and γ, which form a single medial lobe in the adult (Trannoy, 2011).

Several molecular-level studies have demonstrated that the cyclic AMP (cAMP) pathway plays a pivotal role in associative learning. In particular, calcium/calmodulin-dependent adenylyl cyclase (AC) encoded by the rutabaga (rut) gene is necessary to aversive olfactory conditioning where an odorant is associated to electric shock. Rut AC was proposed to function as a coincidence detector, integrating both the olfactory information carried by projection neurons to the MB and the electric shock carried by dopaminergic neurons. Interestingly, Rut cAMP signaling is required in γ neurons to form aversive STM (Zars, 2000; Blum, 2009) and in αβ neurons to form LTM (Blum, 2009), suggesting an independence of these two memory phases. However, several results suggest that aversive STM and LTM are not processed by fully independent neuronal pathways. Thus, a more efficient rescue of rut STM or LTM defect is observed when Rut is expressed in both γ and αβ neurons, suggesting that Rut is also involved in αβ neurons for aversive STM and in γ neurons for LTM. In addition, blocking αβ neuron synaptic transmission during memory retrieval impairs both aversive STM and LTM. Moreover, the induction of aversive STM and LTM requires different conditioning protocols, because STM is induced by one cycle of conditioning, whereas LTM formation requires spaced conditioning consisting of repeated training sessions separated by 15 min rest periods. These different training protocols may induce different physiological states within the relevant neurons, making it more difficult to interpret whether LTM is or is not built upon STM (Trannoy, 2011).

In Drosophila, appetitive STM and LTM are both generated after a single session of odorant-plus-sugar association, offering a powerful situation to study the link between the short- and the long-term trace. Rut AC has been hypothesized to be the coincidence detector in olfactory appetitive memory, because rut mutants exhibit poor immediate memory. It was shown that Rut AC in MB αβ and γ neurons or in projection neurons is sufficient for appetitive learning and STM, but it remains unknown which brain structure involves Rut activity for appetitive LTM (Trannoy, 2011).

Consolidation of appetitive STM and LTM requires output from α'β' neurons for 1 hr after training but not from αβ neurons. The role of γ neurons in appetitive STM or LTM consolidation has not yet been addressed. STM retrieval involves output from αβ and/or γ neurons, but the role of α'β' neurons in STM retrieval remains unknown. LTM retrieval involves output from αβ neurons but not from α'β' neurons, and the role of γ neurons in LTM retrieval has not yet been addressed. Thus a full picture of the role of MB neurons in appetitive memory processing has yet to emerge (Trannoy, 2011).

To clarify the role of the different MB neurons in appetitive STM and LTM, the c739-GAL4 driver and the UAS-shi c739-GAL4ts (shi) transgene were used to block synaptic transmission in αβ neurons during memory retrieval. The dominant temperature-sensitive SHITS protein blocks dynamin-dependent membrane recycling and synaptic vesicle release at restrictive temperature (33°C). This effect is reversible when the temperature is shifted back to 25°C. It was previously reported that c739/+; shi/+ flies have normal olfactory acuity. This study first checked that c739/+; shi/+ flies present a normal sugar response at restrictive temperature. It was then found that blocking synaptic transmission from MB αβ neurons did not affect appetitive STM retrieval. This was a surprising observation, because it was previously shown that output from MB αβ neurons is required for appetitive LTM retrieval, which was confirmed in this study. To rule out the possibility that the LTM retrieval defect might be due to c739-driven expression of shits outside of the MB, the MB247-GAL80+ construct (MB-GAL80) was used to inhibit GAL4 activity in αβ neurons. As expected, c739/MB-GAL80; shi/+ flies showed normal LTM performance when tested at restrictive temperature. Furthermore, appetitive LTM performance of c739/+; shi/+ flies at permissive temperature was normal. Hence, these data indicate that MB αβ neuron output is required for appetitive LTM retrieval but not for STM retrieval (Trannoy, 2011).

It was previously shown that output from MB αβ and γ neurons is required for STM retrieval. Because the data established that output from αβ neurons is not required for this process, the role of γ neurons in STM retrieval was examined. shits was expressed in γ neurons using the NP21-GAL4 driver. First, it was checked whether NP21/shi flies present normal sugar response and olfactory acuity at restrictive temperature. Blocking γ neuron output during the memory test significantly impaired appetitive STM. Inhibition of NP21 activity in the MB by MB-GAL80 rescued the STM defect of NP21/shi flies. Furthermore, the STM performance of NP21/shi flies was indistinguishable from controls at permissive temperature. Interestingly, blocking γ neuron output during the test did not affect LTM retrieval. The specific role of γ neurons in appetitive STM retrieval was confirmed with another γ neuron driver, 1471-GAL4. Taken together, the results indicate that MB γ neuron output is indispensable for appetitive STM retrieval but dispensable for LTM retrieval (Trannoy, 2011).

Appetitive STM and LTM retrieval each mobilize specific subsets of MB neurons, namely γ neurons for STM and αβ neurons for LTM. This might be due to the fact that STM and LTM are actually mutually independent, being formed and stored in spatially distinct compartments. Alternatively, γ and αβ neurons might be sequentially recruited: in this scenario, STM would form in γ neurons and information would be further transferred from γ to αβ neurons during the consolidation phase to build LTM. Under this latter assumption, blocking output from γ neurons during the LTM consolidation phase should lead to an LTM defect. To discriminate between the two hypotheses, γ neuron neurotransmission was blocked during training and consolidation and then LTM performance was measured. First, it was observed that blocking γ neuron output during training and consolidation did not affect STM. Then, to test the putative role of γ neurons in LTM formation, NP21/shi flies were trained at restrictive temperature and maintained at this temperature for 14 hr during the memory consolidation phase (the flies were kept at 33oC for 14 hr and not for the full 24 hr consolidation period because they started to die after 14 hr; given that appetitive LTM is being detectable 6 hr after training, it is likely that LTM consolidation takes place during the 14 hr time-period of γ neuron neurotransmission blockade). NP21/shi flies showed a normal 24 hr memory in this condition, suggesting that γ neuron output is dispensable during appetitive LTM acquisition and consolidation (Trannoy, 2011).

To further prove that LTM could be formed independently of STM, neurotransmission was constitutively blocked from γ neurons using UAS-TNT (TNT) construct encoding the tetanus toxin [ 33]. TNT/+; NP21/+ flies are viable and present normal sugar response and olfactory acuity. Interestingly, a continuous blockade of γ neurons abolished STM but left LTM unaffected. Thus, TNT/+; NP21/+ flies trained with a single protocol showed no appetitive STM but a normal LTM at 24 hr. These results indicate that appetitive LTM formation is independent of STM and does not require synaptic communication between γ and αβ neurons (Trannoy, 2011).

Rut AC has been hypothesized to be the coincidence detector in olfactory appetitive memory. rut appetitive STM defect can be rescued by expressing Rut in αβ and γ neurons, but it had not yet been addressed whether Rut is specifically involved in γ or αβ neurons. Because circuit blocking experiments suggested that STM and LTM operate independently and involve different subsets of MB neurons, whether rut STM and LTM defects could be rescued independently by expressing Rut in γ and αβ neurons, respectively, was investigated. NP21 and c739 transactivators were used to express UAS-rut were used inrut2080 mutant flies. Expressing Rut in γ neurons fully rescued the rut STM defect, whereas expressing Rut in αβ neurons failed to rescue the rut STM defect. Conversely, expressing Rut in γ neurons failed to rescue the rut LTM defect, whereas expressing Rut in αβ neurons fully rescued the rut LTM defect. These results indicate that Rut AC is specifically required in γ neurons to form STM and in αβ neurons to form LTM, which further argues that appetitive STM and LTM are formed independently of each other (Trannoy, 2011).

The data suggest that appetitive STM and LTM are processed independently in γ and αβ neurons, respectively. Accordingly, immediate appetitive memory processing should involve γ neurons. To test this hypothesis, neurotransmission was constitutively blocked from γ neurons. As expected, TNT/+; NP21/+ flies displayed a 3 min memory defect. The involvement of γ neurons was further confirmed as 1471/+; shi/+ flies displayed a 3 min memory defect at restrictive temperature but not at permissive temperature. Strikingly, blocking neurotransmission from αβ neurons did not affect immediate memory. These results are in agreement with previous observations, suggesting that γ neurons support appetitive STM and αβ neurons support appetitive LTM. It has been shown that appetitive immediate memory is abolished by expressing SHITS in αβ and γ neurons under the MB247 driver. The partial inhibition observed with NP21 and 1471 GAL4 drivers might be due to the fact that MB247 shows a very strong expression in γ neurons, unlike 1471 or NP21. To further prove that the immediate appetitive memory forms in γ neurons, whether rut defect could be rescued was investigated by expressing Rut in γ neurons. Indeed, Rut expression under the NP21 driver restored rut immediate memory defect. On the contrary, expressing Rut in αβ neurons failed to rescue the rut immediate memory defect (Trannoy, 2011).

Appetitive conditioning offers a powerful situation for studying the link between STM and LTM, because both are formed after a single training cycle. It remained unknown whether the same MB neurons process both appetitive STM and LTM formation or whether these two memory phases are underpinned by specialized pathways. This study leads to a new understanding of the role of αβ and γ neurons in appetitive STM and LTM. Using distinct GAL4 drivers to specifically express SHITS or the tetanus toxin in either αβ or γ neurons, this study has shown that appetitive STM and LTM involve γ and αβ neurons, respectively. This study found the following: (1) immediate memory and STM processing involves Rut AC specifically in γ neurons, whereas LTM formation involves Rut in αβ neurons; (2) MB γ neuron output is required to retrieve immediate memory and STM but not LTM, and conversely, αβ neuron output is required to retrieve LTM but neither immediate memory nor STM; (3) γ neuron output is dispensable during memory consolidation, and therefore short-term information is not transferred from γ to αβ neurons to form LTM. Blocking γ neurons using tetanus toxin resulted in a striking phenotype, because flies completely deprived of appetitive STM exhibited normal LTM at 24 hr. In conclusion, this study provides strong evidence that in Drosophila, appetitive STM and LTM are two parallel and independent processes, involving different subsets of neurons within the MB (Trannoy, 2011).

The dynamics of the appetitive memory phase involve other neural circuits than just αβ and γ neurons. Blocking output from α'β' neurons for 1 hr after training affects both STM and LTM. Similarly, blocking output from dorsal paired medial (DPM) neurons, which project onto the MB lobes, for 1 hr after appetitive conditioning affects both STM and LTM. And it was recently shown that blocking GABAergic anterior paired lateral (APL) neurons, which project onto the MB lobes and dendrites, for 2 hr after appetitive conditioning affects STM but not LTM. It has been proposed that α'β'-DPM neurons form a recurrent loop that stabilizes STM and LTM and that APL activity regulates this loop for STM-related processes (Pitman, 2011). Because α'β' neurons are not required for either LTM or STM retrieval, the current results are in agreement with this scheme, where independent STM and LTM traces in γ and αβ neurons are maintained by output from α'β' neurons and MB-extrinsic neurons (Trannoy, 2011).

This model of STM and LTM independence is supported by several studies in other species. In Aplysia, synaptic connection between tail sensory neurons and motor neurons exhibits short- and long-term synaptic facilitation following learning. It has been shown that the induction of short-term synaptic plasticity is not necessary for the induction of long-term plasticity. Studies in vertebrates indicate that STM and LTM involve different biochemical pathways or distinct connected brain areas. This study goes one step further, because it identified neuronal structures that independently process STM and LTM, providing a unique opportunity to analyze biochemical and cellular processes specifically associated with STM and LTM (Trannoy, 2011).

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A simple computational model of the bee mushroom body can explain seemingly complex forms of olfactory learning and memory

Peng, F. and Chittka, L. (2016). Curr Biol [Epub ahead of print]. PubMed ID: 28017607

Honeybees are models for studying how animals with relatively small brains accomplish complex cognition, displaying seemingly advanced (or "non-elemental") learning phenomena involving multiple conditioned stimuli. These include "peak shift"-where animals not only respond to entrained stimuli, but respond even more strongly to similar ones that are farther away from non-rewarding stimuli. Bees also display negative and positive patterning discrimination, responding in opposite ways to mixtures of two odors than to individual odors. Since Pavlov, it has often been assumed that such phenomena are more complex than simple associate learning. This paper presents a model of connections between olfactory sensory input and bees' mushroom bodies, incorporating empirically determined properties of mushroom body circuitry (random connectivity, sparse coding, and synaptic plasticity). The model's parameters were not optimized to replicate specific behavioral phenomena, because the study was interested in the emergent cognitive capacities that would pop out of a network constructed solely based on empirical neuroscientific information and plausible assumptions for unknown parameters. The circuitry mediating "simple" associative learning was shown to also replicate the various non-elemental forms of learning mentioned above and can effectively multi-task by replicating a range of different learning feats. It was found that projection neuron-kenyon cell (PN-KC) synaptic plasticity is crucial in controlling the generalization-discrimination trade-off - it facilitates peak shift and hinders patterning discrimination - and that PN-to-KC connection number can affect this trade-off. These findings question the notion that forms of learning that have been regarded as "higher order" are computationally more complex than "simple" associative learning (Chittka, 2016).

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Optimal degrees of synaptic connectivity

Litwin-Kumar, A., Harris, K. D., Axel, R., Sompolinsky, H. and Abbott, L. F. (2017). Neuron 93(5): 1153-1164. PubMed ID: 28215558

Synaptic connectivity varies widely across neuronal types. Cerebellar granule cells receive five orders of magnitude fewer inputs than the Purkinje cells they innervate, and cerebellum-like circuits, including the insect mushroom body, also exhibit large divergences in connectivity. In contrast, the number of inputs per neuron in cerebral cortex is more uniform and large. This study investigated how the dimension of a representation formed by a population of neurons depends on how many inputs each neuron receives and what this implies for learning associations. This theory predicts that the dimensions of the cerebellar granule-cell and Drosophila Kenyon-cell representations are maximized at degrees of synaptic connectivity that match those observed anatomically, showing that sparse connectivity is sometimes superior to dense connectivity. When input synapses are subject to supervised plasticity, however, dense wiring becomes advantageous, suggesting that the type of plasticity exhibited by a set of synapses is a major determinant of connection density (Litwin-Kumar, 2017).

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Memory elicited by courtship conditioning requires mushroom body neuronal subsets similar to those utilized in appetitive memory

Montague, S. A. and Baker, B. S. (2016). PLoS One 11: e0164516. PubMed ID: 27764141

In Drosophila courtship conditioning, male flies learn not to court females during training with an unreceptive female. He retains a memory of this training and for several hours decreases courtship when subsequently paired with any female. Courtship conditioning is a unique learning paradigm; it uses a positive-valence stimulus, a female fly, to teach a male to decrease an innate behavior, courtship of the female. As such, courtship conditioning is not clearly categorized as either appetitive or aversive conditioning. The mushroom body (MB) region in the fruit fly brain is important for several types of memory; however, the precise subsets of intrinsic and extrinsic MB neurons necessary for courtship conditioning are unknown. This study disrupted synaptic signaling by driving a shibirets effector in precise subsets of MB neurons, defined by a collection of split-GAL4 drivers. Out of 75 lines tested, 32 showed defects in courtship conditioning memory. Surprisingly, there were no hits in the γ lobe Kenyon cells, a region previously implicated in courtship conditioning memory. Several γ lobe extrinsic neurons were necessary for courtship conditioning memory. Overall, the memory hits in the dopaminergic neurons (DANs) and the mushroom body output neurons were more consistent with results from appetitive memory assays than aversive memory assays. For example, protocerebral anterior medial DANs were necessary for courtship memory, similar to appetitive memory, while protocerebral posterior lateral 1 (PPL1) DANs, important for aversive memory, were not needed. Overall, these results indicate that the MB circuits necessary for courtship conditioning memory coincide with circuits necessary for appetitive memory (Montague, 2016).

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A pair of inhibitory neurons are required to sustain labile memory in the Drosophila mushroom body

Pitman, J. L., Huetteroth, W., Burke, C. J., Krashes, M. J., Lai, S. L., Lee, T., Waddell, S. (2011). Curr Biol 21: 855-861. PubMed ID: 21530258

Labile memory is thought to be held in the brain as persistent neural network activity. However, it is not known how biologically relevant memory circuits are organized and operate. Labile and persistent appetitive memory in Drosophila requires output after training from the α'β' subset of mushroom body (MB) neurons and from a pair of modulatory dorsal paired medial (DPM) neurons. DPM neurons innervate the entire MB lobe region and appear to be pre- and postsynaptic to the MB, consistent with a recurrent network model. This study identified a role after training for synaptic output from the GABAergic anterior paired lateral (APL) neurons. Blocking synaptic output from APL neurons after training disrupts labile memory but does not affect long-term memory. APL neurons contact DPM neurons most densely in the α'β' lobes, although their processes are intertwined and contact throughout all of the lobes. Furthermore, APL contacts MB neurons in the α' lobe but makes little direct contact with those in the distal α lobe. It is proposed that APL neurons provide widespread inhibition to stabilize and maintain synaptic specificity of a labile memory trace in a recurrent DPM and MB α'β' neuron circuit (Pitman, 2011).

Fruit flies form robust aversive or appetitive olfactory memory following a training session pairing odorant exposure with electric shock punishment or sucrose reward, respectively. Olfactory memories are believed to be stored in the output synapses of third-order olfactory system neurons in the mushroom body (MB), a symmetrical structure comprised of roughly 2500 neurons on each side of the brain that can be structurally and functionally dissected into αβ, α′β′, and γ neuron systems (Pitman, 2011).

Similar to aversive memory, appetitive memory measured 3 hr after training is referred to as middle-term memory and is comprised of a labile anesthesia-sensitive memory (ASM) and an anesthesia-resistant memory (ARM) component. Both of these phases and later long-term memory (LTM) require the action of the dorsal paired medial (DPM) neurons. DPM neurons exclusively innervate the lobes and base of the peduncle regions of the MB, where functional imaging suggests they are pre- and postsynaptic to MB neurons. DPM neuron projections to the α′β′ MB neuron subdivision appear to be of particular importance, and blocking output from α′β′ neurons themselves during a similar time period after training phenocopies a DPM neuron block. These data led to a proposal that reverberant activity in a recurrent MB α′β′-to-DPM neuron circuit is required to hold labile memory and for consolidation to LTM within αβ neurons (Pitman, 2011).

As part of a screen for additional neurons contributing to appetitive memory processing after training, A role for the second-order olfactory projection neurons (PNs) was tested. A uas-shibirets1 transgene was tested with the two most frequently utilized PN GAL4 drivers, GH146 and NP225. The uas-shits1 transgene allows one to temporarily block synaptic transmission from specific neurons by shifting the flies from the permissive temperature of <25°C to the restrictive temperature of >29°C. Appetitive olfactory memory was tested in GH146;uas-shits1 and NP225;uas-shits1 flies in parallel with control flies harboring the GAL4 drivers or the uas-shits1 transgene alone. c316/uas-shits1 flies, in which the DPM neurons were blocked for comparison, was also tested. No defects were apparent when the flies were trained and tested at the permissive temperature. To test for a role after training, all flies were trained at 23°C and immediately after training shifted to 31°C for 2 hr to disrupt neurotransmission from PN or DPM neurons. All flies were then returned to 23°C and tested for 3 hr memory. Memory was significantly impaired by GH146;uas-shits1 and c316/uas-shits1 manipulation, but not by NP225;uas-shits1. The performance of GH146;uas-shits1 and c316/uas-shits1 flies was significantly different from their respective control flies. In contrast, the performance of NP225;uas-shits1 flies was not significantly different from control flies. GH146 and NP225 label a large number of largely overlapping PNs. However, because NP225;uas-shits1 flies did not exhibit a memory defect, it is concluded that other neurons labeled by GH146 that are downstream of PNs could be responsible for the observed memory defect. GH146 most obviously differs from NP225 by also expressing in two anterior paired lateral (APL) neurons that innervate the MB. Each APL ramifies throughout the entire ipsilateral MB. This anatomy is similar to the DPM neurons, which project ipsilaterally throughout the MB lobes and base of the peduncle. Therefore whether the APL neurons were required for memory processing after training was further investigated (Pitman, 2011).

The NP5288 and NP2631 GAL4 lines have also been reported to label the APL neurons. NP5288 is expressed in a subset of PNs similar to that of NP225, as well as a few other distributed neurons in the brain. NP2631 does not label PNs but labels many other neurons in the brain including those in the median bundle, protocerebral bridge, and subesophageal ganglion. The consequence on memory of blocking synaptic output after training was tested from the neurons labeled in these additional APL-expressing lines. As before, no apparent defects were observed when the flies were trained and tested at the permissive temperature. However, flies trained at 23°C, shifted to 31°C for 2 hr after training, and tested for 3 hr memory at 23°C revealed defective memory. Memory performance of NP5288;uas-shits1 and NP2631;uas-shits1 flies was statistically different from the performance of their genetic control groups. These data are consistent with a role for APL neurons in memory processing after training (Pitman, 2011).

Others have reported that combining a ChaGAL80 transgene with GH146 inhibits expression in the APL neurons but leaves expression in PNs relatively intact. This approach was used to further test the requirement of uas-shits1 expression in APL neurons for observed memory defects. The ChaGAL80 transgene was combined with the GH146, NP5288, and NP2631 GAL4 drivers and uas-mCD8::GFP to visualize the extent of GAL4 inhibition by ChaGAL80 in these flies. As described for GH146;ChaGAL80 flies, confocal imaging of the GFP-labeled brains revealed that the ChaGAL80 transgene efficiently suppressed APL expression. The APL neurons were evident in all flies lacking ChaGAL80 but were not labeled in any of the three genotypes containing ChaGAL80. ChaGAL80 affected the expression in other neurons labeled by each GAL4 line to varying degrees. This analysis revealed a strong inhibition in GFP expression in the PNs labeled by GH146 and NP5288, although more PNs retained expression in NP5288 than in GH146, consistent with these two GAL4 drivers labeling partially nonoverlapping PN populations. ChaGAL80 inhibited APL expression in NP2631 and also removed expression from several other neurons. Expression was lost in some neurons innervating the subesophageal ganglion, whereas robust expression remained in the median bundle and protocerebral bridge of the central complex. Unfortunately, several intersectional approaches to create more specific control of APL neurons were unsuccessful (Pitman, 2011).

