The Interactive Fly

Genes involved in tissue and organ development

The Drosophila Brain: Central Complex

Neuroarchitecture of the Drosophila central complex: A catalog of nodulus and asymmetrical body neurons and a revision of the protocerebral bridge

Drosophila embryonic type II neuroblasts: origin, temporal patterning, and contribution to the adult central complex

Drosophila neuroblasts are an excellent model for investigating how neuronal diversity is generated. Most brain neuroblasts generate a series of ganglion mother cells (GMCs) that each make two neurons (type I lineage), but sixteen brain neuroblasts generate a series of intermediate neural progenitors (INPs) that each produce 4-6 GMCs and 8-12 neurons (type II lineage). Thus, type II lineages are similar to primate cortical lineages, and may serve as models for understanding cortical expansion. Yet the origin of type II neuroblasts remains mysterious: do they form in the embryo or larva? If they form in the embryo, do their progeny populate the adult central complex, as do the larval type II neuroblast progeny? This study presents molecular and clonal data showing that all type II neuroblasts form in the embryo, produce INPs, and express known temporal transcription factors. Embryonic type II neuroblasts and INPs undergo quiescence, and produce embryonic-born progeny that contribute to the adult central complex. These results provide a foundation for investigating the development of the central complex, and tools for characterizing early-born neurons in central complex function (Walsh, 2017).

It has been difficult to link embryonic neuroblasts to their larval counterparts in the brain and thoracic segments owing to the period of quiescence at the embryo-larval transition, and owing to dramatic morphological changes of the CNS that occur at late embryogenesis. Recent work has revealed the embryonic origin of some larval neuroblasts: the four mushroom body neuroblasts in the central brain and about 20 neuroblasts in thoracic segments. This study used molecular markers and clonal analysis to identify all eight known type II neuroblasts in each brain lobe and show they all form during embryogenesis, perhaps the last-born central brain neuroblasts. It was not possible to identify each neuroblast individually, however, owing to their tight clustering, movements of the brain lobes, and the lack of markers for specific type II neuroblasts (Walsh, 2017).

The single previously reported embryonic type II neuroblast formed from PntP1+ neuroectodermal cells with apical constrictions called a placode. This study has not investigated this neuroectodermal origin of type II neuroblasts in much detail, but this study also observe multiple type II neuroblasts developing from PntP1+ neuroectoderm. In the future, it would be interesting to determine whether all type II neuroblasts arise from PntP1+ neuroectoderm or from neuroectodermal placodes. Interestingly, one distinguishing molecular attribute of type II neuroblasts is PntP1, which is not detected in type I neuroblasts. Thus, a candidate for distinguishing type I/type II neuroblast identity is EGF signaling, which can be detected in the three head placodes and is required for PntP1 expression. Clearly, there are more PntP1+ neuroectodermal cells than there are type II neuroblasts, and expression of an EGF negative regulator such as Argos might be necessary to divert some of these neuroectodermal cells away from type II neuroblast specification. The earliest steps of type II neuroblast formation represent an interesting spatial patterning question for future studies (Walsh, 2017).

Now that the embryonic type II neuroblasts have been identified, it is worth considering whether there are differences between embryonic and larval type II neuroblasts or their INP progeny. To date, molecular markers do not reveal any differences between embryonic and larval type II neuroblasts, with the exception that embryonic neuroblasts transiently express the temporal transcription factor Pdm. Interestingly, type I embryonic neuroblasts require Cas to close the Pdm expression window, whereas this study finds that cas mutants do not exhibit extension of the Pdm expression window in the earliest-born type II neuroblast or de novo expression of Pdm in the later-forming neuroblasts. Are there differences between embryonic and larval INPs? Larval INPs mature over a period of 6 h and then divide four to six times with a cell cycle of about 1 h. In contrast, embryonic INPs might have a more rapid maturation because Elav+ neurons are seen within 9D11+ INP lineages by stage 14, just 3 h after the first type II neuroblast forms. This study found that INPs undergo quiescence at the embryo-larval transition, as shown by the pools of INPs at stage 16 that do not stain for the mitotic marker pH3. The fate of these quiescent INPs - whether they resume proliferation, differentiate or die - remains to be determined (Walsh, 2017).