Next ChaGAL80 was combined with each APL-expressing GAL4 driver and the uas-shits1 transgene to test whether APL expression was necessary for the observed memory phenotypes when GH146, NP5288, and NP2631 neurons were blocked after training. Memory performance of GH146, NP5288, and NP2631 flies expressing uas-shits1 was assayed with or without the ChaGAL80 transgene along with GAL4;ChaGAL80 and uas-shits1 control flies for comparison. Again flies were trained at 23°C, shifted to 31°C for 2 hr after training, and tested 3 hr appetitive memory at 23°C. This manipulation significantly impaired memory performance in all flies without the ChaGAL80 transgene but not in flies with the ChaGAL80 transgene. Memory performance of GH146;uas-shits1, NP5288;uas-shits1, and NP2631;uas-shits1 flies was significantly different from uas-shits1 and GAL4;ChaGAL80 flies. In contrast, memory performance of all flies also harboring the ChaGAL80 transgene was not significantly different from the performance of the genetic control flies. These data suggest that expression in APL neurons is critical to disrupt 3 hr memory when blocking neurotransmission after training (Pitman, 2011).

The memory experiments described did not disrupt synaptic transmission during training or testing. Nevertheless, to control for possible confounding effects, the olfactory acuity and motivation to seek sucrose was further investigated in naive flies following a 2 hr disruption of synaptic transmission and 1 hr recovery as employed in the memory experiments. No olfactory acuity defects were observed in GH146;uas-shits1 or NP5288;uas-shits1 flies. However, NP2631;uas-shits1 flies exhibited a pronounced defect, which questions the validity of the memory experiments with this line. Reliance was therefore placed on the GH146;uas-shits1 and NP5288;uas-shits1 flies and the comparison to NP255;uas-shits1 flies to draw the conclusions. GH146;uas-shits1 and NP5288;uas-shits1 flies also exhibited sucrose acuity that was statistically indistinguishable from uas-shits1 controls. NP5288;uas-shits1 flies performed better than NP5288, which had an apparent defect. These data suggest that 3 hr appetitive memory requires synaptic output from the APL neurons after training, similar to the requirement for output from DPM and MB α′β′ neurons [5635563">5 (Pitman, 2011).

DPM neuron output is also required after training for appetitive LTM. Therefore GH146 and NP5288 were used to test whether APL block disrupted LTM. APL output was blocked for 2 hr after training and 24 hr memory was tested. Surprisingly, performance of GH146;uas-shits1 and NP5288;uas-shits1 flies was not significantly different from uas-shits1 or GAL4 flies, suggesting that APL output is specifically required for an earlier memory phase. Appetitive memory at 3 hr has been shown to be sensitive to cold-shock anesthesia delivered 2 hr after training. Therefore whether APL block affected this labile component was tested by performing experiments with cold shock. Wild-type flies were trained, half of them were subjected 2 hr afterward to a 2 min cold shock, allowed them to recover at room temperature, and tested for 3 hr memory. Performance of these flies was significantly different from those not receiving a cold shock. Interestingly, the performance of GH146;uas-shits1 flies in which APL neurons were blocked for 2 hr after training was statistically indistinguishable from cold-shocked wild-type flies. To further test whether APL-blocked flies were missing the cold-shock-sensitive memory component, the shits1 block and cold-shock treatments were combined. GH146;uas-shits1 flies were trained, APL was blocked after training by shifting flies to 31°C for 105 min, they were returned to 25°C for 15 min, given a 2 min cold shock, and tested for 3 hr memory. The performance of these flies was statistically different from GH146;uas-shits1 flies that received all treatment except the cold shock, suggesting that some ASM was present in GH146;uas-shits1-blocked flies. Importantly, memory performance was not totally abolished. Because significant memory remained following the uas-shits1 block and the cold shock, it was concluded that APL neuron block largely affects the labile anesthesia-sensitive appetitive memory. However, it is worth noting that APL block and cold shock cannot be considered to be operationally equivalent because the 2 min cold shock at 2 hr reduced memory observed at 24 hr, whereas blocking APL for 2 hr did not impact 24 hr memory. Therefore, blocking GH146 and NP5288 neurons appears to be more specific to labile appetitive memory than cold-shock treatment at this time (Pitman, 2011).

To determine possible sites of cell-cell contact, GFP reconstitution across synaptic partners (GRASP) was used. GRASP is detectable when neurons expressing complementary parts of an extracellular split-GFP are close enough that functional GFP is reconstituted. Flies were constructed that express lexAop-mCD4::spGFP11 in MB with 247-LexA and uas-mCD4::spGFP1-10 in APL or DPM with NP5288 or c316-GAL4. This analysis revealed distinct innervation of the MB by DPM and APL. DPM-MB GRASP was very dense and punctate throughout the MB lobes and peduncle and generally resembled the mCD8::GFP pattern covering all the major MB lobe regions. APL-MB GRASP was most notable for structure that is absent. The regular net-like appearance of APL seen with mCD8::GFP was not apparent, and label mostly decorated fibers running in parallel with MB neurons in the lobes. APL-MB GRASP in the vertical lobes was particularly revealing. Whereas the APL mCD8::GFP network extended throughout the vertical lobes and for APL mCD8::mCherry, APL-MB GRASP labeled processes extending in the α′ lobe but very little in the α lobe. Because GRASP is most reliably an indicator of proximity rather than connectivity, these data indicate that much of the APL network is distant to the MB neurons in the α lobe. GRASP was also used to visualize contact between APL and DPM neurons using NP5288-GAL4 for APL and L0111-LexA for DPM. APL-DPM GRASP revealed punctate labeling throughout the MB lobes that was most dense in the α′β′ lobes and base of the peduncle region. It is concluded that APL contacts DPM and MB neurons preferentially in the α′ lobe. In the horizontal lobes, APL contacts DPM throughout and makes dense contact with proximal portions of the MB β, β′, and γ neurons. The density of contact decreases toward the distal end of each horizontal lobe. It seems plausible that APL contacts other unidentified neurons, especially in the areas where they are apparently avoiding MB neurons (Pitman, 2011).

Presynaptic active zones were labelled in APL and DPM neurons by expressing a uas-Bruchpilot::GFP with a mCD8::mCherry transgene that should label the entire cell surface. Brp::GFP driven in APL with GH146 revealed presynaptic zones throughout the MB lobes with elevated levels in the α′β′ lobes. In contrast, Brp::GFP driven in DPM neurons with c316 revealed presynaptic zones throughout the lobes but very pronounced labeling in the αβ lobes (Pitman, 2011).

The anatomical data are consistent with a model of a recurrent MB α′β′-DPM-APL circuit and flow of activity from the α′β′ lobes through the DPM neurons to the αβ lobes. Importantly, GRASP suggests that APL and DPM contact is most dense within the α′β′ lobes, and Brp::GFP indicates strongest APL neurotransmitter release in α′β′. APL-MB GRASP indicates that APL preferentially contacts α′β′ MB neurons (most apparent in the vertical lobes). Interestingly, others have found that APL and DPM neurons are electrically coupled via heterotypic gap junctions. It will therefore be important to determine whether APL-DPM contact in α′β′ is exclusively electrical or a mixture of electrical and chemical (Pitman, 2011).

In conclusion, this study has identified a role after training for synaptic output from the GABAergic APL neurons. APL neurons appear to be specifically required for labile memory, and not for consolidation of long-term memory. APL and DPM neurons are functionally connected, yet outside of labile memory described in this study, disrupting either neuron can have different consequences. First, reducing GABA synthesis in APL neurons enhances learning, whereas DPM neurons are not required during acquisition. Functional imaging data suggests that learning specifically increases DPM neuron activity but reduces APL activity driven by the conditioned odor. It is suspected that these differences relate to APL also having processes in the MB calyx, where GRASP suggests that APL directly contacts MB neurons. Second, APL neurons are only required for earlier labile memory, whereas DPM neurons are required for labile and consolidated memory. It is suspected that this reflects the mode and function of their respective transmitters. It is proposed that APL provides broad nonselective cross-inhibition to maintain synaptic specificity in the recurrent DPM-MB-APL circuit that was originally set by the conditioned odor at acquisition. DPM in contrast might return activity to MB α′β′ neurons and supply consolidating signals to MB αβ neurons. It is expected that additional neurons contribute to the network and await identification. It will also be important to gain exclusive control of APL neurons (Pitman, 2011).

Active memory storage is thought of mostly on a seconds-to-minute timescale in mammals. ASM in Drosophila suggests a prolonged-duration active memory system. It will be important to determine the physiological property that is 'held' in the putative recurrent network. A step change in membrane potential accompanies periods of persistent activity in the oculomotor neural integrator of the goldfish. Such a change in the MB neurons coding olfactory memory would render them more easily excited by the conditioned odorant. Physiology will be needed to definitively add ASM in Drosophila to goldfish gaze stabilization and head direction and prefrontal cortical circuits in mammals as models to understand how memory is stored as persistent activity in recurrent neural networks. Nevertheless, the architecture and prolonged requirement for neurotransmission within the MB-DPM-APL neural circuit are suggestive. In addition, a recent gene profiling study of developing vertebrate cortex and annelid MB indicates a common evolutionary origin (Pitman, 2011).

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Two pairs of mushroom body efferent neurons are required for appetitive long-term memory retrieval in Drosophila

Placais, P. Y., Trannoy, S., Friedrich, A. B., Tanimoto, H. and Preat, T. (2013). Cell Rep. 5(3): 769-80 PubMed ID: 24209748

One of the challenges facing memory research is to combine network- and cellular-level descriptions of memory encoding. In this context, Drosophila offers the opportunity to decipher, down to single-cell resolution, memory-relevant circuits in connection with the mushroom bodies (MBs), prominent structures for olfactory learning and memory. Although the MB-afferent circuits involved in appetitive learning were recently described, the circuits underlying appetitive memory retrieval remain unknown. This study has identified two pairs of cholinergic neurons efferent from the MB alpha vertical lobes, named MB-V3, that are necessary for the retrieval of appetitive long-term memory (LTM). Furthermore, LTM retrieval was correlated to an enhanced response to the rewarded odor in these neurons. Strikingly, though, silencing the MB-V3 neurons did not affect short-term memory (STM) retrieval. This finding supports a scheme of parallel appetitive STM and LTM processing (Placais, 2013).

This study identified two pairs of cholinergic neurons, MBV3 neurons, that are efferent from the tip of the MB α lobes and are required for the retrieval of appetitive LTM, but not STM. It was previously established that appetitive STM and LTM are formed and retrieved through different sets of KCs (Trannoy, 2011). STM formation involves the rutabaga adenylylcyclase, probably as a coincidence detector, in γ KCs, and STM retrieval requires output from the same γ KCs. Conversely, LTM formation requires the same cyclase in α/β KCs, and LTM retrieval requires the output from α/β KCs (Trannoy, 2011). The fact that MB-V3 cholinergic neurons are specifically recruited for the retrieval of appetitive LTM, but not STM, and that they are efferent from the tip of a lobes is fully consistent with this scheme of parallel processing of STM and LTM. On this basis, it is anticipated that other as yet unidentified γ lobe-efferent neurons could mediate the transmission of the STM trace to relevant downstream areas (Placais, 2013).

This work, has also addressed the question of the specific requirement of MB-V3 neurons for the retrieval of appetitive LTM, as opposed to aversive forms of memory. MB-V3 neurons were found to be dispensable for the retrieval of aversive STM and ARM, in accordance with a recently published study by Pai (2013). However, the current results diverge from theirs on the retrieval of aversive LTM because they found that blocking MB-V3 neurons, with the same G0239 GAL4 driver this study used and Shits-thermosensitive neural blocker, yielded a mild but significant defect after spaced training. In addition, calcium-imaging experiments were performed with the MB-V3- specific driver G0239 that revealed no alteration of MB-V3 neuron olfactory responses after spaced training, consistent with behavioral results. In contrast, Pai (2013) reported an increase of the response to CS+ compared to CS after spaced training, but not massed training. It should be noted that they used for their imaging experiments a GAL4 driver that is not specific for MB-V3 neurons and especially labels other MB-extrinsic neurons that have projections on the vertical lobes close to MB-V3 dendrites (MB-V4 neurons according another the nomenclature). The conclusions are drawn from a lack of effect, which as a negative result, should be interpreted with caution. However, the imaging data are consistent with behavior experiments using three different effectors (Shits, ChATRNAi, and dTrpA1) that were all strong enough to completely abolish or very strongly affect (ChATRNAi, dTrpA1) appetitive LTM retrieval. Thus, it seems unlikely that the effects of all these manipulations could have been below detection limits. Two hypotheses are proprosed that would explain the discrepancy between the two reports. First, this study showed that MB-V3 neurons are required for the retrieval of aversive fLTM. This form of aversive LTM shares molecular featurescurrent and retrieval circuit with appetitive LTM. The formation of fLTM requires that flies are mildly fasted before training and put back on food immediately after training. Longer fasting periods before training and/or prolonged starvation after training prevents fLTM formation. Aversive LTM in the study of Pai (2013) might have contained fLTM because their spaced-training protocol takes twice as long as the current protocol (ten versus five cycles), during which flies may be mildly fasted. Being put back on food after training, flies could form some fLTM, which would result in the mild memory impairment they observed. In addition, it could be that other neurons (for example, the MB-V4 neurons, labeled in two other GAL4 drivers they used for behavior experiments and for imaging) are actually involved in aversive LTM retrieval, by themselves or maybe in combination with MB-V3 neurons. Testing this latter hypothesis would require another GAL4 driver that would target MB-V4 neurons independently of MB-V3 neurons. Unfortunately, no such tool has been reported so far (Placais, 2013).

Retrieval of appetitive LTM was functionally correlated to an increased response of MB-V3 neurons to the odor that was associated with sugar ingestion during training, an increase that did not occur in the hour range after training when only STM is formed, and that was abolished under two conditions that disrupt appetitive LTM formation or retrieval. In order to know if this increased response in MB-V3 neurons was the direct consequence of a similar phenomenon occurring upstream in the circuit, similar calcium-imaging experiments were performed in the a branch of α/β KCs, which are directly presynaptic to MB-V3 neurons. No trace of LTM formation was detected in these neurons, either by comparing responses to CS+ and CS within a fly or by comparing flies that are trained to make LTM and flies that undergo an unpaired protocol. These data contradict the conclusion from a recent study claiming that appetitive training induces an increase in the CS+ response in the MB α lobes 24 hr after training (Cervantes-Sandoval, 2013). However, what is shown in this latter study is that the average of the CS+/CS ratio is higher than one, but this effect may in fact be a bias toward high ratio values due to an inappropriate mathematical method of data analysis: the correct way for analyzing the ratio of experimental measurements is to average the logarithm of the ratio, as performed by several groups for similar imaging experiments. Furthermore, Cervantes-Sandoval (2013) did not show in their article the most relevant control data: comparing trained flies with flies that underwent an unpaired protocol would have been more accurate than statistical comparison of KC response between naive and trained flies. Of course, one cannot exclude that a calcium trace might eventually be described in KCs that this study would have missed. However, in the current situation, it seems likely that the LTM retrieval trace observed in MB-V3 neurons is not a simple readout of a similar calcium trace already present in upstream KC axons. In this scheme, appetitive LTM formation likely results in plasticity located at the level of the synapses between α/β KCs and MB-V3 neurons. When the conditioned odor is perceived, potentiation of these synapses would result in an increased response in MB-V3 neurons, which in turn could alter olfactory information to subsequent brain structures. The current data show that blocking the output of MB-V3 neurons is sufficient to fully abolish appetitive LTM retrieval. This of course does not exclude that other MB-extrinsic neurons may also be necessary, but it remains striking that appetitive LTM retrieval depends on signaling from as few as two neurons per brain hemisphere, which represents a huge convergence from the 1,000 α/β KCs. This drastic convergence is consistent with proposed models of memory encoding in insects, where the specificity of memory toward a given odor is conferred by the sparse representation of olfactory stimuli in the KCs, whereas an altered -- in this case increased -- response in the restricted number of output neurons is sufficient to encode an alteration of the valence of an odorant. The specificity of memory expression toward the conditioned odor is preserved provided that synaptic plasticity occurs only in the conditioned odor-responsive KCs; in the present case, at the synapse with MB-V3 neurons. At present, there is no straightforward way to target the KCs specifically responding to a given odor. The identification of MB-V3 should prove a key step in unraveling the precise mechanisms of synaptic plasticity underlying appetitive LTM (Placais, 2013).

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Plasticity of local GABAergic interneurons drives olfactory habituation

Das, S., Sadanandappa, M. K., Dervan, A., Larkin, A., Lee, J. A., Sudhakaran, I. P., Priya, R., Heidari, R., Holohan, E. E., Pimentel, A., Gandhi, A., Ito, K., Sanyal, S., Wang, J. W., Rodrigues, V. and Ramaswami, M. (2011). Proc Natl Acad Sci U S A 108: E646-654. PubMed ID: 21795607

Despite its ubiquity and significance, behavioral habituation is poorly understood in terms of the underlying neural circuit mechanisms. This study presents evidence that habituation arises from potentiation of inhibitory transmission within a circuit motif commonly repeated in the nervous system. In Drosophila, prior odorant exposure results in a selective reduction of response to this odorant. Both short-term (STH) and long-term (LTH) forms of olfactory habituation require function of the rutabaga-encoded adenylate cyclase in multiglomerular local interneurons (LNs) that mediate GABAergic inhibition in the antennal lobe; LTH additionally requires function of the cAMP response element-binding protein (CREB2) transcription factor in LNs. The odorant selectivity of STH and LTH is mirrored by requirement for NMDA receptors and GABAA receptors in odorant-selective, glomerulus-specific projection neurons (PNs). The need for the vesicular glutamate transporter in LNs indicates that a subset of these GABAergic neurons also releases glutamate. LTH is associated with a reduction of odorant-evoked calcium fluxes in PNs as well as growth of the respective odorant-responsive glomeruli. These cellular changes use similar mechanisms to those required for behavioral habituation. Taken together with the observation that enhancement of GABAergic transmission is sufficient to attenuate olfactory behavior, these data indicate that habituation arises from glomerulus-selective potentiation of inhibitory synapses in the antennal lobe. It is suggested that similar circuit mechanisms may operate in other species and sensory systems (Das, 2011).

A key observation is that rut function is uniquely required in adult-stage GABAergic local interneurons for STH and LTH. This observation contrasts with the rut requirement in mushroom-body neurons for olfactory aversive memory. The demonstration of fundamentally different neural mechanisms used in olfactory habituation and olfactory-associative memory elegantly refutes a proposal of the Rescorla-Wagner model that habituation (and extinction) may be no more than associations made with an unconditioned stimulus of zero intensity (Das, 2011).

The requirement for rut in inhibitory LNs also indicates that intrinsic properties of multiglomerular LNs change during habituation. However, logic, as well as anatomical and functional imaging data, indicate that glomerulus-selective plasticity must be necessary if LN changes produce odorant-selective habituation. A potentially simple mechanism for glomerulus-specific potentiation of LN terminals is suggested by the specific requirement for postsynaptic NMDAR in odorant-responsive glomeruli (Das, 2011).

The observation that LTH and STH show similar dependence on rut, NMDAR, VGLUT, GABAA receptors, and transmitter release from LN1 cells indicates a substantially shared circuit mechanism for the two timescales of habituation. The data point to a model in which transient facilitation of GABAergic synapses underlies STH; long-lasting potentiation of these synapses through CREB and synaptic growth-dependent processes underlies LTH. This finding differs in three ways from synaptic facilitation that underlies Aplysia sensitization. First, it refers to inhibitory synapses, with potentiation that may involve a specific heterosynaptic mechanism similar to that used for inhibitory Long Term Potentiation (iLTP) in the rodent ventral tegmentum. Second, by presenting evidence for necessary glutamate corelease from GABAergic neurons, it proposes the involvement of a relatively recently discovered synaptic mechanism for plasticity. Third, it posits an in vivo mechanism to enable glomerulus- specific plasticity of LN terminals (Das, 2011).

It is pleasing that, in all instances tested, physiological and structural plasticity induced by 4-d odorant exposure requires the same mechanisms required for behavioral LTH. When taken together, these different lines of experimental evidence come close to establishing a causal connection between behavioral habituation and accompanying synaptic plasticity in the antennal lobe (Das, 2011).

It is important to acknowledge that, although the current experiments show that plasticity of LN-PN synapses contributes substantially to the process of behavioral habituation, it remains possible that plasticity of other synapses, such as of recently identified excitatory inputs made onto inhibitory LNs, also accompany and contribute to olfactory habituation (Das, 2011).

The conserved organization of olfactory systems suggests that mechanisms of olfactory STH and LTH could be conserved across species. Although this prediction remains poorly tested, early observations indicate that a form of pheromonal habituation in rodents, termed the Bruce effect, may arise from enhanced inhibitory feedback onto mitral cells in the vomeronasal organ (Das, 2011).

Less obviously, two features of the circuit mechanism that we describe suggest that it is scalable and generalizable. First, selective strengthening of inhibitory transmission onto active glomeruli can be used to selectively dampen either uniglomerular (CO2) or multiglomerular (EB) responses; thus, the mechanism is scalable. Second, the antennal lobe/olfactory bulb uses a circuit motif commonly repeated throughout the brain, in which an excitatory principal cell activates not only a downstream neuron but also local inhibitory interneurons, which among other things, limit principal cell excitation (Das, 2011).

It is possible that, in nonolfactory regions of the brains, a sustained pattern of principal neuron activity induced by a prolonged, unreinforced stimulus could similarly result in the specific potentiation of local inhibition onto these principal neurons. Subsequently, the pattern of principal cell activity induced by a second exposure to a now familiar stimulus would be selectively gated such that it would create only weak activation of downstream neurons. In this manner, the circuit model that is proposed for olfactory habituation could be theoretically generalized. More studies are expected to test the biological validity of this observation (Das, 2011).

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The GABAergic anterior paired lateral neurons facilitate olfactory reversal learning in Drosophila

Wu, Y., Ren, Q., Li, H. and Guo, A. (2012). Learn Mem. 19: 478-486. PubMed ID: 22988290

Reversal learning has been widely used to probe the implementation of cognitive flexibility in the brain. Previous studies in monkeys identified an essential role of the orbitofrontal cortex (OFC) in reversal learning. However, the underlying circuits and molecular mechanisms are poorly understood. This study used the T-maze to investigate the neural mechanism of olfactory reversal learning in Drosophila. In reversal learning flies selectively avoid the odor more recently paired with shock in the second cycle of learning, regardless of what they learned during cycle 1. By adding a reversal training cycle to the classical learning protocol, it was shown that wild-type flies are able to reverse their choice according to the alteration of conditioned stimulus (CS)-unconditioned stimulus (US) contingency. The reversal protocol induced a specific suppression of the initial memory, an effect distinct from memory decay or extinction. GABA down-regulation in the anterior paired lateral (APL) neurons, which innervate the mushroom bodies (MBs), eliminates this suppression effect and impairs normal reversal. These findings reveal that inhibitory regulation from the GABAergic APL neurons facilitates olfactory reversal learning by suppressing initial memory in Drosophila (Wu, 2012).

The one-trial instant reversal paradigm was chosen as the primary reversal protocol for several reasons in addition to its being concise and simple to execute. First, if cycle 2 immediately follows cycle 1, the memory decay factor of cycle 1 is minimized, and the contribution of the reversal factor is highlighted. In fact, an elegant early analysis of the interaction between cycle 1 memory and cycle 2 training already disclosed that, although the reversal learning PI increases along with the delay of the cycle 2 training, the nonadditive effect of the two cycles is most salient when the delay is shorter than 30 min. Therefore, it would be more suitable to adopt the short delay protocol when examining the reversal effect (Wu, 2012).

Second, the necessity was demonstrated of the protocol (A+B– B+A–) for the investigation of reversal learning. Since CS+ odor presentation alone is sufficient to produce an optimal learning result in classical learning, CS– odor is dispensable in classical learning. Therefore, it brought the concern about whether CS– odor is also dispensable in reversal learning. A timeline-aligned direct comparison between the basic reversal learning protocol (A+B– B+A–) and the CS– odor absent protocol (A+B+) indicated that the reversal protocol exerted a stronger inverting power than CS– absent protocol. Therefore, CS– odor is indispensable in reversal learning protocol. Additional experiments showed that the flies developed distinguishable memory strengths for the two trained odors before testing, as significantly different PIs were observed when the two odor memories were separately evaluated. Moreover, a detailed investigation of a 'two-event choice' protocol, which actually is also A+B+, revealed that the flies are unable to make a consistent choice when the time delay between the two conditioning sessions is shorter than 2 min. This confirmed the effectiveness of the protocol and further differentiated the reversal learning from a decision-making process, which was probed through the 'two-event choice' protocol (Wu, 2012).

Third, the serial reversal paradigm that has been used in other model systems demonstrated that increased reversal experience expedited the reversal acquisition. Sequential reversal learning was also assayed, but so far improved reversal PIs with increasing reversal cycle numbers in Drosophila have not been observed. The difference could be due to a lower efficiency of Pavlovian training on the T-maze platform compared with operant training (Wu, 2012).

The importance of MBs for olfactory learning and memory in Drosophila has been extensively addressed. Genetic suppression of Rac expression in MBs disturbed reversal learning. In honeybees, MBs are required for reversal learning. Our experimental results further demonstrated that Drosophila olfactory reversal learning also requires the MBs. It is not surprising that the MBs have such a vital role since the reversal learning protocol is based on classical associative learning. For the same reason, it is difficult to distill reversal-specific mechanisms in MBs. Therefore, the role of GABA regulation in reversal learning is emphasized (Wu, 2012).

Previous studies have shown that down-regulation of GABA through knock- down of the GABAA receptor, resistance to dieldrin (RDL), or through reducing GABA synthesis in the APL neurons improves the associative learning ability of flies. The role of the GABAergic APL neurons in Drosophila learning and memory has recently garnered attention. The APL neurons are required to sustain labile memory, and gap junctions between the APL and the DPM neurons play a critical role in olfactory memory. Moreover, in locusts, the giant GABAergic neurons (GGN), which are anatomical equivalents to the Drosophila APL neurons, were found to form a normalizing negative-feedback loop within the MBs. Taken together with the finding that reducing GABA synthesis in APL neurons disrupted the reversal learning ability in flies, it is proposed that the APL neurons mediate the olfactory reversal learning, which might be acquired inside MBs. Specifically, it is speculated that when the flies face reversal training that contradicts previous learning, the APL neurons inhibit the initial memory and facilitate the reversal acquisition by releasing an appropriate amount of GABA. Since the APL neurons innervate the MBs broadly, it is difficult to imagine how the release of GABA would occur specifically on the MB neurons that represent the initially learned odor. Perhaps there exists some retrograde information from the MB neurons, representing the initially learned odor, that is sent to the presynaptic dendrites of the APL neurons, thus regulating the GABA release accordingly (Wu, 2012).

Attempts to manipulate RDL expression and up-regulate GABA synthesis in APL neurons failed to yield meaningful results; no significant change of reversal learning was observed in those experiments. The reason might be that the efficiencies of those manipulations were not sufficient to generate detectable differences in reversal learning. Nevertheless, enhanced GABAergic innervation has been shown to improve reversal learning in mice, which supports the speculation regarding GABA modulation in reversal learning (Wu, 2012).

Memory extinction occurs when the CS+ that was previously associated with US is presented without US pairing. In the reversal protocol, the memory extinction component could not fully account for the reversal learning PI. In honeybees, the blockade of MBs led to reversal defects without affecting extinction, which suggests an obvious divergence between extinction and reversal. Despite these apparent differences, there appears to be some common underlying mechanisms. Overlapping neural systems mediating extinction and reversal were reported in humans. In Drosophila, odorant memory extinction is supposed to be an intracellular process and antagonizes the previous memories at the molecular level, affecting cAMP signaling. The experimental results demonstrated that reversal is also cAMP-dependent, which indicates that there is a similar foundation for extinction and reversal at the molecular level. Based on those evidences, the relationship between memory extinction and reversal learning seems to be complicated and might involve different but not completely separate neuronal mechanisms (Wu, 2012).

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The GABA system regulates the sparse coding of odors in the mushroom bodies of Drosophila

Lei, Z., Chen, K., Li, H., Liu, H. and Guo, A. (2013). Biochem Biophys Res Commun 436: 35-40. PubMed ID: 23707718

In the mushroom bodies (MBs) of Drosophila, an analogue of the mammalian olfactory cortex, olfactory stimuli are sparsely encoded by Kenyon cells (KCs) that exhibit a high level of odor selectivity. Sparse coding of olfactory stimuli has significant advantages for maximizing the discrimination power and storage capacity of MBs. The inhibitory gamma-aminobutyric acid (GABA) system is important for regulating information processing in MBs, but its specific role in the sparse coding of odors is unclear. This study investigated the role of the GABA system in the sparse coding of odors using an in vivo calcium imaging strategy, which allowed measurment of the activity of the KC population at single cell resolution while the components of the GABA system were genetically manipulated. It was found that the down-regulation of GABAA but not GABAB receptors in KCs reduced the sparseness of odor representations in the MB, as shown by an increase in the population response probability and decrease in the odor selectivity of single KCs. Furthermore, the down-regulation of GABA synthesis in a pair of large GABAergic neurons innervating the entire MB reduced the sparseness of odor representations in KCs. In conclusion, the sparse coding of odors in MBs is regulated by a pair of GABAergic neurons through the GABAA receptors on KCs, thus demonstrating a specific role of the inhibitory GABA system on information processing in the MB (Lei, 2013).

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Origins of cell-type-specific olfactory processing in the Drosophila mushroom body circuit

Inada, K., Tsuchimoto, Y. and Kazama, H. (2017). Neuron 95(2): 357-367. PubMed ID: 28728024

How cell-type-specific physiological properties shape neuronal functions in a circuit remains poorly understood. This issue has been addressed in the Drosophila mushroom body (MB), a higher olfactory circuit, where neurons belonging to distinct glomeruli in the antennal lobe feed excitation to three types of intrinsic neurons, α/β, α'/&beta', and γ Kenyon cells (KCs). Two-photon optogenetics and intracellular recording revealed that whereas glomerular inputs add similarly in all KCs, spikes were generated most readily in α'/β' KCs. This cell type was also the most competent in recruiting GABAergic inhibition fed back by anterior paired lateral neuron, which responded to odors either locally within a lobe or globally across all lobes depending on the strength of stimuli. Notably, as predicted from these physiological properties, α'/β' KCs had the highest odor detection speed, sensitivity, and discriminability. This enhanced discrimination required proper GABAergic inhibition. These results link cell-type-specific mechanisms and functions in the MB circuit (Inada, 2017).

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Synapsin function in GABA-ergic interneurons is required for short-term olfactory habituation

Sadanandappa, M. K., Redondo, B. B., Michels, B., Rodrigues, V., Gerber, B., Vijayraghavan, K., Buchner, E. and Ramaswami, M. (2013). J Neurosci 33: 16576-16585. PubMed ID: 24133261

In Drosophila, short-term (STH) and long-term habituation (LTH) of olfactory avoidance behavior are believed to arise from the selective potentiation of GABAergic synapses between multiglomerular local circuit interneurons (LNs) and projection neurons in the antennal lobe. However, the underlying mechanisms remain poorly understood. This study shows that synapsin (syn) function is necessary for STH and that syn97-null mutant defects in STH can be rescued by syn+ cDNA expression solely in the LN1 subset of GABAergic local interneurons. As synapsin is a synaptic vesicle-clustering phosphoprotein, these observations identify a presynaptic mechanism for STH as well as the inhibitory interneurons in which this mechanism is deployed. Serine residues 6 and/or 533, potential kinase target sites of synapsin, are necessary for synapsin function suggesting that synapsin phosphorylation is essential for STH. Consistently, biochemical analyses using a phospho-synapsin-specific antiserum show that synapsin is a target of Ca2+ calmodulin-dependent kinase II (CaMKII) phosphorylation in vivo. Additional behavioral and genetic observations demonstrate that CaMKII function is necessary in LNs for STH. Together, these data support a model in which CaMKII-mediated synapsin phosphorylation in LNs induces synaptic vesicle mobilization and thereby presynaptic facilitation of GABA release that underlies olfactory STH. Finally, the striking observation that LTH occurs normally in syn97 mutants indicates that signaling pathways for STH and LTH diverge upstream of synapsin function in GABAergic interneurons (Sadanandappa, 2013).

Mechanisms for synaptic plasticity have been intensively analyzed in reduced preparations, e.g., in hippocampal or cortical-slice preparations and in neuromuscular synapses, e.g., of Aplysia, crayfish, frog, lamprey, and Drosophila. In contrast, synaptic mechanisms underlying specific forms of behavioral learning are less well understood in vivo, in terms of the signaling pathways engaged by experience as well as the cell types in which these mechanisms operate. The analysis of such in vivo mechanisms of plasticity requires an accessible neural circuit, whose properties are measurably altered by experience (Sadanandappa, 2013).

The olfactory response in Drosophila is initiated by the activation of odorant receptors expressed in the olfactory sensory neurons (OSNs), which project into the antennal lobe (AL) and form synapses with glomerulus-specific projection neurons (PNs) that wire to both, the mushroom bodies (MB) and the lateral protocerebrum. OSNs and PNs also activate multiglomerular excitatory and inhibitory local interneurons (LNs), which mediate lateral and intraglomerular inhibition in the AL. Strong evidence has been proved for a model in which Drosophila olfactory habituation, i.e., reduced olfactory avoidance caused by previous exposure to an odorant arises through potentiation of inhibitory transmission between GABAergic LNs and PNs of the AL. This study analyzes the molecular basis of this potentiation and propose a mechanism that could lead to increased presynaptic GABA release after odorant exposure (Sadanandappa, 2013).

Synapsins are a conserved family of synaptic vesicle-associated proteins. They are predominantly associated with the reserve pool of synaptic vesicles and their phosphorylation by kinases such as calcium-dependent protein kinases (CaMKs), protein kinase A (PKA), and MAPK/Erk, result in the mobilization of these vesicles and thereby induces presynaptic facilitation. While synapsin may play key roles in behavioral plasticity in mammals, its functions in learning and memory remain mysterious in part because mammals have three synapsins (I, II, and III) encoded by three different genes (Sadanandappa, 2013).

Recent studies of the single synapsin gene in Drosophila show that it is required for adult anesthesia-sensitive memory of odor-shock association (Knapek, 2010). Larval associative memory requires synapsin with intact phosphorylation target sites (Ser6 and Ser533) likely operating in a subset of MB neuron (Sadanandappa, 2013).

This study asked whether, where, and how synapsin functions in olfactory habituation. The observations indicate that short-term habituation (STH) requires synapsin function as well as its CaMKII-dependent phosphorylation in the LN1 subset of inhibitory interneurons in the AL. These point to presynaptic facilitation of GABA release as being a crucial mechanism for STH. The observation that long-term habituation (LTH) forms normally in syn97 mutants indicates that this form of long-term memory can be encoded without transition through a short-term memory stage (Sadanandappa, 2013).

Previous studies have established the important roles for vertebrate and invertebrate synapsins in short-term synaptic plasticity. The conclusion that increased GABA release underlies olfactory STH is built on previous studies that have established the role of synapsin in synaptic vesicle mobilization and presynaptic facilitation. Several in vivo and in vitro studies have provided evidence that synapsin phosphorylation and dephosphorylation regulate the effective size of different vesicle pools and thereby control neurotransmitter release. In the mollusks Aplysia californica and Helix pomatia/aspersa, the phosphorylation and redistribution of synapsin induced by the PKA or MAPK/Erk-pathways mediates short-term facilitation of transmitter release. In Drosophila larval neuromuscular junctions, post-tetanic potentiation of transmitter release requires synapsin function and is accompanied by mobilization of a reserve pool of synaptic vesicles. And in the mouse CNS , enhanced ERK signaling in the inhibitory neurons results in increased levels of synapsin-1 phosphorylation and enhanced GABA release from hippocampal interneurons (Sadanandappa, 2013).

In context of these prior studies of synapsin, the current observation that synapsin and its phosphorylation are necessary in GABAergic local interneurons for STH indicates that the facilitation of GABA release from LNs attenuates excitatory signals in the AL and thereby results in the reduced behavioral response, characteristic of habituation. The molecular reversibility of phosphorylation could potentially account for the spontaneous recovery of the olfactory response after STH. These in vivo observations on synapsin function constitute a substantial advance as they show that synapsin-mediated plasticity, usually observed in response to experimentally enforced electrophysiological stimulations, can underlie behavioral learning and memory induced by sensory experience. In addition, by placing these changes in an identified subpopulation of local inhibitory interneurons in the AL, they implicate presynaptic plasticity of LNs as a mechanism necessary for habituation and thereby substantially clarify a neural circuit mechanism for this form of nonassociative memory (Sadanandappa, 2013).

A significant question is how synapsin phosphorylation is regulated in vivo for synaptic plasticity and how this contributes to altered circuit function that underlies behavioral learning. This has been difficult to address for two reasons: first, due to the complexity and potential promiscuity of kinase signaling pathways, and second, this requires not only the identification of neurons that show synapsin-dependent plasticity, but also concurrent understanding of the circuit functions of these neurons and their postsynaptic target(s) in vivo. The latter has been a particular challenge in neural networks for behavioral memory. For instance, although synapsin- and S6/S533-dependent odor-reward memory trace localized to the MBs, the downstream targets of the MB to mediate learned behavior are only beginning to be unraveled. This makes it difficult to comprehensively interpret the complex role of synapsin in associative memory illustrated by the finding that 3 min memory and anesthesia-sensitive 2 h memory require synapsin, whereas 5 h memory and anesthesia-resistant 2 h memory do not (Knapek, 2010). In the Drosophila neural circuit that underlies olfactory habituation, this study presents evidence that is most parsimoniously explained by a model in which CaMKII regulates synapsin phosphorylation in GABAergic LNs of the AL, neurons that are known to inhibit projection neurons that transmit olfactory input to higher brain centers (Sadanandappa, 2013).

in vivo CaMKII studies not only show the requirement of its function in olfactory habituation, but also demonstrate that the predominant form of synapsin, which arises from pre-mRNA editing, is a potent substrate for CaMKII. Thus, expression of an inhibitory CaMKII peptide in neurons not only reduces (yet does not abolish) the S6-phosphorylated form of synapsin detected using S6 phospho-specific antibody, it also blocks olfactory habituation, thereby providing experimental evidence for presynaptic function of CaMKII. These findings provide in vivo support for a model that proposed the primacy of CaMKII regulation of synapsin function; however, the structural basis for this regulation may be slightly different as invertebrate synapsins lack the D domain found on mammalian homologs that appear to be the major targets of CaMKII-dependent synapsin phosphorylation (Sadanandappa, 2013).

These conclusions on the role of CaMKII must be qualified in two ways. First, though tight correlations were shown between CaMKII phosphorylation of synapsin and the protein's function in STH, the data fall short of establishing causality. Second, it was not possible to directly demonstrate that odorant exposure that induces STH results in CaMKII-dependent synapsin phosphorylation in LNs. Attempts to address the latter issue failed because of technical difficulties in using phospho-specific antibodies for in vivo immunohistochemistry. Finally, although it is proposed that CaMKII phosphorylation is necessary for synapsin function during STH, it remains possible that other additional kinases, e.g., PKA and CaMKI, also contribute to synapsin regulation in vivo required for STH (Sadanandappa, 2013).

Several studies have discriminated between mechanisms of short-term and long-term memory (STM and LTM) formation. Most have focused on the distinctive requirement for protein synthesis in LTM and have not established whether STM is a necessary step in the formation of LTM or whether STM and LTM arise via distinctive, if partially overlapping molecular pathways. However, a few reports describe experimental perturbations that greatly reduce STM, without altering LTM (Sadanandappa, 2013).

In cultured sensorimotor synapses, which provide a surrogate model for behavioral sensitization in Aplysia, it has been shown that synaptic application of a selective 5-HT receptor antagonist blocked short-term facilitation while leaving long-term facilitation unaffected. In contrast, somatic application of the same antagonist selectively blocked long-term facilitation. This showed that long-term synaptic plasticity, though triggered by similar inputs (5-HT in this case), can progress through a pathway that does not require short-term plasticity (Sadanandappa, 2013).

In mammalian systems, it has been shown that a variety of pharmacological infusions into the hippocampal CA1 region or in entorhinal/ parietal cortex inhibited STM without affecting LTM of a shock avoidance memory task. In Drosophila, different isoforms of A-kinase anchor protein (AKAP) interacts with cAMP-PKA and play a distinct role in the formation of STM and LTM (Lu, 2007; Zhao, 2013). While these studies indicate that LTM is not built on STM, they do not rule out the possibility that they share an early common synaptic mechanism, but differ in subsequent mechanisms of consolidation, which occur in anatomically distinct brain regions (Sadanandappa, 2013).

The current observations on the absolute requirement for synapsin in STH but not LTH extend a model in which LTM can be encoded without transition through STM, particularly because STH and LTH involve different timescales of plasticity in the very same olfactory neurons. In the simple learning circuit for STH and LTH, the current observations are interpreted in a biochemical model. While both STH and LTH occur through potentiation of iLN-PN synapses, it is proposed that the signaling mechanisms for short- and long-term synaptic plasticity diverge before the stage of synapsin phosphorylation in GABAergic local interneurons. Thus, odorant exposure results in the activation of key signaling molecules such as PKA and CaMKII in LNs required for both forms of olfactory habituation. However, the kinases affect STH through synapsin phosphorylation, which results in a rapid but transient increase in evoked GABA release. Meanwhile, the same signaling molecules also participate in the activation of translational and/or transcriptional control machinery, which act, on a slower timescale, to cause the formation of additional GABAergic synapses that persist stably for much longer periods of time (Sadanandappa, 2013).

The unusual behavioral state, in which an animal is unable to form an STM but capable of longer term memory may have some clinical significance. Recently, a comprehensive mouse model for Down syndrome, which is trisomic for ~92% of the human chromosome 21, was shown to have defective STM of novel object recognition, while still showing normal LTM in this task, which is conceptually similar to behavioral habituation. Thus, it is suggested that further studies may eventually identify several other molecules which, like synapsin, are selectively necessary for short-term but not for long-term memory (Sadanandappa, 2013).

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Aging impairs protein-synthesis-dependent long-term memory in Drosophila

Tonoki, A. and Davis, R.L. (2015). J Neurosci 35: 1173-1180. PubMed ID: 25609631

Although aging is known to impair intermediate-term memory in Drosophila, its effect on protein-synthesis-dependent long-term memory (LTM) is unknown. This study shows that LTM is impaired with age, not due to functional defects in synaptic output of mushroom body (MB) neurons, but due to connectivity defects of dorsal paired medial (DPM) neurons with their postsynaptic MB neurons. GFP reconstitution across synaptic partners (GRASP) experiments revealed structural connectivity defects in aged animals of DPM neurons with MB axons in the α lobe neuropil. As a consequence, a protein-synthesis-dependent LTM trace in the α/β MB neurons fails to form. Aging thus impairs protein-synthesis-dependent LTM along with the α/β MB neuron LTM trace by lessening the connectivity of DPM and α/β MB neurons (Tonoki, 2015).

The data presented in this study offer several important findings about the neural circuitry and the forms of memory disrupted by aging. First, it shows that aging impairs only one of the two mechanistically distinct forms of LTM generated by spaced, aversive classical conditioning in Drosophila. LTM that is independent of protein synthesis remains unaffected by age, whereas that form of LTM requiring protein synthesis becomes impaired. Therefore, there is mechanistic specificity in the effects of aging on LTM. Although aging, in principal, could disrupt processes like protein synthesis at the molecular level leading to a LTM deficit, these results indicate that the problem is traceable to the circuitry involved in generating protein-synthesis-dependent LTM (Tonoki, 2015).

The normal synaptic transmission from DPM neurons onto follower neurons during spaced training that is required for generating LTM is lost with age. This is attributable to the reduction of synaptic contacts between DPM neuron processes and MB axons specifically in the tip of the α lobe neuropil as revealed by GRASP signals. The loss of synaptic contacts between DPM and MB neurons in this region also may explain why synaptic blockade of DPM neurons during acquisition disrupts protein-synthesis-dependent LTM in young but not old flies. Therefore, a second major finding is that neural contacts and subsequent synaptic activity between DPM and α/β MB neurons are required for generating protein-synthesis-dependent LTM, and aging impairs this process. Consistent with this model, it is found that aging blocks the formation of a calcium-based, protein-synthesis-dependent memory trace in the α/β MB neurons (Tonoki, 2015).

It was found previously that ITM is impaired in flies of 30 d of age along with the capacity to form an ITM trace in the DPM neurons. Nevertheless, aging does not compromise the capacity to form an STM trace in the α'/β' MB neurons. Therefore, aging disrupts specific temporal forms of memory, including ITM and protein synthesis LTM, but not STM and protein-synthesis-independent LTM. It is possible that the loss of connectivity of DPM neurons with the α tip neuropil is responsible for the loss of both ITM and protein-synthesis-dependent LTM, along with their respective memory traces. Previous and this study's data indicate that STM appears to bypass the DPM neurons, whereas the reciprocal activity between DPM and MB neurons is required for ITM and LTM. Aging puts a kink in this neural system by impairing connectivity (Tonoki, 2015).