Neuroblasts in the embryonic ventral nerve cord use the temporal transcription factor cascade Hb>Krüuppel>Pdm>Cas>Grh to generate neural diversity. This study shows that the type II neuroblasts are among the last neuroblasts to form in the embryonic brain and that they sequentially express only the late temporal transcription factors Pdm (in the earliest-forming neuroblast) followed by Cas and Grh (in all eight type II neuroblasts). It is unknown why most type II neuroblasts skip the early Hb>Krüppel>Pdm temporal transcription factors; perhaps it is due to their late time of formation, although several earlier-forming thoracic neuroblasts also skip Hb (NB3-3), Hb>Krüppel (NB5-5), or Hb>Krüppel->Pdm (NB6-1). This is another interesting spatial patterning question for the future. Furthermore, misexpression of the early factors (Hb and Krüppel) would be unlikely to affect the progeny produced by type II NBs during embryogenesis, as the competence window for Hb (i.e., the stage at which neuroblasts are responsive to Hb expression) closes with the loss of Dan/Danr expression in all neuroblasts at stage 12. Thus, most embryonic type II neuroblasts form after closing of the Hb competence window and would probably be unresponsive (Walsh, 2017).

Type I neuroblasts show persistent expression of the temporal transcription factors within neurons born during each window of expression (i.e. a Hb+ neuroblast divides to produce a Hb+ GMC which makes Hb+ neurons). In contrast, this study found that type II lineages do not show persistent Cas or Grh expression in INPs born during each expression window, but do contain some Cas+ neurons. Both Cas and Grh transcription factors can be seen in INPs immediately adjacent to the parental neuroblast, consistent with transient perdurance from the parental neuroblast, but they are typically lacking in INPs more distant. The function of Pdm, Cas and Grh in embryonic type II neuroblasts awaits identification of specific markers for neural progeny born during each expression window (Walsh, 2017).

During larval neurogenesis, virtually all INPs sequentially express the temporal transcription factors Dichaete->Grh->Ey. In contrast, embryonic INPs express only Dichaete. These data, together with the short time frame of embryogenesis, suggest that INP quiescence occurs during the Dichaete window, preventing expression of the later Grh->Ey cascade. Interestingly, INPs in the posterior cluster (presumptive DL1 and DL2 type II neuroblast progeny) completely lack Dichaete; this is similar to the DL1 and DL2 larval lineages, which also do not express Dichaete. It is possible that DL1/DL2 neuroblasts make INPs that generate identical progeny (and thus do not require an INP temporal cascade), or perhaps these two neuroblasts use a novel temporal cascade in both embryonic and larval stages (Walsh, 2017).

Larval type II neuroblasts produce many intrinsic neurons of the adult central complex. This study shows that embryonic INPs also produce neurons that contribute to the adult central complex. The data show ~54 neurons (64 minus 10 due to 'leaky' expression) born from embryonic-born INPs survive to adulthood and innervate the central complex. It is likely that this is an underestimate, however, because (1) 9D11-gal4 expression is lacking from a few INPs in the embryonic brain and (2) the time to achieve sufficient FLP protein levels to achieve immortalization could miss the earliest born neurons. The variation in immortalization of the widefield ellipsoid body neuron might represent a neuron born early in the type II lineages, thus unlabeled in a subset of embryos. Additionally, some embryonic-born neurons might perform important functions in the larval/pupal stages but die prior to eclosion (Walsh, 2017).

Further studies will be required to understand the function of neurons born from embryonic type II lineages. It remains to be experimentally determined whether some or all embryonic progeny of type II neuroblasts (1) remain functionally immature in both the larval and adult brain, but serve as pioneer neurons to guide larval-born neurons to establish the central complex, (2) remain functionally immature in the larval brain, but differentiate and function in the adult central complex, or (3) differentiate and perform a function in both the larval and adult CNS. It will be informative to ablate embryonic-born neurons selectively and determine the effect on the assembly of the larval or adult central complex, and their role in generating larval and adult behavior (Walsh, 2017).