The study offers a model to explain the neural circuitry involved in protein-synthesis-dependent LTM formation and how aging impairs this form of memory. Although DPM neurons make contacts widely throughout the MB lobe neuropil with processes of many cell types, the critical interaction for LTM formation occurs in the vertical lobes of the MB through contacts onto the axons of α/β MB neurons. DPM neuron synaptic activity during spaced training, which occurs due to their stimulation by MB neurons, promotes synaptic changes in the postsynaptic α/β MB neurons and leads to the formation of memory trace in the α/β MB neurons. Aging impairs protein-synthesis-dependent LTM along with a LTM trace that normally forms in the α/β MB neurons by lessening the connectivity of DPM and α/β MB neurons. Identifying the mechanisms by which the DPM neurons lose their connectivity with only the tips of α/β MB neurons might reveal how aging impairs protein-synthesis-dependent LTM (Tonoki, 2015).

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Wnt signaling is required for long-term memory formation

Tan, Y., Yu, D., Busto, G. U., Wilson, C. and Davis, R. L. (2013). Cell Rep 4: 1082-1089. PubMed ID: 24035392

Wnt signaling regulates synaptic plasticity and neurogenesis in the adult nervous system, suggesting a potential role in behavioral processes. This study probed the requirement for Wnt signaling during olfactory memory formation in Drosophila using an inducible RNAi approach. Interfering with β-catenin expression in adult mushroom body neurons specifically impairs long-term memory (LTM) without altering short-term memory. The impairment is reversible, being rescued by expression of a wild-type β-catenin transgene, and correlates with disruption of a cellular LTM trace. Inhibition of wingless, a Wnt ligand, and arrow, a Wnt coreceptor, also impairs LTM. Wingless expression in wild-type flies is transiently elevated in the brain after LTM conditioning. Thus, inhibiting three key components of the Wnt signaling pathway in adult mushroom bodies impairs LTM, indicating that this pathway mechanistically underlies this specific form of memory (Tan, 2013).

This study was prompted by a previous discovery that a casein kinase Iγ homolog (CkIγ), gilgamesh (gish), is required for STM in Drosophila. CkIgγmediated phosphorylation of the cytoplasmic tail of Lrp5/6 (Arr) is crucial for Wnt/β-catenin signaling (Davidson, 2005), and it was predicted that disruption of the Wnt signaling pathway would perturb STM. Surprisingly, however, it was found that knockdown of the four Wnt signaling components leaves STM intact. The likely explanation for this discrepancy is that Gish serves other important functions in STM formation besides its role in LTM through phosphorylation of the Arr receptor (Tan, 2013).

How does Wnt signaling in the MB neurons mediate the formation of LTM? Since the normal expression of β-catenin, Wg, and Arr is required in the set of MB neurons defined by P{MB-GeneSwitch}12-1, and Wg is a short-range ligand, a model is favored in which the Wnt ligand, Wg, participates in an autocrine fashion in the MB neurons. Spaced conditioning, which produces long-term behavioral memory, but not massed or single-cycle conditioning, leads to a transient increase in wg expression in the MB neurons, perhaps as a step downstream of Creb. The subsequent secretion of Wg by the MB neurons activates the Fz/Arr receptor, leading to the accumulation of β-catenin in the MB neurons. β-catenin, in turn, orchestrates transcriptional changes in the MB neurons that are required for LTM, as well as the breaking and remaking of cell contacts through N-cadherin function, which is necessary for the reorganization of synapses for LTM storage. Recently, ribonucleoprotein particles containing synaptic protein transcripts were shown to exit the nucleus through a nuclear envelope budding process in response to Wnt signaling at the Drosophila neuromuscular junction (Speese, 2012). Wnt-dependent nuclear budding could provide the initial step for transporting RNAs to synapses for local protein synthesis and LTM formation (Tan, 2013).

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Fasting launches CRTC to facilitate long-term memory formation in Drosophila

Hirano, Y., Masuda, T., Naganos, S., Matsuno, M., Ueno, K., Miyashita, T., Horiuchi, J. and Saitoe, M. (2013). Science 339: 443-446. PubMed ID: 23349290

Canonical aversive long-term memory (LTM) formation in Drosophila requires multiple spaced trainings, whereas appetitive LTM can be formed after a single training. Appetitive LTM requires fasting prior to training, which increases motivation for food intake. However, this study found that fasting facilitates LTM formation in general; aversive LTM formation also occurred after single-cycle training when mild fasting was applied before training. Both fasting-dependent LTM (fLTM) and spaced training-dependent LTM (spLTM) requires protein synthesis and cyclic adenosine monophosphate response element-binding protein (CREB) activity. However, spLTM requires CREB activity in two neural populations--mushroom body and dorsal-anterior-lateral (DAL) neurons--whereas fLTM required CREB activity only in mushroom body neurons. fLTM uses the CREB coactivator CREB-regulated transcription coactivator (CRTC), whereas spLTM uses the coactivator CBP. Thus, flies use distinct LTM machinery depending on their hunger state (Hirano, 2013).

In Drosophila, canonical aversive long-term memory (LTM), which is dependent on de novo gene expression and protein synthesis, is generated after multiple rounds of spaced training. In contrast, appetitive LTM can be formed by single-cycle training. Because both aversive and appetitive LTM require protein synthesis and activation of CREB, it is likely that both types of LTM are formed by similar mechanisms. Appetitive and aversive LTM are known to differ (i.e., octopamine is specifically involved in appetitive but not aversive memory formation). However, it remains unclear why single-cycle training is sufficient for appetitive but not aversive LTM formation. Appetitive LTM cannot form unless fasting precedes training. Although fasting increases motivation for food intake (a requirement for appetitive memory) it was suspected that fasting may activate a second, motivation-independent, memory mechanism that facilitates LTM formation after single-cycle training (Hirano, 2013).

Flies were deprived of food for various periods of time and then subjected to aversive single-cycle training. Fasting prior to training significantly enhanced 1-day memory, with a peak at 16 hours of fasting and a return to nonfasting levels at 20 to 24 hours of fasting. In contrast, 16 hours of fasting did not increase short-term memory (STM, measured 1 hour after training). In this protocol, flies were returned to food vials after training, raising a possibility that the perception of food as a reward after training may enhance the previous aversive memory. This possibility was tested by inserting refeeding periods between food deprivation and training. Although fasting followed by a 4-hour refeeding period failed to induce appetitive LTM, it significantly enhanced aversive 1-day memory; this finding suggests that enhancement of aversive memory occurs through a mechanism unrelated to increased motivation or perception of food as a reward. A 6-hour refeeding period was sufficient to prevent aversive memory enhancement. Continuous food deprivation after training suppressed aversive memory enhancement, which indicates that both fasting before training and feeding after training are required to enhance aversive memory (Hirano, 2013).

Administration of the protein synthesis inhibitor cycloheximide (CHX) abolished 1-day memory enhancement but had no effect on 1-hour memory, supporting the idea that memory enhancement consists of an increase of LTM. Memory remaining after CHX treatment is likely to be protein synthesis-independent, anesthesia-resistant memory (ARM). Fasting for 16 hours neither enhanced protein synthesis-independent memory nor canonical aversive LTM generated by spaced training (spLTM). Furthermore, fasting-dependent memory decayed within 4 days, and food deprivation did not enhance 4-day spLTM, indicating that fasting-dependent memory is physiologically different from spLTM (Hirano, 2013).

Fasting-dependent memory was blocked by acute, dose-dependent, expression of CREB2-b, a repressor isoform of CREB, in the mushroom bodies (MBs). Expression of the repressor from two copies of UAS-CREB2-b under control of the MB247-Switch (MBsw) GAL4 driver, which induces UAS transgene expression upon RU486 feeding, significantly suppressed fasting-dependent memory upon RU486 feeding, whereas expression from one copy of UAS-CREB2-b did not. Defects in LTM formation are highly correlated with CREB2-b amounts. Significantly higher MBsw-dependent expression of CREB proteins was found in flies carrying two copies of UAS-CREB2-b relative to flies carrying one copy. MBsw-dependent CREB2-b expression did not affect STM in either fed or food-deprived conditions. Because the aversive memory enhanced by fasting is mediated by protein synthesis and CREB, this memory is referred to as fasting-dependent LTM (fLTM). Similar to the results in aversive fLTM, MBsw-dependent CREB2-b expression also decreased appetitive LTM but not appetitive STM (Hirano, 2013).

A recent study (Chen, 2012) concluded that CREB activity in MB neurons is not required for spLTM. In that study, CREB2-b was expressed using the OK107 MB driver and GAL80ts was used to restrict CREB2-b expression to 30°C. However, this study found that the GAL80ts construct still inhibited expression of CREB considerably at 30°C. When higher amounts of CREB2-b were acutely expressed in MBs using MBsw, a significant decrease was observed in 1-day spLTM, indicating that CREB activity in the MBs is likely to be required for spLTM (Hirano, 2013).

Expression of CREB2-b in two dorsal-anterior-lateral (DAL) neurons impaired aversive spLTM. In contrast, expression of CREB2-b in DAL neurons did not affect aversive fLTM. Moreover, appetitive LTM was also not affected by expression of CREB2-b in DAL neurons. MBsw did not express GAL4 in DAL neurons (Hirano, 2013).

CREB requires coactivators, including CBP (CREB-binding protein), to activate transcription needed for LTM formation. Acute expression of an inverted repeat of CBP (CBP-IR) in MBs significantly impaired spLTM without affecting either STM or 1-day memory after multiple massed trainings, which do not lead to LTM formation. However, neither aversive fLTM nor appetitive LTM was impaired by CBP-IR expression, indicating that an alternative coactivator may be required for fasting-dependent memory (Hirano, 2013).

Recent studies demonstrate the involvement of a cAMP-regulated transcriptional coactivator (CRTC) in hippocampal plasticity. In metabolic tissues, phosphorylated CRTC is sequestered in the cytoplasm while dephosphorylated CRTC translocates to the nucleus to promote CREB-dependent gene expression. Fasting causes CRTC dephosphorylation and activation. In line with this, significant accumulation of hemagglutinin (HA)-tagged CRTC (CRTC-HA) was found within MB nuclei after 16 hours of food deprivation. Subcellular fractionation indicated that food deprivation causes CRTC-HA nuclear translocation without affecting total CRTC-HA amounts (Hirano, 2013).

To examine the role of CRTC in fLTM and spLTM, a CRTC inverted repeat (CRTC-IR) was acutely expressed using MBsw, and suppression of aversive fLTM was observed but no effect was seen on STM. CHX treatment did not further decrease 1-day aversive memory, and CRTC-IR expression from a second MB driver, OK107, also impaired fLTM formation. CRTC-IR expression from MBsw also impaired appetitive LTM without affecting appetitive STM. In contrast, CRTC-IR expression from MBsw did not impair spLTM. CRTC-IR expression in DAL neurons had no effect on either aversive fLTM or appetitive LTM. Consistent with these results showing lack of fLTM after 24-hour fasting, 1-day aversive memory after 24-hour fasting did not decrease upon CRTC-IR expression in MBs (Hirano, 2013).

To examine the effects of spaced training on fLTM and the effects of fasting on spLTM, fed or fasted flies expressing either CBP-IR or CRTC-IR were space-trained. When CBP-IR was expressed to impair spLTM, 1-day memory after spaced training was impaired in fed conditions but not in fasting conditions, which suggested that spaced training protocols do not block fLTM. When CRTC-IR was expressed to impair fLTM formation, 1-day memory after spaced training was not affected by fasting, which suggested that mild fasting does not impair spLTM formation (Hirano, 2013).

Is activation of CRTC sufficient to generate fLTM in the absence of fasting? HA-tagged constitutively active CRTC (CRTC-SA-HA) was expressed from MBsw, and its nuclear accumulation was observed in the absence of fasting. Acute expression of CRTC-SA-HA from MBsw increased 1-day aversive memory after single-cycle training in fed flies, and this increase was not further enhanced by fasting. In contrast, expression of control CRTC-HA did not alter the fasting requirement for memory enhancement. CRTC-SA-HA expression did not affect feeding itself, which suggested that the memory enhancement is not due to impaired feeding. Taken together, CRTC activity in MBs is necessary and sufficient to form fLTM. Similar to the effects of fasting, CRTC-SA-HA expression did not affect STM or 4-day spLTM (Hirano, 2013).

In mammalian metabolic tissues, CRTC is phosphorylated by insulin signaling, which is suppressed by fasting. CRTC phosphorylation is also regulated by insulin signaling in flies. To determine whether reduced insulin signaling activates CRTC and promotes fLTM formation, heterozygous mutants for chico, which encodes an adaptor protein required for insulin signaling, were tested. Although chico1 null mutants are semilethal and defective for olfactory learning, heterozygous chico1/+ mutants are viable and display normal learning (Hirano, 2013).

CRTC accumulated in MB nuclei in chico1/+ mutants in the absence of food deprivation. Under conditions where flies were fed, chico1/+ flies had significantly greater 1-day memory after single-cycle training relative to control flies, whereas 1-hour memory was unaffected. Enhanced 1-day memory in chico1/+ flies was not further enhanced by fasting. Because the chico1/+ mutation does not affect feeding itself, the memory enhancement would not seem to be attributable to impaired feeding. The increased 1-day memory in chico1/+ mutants was suppressed by CHX treatment and CRTC-IR expression using MBsw, which suggests that reduced insulin signaling mimics fLTM through activation of CRTC in MBs (Hirano, 2013).

Single-cycle training after mild fasting generates both appetitive and aversive LTM, and CRTC in the MBs plays a key role in both types of LTM. A CRTC-dependent LTM pathway is unlikely to be involved in increasing motivation required to form appetitive memory, because CRTC knockdown did not affect appetitive STM and because CRTC-SA expression was not sufficient to form appetitive LTM without prior fasting. Although mild 16-hour fasting induced aversive fLTM, longer 24-hour fasting impaired aversive fLTM but not appetitive LTM. Thus, although aversive and appetitive fLTM share mechanistic similarities, they may be regulated by different inputs controlling motivation and fasting time courses. Because nuclear translocation of CRTC was sustained even after 24 hours of food deprivation, prolonged fasting may suppress a CRTC-independent step in aversive fLTM formation. spLTM was not affected by 24-hour fasting prior to training, which suggests that the unknown inhibitory effect of 24-hour fasting does not occur after spaced training. Continuous food deprivation after training suppressed aversive fLTM. Another study has reported that continuous food-deprivation after spaced training suppresses spLTM as well (Hirano, 2013).

Suppression of aversive LTM by prolonged fasting may ensure that starving flies pursue available food, with less concern for safety. Although the biological importance of aversive fLTM in natural environments is currently unclear, the current results indicate that different physiological states may induce different types of LTM in flies (Hirano, 2013).

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Muscarinic ACh receptors contribute to aversive olfactory learning in Drosophila

Silva, B., Molina-Fernandez, C., Ugalde, M. B., Tognarelli, E. I., Angel, C. and Campusano, J. M. (2015). Neural Plast 2015: 658918. PubMed ID: 26380118

The most studied form of associative learning in Drosophila consists in pairing an odorant, the conditioned stimulus (CS), with an unconditioned stimulus (US). The timely arrival of the CS and US information to a specific Drosophila brain association region, the mushroom bodies (MB), can induce new olfactory memories. Thus, the MB is considered a coincidence detector. It has been shown that olfactory information is conveyed to the MB through cholinergic inputs that activate acetylcholine (ACh) receptors, while the US is encoded by biogenic amine (BA) systems. This study evaluates the proposition that, as in mammals, GPCR muscarinic ACh receptors (mAChRs) contribute to memory formation in Drosophila. The results show that pharmacological and genetic blockade of mAChRs in MB disrupts olfactory aversive memory in larvae. This effect is not explained by an alteration in the ability of animals to respond to odorants or to execute motor programs. These results show that mAChRs in MB contribute to generating olfactory memories in Drosophila (Silva, 2015).

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Metabolic learning and memory formation by the brain influence systemic metabolic homeostasis

Zhang, Y., Liu, G., Yan, J., Zhang, Y., Li, B. and Cai, D. (2015). Nat Commun 6: 6704. PubMed ID: 25848677

Metabolic homeostasis is regulated by the brain, but whether this regulation involves learning and memory of metabolic information remains unexplored. This study use a calorie-based, taste-independent learning/memory paradigm to show that Drosophila form metabolic memories that help in balancing food choice with caloric intake; however, this metabolic learning or memory is lost under chronic high-calorie feeding. Loss of individual learning/memory-regulating genes causes a metabolic learning defect, leading to elevated trehalose and lipid levels. Importantly, this function of metabolic learning requires not only the mushroom body but also the hypothalamus-like pars intercerebralis, while NF-κB activation in the pars intercerebralis mimics chronic overnutrition in that it causes metabolic learning impairment and disorders. Finally, this study evaluated this concept of metabolic learning/memory in mice, suggesting that the hypothalamus is involved in a form of nutritional learning and memory, which is critical for determining resistance or susceptibility to obesity. In conclusion, these data indicate that the brain, and potentially the hypothalamus, direct metabolic learning and the formation of memories, which contribute to the control of systemic metabolic homeostasis (Zhang, 2015).

This work consists of a series of studies in Drosophila: these animals were found to temporarily develop metabolic learning to balance food choice with caloric intake. In Drosophila research, sugar has often been used for studying the appetitive reward value of food taste. Of interest, recent research has suggested that fruit flies can distinguish caloric values from the taste property of food. Using tasteless sorbitol as a carbohydrate source to generate an environmental condition that contained NC versus HC food, this study revealed that Drosophila can develop a form of metabolic learning and memory independently of taste, by which flies are guided to have a preference for normal caloric environment rather than high-caloric environment. However, this form of metabolic memory does not seem robust, as it is vulnerably diminished under genetic or environmental influences. It is postulated that this vulnerability to overnutrition is particularly prominent for mammals (such as C57BL/6J mice), and overnutritional reward-induced excess in caloric intake can quickly become dominant. This effect can be consistently induced in Drosophila when learning/memory-regulating genes are inhibited in the brain or the hypothalamus-like PI region. It was observed that each of these genetic disruptions led to impaired metabolic learning, resulting in increased caloric intake and, on a chronic basis, the development of lipid excess and diabetes-like phenotype. Indeed, it has been documented that chronic high-sugar feeding is sufficient to cause insulin resistance, obesity and diabetes in Drosophila. It is yet unclear whether this metabolic learning can induce an appetitive memory of normal caloric environment or an aversive memory of high-caloric environment. Regardless, the findings in this work have provoked a stimulating question, that is, whether this form of metabolic learning and memory is present in the mammals and, if so, whether this mechanism can be consolidated to improve the control of metabolic physiology and prevent against diseases. These mouse studies may provide an initial support to this concept and strategy, but clearly, in-depth future research is much needed (Zhang, 2015).

In light of the underlying neural basis for this metabolic learning, this study indicates that multiple brain regions are required, including the hypothalamus-like PI region in addition to the MB (equivalent to the hippocampus in mammals), which is classically needed for learning and memory formation. Anatomically, the PI region is located in the unpaired anteromedial domain of the protocerebral cortex, which is near the calyces of the MB and the dorsal part of the central complex (another brain region for regulating learning and memory). Functionally, the PI region has been demonstrated to coordinate with the MB in regulating various physiological activities in Drosophila. Thus, it is very possible that some PI neurons present nutritional information to the MB and thus induce metabolic learning and memory formation. However, the underlying detailed mechanism is still unknown, especially if this process involves a role of dilps, which represent the prototypical neuropeptides produced by the PI neurons. Considering that the PI region in flies is equivalent to the mammalian hypothalamus, this study was extended to mouse models by comparatively analysing A/J versus C57BL/6J mice—which are known to have different diet preference as well as different susceptibilities to obesity development. While A/J mice showed a learning process of distinguishing NC versus HC food, C57BL/6J mice failed to do so. It is particularly notable that this difference of learning and memory between these two strains is associated with differential expression profiles of learning/memory genes in the hypothalamus rather than the hippocampus. This finding, in conjunction with the Drosophila study, highlights a potential that the hypothalamus has a unique role in mediating metabolic learning and memory formation. Although the mouse experiments cannot exclude the impacts from the taste/smell properties of the studied food, the results demonstrated that there is a form of nutritional memory, which seems dissociable from the memory of overnutritional reward. These initial observations in mice lend an agreement with findings in Drosophila, suggesting that the brain and potentially the hypothalamus can link nutritional environment to a form of metabolic learning and memory homeostasis (Zhang, 2015).

From a disease perspective, metabolic learning in Drosophila is impaired under chronic overnutrition, and the mouse study was in line with this understanding. This response to overnutrition is useful when famine is outstanding; however, it is a dilemma when metabolic disease is of concern, much like the scenario pertaining to leptin resistance under chronic overnutrition, whereas an increase in leptin sensitivity is demanded to reduce obesity. Recently, it was established that NF-κB-dependent hypothalamic inflammation links chronic overnutrition to the central dysregulation of metabolic balance. This study showed that activation of the NF-κB pathway in the PI region weakened the function of metabolic learning and, conversely, NF-κB inhibition in this region provided a protective effect against chronic overnutrition-impaired metabolic learning. These findings are in alignment with the literature, for example, pan-neuronal NF-κB inhibition was shown to improve activity-dependent synaptic signalling and cognitive function including learning and memory formation, and persistent NF-κB activation inhibits neuronal survival and the function of learning and memory formation. Hence, overnutrition-induced neural NF-κB activation has a negative impact on metabolic learning and memory formation in regulating metabolic homeostasis homeostasis (Zhang, 2015).

To summarize the findings in this work, a series of behavioural studies was performed revealing that Drosophila have a form of metabolic learning and memory, through which the flies are directed to balance food choice with caloric intake in relevant environments. Several learning/memory-regulating genes including rut, dnc and tequila are involved in this function, and brain regions including the PI in addition to the MB are required to induce this mechanism. On the other hand, metabolic learning is impaired under chronic overnutrition through NF-κB activation, leading to excess exposure to calorie-enriched environment, which causes metabolic disorders. Overall, metabolic learning and memory formation by the brain and potentially the hypothalamus play a role in controlling metabolic homeostasis homeostasis (Zhang, 2015).

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Spatio-temporal in vivo recording of dCREB2 dynamics in Drosophila long-term memory processing

Zhang, J., Tanenhaus, A. K., Davis, J. C., Hanlon, B. M. and Yin, J. C. (2014). Neurobiol Learn Mem 118C: 80-88. PubMed ID: 25460038

CREB (cAMP response element-binding protein) is an evolutionarily conserved transcription factor, playing key roles in synaptic plasticity, intrinsic excitability and long-term memory (LTM) formation. The Drosophila homologue of mammalian CREB, dCREB2, is also important for LTM. However, the spatio-temporal nature of dCREB2 activity during memory consolidation is poorly understood. Using an in vivo reporter system, this study examined dCREB2 activity continuously in specific brain regions during LTM processing. Two brain regions that have been shown to be important for Drosophila LTM are the ellipsoid body (EB) and the mushroom body (MB). dCREB2 reporter activity is persistently elevated in EB R2/R4m neurons, but not neighboring R3/R4d neurons, following LTM-inducing training. In multiple subsets of MB neurons, dCREB2 reporter activity is suppressed immediately following LTM-specific training, and elevated during late windows. In addition, heterogeneous responses were observed across different subsets of neurons in MB αβ lobe during LTM processing. All of these changes suggest that dCREB2 functions in both the EB and MB for LTM formation, and that this activity contributes to the process of systems consolidation (Zhang, 2014).

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Tip60 HAT action mediates environmental enrichment induced cognitive restoration

Xu, S., Panikker, P., Iqbal, S. and Elefant, F. (2016). PLoS One 11: e0159623. PubMed ID: 27454757

Environmental enrichment (EE) conditions have beneficial effects for reinstating cognitive ability in neuropathological disorders like Alzheimer's disease (AD). While EE benefits involve epigenetic gene control mechanisms that comprise histone acetylation, the histone acetyltransferases (HATs) involved remain largely unknown. This study examine a role for Tip60 HAT action in mediating activity- dependent beneficial neuroadaptations to EE using the Drosophila CNS mushroom body (MB) as a well-characterized cognition model. Flies raised under EE conditions were shown to display enhanced MB axonal outgrowth, synaptic marker protein production, histone acetylation induction and transcriptional activation of cognition linked genes when compared to their genotypically identical siblings raised under isolated conditions. Further, these beneficial changes are impaired in both Tip60 HAT mutant flies and APP neurodegenerative flies. While EE conditions provide some beneficial neuroadaptive changes in the APP neurodegenerative fly MB, such positive changes are significantly enhanced by increasing MB Tip60 HAT levels. These results implicate Tip60 as a critical mediator of EE-induced benefits, and provide broad insights into synergistic behavioral and epigenetic based therapeutic approaches for treatment of cognitive disorder (Xu, 2016).

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Drosophila neprilysins are involved in middle-term and long-term memory

Turrel, O., Lampin-Saint-Amaux, A., Préat, T. and Goguel, V. (2016). J Neurosci 36: 9535-9546. PubMed ID: 2762970

Neprilysins are type II metalloproteinases known to degrade and inactivate a number of small peptides. Neprilysins in particular are the major amyloid-β peptide-degrading enzymes. In mouse models of Alzheimer's disease, neprilysin overexpression improves learning and memory deficits, whereas neprilysin deficiency aggravates the behavioral phenotypes. However, whether these enzymes are involved in memory in nonpathological conditions is an open question. Drosophila melanogaster is a well suited model system with which to address this issue. Several memory phases have been characterized in this organism and the neuronal circuits involved are well described. The fly genome contains five neprilysin-encoding genes, four of which are expressed in the adult (see Neprilysin 4). Using conditional RNA interference, this study shows that all four neprilysins are involved in middle-term and long-term memory. Strikingly, all four are required in a single pair of neurons, the dorsal paired medial (DPM) neurons that broadly innervate the mushroom bodies (MBs), the center of olfactory memory. Neprilysins are also required in the MB, reflecting the functional relationship between the DPM neurons and the MB, a circuit believed to stabilize memories. Together, these data establish a role for neprilysins in two specific memory phases and further show that DPM neurons play a critical role in the proper targeting of neuropeptides involved in these processes (Turrell, 2016).

Research on neprilysins has essentially focused on their role as the main Aβ-degrading enzymes in pathological situations and as biomarkers in heart failure. Using Drosophila this study has established that neprilysins are involved in specific types of memory. Disrupting the expression of any neprilysin impairs MTM and LTM, revealing that one or several neuropeptides need to be targeted to enable proper memory formation. Interestingly, all four neprilysins expressed in the fly are required in the MB and also in DPM neurons, a pair of large neurons that broadly innervates the MB and are involved in memory consolidation (Turrel, 2016).

Neprilysins have been described extensively as proteases acting on substrates of no more than 50 residues, except Drosophila Nep4, which is involved in muscle integrity independently of its catalytic activity. There is a consensus that neprilysins function by turning off neuropeptide signals at the synapse. In addition, there is evidence to suggest that neprilysin processing could lead to the activation of neuromodulators. Therefore, in addition to their role in Aβ degradation, neprilysins also inactivate a large number of peptides and are thus equally involved in a large number of processes (Turrel, 2016).

In Drosophila, several small peptides have been linked to olfactory memory. Short neuropeptide F (sNPF) is highly expressed in the MB and has been described as a functional neuromodulator of appetitive memory. Drosophila neuropeptide F (dNPF) has been shown to provide a motivational switch in the MB that controls appetitive memory output. Interestingly, dNPF is an ortholog of mammalian NPY, a peptide identified as an hNEP substrate. hNEP can process NPY in transgenic mice to produce neuroactive fragments. Because components of dNPF/NPY signaling are conserved at both the functional and molecular levels, it is possible that dNPF is targeted by neprilysins. It remains to be determined whether such peptides are involved in aversive memory and, conversely, whether neprilysins are involved in appetitive memory (Turrel, 2016).

Although all four Drosophila neprilysins are involved in identical memory phases, they exhibit distinct features in terms of the neuronal circuits involved. Only Nep1 inhibition in α/β MB and DPM neurons alters both MTM and LTM. One hypothesis is that Nep1 expressed in DPM and MB neurons plays the same role, targeting a single substrate at synapses connecting the two structures. If so, the lifetime of such a substrate would need to be restricted strictly to limit its effect (Turrel, 2016).

Like the other neprilysins, Nep2 is involved in MTM and LTM, but it exhibits a peculiar characteristic: Nep2 inhibition in DPM neurons leads to MTM disruption, whereas it does not alter LTM. Although it cannot be ruled out that Nep2 expression in DPM neurons is required for LTM, but that its silencing does not reach a level critical for this process, the data suggest that Nep2 expression in DPM neurons is not required for LTM formation. It is noteworthy that neprilysins are synthesized as type II integral membrane proteins, whereas Nep2 is a soluble secreted endopeptidase. Whether an endopeptidase is tethered or fully secreted will have important implications in terms of field of activity and enzyme concentration at the membrane surface. It is possible that Nep2 secreted from either DPM neurons or another structure in the vicinity, such as MB neurons, is able to play an identical role. Therefore, Nep2 reduction in either neuronal structure would not be sufficient to affect LTM. In contrast, Nep2 expression in such a structure would not be able to compensate Nep2 silencing in DPM neurons for MTM, pointing to a distinct requirement for MTM and LTM formation. Nep2 might be required at a distinct concentration and/or localization for MTM and LTM or it may target distinct substrates for these two processes (Turrel, 2016).

The data reveal functional redundancy among Nep2, Nep3, and Nep4 for LTM formation in the α/β neurons. Namely, concomitant silencing of Nep2 + Nep3 or Nep3 + Nep4 leads to altered LTM. It is possible that several neprilysins target a single neuropeptide. However, because concomitant silencing of Nep2 + Nep4 does not affect LTM, it seems more likely that several targets are involved in LTM (Turrel, 2016).

The memory phenotypes observed after each neprilysin reduction are reminiscent of the pattern in APPL mutants. Indeed, it was shown previously that expression of APPL, the APP fly ortholog, is required in the MB for MTM and LTM formation, but not for learning and ARM (Goguel, 2011; Bourdet, 2015). An attractive hypothesis is that Aβ peptide derived from physiological processing of APPL might play a role in memory and act as a substrate for one of the neprilysin peptidases. Nep2 would be a good candidate because several studies have shown that it is capable of degrading human Aβ. Supporting this hypothesis, several reports in mammals have implicated low physiological concentrations of Aβ peptide in memory formation (Turrel, 2016).

The memory phenotypes observed in this study are equally reminiscent of the pattern displayed by amnesiac (amn) mutants. The amn gene isolated through behavioral screening for memory mutants was later shown to encode a predicted neuropeptide precursor. Although the mature products of the amn gene have not been identified, sequence analyses suggested the existence of three potential peptides. One of them is homologous to mammalian pituitary adenylate cyclase-activating peptide (PACAP), a neuromodulator and neurotransmitter that regulates a variety of physiological processes through stimulation of cAMP production. In vitro studies have shown that hNEP can degrade PACAP and the analysis of the biological properties of the resulting fragments found that PACAP degradation by hNEP produces active metabolites selective for a particular receptor subtype. One of the major sites of PACAP cleavage by hNEP is conserved in the AMN peptide. It was shown that AMN is highly expressed in DPM neurons, where the four neprilysins are required for MTM. DPM output is required during the consolidation phase for MTM and it was suggested that DPM might release the AMN modulatory neuropeptide that alters the physiology of MB neurons to help stabilize or consolidate odor memories. The fact that neuropeptides are often coreleased with classical neurotransmitters, but generally have slower and longer-lasting postsynaptic effects, has prompted the hypothesis that AMN peptides may be released at the MB to produce relatively long-lasting, physiological changes. Given this context, it is tempting to speculate that AMN might be one of the Drosophila neprilysin's targets (Turrel, 2016).

Both the axons and dendrites of DPM are evenly distributed in different lobes of the MB, and it has been suggested that DPM neurons are presynaptic and postsynaptic to the MB neurons and are recurrent feedback neurons. Because neprilysins are necessary in the DPM, and also in the α/β neurons of the MB where MTM and LTM are stored, these proteins could be involved in maintaining a loop between the DPM and MB lobes by restricting the lifetime of neuromodulators. The DPM-α/β neurons circuit has been shown recently to also modulate egg-laying decision via the AMN neuropeptide. It would be interesting to learn whether neprilysins are involved in this process or if their function is restricted to memory formation (Turrel, 2016).

Despite the importance of the MB for olfactory memory, a functional neurotransmitter or coreleased peptidic neuromodulators produced by MB-intrinsic cells has long remained elusive. It was shown recently that acetylcholine is a Kenyon cell transmitter. The fact that several neprilysins are required for MTM and LTM suggests the involvement of at least one neuropeptide. It remains to be determined whether neprilysin targets are released from the DPM and/or MB and whether identical or distinct neuropeptide substrates support MTM and LTM processes. The sum of the work reported in this study highlights the critical role of the DPM in inactivating and/or processing neuropeptides involved in memory processes connected to the MB (Turrel, 2016).

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Temporal integration of cholinergic and GABAergic inputs in isolated insect mushroom body neurons exposes pairing-specific signal processing

Raccuglia, D. and Mueller, U. (2014). J Neurosci 34: 16086-16092. PubMed ID: 25429149

GABAergic modulation of neuronal activity plays a crucial role in physiological processes including learning and memory in both insects and mammals. During olfactory learning in honeybees (Apis mellifera) and Drosophila melanogaster the temporal relation between excitatory cholinergic and inhibitory GABAergic inputs critically affects learning. However, the cellular mechanisms of temporal integration of these antagonistic inputs are unknown. To address this question, this study used calcium imaging of isolated honeybee and Drosophila Kenyon cells (KCs), which are targets of cholinergic and GABAergic inputs during olfactory learning. In the whole population of honeybee KCs, pairing of acetylcholine (ACh) and γ-aminobutyric acid (GABA) was found to reduce the ACh-induced calcium influx, and depending on their temporal sequence, induces different forms of neuronal plasticity. After ACh-GABA pairing the calcium influx of a subsequent excitatory stimulus is increased, while GABA-ACh pairing affects the decay time leading to elevated calcium levels during the late phase of a subsequent excitatory stimulus. In an exactly defined subset of Drosophila KCs implicated in learning similar pairing-specific differences were found. Specifically the GABA-ACh pairing splits the KCs in two functional subgroups: one is only weakly inhibited by GABA and shows no neuronal plasticity and the other subgroup is strongly inhibited by GABA and shows elevated calcium levels during the late phase of a subsequent excitatory stimulus. These findings provide evidence that insect KCs are capable of contributing to temporal processing of cholinergic and GABAergic inputs, which provides a neuronal mechanism of the differential temporal role of GABAergic inhibition during learning (Raccuglia, 2014).

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Debra, a protein mediating lysosomal degradation, is required for long-term memory in Drosophila

Kottler, B., Lampin-Saint-Amaux, A., Comas, D., Preat, T. and Goguel, V. (2011). PLoS One 6: e25902. PubMed ID: 21991383

A central goal of neuroscience is to understand how neural circuits encode memory and guide behavior changes. Many of the molecular mechanisms underlying memory are conserved from flies to mammals, and Drosophila has been used extensively to study memory processes. To identify new genes involved in long-term memory, Drosophila enhancer-trap P(Gal4) lines were screened showing Gal4 expression in the mushroom bodies, a specialized brain structure involved in olfactory memory. This screening led to the isolation of a memory mutant that carries a P-element insertion in the debra locus. debra encodes a protein involved in the Hedgehog signaling pathway as a mediator of protein degradation by the lysosome. To study debra's role in memory, debra overexpression, as well as debra silencing mediated by RNA interference, were achieved. Experiments conducted with a conditional driver that allowed transgene expression to be resticted in the adult mushroom bodies led to a long-term memory defect. Several conclusions can be drawn from these results: (1) debra levels must be precisely regulated to support normal long-term memory, (2) the role of debra in this process is physiological rather than developmental, and (3) debra is specifically required for long-term memory, as it is dispensable for earlier memory phases. Drosophila long-term memory is the only long-lasting memory phase whose formation requires de novo protein synthesis, a process underlying synaptic plasticity. It has been shown in several organisms that regulation of proteins at synapses occurs not only at translation level of but also via protein degradation, acting in remodeling synapses. This work gives further support to a role of protein degradation in long-term memory, and suggests that the lysosome plays a role in this process (Kottler, 2011).

Drosophila melanogaster constitutes a useful model to study the molecular basis underlying memory processes. Its brain, despite its small size, is highly organized and exhibits specialized structures. Furthermore, many of the mechanisms inherent in memory are conserved from flies to mammals. Studies in Drosophila combine the use of powerful genetic tools together with the possibility of analyzing a large repertoire of behaviors. The genetic basis of olfactory learning and memory has been studied for more than 30 years in Drosophila, providing insights into some of the genes involved in short-term and long-term memory formation (Kottler, 2011).

Aversive olfactory memory studies generally rely on classical conditioning of an odor-avoidance response. In this paradigm, groups of flies are successively exposed to two distinct odors, only one of which is accompanied by electric shocks. Memory scores are determined by placing the flies in the center of a T-maze where they are simultaneously exposed to the two odors during one minut. Depending on the training protocol, different types of memory can be measured. Short-term memory (STM) and anaesthesia-resistant memory (ARM) are formed after one cycle of training. STM is a labile memory phase sensitive to cold shock anaesthesia that lasts for a few hours. In contrast, ARM is a consolidated form of memory resistant to cold shock that can last for days. Long-term memory (LTM) is also a form of consolidated memory, but unlike ARM, its formation is sensitive to an inhibitor of cytoplasmic protein synthesis, indicating that de novo protein synthesis is required. LTM is generated after spaced-conditioning consisting of repeated training sessions, each separated by a rest period. LTM is generally thought to occur through changes in synaptic efficacy produced by a restructuring of synapses (Kottler, 2011).

The requirement for de novo gene expression during LTM formation has been widely observed in a number of different model systems. The cAMP response element-binding protein is an LTM-specific regulator of gene expression in Drosophila and in other species. Several other transcription regulators are required for proper LTM including Adf-1 and Stat92E in Drosophila, and CCAAT/enhancer-binding protein, Zif-268, AP-1, and NF-kB in mammals. The Notch signaling receptor has also been implicated in LTM. In addition to transcription, local control of translation, and proteases are as well involved in Drosophila LTM. Crammer, a protein required for LTM, has been shown to inhibit Cathepsin L, a protease that could be involved in lysosome function (Kottler, 2011 and references tgerein).

A large collection of evidence indicates that mushroom bodies (MBs) play a pivotal role in olfactory memory. The MBs form a bilaterally symmetrical structure in the central brain and consist of approximately 4,000 neurons called Kenyon cells. Three types of Kenyon cells (α/β, α'/β', and γ) project their axons ventrally to form the peduncle that splits into five lobes, two vertical (α and α') and three median (β, β', and γ). The lobes are assumed to be the synaptic output region of the MBs. In addition, neurons of the lobes are targeted by multiple inputs (Kottler, 2011).

Many genes required for LTM have been shown to be expressed in the MBs, prompting this study to analyze enhancer-trap P(Gal4) lines showing Gal4 expression in the MBs to characterize new LTM mutants. This report identified debra, a gene involved in protein degradation by the lysosome, as being specifically required for LTM (Kottler, 2011).

An enhancer-trap P(Gal4) inserted nearby the dbr gene lead to Gal4-dependent expression in the MBs, a major center of olfactory memory. The MB247 driver used to affect dbr levels in this study leads to a specific expression in the MB α/β and γ neurons, consistent with additional reports showing that these neurons are involved in aversive olfactory LTM (Kottler, 2011).

Several reports have shown that dbr is involved in various developmental processes. Importantly, the use of conditional silencing in this study reveals that the LTM-specific impairment observed is not caused by a developmental defect, demonstrating that dbr is physiologically involved in LTM processing (Kottler, 2011).

Dbr does not exhibit any obvious homology with known proteins, and its molecular function is unknown. Dbr has been shown to interact with the F-box protein Slimb, an ubiquitin ligase (Dai, 2003). In cooperation with Slimb, Dbr induces the polyubiquitination of phosphorylated Ci-155, a transcription factor that mediates Hedgehog signaling. Interestingly, similar to Dbr, Slimb has been implicated in LTM formation, thus pointing to a role for ubiquitination in LTM processing. These observations are reminiscent of a previous study showing that the highly conserved ubiquitin ligase Neuralized (Neur) is involved in LTM. Neur is expressed in the adult MB α/β neurons and is a limiting factor for LTM formation: loss of one copy of neur gene results in significant LTM impairment whereas Neur overexpression results in a dose-dependent enhancement of LTM. In contrast, both dbr silencing and dbr overexpression in the adult MBs generate a LTM defect, showing that dbr levels must be precisely regulated to support normal LTM, a situation similar to previous reports describing LTM-specific mutants (Kottler, 2011).

Interestingly, dbr is specifically required for LTM since it is dispensable for earlier memory phases. LTM is the only form of memory that relies on de novo protein synthesis, a process thought to underlie synaptic plasticity. Since proteins are the molecular actors that mediate signal transduction, protein synthesis as well as protein degradation must be important for plasticity and memory. Indeed, regulated proteolysis plays a critical role in the remodeling of synapses. Regulated proteolysis is achieved by two major systems in eukaryotic cells: the proteasome and the lysosome. The lysosome degrades most membrane and endocytosed proteins. Owing to their large surface-to-volume ratio, the degradation of membrane proteins such as receptors by the endocytic/lysosomal pathway must be especially efficient and tightly regulated in neurons. Whereas several studies have implicated the proteasome in LTM in Aplysia, in the crab and in mammals, less is known about the implication of the lysosome in this process. It has been suggested that Neur is implicated in both the proteasome and the lysosome degradation pathways. Dbr is involved in protein degradation, and has been characterized as a component of the multivesicular bodies (MVB), an actor of the lysosome pathway (Dai 2003). Ubiquitinated receptors undergo endocytosis and become incorporated into endosomes that are in turn sequestered into MVB. Subsequently, the MVB membrane becomes continuous with lysosomes leading to degradation of the receptor. Although it cannot be ruled out that dbr could be implicated in LTM via another pathway, it is suggested that its function in LTM takes place through the lysosomal protein degradation pathway (Kottler, 2011).

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Imp promotes axonal remodeling by regulating profilin mRNA during brain development

Medioni, C., Ramialison, M., Ephrussi, A. and Besse, F. (2014). Curr Biol 24(7): 793-800. PubMed ID: 24656828

Neuronal remodeling is essential for the refinement of neuronal circuits in response to developmental cues. Although this process involves pruning or retraction of axonal projections followed by axonal regrowth and branching, how these steps are controlled is poorly understood. Drosophila mushroom body (MB) γ neurons provide a paradigm for the study of neuronal remodeling, as their larval axonal branches are pruned during metamorphosis and re-extend to form adult-specific branches. This study identified the RNA binding protein Imp as a key regulator of axonal remodeling. Imp is the sole fly member of a conserved family of proteins that bind target mRNAs to promote their subcellular targeting. Whereas Imp is dispensable for the initial growth of MB γ neuron axons, it is required for the regrowth and ramification of axonal branches that have undergone pruning. Furthermore, Imp is actively transported to axons undergoing developmental remodeling. Finally, it was demonstrated that profilin mRNA is a direct and functional target of Imp that localizes to axons and controls axonal regrowth. This study reveals that mRNA localization machineries are actively recruited to axons upon remodeling and suggests a role of mRNA transport in developmentally programmed rewiring of neuronal circuits during brain maturation (Medroni, 2014).

In cultured vertebrate neurons, ZBP1 mediates the transport of β-actin mRNA to axons, a process required for the chemiotropic response of growth cones to guidance cues. Whether these observations reflect a general requirement for ZBP1 and axonal mRNA transport during brain development has remained unclear. This study found that Imp, the Drosophila ZBP1 ortholog, accumulates in the cell bodies of a large number of neural cells in adult brain. Strikingly, Imp was additionally observed in the axonal compartment of a subpopulation of mushroom body (MB) neurons. MBs are composed of three main neuronal types (αβ, α'β', and γ) with specific axonal projection patterns and developmental programs. α'β' and αβ neurons are generated during late larval stage and early metamorphosis and are maintained until adulthood. γ neurons are born during late embryogenesis and early larval stages and undergo extensive remodeling during metamorphosis. Imp was found to be enriched in adult γ neuron axons where it colocalized with FasciclinII, but it was not detected in the axons of nonremodeling MB neurons (αβ and α'β' neurons). To test whether Imp is expressed in αβ and α'β' neurons, brains expressing GFP in γ and αβ-core neurons were labelled with antibodies against Imp and Trio, a protein specifically expressed in adult α'β' and γ neurons. Imp was not detected in αβ-core neurons but accumulated in the cell bodies of both α'β' and γ neurons. Thus, both the expression and subcellular distribution of Imp are tightly regulated in Drosophila MB neurons (Medroni, 2014).