Development of the anterior visual input pathway to the Drosophila central complex

The anterior visual pathway (AVP) conducts visual information from the medulla of the optic lobe via the anterior optic tubercle (AOTU) and bulb (BU) to the ellipsoid body (EB) of the central complex. This paper analyzes the formation of the AVP from early larval to adult stages. The immature fiber tracts of the AVP, formed by secondary neurons of lineages DALcl1/2 and DALv2, assemble into structurally distinct primordia of the AOTU, BU, and EB within the late larval brain. During the early pupal period (P6-P48) these primordia grow in size and differentiate into the definitive subcompartments of the AOTU, BU, and EB. The primordium of the EB has a complex composition. DALv2 neurons form the anterior EB primordium, which starts out as a bilateral structure, then crosses the midline between P6 and P12, and subsequently bends to adopt the ring shape of the mature EB. Columnar neurons of the central complex, generated by the type II lineages DM1-4, form the posterior EB primordium. Starting out as an integral part of the fan-shaped body (FB) primordium, the posterior EB primordium moves forward and merges with the anterior EB primordium. This paper documents the extension of neuropil glia around the nascent EB and BU and analyzes the relationship of primary and secondary neurons of the AVP lineages (Lovick, 2017).

Neuroarchitecture and neuroanatomy of the Drosophila central complex: A GAL4-based dissection of protocerebral bridge neurons and circuits

Insects exhibit an elaborate repertoire of behaviors in response to environmental stimuli. The central complex plays a key role in combining various modalities of sensory information with an insect's internal state and past experience to select appropriate responses. Progress has been made in understanding the broad spectrum of outputs from the central complex neuropils and circuits involved in numerous behaviors. Many resident neurons have also been identified. However, the specific roles of these intricate structures and the functional connections between them remain largely obscure. Significant gains rely on obtaining a comprehensive catalogue of the neurons and associated GAL4 lines that arborize within these brain regions, and on mapping neuronal pathways connecting these structures. Toward this end, small populations of neurons in the Drosophila melanogaster central complex were stochastically labeled using the multicolor flip-out technique and a catalogue was created of the neurons, their morphologies, trajectories, relative arrangements and corresponding GAL4 lines. This report focuses on one structure of the central complex, the protocerebral bridge, and identifies just 17 morphologically distinct cell types that arborize in this structure. This work also provides new insights into the anatomical structure of the four components of the central complex and its accessory neuropils that are arborized by PB neurons include the crepine (CRE), rubus (RUB), gall (GA), and lateral accessory lobe (LAL). Most strikingly, the protocerebral bridge was found to contain 18 glomeruli, not 16, as previously believed. Revised wiring diagrams that take into account this updated architectural design are presented. This updated map of the Drosophila central complex will facilitate a deeper behavioral and physiological dissection of this sophisticated set of structures (Wolff, 2014).

The work presented in this study builds on published studies by both defining previously unidentified anatomical features of each of the four components of the central complex as well as updating wiring diagrams to accommodate these new anatomical insights. This paper also reports new cells and new features of previously identified cells and the genetic reporter lines that reveal them, with the prospect that these will form an essential stepping stone both to synaptic studies at the electron microscope level and to functional studies. The most significant new insights from this work are summarized below. As noted earlier, the statements below are drawn from neurons that arborize in the PB (Wolff, 2014).

The most surprising finding of this study is that the Drosophila protocerebral bridge comprises 18 glomeruli. This finding has an important impact on the wiring relationships between the glomeruli and their respective vertical units in the FB, the columns, and in the EB, the wedges and a new volume described in this study, the tiles (Wolff, 2014).