To investigate whether Imp axonal translocation is developmentally regulated, the distribution of Imp within γ neurons was examined at different stages. In third-instar larvae, Imp accumulated exclusively in the cell bodies and was not observed in axons. During metamorphosis (pupariation), MB γ neurons first prune the distal part of their axons and then re-extend a medial branch to establish adult-specific projections. Six hours after puparium formation (APF), Imp was weakly detected in γ neuron axons. Such an axonal accumulation of Imp was visible at the time larval γ neurons have completed the pruning of their axonal processes (18 hr APF). During the subsequent intensive growth phase, Imp was enriched at the tip of axons, where it accumulated in particles. Thus, the translocation of Imp to axons is developmentally controlled, and correlates with axonal remodeling (Medroni, 2014).

To test whether Imp is required for γ axon developmental remodeling, the morphology was analyzed of adult homozygous mutant neurons generated using the MARCM (mosaic analysis with a repressible cell marker) system. Clones in which the entire progeny of a neuroblast was mutant exhibited a reduced number of cells and an altered morphology. Although wild-type adult γ axons typically span the entire medial lobe, a mixture of elongated and nonelongated axons was observed upon imp inactivation. To better visualize the morphology of mutant neurons, single labeled neurons were analyzed. Wild-type adult γ neurons extend one main axonal process that reaches the extremity of the MB medial lobe. Several secondary branches typically form along this main axonal process. In contrast, about 50% of imp γ axons failed to reach the end of the medial lobe. These defects did not result from axon retraction, as the proportion of defective axons did not increase with age. Interestingly, mutant axons of normal length but lost directionality were observed, suggesting that imp may be required for the response of γ axons to guidance cues during metamorphosis. imp mutant neurons also exhibited an overall decrease in the complexity of axonal arborization patterns characterized by a reduced number of terminal branches. Both phenotypes were significantly suppressed upon expression of a wild-type copy of Imp in γ neurons, revealing that imp acts cell autonomously to control axonal regrowth and branching (Medroni, 2014).

To determine whether Imp function in axonal growth correlates with its accumulation in axons, the requirement for Imp was investigated in two neuronal cell types where it is exclusively detected in cell bodies: larval γ neurons and α'β' neurons. Both single larval γ neurons and single adult α'β' neurons mutant for imp projected their axons normally. Furthermore, larval γ neuron neuroblast clones exhibited a normal morphology, confirming that imp is not necessary for initial axon growth. These results show that Imp is specifically required for the growth and branching of remodeling γ axons and suggest that its translocation to axons is critical for this function (Medroni, 2014).

To address whether Imp is transported actively to the axons of regrowing γ neurons, a live-imaging protocol was developed using cultured pupal brains expressing functional GFP-Imp fusions specifically in γ neurons). The culture conditions supported efficient axonal growth, as MB neurons from cultured brains grew similarly to their counterparts developing inside the pupa. Fast confocal imaging of axon bundles revealed that GFP-Imp fusions accumulated in particles undergoing bidirectional movement. In contrast, no particles could be detected upon expression of GFP alone. Motile GFP-Imp particles were distributed into three classes: particles with a strong net anterograde (56%) or retrograde (36%) movement and particles with little net bias (8%). Individually tracked particle trajectories were broken into segments to calculate velocities. Segmental velocities distributed over a wide range, with mean anterograde and retrograde segmental velocities of 0.98 ± 0.05 microm/s and 0.73 ± 0.03 microm/s, respectively. Furthermore, curves matching the graph of a quadratic function were obtained upon plotting of the mean square displacement (MSD) values over time, indicating that GFP-Imp particles undergo directed transport rather than diffusion. To assess the role of microtubules (MTs) in this process, brains were treated with colchicine. This treatment abolished MT dynamics, as revealed by the loss of EB1-GFP comets characteristic of growing MT plus ends. Strikingly, motile GFP-Imp particles were no longer observed under these conditions. These results demonstrate that Imp is a component of particles undergoing active MT-dependent transport during midpupariation, consistent with a role of Imp in the transport of selected mRNAs to regrowing γ axons (Medroni, 2014).

Previous in vitro studies have revealed that the axons of immature neurons are enriched in mRNAs encoding regulators of the actin cytoskeleton that play critical roles in axonal growth and guidance. To identify Imp mRNA targets, an immunoprecipitation RT-PCR-based screen was performed for mRNAs encoding actin regulators. Imp was found to selectively associate with chickadee (chic) mRNA, which encodes the G-actin binding protein Profilin. As revealed by affinity pull-down assays, endogenous Imp associated with the chic 3' untranslated region (UTR), but not with the chic coding sequence. To test whether Imp can interact with chic mRNA directly, the binding of recombinant MBP-Imp to the chic 3' UTR was analyzed in electrophoretic mobility shift assays. Retarded complexes formed in the presence of the chic 3' UTR, but not in the presence of a nonrelated RNA (y14). Furthermore, no significant interaction was observed when other MBP-tagged proteins were used. Notably, two discrete complexes were detected in the presence of low amounts of Imp, whereas higher-order complexes were formed with increasing amounts of Imp. Formation of these complexes was outcompeted by the addition of nonlabeled RNAs corresponding to the chic 3' UTR, but not to the chic coding sequence. Altogether, these results show that Imp associates with chic mRNA in vivo and that it can bind directly and specifically to the chic 3' UTR (Medroni, 2014).

To test whether chic mRNA localizes to the neurites of regrowing γ neurons, in situ hybridization was performed on pupal and adult brains. The poor signal-to-noise ratio obtained with this method at these stages, combined with the relatively low levels of axonally localized mRNAs, did not allow chic transcripts or reporters to be unambiguously detected in axons. Thus chic reporter constructs expressed under the control of the γ-specific 201Y-Gal4 driver was used and fluorescent in situ hybridizations was used on dissociated neurons extracted from 24 hr APF pupae and cultured for 3-4 days. chic reporter mRNAs could be observed in the neurites of γ neurons at a significantly higher frequency than control gfp mRNAs. Furthermore, chic mRNA and Imp colocalized in developing neurites, consistent with their association within mRNA transport complexes (Medroni, 2014).

To test whether the region of chic bound by Imp is required for chic mRNA localization to developing neurites, the distribution of reporters containing both the chic coding sequence and 3' UTR was compared with that of reporters lacking the chic 3' UTR. Transcripts with the chic 3' UTR localized more efficiently than transcripts lacking it, suggesting that Imp binding to the 3' UTR promotes chic axonal targeting. To exclude an effect of Imp on chic mRNA stability, the levels of chic transcripts were analyzed in cultured S2R+ cells. No significant differences in chic mRNA and Chic protein levels could be observed upon imp inactivation in these conditions (Medroni, 2014).

To functionally test the importance of chic regulation in vivo, the phenotypes associated with chic downregulation were examined. Consistent with described roles of Profilin in regulating F-actin polymerization and axonal pathfinding, it was observed that chic mutant γ neurons fail to properly extend their axons. More importantly, overexpression of chic significantly rescued the axonal growth defects observed in imp mutant neurons. Similar results were obtained with two independent UAS-chic transgenes, but not with overexpression of another regulator of F-actin polymerization (enabled). These results suggest that imp controls axonal remodeling by regulating chic expression in vivo and reveal that forced accumulation of Chic protein in axons can partially compensate for the loss of imp function (Medroni, 2014).

In conclusion, the finding that Drosophila Imp is required for γ axon regrowth but is dispensable for initial axonal growth suggests a novel and specific function of axonal mRNA targeting in developmental remodeling of the brain. Furthermore, these results highlight mechanistic similarities between developmental axonal regrowth and postinjury axonal regeneration, a process known to depend on axonal mRNA transport. Finally, this study uncovers that the translocation of Imp to γ axons is tightly linked to their developmental remodeling program. This reveals that mRNA transport machineries are subject to precise spatiotemporal regulation and may be specifically recruited in the context of developmental rewiring of the brain. It will now be interesting to identify the signals controlling the localization and the activity of mRNA transport machineries during this process (Medroni, 2014).

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Drosophila Hrp48 is required for mushroom body axon growth, branching and guidance

Bruckert, H., Marchetti, G., Ramialison, M. and Besse, F. (2015). PLoS One 10: e0136610. PubMed ID: 26313745

RNA binding proteins assemble on mRNAs to control every single step of their life cycle, from nuclear splicing to cytoplasmic localization, stabilization or translation. This study investigated the role of Drosophila Hrp48, a fly homologue of mammalian hnRNP A2/B1, during central nervous system development. Using a combination of mutant conditions, hrp48 was shown to be required for the formation, growth and guidance of axonal branches in Mushroom Body neurons. Furthermore, hrp48 inactivation induces an overextension of Mushroom Body dorsal axonal branches, with a significantly higher penetrance in females than in males. Finally, as demonstrated by immunolocalization studies, Hrp48 is confined to Mushroom Body neuron cell bodies, where it accumulates in the cytoplasm from larval stages to adulthood. Altogether, these data provide evidence for a crucial in vivo role of the hnRNP Hrp48 in multiple aspects of axon guidance and branching during nervous system development. They also indicate cryptic sex differences in the development of sexually non-dimorphic neuronal structures (Bruckert, 2015).

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The formin DAAM functions as molecular effector of the planar cell polarity pathway during axonal development in Drosophila

Gombos, R., Migh, E., Antal, O., Mukherjee, A., Jenny, A. and Mihaly, J. (2015). J Neurosci 35: 10154-10167. PubMed ID: 26180192

Recent studies established that the planar cell polarity (PCP) pathway is critical for various aspects of nervous system development and function, including axonal guidance. Although it seems clear that PCP signaling regulates actin dynamics, the mechanisms through which this occurs remain elusive. This study established a functional link between the PCP system and one specific actin regulator, the formin DAAM, which has previously been shown to be required for embryonic axonal morphogenesis and filopodia formation in the growth cone. DAAM also plays a pivotal role during axonal growth and guidance in the adult Drosophila mushroom body, a brain center for learning and memory. By using a combination of genetic and biochemical assays, it was demonstrated that Wnt5 and the PCP signaling proteins Frizzled, Strabismus, and Dishevelled act in concert with the small GTPase Rac1 to activate the actin assembly functions of DAAM essential for correct targeting of mushroom body axons. Collectively, these data suggest that DAAM is used as a major molecular effector of the PCP guidance pathway. By uncovering a signaling system from the Wnt5 guidance cue to an actin assembly factor, it is proposed that the Wnt5/PCP navigation system is linked by DAAM to the regulation of the growth cone actin cytoskeleton, and thereby growth cone behavior, in a direct way (Gombos, 2015).

This study has shown that DAAM plays an important role in the regulation of axonal growth and guidance of the Drosophila MB neurons. Several lines of evidence suggest that DAAM acts in concert with Wnt5 and the core PCP proteins to ensure correct targeting of the KC axons. DAAM functions downstream of Dsh and Rac1, and its ability to promote actin assembly is absolutely required for neural development in the MB. These data suggest a simple model in which axon guidance cues, such as Wnt5, signal through the PCP pathway to activate DAAM to control actin filament formation in the neuronal growth cone. Thus, PCP signaling appears to be linked to cytoskeleton regulation in a direct way, and these results provide compelling experimental evidence suggesting that, at least in neuronal cells, the major cellular target of PCP signaling is the actin cytoskeleton (Gombos, 2015).

Formins are highly potent actin assembly factors that are under tight regulation in vivo. The major mechanism of controlling the activity of the Diaphanous-related formin (DRF) subfamily involves an intramolecular autoinhibitory interaction between the N-terminal diaphanous inhibitory domain (DID) and the C-terminal Diaphanous autoinhibitory domain (DAD). This inhibition can be relieved upon binding of an activated Rho family GTPase that interacts with the GBD (GTP-ase binding domain)/DID region and also by proteins that bind to the DAD domain. Consistently, this study found that the Rac1 GTPase and the DAD domain binding Dsh protein both play role in DAAM activation in MB neurons. With this regard, it is notable that, despite that dsh1 is considered a PCP-null allele, the DAAMEx1, dsh1 double hemizygous mutants exhibit a stronger MB phenotype than dsh1 mutants alone, suggesting that DAAM must receive Dsh-independent regulatory inputs for which Rac1 is a prime candidate. Although previous work indicated that Rho GTPases might function downstream of Dsh in a linear pathway), the data suggest that Dsh and Rac1 act in parallel pathways in the MB. As the impairment of GTPase binding severely, but not completely, abolishes DAAM activity, it is concluded that Rac1 is likely to have a stronger contribution to DAAM activation in vivo; nonetheless, the simultaneous binding of Dsh appears to be required for full activation (Gombos, 2015).

Presumably, the most remarkable feature of the PCP system relies in its ability to create subcellular asymmetries. Therefore, it is a tempting idea that, upon guidance signaling, the PCP proteins are involved in the generation of molecular asymmetries within axonal growth cones, yet recent attempts failed to reveal such polarized distributions in MB neurons. Interestingly, however, it was shown that Fz and Vang display a differential requirement during development of the MBs, with Fz predominantly acting in the dorsal lobes and Vang predominantly acting in the medial lobes (MLs). This study found that, in contrast to Fz and Vang, DAAM plays a crucial role in both lobes of the MBs. Additionally, it was demonstrated that Fz promotes the formation of membrane-associated Dsh-DAAM complexes in S2 cells. This result, together with genetic data, suggests that DAAM acts as the downstream effector of a Fz/Dsh module, which is required for the correct growth and guidance of the dorsal MB axon branches (Gombos, 2015).

In addition to their potential connection to Fz signaling in the dorsal lobe, DAAM and Dsh were linked to Vang- and Wnt5-dependent ML development as well. Wnt5 and Vang have an identical effect on ML development when overexpressed, and this GOF phenotype can be suppressed by the same set of mutations (DAAM, dsh, Rac1). In particular, the putative PCP-null dsh1 allele and heterozygosity for Rac1 cause an almost equally strong, yet partial, suppression with regard to the ML fusion phenotype. This is best explained by assuming that Wnt5 and Vang signal both in a Dsh-dependent and in a Dsh-independent, but Rac-dependent, manner. With regard to DAAM, this study has shown that DAAM nearly completely suppresses the GOF of Wnt5 and Vang, and Dsh and Rac1 both contribute to DAAM activation. Collectively, these data suggest a model in which Wnt5 and Vang promote β lobe extension by signaling to Dsh and Rac1 that will activate DAAM in parallel to each other. The colocalization of Vang and DAAM, observed in S2 cells, indicates that they may bind each other directly, which would be in good accordance with genetic data suggesting a close functional link between DAAM and Vang during β lobe development. However, formins are not known to bind Vang proteins; therefore, an indirect interaction, mediated by Rac1, which has recently been shown to be bound and redistributed by Vangl2 in epithelial cell lines, appears a more likely possibility (Gombos, 2015).

As discussed above, and contrary to Vang, Fz does not appear to be required for ML development, or if anything, it might play an opposite role, as loss of fz leads to ML fusion in 16.1% of the lobes. This is a surprising observation at first glance as Wnt proteins are thought to activate members of the Fz receptor family, but former analysis of Wnt5 signaling during MB development also failed to reveal a Fz requirement in the β lobes. Instead, Wnt5 has been linked to other type of Wnt receptors, the Ryk/Derailed atypical tyrosine kinase receptors, which are known to be involved in axonal guidance in flies and vertebrates. In light of these results, it will be of future interest to analyze the Wnt5-Vang connection in the MB in more details and identify the Wnt5 receptor in this context (Gombos, 2015).

Consistent with the lack of lobe-specific requirement for dsh and DAAM, the current studies revealed that Dsh, DAAM, and Rac1 are used as common effector elements of a dorsal lobe-specific Fz-dependent signal and a Vang-dependent ML-specific signal. It follows that Dsh and DAAM are likely to take part in two types of PCP complexes. Although, in vitro, Dsh has the ability to interact with both Fz and Vang, the conclusion that Dsh functions downstream of Vang in the β lobes is markedly different from the classical PCP regulatory context in which the Fz/Dsh and Vang/Pk complexes have opposing effects. Thus, this result, together with the Wnt5-Vang data, substantiates the earlier findings that the PCP system operates at least partly differently in neurons than during tissue polarity signaling (Gombos, 2015).

During PCP signaling, the vertebrate DAAM orthologs control convergence and extension movements, polarized cell movements during vertebrate gastrulatio. In contrast, DAAM is dispensable for classical planar polarity establishment in flies, suggesting that the tissue polarity function of DAAM might be restricted only to vertebrates. Despite the lack of direct function in establishing tissue polarization, this study provides evidence that DAAM is linked to the PCP pathway in another important regulatory context, notably directed neuronal development in the adult brain. Consistent with the results, recent studies revealed that PCP signaling and DAAM regulate neural development in planarians and in Xenopus embryos. Given that the vertebrate PCP proteins are known to be involved in multiple aspects of CNS development, and the vertebrate DAAM orthologs are strongly expressed in the CNS, it is conceivable that the PCP/DAAM module represents a highly conserved regulatory system that is used to regulate various aspects of neuronal development throughout evolution (Gombos, 2015).

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Genetic dissection of aversive associative olfactory learning and memory in Drosophila larvae

Widmann, A., Artinger, M., Biesinger, L., Boepple, K., Peters, C., Schlechter, J., Selcho, M. and Thum, A. S. (2016). PLoS Genet 12: e1006378. PubMed ID: 27768692

Genetic dissection of aversive associative olfactory learning and memory in Drosophila larvae

Memory formation is a highly complex and dynamic process. It consists of different phases, which depend on various neuronal and molecular mechanisms. In adult Drosophila it was shown that memory formation after aversive Pavlovian conditioning includes-besides other forms-a labile short-term component that consolidates within hours to a longer-lasting memory. Accordingly, memory formation requires the timely controlled action of different neuronal circuits, neurotransmitters, neuromodulators and molecules that were initially identified by classical forward genetic approaches. Compared to adult Drosophila, memory formation was only sporadically analyzed at its larval stage. This study deconstructed the larval mnemonic organization after aversive olfactory conditioning. After odor-high salt conditioning (establishing an aversive olfactory memory) larvae form two parallel memory phases; a short lasting component that depends on cyclic adenosine 3'5'-monophosphate (cAMP) signaling and synapsin gene function. In addition, this study shows for the first time for Drosophila larvae an anesthesia resistant component, which relies on radish and bruchpilot gene function, protein kinase C (PKC) activity, requires presynaptic output of mushroom body Kenyon cells and dopamine function. Given the numerical simplicity of the larval nervous system this work offers a unique prospect for studying memory formation of defined specifications, at full-brain scope with single-cell, and single-synapse resolution (Widmann, 2016).

Memory formation and consolidation usually describes a chronological order, parallel existence or completion of distinct short-, intermediate- and/or long-lasting memory phases. For example, in honeybees, in Aplysia, and also in mammals two longer-lasting memory phases can be distinguished based on their dependence on de novo protein synthesis. In adult Drosophila classical odor-electric shock conditioning establishes two co-existing and interacting forms of memory--ARM and LTM--that are encoded by separate molecular pathways (Widmann, 2016).

Seen in this light, memory formation in Drosophila larvae established via classical odor-high salt conditioning seems to follow a similar logic. It consist of LSTM (larval short lasting component) and LARM (anesthesia resistant memory). Aversive olfactory LSTM was already described in two larval studies using different negative reinforcers (electric shock and quinine) and different training protocols (differential and absolute conditioning). The current results introduce for the first time LARM that was also evident directly after conditioning but lasts longer than LSTM. LARM was established following different training protocols that varied in the number of applied training cycles and the type of negative or appetitive reinforcer. Thus, LSTM and LARM likely constitute general aspects of memory formation in Drosophila larvae that are separated on the molecular level (Widmann, 2016).

Memory formation depends on the action of distinct molecular pathways that strengthen or weaken synaptic contacts of defined sets of neurons. The cAMP/PKA pathway is conserved throughout the animal kingdom and plays a key role in regulating synaptic plasticity. Amongst other examples it was shown to be crucial for sensitization and synaptic facilitation in Aplysia, associative olfactory learning in adult Drosophila and honeybees, long-term associative memory and long-term potentiation in mammals (Widmann, 2016).

For Drosophila larvae two studies by Honjo (2005) and Khurana (2009) suggest that aversive LSTM depends on intact cAMP signaling. In detail, they showed an impaired memory for rut and dnc mutants following absolute odor-bitter quinine conditioning and following differential odor-electric shock conditioning. Thus, both studies support the interpretation of the current results. It is argued that odor-high salt training established a cAMP dependent LSTM due to the observed phenotypes of rut, dnc and syn mutant larvae. The current molecular model is summarized in A molecular working hypothesis for LARM formation. Yet, it has to be mentioned that all studies on aversive LSTM in Drosophila larvae did not clearly distinguish between the acquisition, consolidation and retrieval of memory. Thus, future work has to relate the observed genetic functions to these specific processes (Widmann, 2016).

In contrast, LARM formation utilizes a different molecular pathway. Based on different experiments, it was ascertained, that LARM formation, consolidation and retrieval is independent of cAMP signaling itself, PKA function, upstream and downstream targets of PKA, and de-novo protein synthesis. Instead it was found that LARM formation, consolidation and/or retrieval depends on radish (rsh) gene function, brp gene function, dopaminergic signaling and requires presynaptic signaling of MB KCs (Widmann, 2016).

Interestingly, studies on adult Drosophila show that rsh and brp gene function, as well as dopaminergic signaling and presynaptic MB KC output are also necessary for adult ARM formation. Thus, although a direct comparison of larval and adult ARM is somehow limited due to several variables (differences in CS, US, training protocols, test intervals, developmental stages, and coexisting memories), both forms share some genetic aspects. This is remarkable as adult ARM and LARM use different neuronal substrates. The larval MB is completely reconstructed during metamorphosis and the initial formation of adult ARM requires a set of MB α/β KCs that is born after larval life during puparium formation (Widmann, 2016).

In addition, this study has demonstrated the necessity of PKC signaling for LARM formation in MB KCs. The involvement of the PKC pathway for memory formation is also conserved throughout the animal kingdom. For example, it has been shown that PKC signaling is an integral component in memory formation in Aplysia, long-term potentiation and contextual fear conditioning in mammals and associative learning in honeybees. In Drosophila it was shown that PKC induced phosphorylation cascade is involved in LTM as well as in ARM formation. Although the exact signaling cascade involved in ARM formation in Drosophila still remains unclear, this study has established a working hypothesis for the underlying genetic pathway forming LARM based on the current findings and on prior studies in different model organisms. Thereby this study does not take into account findings in adult Drosophila. These studies showed that PKA mutants have increased ARM and that dnc sensitive cAMP signaling supports ARM. Thus both studies directly link PKA signaling with ARM formation. (Widmann, 2016).