The longstanding belief regarding the correspondence between the PB and FB and PB and EB wedges was that there is a 1:1 relationship between the vertical subdomains of these structures. The finding that there are 18 glomeruli raised the possibility that the FB and EB also exhibit an octodecimal organization. However, compelling evidence is provided that there are just 16 wedges in the EB. and it was further show, that some cells arborize in just half a wedge, indicating the further division of wedges into 32 demi-wedges. The observation that a simple 1:1 correspondence between the PB and EB wedges is lacking and, furthermore, that there are also demi-wedges, has implications for how the system is wired to accommodate this numerical discrepancy (Wolff, 2014).

Another unexpected finding from this work is the existence of a second EB volume that also partitions the EB around its circumference: the tile domain. Tiles are distinct from wedges in that there are half as many tiles as wedges (eight tiles), they are functionally distinct from the wedge (output versus input, respectively), and these two volumes survey different volumes of the EB since they extend to different depths of the EB. Only two PB cell types target the tile domain (Wolff, 2014).

Although a columnar morphology is apparent in layers 1–8 of the FB in nc82-labeled samples, the organization of the cells that populate these layers is not universally columnar. There is a minimum of nine layers in the FB, yet a columnar organization (i.e., vertical stratification) of cell arbors is restricted to layers 1–5 for single column widths (where the columnar organization for layers 4 and 5 is revealed by the PBG1–8.s-FBℓ3,4,5.s.b-rub.b cell); wider, more loosely organized arbors occur in more dorsal layers. With the exception of arbors in layer 1, the column borders are not rigid, as neighboring arbors overlap one another, sometimes extensively. The unique tooth-like structure of layer 1 of the FB definitively shows that there are nine columns in this layer. Due to the overlap of arbors, it is more difficult to count columns in the other layers, but layers 2 and 3, which exhibit a tighter columnar organization than more dorsal layers, likely have 16 columns based on mapping data. This would be consistent with parallel divisions of the EB (wedges) (Wolff, 2014).

Other new anatomical features and subdomains are described in this study. First, it was shown that each of the noduli has subcompartments. The dorsal noduli, NO1, have medial and lateral subcompartments. The medial noduli, NO2, consist of two distinct subcompartments, NO2D and NO2V; no PB cell type arborizes in either of these subcompartments. The ventral noduli, NO3, consist of three distinct subcompartments, NO3A, NO3M, and NO3P. The nubbin is a partial shell on the dorsal, anterior face of the EB, and the "gall tip" is a region at the dorsal tip of the gall. Finally, two undefined regions to which some cells project and that are not clearly demarcated are the dorsal and ventral gall surround (Dga-s and Vga-s) (Wolff, 2014).

Even though the subdomains of the central complex structures can be distinguished from one another, they apparently do not function as isolated subunits. Rather, there is shared communication between most of these subunits. At least for the neurons described in this study (i.e., those that arborize in the PB), both pre- and postsynaptic arbors in the glomeruli, EB tiles, wedges and shells, FB columns, and NO1 (medial and lateral domains) can extend into neighboring domains. This sharing of information is not obvious between NO2D and NO2V, nor between NO3A and NO3M. The boundary between NO3P and NO3M is too obscure to evaluate if arbors in these two domains are completely restricted or shared, although in the examples they appear to be restricted. The frequency and degree to which arbors overlap in the various subunits is cell type-dependent. While some arbors exhibit no or minimal intrusion into adjacent volumes, overlap between neighboring units could serve important circuit functions (Wolff, 2014).

This work identifies 17 unique cell types that arborize in the protocerebral bridge. These fall into four classes: cells that 1) are intrinsic to the PB (n = 2), 2) are intrinsic to the central complex (an additional 6), 3) arborize in the FB, EB, or NO in addition to extra-central complex regions (e.g., the gall; n = 6), and 4) arborize exclusively in the PB and regions outside the central complex (n = 3). Cells that arborize in the PB receive their input from the EB, LAL, PS, IB, and also from within the PB. One cell previously identified in another study (Lin, 2013) was not targeted by any of the ∼35 lines analyzed in this work. To the extent that it is possible to construct wiring diagrams from the images shown in these two studies, it appears that the circuits for these cells are also identical between Drosophila and Schistocerca. In addition, one cell type was identified in this study that was not characterized in Lin (2013) (Wolff, 2014).