KCs have been shown to act on MB output neurons to trigger a conditioned response after training. Work from different insects suggests that the presynaptic output of an odor activated KCs is strengthened if it receives at the same time a dopaminergic, punishment representing signal. The current results support these models as they show that LARM formation requires accurate dopaminergic signaling and presynaptic output of MB KCs. Yet, for LARM formation dopamine receptor function seems to be linked with PKC pathway activation. Indeed, in honeybees, adult Drosophila and vertebrates it was shown that dopamine receptors can be coupled to Gαq proteins and activate the PKC pathway via PLC and IP3/DAG signaling. As potential downstream targets of PKC radish and bruchpilot are suggested. Interference with the function of both genes impairs LARM. The radish gene encodes a functionally unknown protein that has many potential phosphorylation sites for PKA and PKC. Thus considerable intersection between the proteins Rsh and PKC signaling pathway can be forecasted. Whether this is also the case for the bruchpilot gene that encodes for a member of the active zone complex remains unknown. The detailed analysis of the molecular interactions has to be a focus of future approaches. Therefore, the current working hypothesis can be used to define educated guesses. For instance, it is not clear how the coincidence of the odor stimulus and the punishing stimulus are encoded molecularly. The same is true for ARM formation in adult Drosophila. Based on the working hypothesis it can be speculated that PKC may directly serve as a coincidence detector via a US dependent DAG signal and CS dependent Ca2+ activation (Widmann, 2016).

Do the current findings in general apply to learning and memory in Drosophila larvae? To this the most comprehensive set of data can be found on sugar reward learning. Drosophila larva are able to form positive associations between an odor and a number of sugars that differ in their nutritional value. Using high concentrations of fructose as a reinforcer in a three cycle differential training paradigm (comparable to the one used in this study for high salt learning and fructose learning) other studies found that learning and/or memory in syn97 mutant larvae is reduced to ~50% of wild type levels. Thus, half of the memory seen directly after conditioning seems to depend on the cAMP-PKA-synapsin pathway. The current results in turn suggest that the residual memory seen in syn97 mutant larvae is likely LARM. Thus, aversive and appetitive olfactory learning and memory share general molecular aspects. Yet, the precise ratio of the cAMP-dependent and independent components rely on the specificities of the used odor-reinforcer pairings. Two additional findings support this conclusion. First, a recent study has shown that memory scores in syn97 mutant larvae are only lower than in wild type animals when more salient, higher concentrations of odor or fructose reward are used. Usage of low odor or sugar concentrations does not give rise to a cAMP-PKA-synapsin dependent learning and memory phenotype. Second, another study showed that learning and/or memory following absolute one cycle conditioning using sucrose sugar reward is completely impaired in rut1, rut2080 and dnc1 mutants. Thus, for this particular odor-reinforcer pairing only the cAMP pathway seems to be important. Therefore, a basic understanding of the molecular pathways involved in larval memory formation is emerging. Further studies, however, will be necessary in order to understand how Drosophila larvae make use of the different molecular pathways with respect to a specific CS/US pairing (Widmann, 2016).

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Different Kenyon cell populations drive learned approach and avoidance in Drosophila

Perisse, E., Yin, Y., Lin, A. C., Lin, S., Huetteroth, W. and Waddell, S. (2013). Neuron 79: 945-956. PubMed ID: 24012007

In Drosophila, anatomically discrete dopamine neurons that innervate distinct zones of the mushroom body (MB) assign opposing valence to odors during olfactory learning. Subsets of MB neurons have temporally unique roles in memory processing, but valence-related organization has not been demonstrated. This study functionally subdivided the αβ neurons, revealing a value-specific role for the approximately 160 αβ core (αβc) neurons. Blocking neurotransmission from αβ surface (αβs) neurons revealed a requirement during retrieval of aversive and appetitive memory, whereas blocking αβc only impaired appetitive memory. The αβc were also required to express memory in a differential aversive paradigm demonstrating a role in relative valuation and approach behavior. Strikingly, both reinforcing dopamine neurons and efferent pathways differentially innervate αβc and αβs in the MB lobes. It is proposed that conditioned approach requires pooling synaptic outputs from across the αβ ensemble but only from the αβs for conditioned aversion (Perisse, 2013).

Olfactory memories are believed to be represented within the ~2,000 intrinsic Kenyon cells (KCs) of the Drosophila mushroom body (MB). Individual odors activate relatively sparse populations of KCs within the overall MB ensemble providing cellular specificity to odor memories. Prior research of fly memory suggests that the KCs can be functionally split into at least three major subdivisions: the αβ, α′β′, and γ neurons (see Anatomical organization of the olfactory nervous system in Drosophila from Davis, R. Traces of Drosophila Memory, Neuron 70: 8-19, 2011). The current consensus suggests a role for γ in short-term memory, for α′β′ after training for memory consolidation, and for αβ in later memory retrieval, with the αβ requirement becoming more pronounced as time passes. Importantly, odor-evoked activity is observable in each of these cell types, consistent with a parallel representation of olfactory stimuli across the different KC classes (Perisse, 2013).

Value is assigned to odors during training by anatomically distinct dopaminergic (DA) neurons that innervate unique zones of the MB. Negative value is conveyed to MB γ neurons in the heel and junction and to αβ neurons at the base of the peduncle and the tip of the β lobe. In contrast, a much larger number of rewarding DA neurons project to approximately seven nonoverlapping zones in the horizontal β, β′, and γ lobes. This clear zonal architecture of reinforcing neurons suggests that plastic valence-relevant KC synapses may lie adjacent to these reinforcing neurons. Furthermore, presumed downstream MB efferent neurons also have dendrites restricted to discrete zones on the MB lobes, consistent with memories being formed at KC-output neuron synapses (Perisse, 2013).

Long before the zonal DA neuron innervation of the MB was fully appreciated, experiments suggested that appetitive and aversive memories were independently processed and stored. Subsequently, models were proposed that represented memories of opposite valence at distinct output synapses on the same odor-activated KCs or on separate KCs. Importantly, memory retrieval through these modified KC-output synapses was predicted to guide either odor avoidance or approach behavior. A KC synapse-specific representation of memories of opposing valence would dictate that it is not possible to functionally separate the retrieval of aversive and appetitive memories by disrupting KC-wide processes. This study therefore tested these models by systematically blocking neurotransmission from subsets of the retrieval-relevant αβ neurons. It was found that aversive and appetitive memories can be distinguished in the αβ KC population, showing that opposing odor memories do not exclusively rely on overlapping KCs. Whereas output from the αβs neurons is required for aversive and appetitive memory retrieval, the αβ core (αβc) neurons are only critical for conditioned approach behavior. Higher-resolution anatomical analysis of the innervation of reinforcing DA neurons suggests that valence-specific asymmetry may be established during training. Furthermore, dendrites of KC-output neurons differentially innervate the MB in a similarly stratified manner. It is therefore proposed that aversive memories are retrieved and avoidance behavior triggered only from the αβ surface (αβs) neurons, whereas appetitive memories are retrieved and approach behavior is driven by efferent neurons that integrate across the αβ ensemble (Perisse, 2013).

When faced with a choice, animals must select the appropriate behavioral response. Learning provides animals the predictive benefit of prior experience and allows researchers to influence behavioral outcomes. After olfactory learning, fruit flies are provided with a simple binary choice in the T-maze. Aversively trained flies preferentially avoid the conditioned odor, whereas appetitively conditioned flies approach it. A major goal of the field is to understand the neural mechanisms through which the fly selects the appropriate direction (Perisse, 2013).

In mammals, mitral cells take olfactory information direct from the olfactory bulb to the amygdala and the perirhinal, entorhinal, and piriform cortices. In doing so, odor information is segregated into different streams, allowing it to be associated with other modalities and emotionally salient events. In contrast, most olfactory projection neurons in the fly innervate the MB calyx and lateral horn or only the lateral horn. The lateral horn has mostly been ascribed the role of mediating innate responses to odors, leaving the MB to fulfill the potential roles of the mammalian cortices (Perisse, 2013).

Although morphological and functional subdivision of the αβ, α′β′, and γ classes of MB neuron has been reported, until now a valence-restricted role has been elusive. This study investigated the functional correlates of substructure within the αβ population. An appetitive memory-specific role was identified for the αβc neurons. Whereas blocking output from the αβs neurons impaired aversive and appetitive memory retrieval, blocking αβc neurons produced only an appetitive memory defect. These behavioral results, taken with functional imaging of odor-evoked activity, suggest that beyond the αβ, α′β′, and γ subdivision, odors are represented as separate streams in subsets of MB αβ neurons. These parallel information streams within αβ permit opposing value to be differentially assigned to the same odor. Training therefore tunes the odor-activated αβc and αβs KCs so that distinct populations differentially drive downstream circuits to generate aversive or appetitive behaviors. Such a dynamic interaction between appetitive and aversive circuits that is altered by learning is reminiscent of that described between the primate amygdala and orbitofrontal cortex. It will be important to determine the physiological consequences of appetitive and aversive conditioning on the αβc and αβs neurons. Positively and negatively reinforced olfactory learning in rats produced bidirectional plasticity of neurons in the basolateral amygdala (Perisse, 2013).

The αβp neurons, which do not receive direct olfactory input from projection neurons in the calyx, are dispensable for aversive and appetitive 3 hr memory and for 24 hr appetitive memory. The αβp neurons were reported to be structurally linked to dorsal anterior lateral (DAL) neurons and both DAL and αβp neurons were shown to be required for long-term aversive memory retrieval. This study found that, like αβp neurons, DAL neurons are not required for appetitive long-term memory retrieval. In addition, the αβp neurons were inhibited by odor exposure, which may reflect cross-modal inhibition within the KC population (Perisse, 2013).

Observing a role for the αβc neurons in the relative aversive paradigm argues against the different requirement for αβc neurons in the routine shock-reinforced aversive and sugar-reinforced appetitive assays being due to different timescales of memory processing. In addition, a pronounced role was observed for αβc neurons in retrieval of 24 hr appetitive LTM, whereas others have reported that αβc neurons are not required for the retrieval of 24 hr aversive LTM . Nevertheless, time and the methods of conditioning may be important variables. Although appetitive and aversive memory retrieval requires output from the αβ ensemble at 3 hr and 24 hr after conditioning, αβ neurons were shown to be dispensable for 2 hr appetitive memory retrieval. Instead, appetitive retrieval required γ neuron output at this earlier point. The current experiments were generally supportive of the γ-then-αβ neuron model but revealed a slightly different temporal relationship. The αβ neurons were dispensable for memory retrieved 30 min after training but were essential for 2 hr and 3 hr memory after training. An early role for γ neurons is further supported by the importance of reinforcing DA input to the γ neurons for aversive memory formation. It will be interesting to determine whether there is a stratified representation of valence within the γ neuron population (Perisse, 2013).

Finding an appetitive memory-specific role for αβc neurons suggests that the simplest model in which each odor-activated KC has plastic output synapses driving either approach or avoidance appears incorrect. Such a KC output synapse-specific organization dictates that it would not be possible to functionally segregate aversive and appetitive memory by blocking KC-wide output. This study however found a specific role for the αβc neurons in conditioned approach that supports the alternative model of partially nonoverlapping KC representations of aversive and appetitive memories. The anatomy of the presynaptic terminals of reinforcing DA neurons in the MB lobes suggests that the functional asymmetry in αβ could be established during training in which αβc only receive appetitive reinforcement. Rewarding DA neurons that innervate the β lobe tip ramify throughout the βs and βc, whereas aversive reinforcing DA neurons appear restricted to the αβs. Consistent with this organization of memory formation, aversive MB-V2α output neurons have dendrites biased toward αs, whereas the dendrites of aversive or appetitive MB-V3 output neurons are broadly distributed throughout the α lobe tip. Therefore, a model is proposed that learned odor aversion is driven by αβs neurons, whereas learned approach comes from pooling inputs from the αβs and αβc neurons (Perisse, 2013).

Another property that distinguishes appetitive from aversive memory retrieval is state dependence; flies only efficiently express appetitive memory if they are hungry. Prior work has shown that the dopaminergic MB-MP1 neurons are also critical for this level of control. Since the MB-MP1 neurons more densely innervate the αβs than αβc, it would seem that satiety state differentially tunes the respective drive from parts of the αβ ensemble to promote or inhibit appetitive memory retrieval (Perisse, 2013).

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Convergence of multimodal sensory pathways to the mushroom body calyx in Drosophila melanogaster

Yagi, R., Mabuchi, Y., Mizunami, M. and Tanaka, N. K. (2016). Sci Rep 6: 29481. PubMed ID: 27404960

Detailed structural analyses of the mushroom body which plays critical roles in olfactory learning and memory revealed that it is directly connected with multiple primary sensory centers in Drosophila, for example the γ lobe neurons innervating the ventral accessory calyces respond to visual stimuli, the antennal lobe tracts neuron terminating in the lateral accessory calyces shows calcium responses to temperature shifts, and taste activity has been observed in the dorsal accessory calyces. Connectivity patterns between the mushroom body and primary sensory centers suggest that each mushroom body lobe processes information on different combinations of multiple sensory modalities. This finding provides a novel focus of research by Drosophila genetics for perception of the external world by integrating multisensory signals (Yagi, 2016).

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Octopamine and Dopamine differentially modulate the nicotine-induced calcium response in Drosophila Mushroom Body Kenyon Cells

Leyton, V., Goles, N. I., Fuenzalida-Uribe, N. and Campusano, J. M. (2013). Neurosci Lett 560: 16-20. PubMed ID: 24334164

In Drosophila associative olfactory learning, an odor, the conditioned stimulus (CS), is paired to an unconditioned stimulus (US). The CS and US information arrive at the Mushroom Bodies (MB), a Drosophila brain region that processes the information to generate new memories. It has been shown that olfactory information is conveyed through cholinergic inputs that activate nicotinic acetylcholine receptors (nAChRs) in the MB, while the US is coded by biogenic amine (BA) systems that innervate the MB. In this regard, the MB acts as a coincidence detector. A better understanding of the properties of the responses gated by nicotinic and BA receptors are required to get insights on the cellular and molecular mechanisms responsible for memory formation. In recent years, information has become available on the properties of the responses induced by nAChR activation in Kenyon Cells (KCs), the main neuronal MB population. However, very little information exists on the responses induced by aminergic systems in fly MB. This study evaluated some of the properties of the calcium responses gated by Dopamine (DA) and Octopamine (Oct) in identified KCs in culture. Exposure to BAs induces a fast but rather modest increase in intracellular calcium levels in cultured KCs. The responses to Oct and DA are fully blocked by a Voltage-gated Calcium Channel (VGCC) blocker, while they are differentially modulated by cAMP. Moreover, co-application of BAs and nicotine has different effects on intracellular calcium levels: while DA and nicotine effects are additive, Oct and nicotine induce a synergistic increase in calcium levels. These results suggest that a differential modulation of nicotine-induced calcium increase by DA and Oct could contribute to the events leading to learning and memory in flies (Leyton, 2013).

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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 [Epub ahead of print]. 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, 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. 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. 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. 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, 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).

Two DA receptors that share homology to vertebrate DA type 1 receptors are expressed in Drosophila MB, DAMB (Dopamine 1-like receptor 2 or Dop1R2) and dDA1/DmDOP1/DopR. These receptors have been cloned and expressed in heterologous systems, where they are positively coupled to AC. Moreover, these receptors participate in the generation or modification of new olfactory memories in MB. The third cloned DA receptor, Dop2R/D2R, is not expressed in Drosophila MB. The current results are consistent with the general idea that DA receptors modulate intracellular cAMP levels, which could lead to the modification of the activity of VGCCs in KCs. The EC50 describe in this study is in agreement with previous studies in heterologous systems, which report EC50 in the range of 300-500 nM for both DA type 1 receptors. Thus, it is very likely that DAMB and/or dDA1/DmDOP1 are contributing to the DA-induced calcium response in Drosophila KCs. It would be expected that DA receptors increase cAMP levels to activate calcium currents in fly MB KCs. However, data using SQ22536 suggest that cAMP inhibits calcium fluxes in KCs. Although the cellular mechanisms responsible for this effect are not evident, it has been previously shown that increased cAMP signaling negatively modulates the activity of VGCCs through the activation of specific phosphatases in the vertebrate Nucleus Accumbens. Remarkably, the Nucleus Accumbens and MB are brain regions highly associated to the plastic behavioral effects induced by addictive drugs. Thus, it would not be particularly surprising to find similarities in the mechanisms responsible for the modulation of neuronal communication and excitability byDA in these two brain structures, as previously suggested.On the other hand, several Oct receptors have been previously cloned in Drosophila: one Oct receptor with high sequence homology to vertebrate -type receptors (Oct1R/OAMB) is expressed in dendrites and axons of the MB, and is the main candidate for the calcium responses induced by Oct in KCs, since the other cloned Oct receptors are not expressed in MB. In agreement with this, the calculated EC50, and the description that the response depends on VGCC activation and is independent on cAMP, further support this suggestion (Leyton, 2013).

An interaction of the neural systems responsible for CS and US stimuli in the MB region could mediate the generation of new memories. This interaction could occur at the presynaptic level, for instance, through the nAChR modulation of aminergic innervation to the MB region. However, the most accepted idea is that cholinergic and aminergic receptors expressed in MB KCs gate intracellular cascades that could cross-talk to modify the activity of KCs, a cellular event that could underlie long-lasting changes responsible for the generation of new olfactory memories in the fly (Leyton, 2013).

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An octopamine-mushroom body circuit modulates the formation of anesthesia-resistant memory in Drosophila

Wu, C. L., Shih, M. F., Lee, P. T. and Chiang, A. S. (2013). Curr Biol 23(23): 2346-54. PubMed ID: 24239122

Drosophila olfactory aversive conditioning produces two components of intermediate-term memory: anesthesia-sensitive memory (ASM) and anesthesia-resistant memory (ARM). Recently, the anterior paired lateral (APL) neuron innervating the whole mushroom body (MB) has been shown to modulate ASM via gap-junctional communication in olfactory conditioning. Octopamine (OA), an invertebrate analog of norepinephrine, is involved in appetitive conditioning, but its role in aversive memory remains uncertain. This study shows that chemical neurotransmission from the anterior paired lateral (APL) neuron, after conditioning but before testing, is necessary for aversive ARM formation. The APL neurons are tyramine, Tβh, and OA immunopositive. An adult-stage-specific RNAi knockdown of Tβh in the APL neurons or Octβ2R OA receptors in the MB α'β' Kenyon cells (KCs) impaired ARM. Importantly, an additive ARM deficit occurred when Tβh knockdown in the APL neurons was in the radish mutant flies or in the wild-type flies with inhibited serotonin synthesis. It is concluded that OA released from the APL neurons acts on α'β' KCs via Octβ2R receptor to modulate Drosophila ARM formation. Additive effects suggest that two parallel ARM pathways, serotoninergic DPM-αβ KCs and octopaminergic APL-α'β' KCs, exist in the MB (Wu, 2013).

The key finding of this study is that OA from the single APL neuron innervating the entire MB is required specifically for ARM formation in aversive olfactory conditioning in Drosophila. This conclusion is supported by five independent lines of evidence. First, blocking neurotransmission from APL neurons after training, but before testing, impaired ARM. Second, the APL neurons are tyramine, Tβh, and OA antibody immunopositive. Third, adult-stage-specific reduction of Tβh levels in the APL neurons, but not in dTdc2-GAL4 neurons that do not include the APL neurons, specifically abolishes ARM without affecting learning or ASM. Fourth, Octβ2R is expressed preferentially in the α'β' lobes, and adult-stage-specific reduction of Octβ2R expression in the α'β' KCs impaired ARM. Fifth, the additive memory impairments demonstrated in flies subjected to Tβh plus inx7 knockdowns and Tβh knockdown plus cold shock, but not inx7 knockdown plus cold shock, confirm that a single APL neuron modulates both ASM and ARM through gap-junctional communication and OA neurotransmission, respectively. Although it has been shown that the APL neurons are also GABAergic, the current results showed that OA is the primary neurotransmitter from the APL neurons involved in ARM formation because reduced GABA levels induced by Gad1RNAi inhibition in the APL neurons did not affect 3 hr memory (Wu, 2013).

In Drosophila olfactory memories, OA and dopamine have been shown to act as appetitive and aversive US reinforcements, respectively. It is important to point out that the original claim that Tβh plays no role in aversive learning only examined 3 min memory, not 3 hr memory or ARM. It is not surprising to find that OA modulates ARM in aversive memory because dopamine has also been attributed to diverse memory roles, including a motivation switch for appetitive ITM and appetitive reinforcement. Intriguingly, dopamine negatively inhibits ITM formation, but OA positively modulates ARM formation (Wu, 2013).

Food deprivation in Drosophila larvae induces behavioral plasticity and the growth of octopaminergic arbors via Octβ2R-mediated cyclic AMP (cAMP) elevation in an autocrine fashion. This study showed that the APL neurons release OA acting on the Octβ2R-expressing α' β' KCs for ARM, instead of inducing autocrine regulation. Applying OA directly onto the adult brain results in an elevation of cAMP levels in the whole MB, and OA has been shown to upregulate protein kinase A (PKA) activity in the MBs. Intriguingly, ARM is enhanced by a decreased PKA activity and requires DUNCE-sensitive cAMP signals. It is speculated that APL-mediated activation of Octβ2R may lead to an intricate regulation of cAMP in the α' β' KCs for ARM formation. (Wu, 2013).

Although it has generally been assumed that, in a particular neuron, the same neurotransmitter is used at all synapses, exceptions continue to accumulate in both vertebrates and invertebrates. Scattered evidence suggests that co-release may be regulated at presynaptic vesicle filling and postsynaptic activation of receptors, but the physiologic significance remains poorly understood. This study reports that the APL neurons co-release GABA and OA. In the APL neurons, a reduced GABA level affects learning, but not ITM, whereas a reduced OA level has no effect on learning, but impairs ITM, suggesting that the two neurotransmitters are regulated in different ways in the same cell (Wu, 2013).