The combined total from this work and Lin (2013) brings the current number of identified cell types that arborize in the protocerebral bridge of Drosophila to 18. A potential 19th cell type was seen just twice, and in neither case could the entire cell be traced. Its PB arbor is spiny and very sparse, and while it clearly arborizes in the central brain, it is not clear if it arborizes elsewhere within the central complex. It is also possible that this "cell type" only constitutes a variant. There will likely be additional cells identified that arborize in the PB, although this number is predicted to be small. A complete inventory of all cells in the Drosophila brain awaits a full reconstruction at an electron microscope level (Wolff, 2014).

The wiring diagrams described in this study differ from published reports, in part due to the fact that previous authors were unaware of the existence of 18 glomeruli in the PB and therefore based their models on the historic interpretation that there are 16 glomeruli. This numerical revision and new insights into the anatomical substructure of the central complex components are the primary basis for revisions of existing circuit diagrams (Wolff, 2014).

Although there are 18 glomeruli, no small-field neuron arborizes in all 18 glomeruli. Instead, most cell types arborize in either G1–G8 or G2–G9. Each of these categories adheres to the following basic wiring principle: Cells that arborize in the lateral four glomeruli of each side of the PB stay ipsilateral in the second neuropil (either the FB or EB, depending on the neuron) and cross to the contralateral side at the third neuropil, whereas cells that arborize in the medial four glomeruli cross to the contralateral side in the second neuropil. Consequently, because there are two subsets of PB neurons, the glomerulus that targets a given column, wedge, or tile is shifted by one glomerulus, depending on the subset of cell type. Furthermore, the observation that no small-field neurons arborize in all 18 glomeruli suggests the number of columns in the FB and wedges in the EB would not need to exceed 16 in order to maintain a 1:1 correspondence between the PB and FB/EB (Wolff, 2014).

Arbors from cells that target the PB alternate with one another in the second neuropil such that arbors from the left glomeruli alternate with those from the right glomeruli. The PB wiring diagrams presented in this study differ somewhat from a recent account (Lin, 2013), as follows. The most lateral FB column (or EB wedge) is occupied not by the ipsilateral G9 (or G8 for the G1–G8 cells), as previously described, but instead by the contralateral G2 (or G1 for the G1–G8 cells). This circuit therefore reverses the pattern in the second neuropil (FB or EB) from one in which the most lateral (L) glomeruli project to the most lateral columns (or wedge or tile) on the ipsilateral side to one in which the medial (M) glomeruli from the contralateral half of the PB project to the most lateral columns. In other words, previously published diagrams indicate a pattern of LMLMLM from lateral to medial in the second neuropil, whereas this report shows that pattern to be MLMLML (Wolff, 2014).

The projection map shown in this study for cells that connect the PB to layer 1 of the FB illustrates conclusively the projection pattern between these domains. Obtaining an accurate map between the PB and layers 2 and 3 is difficult given the greater overlap between arbors of cells in these two layers, but the projection patterns observed between the PB and layers 2 and 3 of the FB are consistent with the PB:FBℓ1 map (Wolff, 2014).

As noted above, distribution of information is not always restricted to the subdomains of each central complex structure. When information is shared between neighboring domains (or alternating domains, in the case of the cells that arborize in the dorsal or ventral gall), generally only a small portion of the arbor is shared. The functional significance of these zones of overlap remains to be determined (Wolff, 2014).

Connections between central complex structures are remarkably restricted. For example, of those neurons that arborize in the PB and FB, only FB layers 1, 2, and 3 connect to the noduli, and only to NO2 and NO3. The only link between the PB and NO1 is via the ellipsoid body, so whereas NO2 and NO3 can be considered to work in conjunction with the FB to elicit a behavior based on output from the PB, NO1 cooperates with the EB to elicit a behavior based on output from the PB. In fact, communication is even more specific: layer 3 of the FB communicates directly only with NO2, layer 2 directly only with the anterior subcompartment of NO3, and layer 1 directly only with NO3M and NO3P. Furthermore, the cells in G1 do not communicate directly with the noduli at all—neither via the FB nor via the EB. The absence of direct connections between the PB and upper layers of the FB is also noteworthy. This streamlined and highly segregated network of connections within and between central complex structures suggests a high degree of regional specialization in function for the components of the central complex (Wolff, 2014).