It has been proposed that the APL neurons might be the Drosophila equivalent of the honeybee GABAergic feedback neurons, receiving odor information from the MB lobes and releasing GABA inhibition to the MB calyx. This negative feedback loop for olfactory sparse coding has been supported by electrophysiological recording of the giant GABAergic neuron in locusts. However, the function of Drosophila APL neurons is complicated by the existence of functioning presynaptic processes in the MB lobes, mixed axon-dendrite distribution throughout the whole MB, and GABA/OA cotransmission (Wu, 2013).

Normal performance of ARM behavior requires serotonin from the DPM neurons acting on ab KCs via d5HT1A serotonin receptors and function of RADISH and BRUCHPILOT in the ab KCs. Surprisingly,the current results show that ARM formation also requires OA from the APL neurons acting on the α' β' KCs via Octβ2R OA receptors, suggesting the existence of two distinct anatomical circuits involved in ARM formation. However, it remains uncertain whether two branches of ARM occur in parallel because combination of various molecular disruptions (i.e., TβhRNAi and pCPA feeding/rsh1 mutant) did not completely abolish ARM and partial disruption of one anatomical circuit will allow additive effects of another treatment even if they act on the same ARM. The hypothesis of the existence of two distinct forms of ARM is favored based on the following observations. First, neither d5HT1ARNAi knockdown in α' β' KCs nor Octβ2RRNAi knockdown in ab KCs affects ARM, suggesting that the two signaling pathways act separately in different KCs and do not affect each other in the same KCs. Second, each of the three ways of molecular disruption (i.e., TβhRNAi, pCPA feeding, and rsh1 mutant) results in a similar degree of ARM impairment, but additive effect did not occur in rsh1 mutant flies fed with pCPA and was evident when TβhRNAi treatment combines with either pCPA feeding or rsh1 mutant. It's noteworthy that ARM is also affected by dopamine modulation because calcium oscillation within dopaminergic MB-MP1 and MB-MV1 neurons controls ARM and gates long-term memory, albeit a different view has been brought up. The target KCs of these dopaminergic neurons on ARM remain to be addressed (Wu, 2013).

Both the APL and DPM neurons are responsive to electric shock and multiple odorants, suggesting that they likely acquire olfactory associative information during learning for subsequent ARM formation. However, the DPM neurons may receive ARM information independently because their fibers are limited within MB lobes and gap-junctional communications between the APL and DPM neurons are specifically required for the formation of ASM, but not ARM. Given that all dopamine reinforcement comes in via the γ KCs, it is possible that the DPM neurons obtain ARM information from γ KCs. Together, these data suggest that two parallel neural pathways, serotoninergic DPM-αβ KCs and octopaminergic APL-α'β' KCs, modulate 3 hr ARM formation in the MB (Wu, 2013).

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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).

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Dopaminergic neurons write and update memories with cell-type-specific rules

Aso, Y. and Rubin, G.M. (2016). Elife [Epub ahead of print]. PubMed ID: 27441388

Associative learning is thought to involve parallel and distributed mechanisms of memory formation and storage. In Drosophila, the mushroom body (MB) is the major site of associative odor memory formation. The anatomy of the adult MB and 20 types of dopaminergic neurons (DANs) that each innervate distinct MB compartments have been previously defined and described. This study compared the properties of memories formed by optogenetic activation of individual DAN cell types. Extensive differences were found in training requirements for memory formation, decay dynamics, storage capacity and flexibility to learn new associations. Even a single DAN cell type can either write or reduce an aversive memory, or write an appetitive memory, depending on when it is activated relative to odor delivery. These results show that different learning rules are executed in seemingly parallel memory systems, providing multiple distinct circuit-based strategies to predict future events from past experiences. The mechanisms that generate these distinct learning rules are unknown. They could arise from differences in the dopamine release properties of different DAN cell types or from local differences in the biochemical response to dopamine signaling in each MB compartment. For example, KCs express four distinct dopamine receptors, which might be deployed differently in each compartment. Or they could originate from circuit properties (Aso, 2016).

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Circuit analysis of a Drosophila Dopamine type 2 receptor that supports anesthesia-resistant memory

Scholz-Kornehl, S. and Schwarzel, M. (2016). J Neurosci 36: 7936-7945. PubMed ID: 27466338

Dopamine is central to reinforcement processing and exerts this function in species ranging from humans to fruit flies. It can do so via two different types of receptors (i.e., D1 or D2) that mediate either augmentation or abatement of cellular cAMP levels. Whereas D1 receptors are known to contribute to Drosophila aversive odor learning per se, this study shows that D2 receptors are specific for support of a consolidated form of odor memory known as anesthesia-resistant memory. By means of genetic mosaicism, this function was localized to Kenyon cells, the mushroom body intrinsic neurons, as well as GABAergic APL neurons and local interneurons of the antennal lobes, suggesting that consolidated anesthesia-resistant memory requires widespread dopaminergic modulation within the olfactory circuit. Additionally, dopaminergic neurons themselves require D2R, suggesting a critical role in dopamine release via its recognized autoreceptor function. Considering the dual role of dopamine in balancing memory acquisition (proactive function of dopamine) and its 'forgetting' (retroactive function of dopamine), this analysis suggests D2R as central player of either process (Scholz-Kornehl, 2016).

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Pre- and postsynaptic role of Dopamine D2 Receptor DD2R in Drosophila olfactory associative learning

Qi, C. and Lee, D. (2014). Biology (Basel) 3: 831-845. PubMed ID: 25422852

Dopaminergic neurons in Drosophila play critical roles in diverse brain functions such as motor control, arousal, learning, and memory. Using genetic and behavioral approaches, it has been firmly established that proper dopamine signaling is required for olfactory classical conditioning (e.g., aversive and appetitive learning). Dopamine mediates its functions through interaction with its receptors. There are two different types of dopamine receptors in Drosophila: D1-like (dDA1, DAMB) and D2-like receptors (DD2R). Currently, no study has attempted to characterize the role of DD2R in Drosophila learning and memory. Using a DD2R-RNAi transgenic line, this study has examined the role of DD2R, expressed in dopamine neurons (i.e., the presynaptic DD2R autoreceptor), in larval olfactory learning. The function of postsynaptic DD2R expressed in mushroom body (MB) was also studied as MB is the center for Drosophila learning, with a function analogous to that of the mammalian hippocampus. These results showed that suppression of presynaptic DD2R autoreceptors impairs both appetitive and aversive learning. Similarly, postsynaptic DD2R in MB neurons appears to be involved in both appetitive and aversive learning. The data confirm, for the first time, that DD2R plays an important role in Drosophila olfactory learning (Qi, 2014).

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Reward signal in a recurrent circuit drives appetitive long-term memory formation

Ichinose, T., Aso, Y., Yamagata, N., Abe, A., Rubin, G. M. and Tanimoto, H. (2015). Elife 4 [Epub ahead of print]. PubMed ID: 26573957

Dopamine signals reward in animal brains. A single presentation of a sugar reward to Drosophila activates distinct subsets of dopamine neurons that independently induce short- and long-term olfactory memories (STM and LTM, respectively). This study shows that a recurrent reward circuit underlies the formation and consolidation of LTM. This feedback circuit is composed of a single class of reward-signaling dopamine neurons (PAM-alpha1) projecting to a restricted region of the mushroom body (MB), and a specific MB output cell type, MBON-α1, whose dendrites arborize that same MB compartment. Both MBON-α1 and PAM-α1 neurons are required during the acquisition and consolidation of appetitive LTM. MBON-α1 additionally mediates the retrieval of LTM, which is dependent on the dopamine receptor signaling in the MB αβ neurons. These results suggest that a reward signal transforms a nascent memory trace into a stable LTM using a feedback circuit at the cost of memory specificity (Ichinose, 2015).

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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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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).

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Hattori, D., Aso, Y., Swartz, K. J., Rubin, G. M., Abbott, L. F. and Axel, R.

(2017). Representations of novelty and familiarity in a mushroom body compartment. 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).

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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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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 (Riemensperger, 2005). 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).

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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).

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Mushroom body signaling is required for locomotor activity rhythms in Drosophila

Mabuchi, I., Shimada, N., Sato, S., Ienaga, K., Inami, S. and Sakai, T. (2016). Neurosci Res [Epub ahead of print]. PubMed ID: 27106579

In the fruitfly Drosophila melanogaster, circadian rhythms of locomotor activity under constant darkness are controlled by pacemaker neurons. To understand how behavioral rhythmicity is generated by the nervous system, it is essential to identify the output circuits from the pacemaker neurons. The importance of mushroom bodies (MBs) in generating behavioral rhythmicity remains controversial because contradicting results have been reported as follows: (1) locomotor activity in MB-ablated flies is substantially rhythmic, but (2) activation of restricted neuronal populations including MB neurons induces arrhythmic locomotor activity. This study reports that neurotransmission in MBs is required for behavioral rhythmicity. For adult-specific disruption of neurotransmission in MBs, the GAL80/GAL4/UAS ternary gene expression system was used in combination with the temperature-sensitive dynamin mutation shibirets1. Blocking of neurotransmission in GAL4-positive neurons including MB neurons induced arrhythmic locomotor activity, whereas this arrhythmicity was rescued by the MB-specific expression of GAL80. These results indicate that MB signaling plays a key role in locomotor activity rhythms in Drosophila (Mabuchi, 2016).

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The full-length form of the Drosophila amyloid precursor protein is involved in memory formation

Bourdet, I., Preat, T. and Goguel, V. (2015). J Neurosci 35: 1043-1051. PubMed ID: 25609621

The APP plays a central role in AD, a pathology that first manifests as a memory decline. Understanding the role of APP in normal cognition is fundamental in understanding the progression of AD, and mammalian studies have pointed to a role of secreted APPα in memory. In Drosophila, APPL, the fly APP ortholog, is required for associative memory. This study aimed to characterize which form of APPL is involved in this process. Expression of a secreted-APPL form in the mushroom bodies, the center for olfactory memory, was able to rescue the memory deficit caused by APPL partial loss of function. The study next assessed the impact on memory of the Drosophila α-secretase kuzbanian (KUZ), the enzyme initiating the nonamyloidogenic pathway that produces secreted APPLα. Strikingly, KUZ overexpression not only failed to rescue the memory deficit caused by APPL loss of function, it exacerbated this deficit. Further, in addition to an increase in secreted-APPL forms, KUZ overexpression caused a decrease of membrane-bound full-length species that could explain the memory deficit. Indeed, transient expression of a constitutive membrane-bound mutant APPL form was sufficient to rescue the memory deficit caused by APPL reduction, revealing for the first time a role of full-length APPL in memory formation. This data demonstrates that, in addition to secreted APPL, the noncleaved form is involved in memory, raising the possibility that secreted and full-length APPL act together in memory processes (Bourdet, 2015).

The majority of studies into APP biology have focused on pathogenic mechanisms. However, it remains crucial to understand the normal physiological function of APP, especially as it is possible that APP loss of function elicits early cognitive impairment in AD patients. This study shows that overexpression of secreted APPL rescues the short-term memory deficit caused by a reduction of APPL level. In sharp contrast, overexpression of the α-secretase, KUZ, which produces sAPPL, exacerbates the memory impairment, a phenotype that is likely due to a deficit in full-length APPL protein level. Supporting this hypothesis, it was further demonstrated that expression of a nonprocessed APPL mutant form is able to restore wild-type memory in an APPL partial loss of function background (Bourdet, 2015).

In the past, two main strategies have been considered as therapeutic approaches for AD. First, inhibition of the β- or γ-secretase has been used to achieve an inhibition of Aβ toxic production. However, reduction of Aβ production is not only an ineffective approach for AD, it also can actually promote further pathology, as these enzymes have numerous substrates. A second proposed approach has been to inhibit the amyloidogenic pathway by activating the α-processing of APP. In addition to the potential beneficial inhibition of the amyloidogenic pathway, the advantage of this type of approach is to also increase the production of sAPPα. Indeed, decreased CSF sAPPα levels were found in familial and sporadic AD patients, and correlated with poor memory performance in patients with AD. Thus, in vitro and in vivo studies indicate that sAPPα is downregulated during AD. Numerous analyses have shown that sAPPα ectodomain has neurotrophic and neuroprotective effects in different models of neuronal stress. In addition, sAPPα exhibits memory-enhancing properties. Intracerebroventricular infusion of anti-sAPPα serum was deleterious for memory, while that of sAPPα was beneficial. However, these studies relied on an exogenous excess of sAPPα and mechanisms of action and potential targets remained to be elucidated. With knock-in mice experiments, showed that sAPPα was sufficient to correct the impairments in spatial learning and long-term potentiation that are present in APP KO mice. This study shows in Drosophila that sAPPL is able to fully rescue the STM deficit caused by a reduction in endogenous APPL level, thus establishing that an APPL soluble form plays a role in memory, and giving further support for a role of secreted forms in memory in mammal systems (Bourdet, 2015).

When the fly α-secretase, KUZ, was overexpressed in the adult MB, no STM-enhancing effect was seen and, unexpectedly, KUZ overexpression in the MB of flies with an APPL partial loss of function exacerbated their memory impairment. Thus, KUZ overexpression was actually deleterious for memory, rather than beneficial. These results contrast with a previous study showing that overexpression of the mammalian α-secretase ADAM10 in an AD mice model led to an increase in sAPPα, and was able to overcome APP-related learning deficits. However, these studies showed that α-secretase activation has a positive impact on memory exclusively under conditions where human APP is overexpressed. In wild-type mice, results were not clear because overexpression of either the wild-type or an inactive form of the bovine ADAM10 altered learning and memory. Furthermore, ADAM10 has many substrates, and no evidence was brought to link the memory deficit to APP (Bourdet, 2015).

Interestingly, this study observed that KUZ overexpression decreases membrane nonproteolyzed APPL level, suggesting that its negative impact on memory in APPL LOF flies is linked to a reduction of nonproteolyzed APPL level. Therefore, strategies aimed at increasing APP α-cleavage may not be appropriate as this could provoke a decrease of fl-APP levels that might be deleterious to APP function (Bourdet, 2015).

Transient expression of a constitutive membrane-bound mutant APPL has the capacity to fully rescue the STM deficit caused by APPL partial loss of function. Thus, both sAPPL and fl-APPL appear to be involved in memory processes. This is in apparent contradiction with the observation that mammalian sAPPα was sufficient to correct spatial learning deficit of APP KO mice. However, in this study APP-like proteins APLP1 and ALPL2 were preserved, and as it is known from double KO analyses that the three APP homologs exert functional redundancy, they may have compensated for the loss of essential fl-APP functions. In consequence, one cannot attribute the memory function exclusively to sAPPα (Bourdet, 2015).

If both fl-APPL and sAPPL carry the capacity to restore wild-type STM in APPL partial LOF flies, it is puzzling to observe that KUZ overexpression in this genetic context is deleterious for memory. Indeed, in addition to causing a decrease in fl-APPL, KUZ overexpression leads to a concomitant increase in sAPPL that should be able to complement fl-APPL deficiency. It is suggested that in this context, fl-APPL level is below threshold so that even high levels of sAPPL cannot restore a wild-type memory. This hypothesis is supported by protein quantification experiments showing a 30% decrease in fl-APPL level. Because APPL was extracted from the whole brain, whereas KUZ overexpression was only driven in a subset of neurons, the effective fl-APPL decrease in the MB must be much higher than 30%. In mammalian cells under steady-state levels, ~10% of APP is located at the plasma membrane. APP has long been suggested to act as a cell-surface receptor; however, such a function has not been unequivocally established. Several reports have shown that APP exists as homodimers. Cis-dimerization of APP would represent a potential mechanism for a negative regulation of APP functions and a concomitant impact on Aβ generation via an increase in β-processing. Interestingly, it has been suggested that APP is a receptor for sAPPα as its binding could disrupt APP dimers (Bourdet, 2015).

In Drosophila, it has been reported that the secreted N-terminal ectodomain of APPL acts as a soluble ligand for neuroprotective functions. Furthermore, coimmunoprecipitation experiments from transfected Drosophila MB intrinsic cells revealed a physical interaction between fl-APPL and sAPPL, suggesting that sAPPL could be a ligand for fl-APPL. The current data showing the involvement of both membrane fl-APPL and sAPPL in memory are consistent with the hypothesis that sAPPL could be a ligand for its own fl-APPL precursor (Bourdet, 2015).

In conclusion, these data reveal for the first time a role for membrane fl-APPL in memory, opening new questions about APP nonpathological functions and relations between secreted and full-length forms in memory processes (Bourdet, 2015).

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Developmental inhibition of miR-iab8-3p disrupts mushroom body neuron structure and adult learning ability

Busto, G. U., Guven-Ozkan, T., Chakraborty, M. and Davis, R. L. (2016). Dev Biol [Epub ahead of print]. PubMed ID: 27634569

MicroRNAs are small non-coding RNAs that inhibit protein expression post-transcriptionally. They have been implicated in many different physiological processes, but little is known about their individual involvement in learning and memory. Several miRNAs have been identified that either increased or decreased intermediate-term memory when inhibited in the central nervous system, including miR-iab8-3p. This paper reports a new developmental role for this miRNA. Blocking the expression of miR-iab8-3p during the development of the organism leads to hypertrophy of individual mushroom body neuron soma, a reduction in the field size occupied by axonal projections, and adult intellectual disability. Four potential mRNA targets of miR-iab8-3p were identified whose inhibition modulates intermediate-term memory including ceramide phosphoethanolamine synthase, which may account for the behavioral effects produced by miR-iab8-3p inhibition. These results offer important new information on a microRNA required for normal neurodevelopment and the capacity to learn and remember normally (Busto, 2016).

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Aging impairs protein-synthesis-dependent long-term memory in Drosophila

Tonoki, A. and Davis, R.L. (2015). J Neurosci 35: 1173-1180. PubMed ID: 25609631

Although aging is known to impair intermediate-term memory in Drosophila, its effect on protein-synthesis-dependent long-term memory (LTM) is unknown. This study shows that LTM is impaired with age, not due to functional defects in synaptic output of mushroom body (MB) neurons, but due to connectivity defects of dorsal paired medial (DPM) neurons with their postsynaptic MB neurons. GFP reconstitution across synaptic partners (GRASP) experiments revealed structural connectivity defects in aged animals of DPM neurons with MB axons in the α lobe neuropil. As a consequence, a protein-synthesis-dependent LTM trace in the α/β MB neurons fails to form. Aging thus impairs protein-synthesis-dependent LTM along with the α/β MB neuron LTM trace by lessening the connectivity of DPM and α/β MB neurons (Tonoki, 2015).

The data presented in this study offer several important findings about the neural circuitry and the forms of memory disrupted by aging. First, it shows that aging impairs only one of the two mechanistically distinct forms of LTM generated by spaced, aversive classical conditioning in Drosophila. LTM that is independent of protein synthesis remains unaffected by age, whereas that form of LTM requiring protein synthesis becomes impaired. Therefore, there is mechanistic specificity in the effects of aging on LTM. Although aging, in principal, could disrupt processes like protein synthesis at the molecular level leading to a LTM deficit, these results indicate that the problem is traceable to the circuitry involved in generating protein-synthesis-dependent LTM (Tonoki, 2015).

The normal synaptic transmission from DPM neurons onto follower neurons during spaced training that is required for generating LTM is lost with age. This is attributable to the reduction of synaptic contacts between DPM neuron processes and MB axons specifically in the tip of the α lobe neuropil as revealed by GRASP signals. The loss of synaptic contacts between DPM and MB neurons in this region also may explain why synaptic blockade of DPM neurons during acquisition disrupts protein-synthesis-dependent LTM in young but not old flies. Therefore, a second major finding is that neural contacts and subsequent synaptic activity between DPM and α/β MB neurons are required for generating protein-synthesis-dependent LTM, and aging impairs this process. Consistent with this model, it is found that aging blocks the formation of a calcium-based, protein-synthesis-dependent memory trace in the α/β MB neurons (Tonoki, 2015).

It was found previously that ITM is impaired in flies of 30 d of age along with the capacity to form an ITM trace in the DPM neurons. Nevertheless, aging does not compromise the capacity to form an STM trace in the α'/β' MB neurons. Therefore, aging disrupts specific temporal forms of memory, including ITM and protein synthesis LTM, but not STM and protein-synthesis-independent LTM. It is possible that the loss of connectivity of DPM neurons with the α tip neuropil is responsible for the loss of both ITM and protein-synthesis-dependent LTM, along with their respective memory traces. Previous and this study's data indicate that STM appears to bypass the DPM neurons, whereas the reciprocal activity between DPM and MB neurons is required for ITM and LTM. Aging puts a kink in this neural system by impairing connectivity (Tonoki, 2015).

The study offers a model to explain the neural circuitry involved in protein-synthesis-dependent LTM formation and how aging impairs this form of memory. Although DPM neurons make contacts widely throughout the MB lobe neuropil with processes of many cell types, the critical interaction for LTM formation occurs in the vertical lobes of the MB through contacts onto the axons of α/β MB neurons. DPM neuron synaptic activity during spaced training, which occurs due to their stimulation by MB neurons, promotes synaptic changes in the postsynaptic α/β MB neurons and leads to the formation of memory trace in the α/β MB neurons. Aging impairs protein-synthesis-dependent LTM along with a LTM trace that normally forms in the α/β MB neurons by lessening the connectivity of DPM and α/β MB neurons. Identifying the mechanisms by which the DPM neurons lose their connectivity with only the tips of α/β MB neurons might reveal how aging impairs protein-synthesis-dependent LTM (Tonoki, 2015).

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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).

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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). Reciprocal synapses between mushroom body and dopamine neurons form a positive feedback loop required for learning. 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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Upregulated energy metabolism in the Drosophila mushroom body is the trigger for long-term memory

Placais, P. Y., de Tredern, E., Scheunemann, L., Trannoy, S., Goguel, V., Han, K. A., Isabel, G. and Preat, T. (2017). . Nat Commun 8: 15510. PubMed ID: 28580949

Efficient energy use has constrained the evolution of nervous systems. However, it is unresolved whether energy metabolism may resultantly regulate major brain functions. The observation that Drosophila flies double their sucrose intake at an early stage of long-term memory formation initiated the investigation of how energy metabolism intervenes in this process. Cellular-resolution imaging of energy metabolism reveals a concurrent elevation of energy consumption in neurons of the mushroom body, the fly's major memory centre. Strikingly, upregulation of mushroom body energy flux is both necessary and sufficient to drive long-term memory formation. This effect is triggered by a specific pair of dopaminergic neurons afferent to the mushroom bodies, via the D5-like DAMB dopamine receptor. Hence, dopamine signalling mediates an energy switch in the mushroom body that controls long-term memory encoding. These data thus point to an instructional role for energy flux in the execution of demanding higher brain functions (Placais, 2017).

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date revised: 10 December 2017

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