The roles of central complex structures, their subdomains, and related neuropils are poorly understood. While functions remain largely unknown, many circuits described in this study are informative in various other ways. For example, some identify commonalities in function between neuropil subregions, such as FBℓ2 and NO3A, which are both arborized by a common neuron. Other circuits reveal spatial segregation between neuropils. The most intriguing instance is the exclusive relay of information between the ventral gall and even-numbered glomeruli and the dorsal gall and odd-numbered glomeruli, which demonstrates that both information and information flow can be spatially segregated from the glomeruli to the gall. It will be interesting to learn the functional role of the gall and why it segregates a portion of the information it receives and sends, as well as what sort of behavioral response requires this rigidly alternating spatial distribution in the PB. Finally, the absence of connections between neuropils may prove informative in functional studies. For example, G1 is distinct from G2–G8 in that it lacks direct connections with the noduli, and NO1 is distinct from NO2 and NO3 in that it communicates with the PB via the EB rather than the FB, raising the questions of what behaviors G1 does and does not contribute to, and what the differences are in behavioral outputs from NO1 and NO2/NO3 (Wolff, 2014).

The observation that there are 18 glomeruli in the Drosophila PB has significant implications for both the architecture and evolution of the Drosophila brain with respect to the brains of other neopterans. Although the suite of genetic tools available in locusts, bees, beetles, and other insects does not yet include MCFO, improvements in imaging and histology may prove sufficient to reevaluate the number of glomeruli in these species, given that glomeruli can be accurately counted in brains that are labeled only with nc82. Either some or all of these species also have 18 glomeruli, or an extra pair of glomeruli arose in Drosophila. The latter may be unlikely but would raise some intriguing possibilities about how the anatomical correspondence and circuitry between glomeruli in the PB and equivalent vertical partitions in the FB and EB PB circuits may differ between flies and other insects thought to have the same basic cellular composition and organization within the central complex, and how the geometric coordinates would then have had to shift along the axis of the PB to effect accurate behavioral responses (Wolff, 2014).

Neuronal constituents and putative interactions within the Drosophila ellipsoid body neuropil

The central complex (CX) is a midline-situated collection of neuropil compartments in the arthropod central brain, implicated in higher-order processes such as goal-directed navigation. This study provides a systematic genetic-neuroanatomical analysis of the ellipsoid body (EB), a compartment which represents a major afferent portal of the Drosophila CX. The neuropil volume of the EB, along with its prominent input compartment, called the bulb, is subdivided into precisely tessellated domains, distinguishable based on intensity of the global marker DN-cadherin. EB tangential elements (so-called ring neurons), most of which are derived from the DALv2 neuroblast lineage, predominantly interconnect the bulb and EB domains in a topographically organized fashion. Using the DN-cadherin domains as a framework, this connectivity was first characterized by Gal4 driver lines expressed in different DALv2 ring neuron (R-neuron) subclasses. 11 subclasses were identified, 6 of which correspond to previously described projection patterns, and 5 novel patterns. These subclasses both spatially (based on EB innervation pattern) and numerically (cell counts) summate to the total EB volume and R-neuron cell number, suggesting that this compilation of R-neuron subclasses approaches completion. EB columnar elements, as well as non-DALv2 derived extrinsic ring neurons (ExR-neurons), were also incorporated into this anatomical framework. Finally, the connectivity between R-neurons and their targets was addressed, using the anterograde trans-synaptic labeling method, trans-Tango (Omoto, 2018).

The central complex (CX) is an evolutionarily conserved, higher-order neuropil in the arthropod brain thought to integrate sensory and motor information to coordinate and maintain locomotor behavior, thus enabling appropriate navigation. Drosophila mutations that produce structural abnormalities in CX neuropils result in flies with deficiencies in walking and flight. More targeted manipulations, such as silencing of specific CX neuron subclasses, compromise vision-based memories associated with spatial orientation and location. Similar themes emerge from anatomical, electrophysiological, and behavioral studies investigating the CX in other insects. In the cockroach CX, for example, single unit activity correlated with changes in locomotor intensity, turning behavior, or heading direction have been identified. In addition, electrical stimulation of CX neurons in the freely walking cockroach has yielded direct evidence linking CX activity to downstream locomotor output. In other insects, such as locust, cricket, monarch butterfly, and dung beetle, neurons in the CX are tuned to celestial visual cues such as the sun or pattern of polarized skylight. These cues provide the stable environmental signals required to accurately derive relative heading information for short or long range navigations (Omoto, 2018).

The CX consists of four neuropil compartments: the upper (CBU) and lower (CBL) halves of the central body (CB), protocerebral bridge (PB), and paired noduli (NO). In Drosophila, the upper and lower halves of the CB are designated as the fan-shaped body (FB) and ellipsoid body (EB), respectively (see General overview of the ellipsoid body (EB): neuronal interactions and compartmentalization). Recently, the asymmetrical body, a paired neuropil located ventral of the FB and adjacent to the NO, has been proposed as a fifth neuropil compartment of the CX. These neuropil compartments are largely formed by two orthogonally arranged neuronal populations: (1) columnar (small-field) neurons which interconnect the CX compartments along the antero-posterior axis; (2) tangential (large-field) neurons which provide input from lateral brain neuropils to the CX. Terminal arborizations of these neurons define distinct vertical columns and horizontal layers that can be visualized by markers for synaptic or cell adhesion proteins that globally label, but exhibit variable density in, the neuropil. Based on Bruchpilot immunostaining, seven layers were identified in the Drosophila CBU (=FB). The CBL (=EB) also exhibits a layered organization. In Drosophila, this compartment undergoes a morphogenetic transformation during pupal development, whereby the lateral ends of the originally bar-shaped EB primordium bend ventrally to adopt a toroidal arrangement. As a result, tangential neurons of the EB display a circular shape, and hence were called 'ring neurons'. Likewise, layers within the EB are annuli, rather than horizontal slabs. Based on labeling with DN-cadherin, this study has defined five distinct annular domains, termed anterior (EBa), inner and outer central (EBic and EBoc), and inner and outer posterior (EBip and EBop) domains (Omoto, 2018).

Clonal studies in Drosophila show that the neuronal architecture of the CX is organized into lineage-based modules, a ground plan that is likely conserved across insects. A lineage refers to the set of sibling neurons derived from an individual neural progenitor called a neuroblast, and the entire central brain is generated from a fixed number of approximately 100 of such neuroblasts. Four lineages (DM1-4) give rise to the large number of columnar neurons of the CX. The great diversity observed among these neurons is achieved via temporal patterning of molecular determinants in dividing progenitors. Lineages giving rise to the tangential neurons of the CX have been characterized morphologically, but have not yet received much attention experimentally. The most notable exception is lineage DALv2/EBa1 (henceforth called DALv2), that generates ring neurons of the EB. Ring neurons project their axons to distinct annular domains of the EB, and typically possess short globular dendrites ('microglomeruli') in the bulb (BU), a neuropil compartment located laterally adjacent to the EB. The BU encompasses three main partitions [anterior (BUa), superior (BUs), and inferior (BUi) bulb] that are associated with different annular domains of the EB. Furthermore, the BUs and BUi appear to be divisible into anterior (aBUs/aBUi) and posterior (pBUs/pBUi) regions. Input to the BU is provided by neurons of two additional lineages, DALcl1 and DALcl2 (also called AOTUv3 and AOTUv4, respectively). As part of the anterior visual pathway, DALcl1/2 form so-called tubercular-bulbar (TuBu) neurons which project from the anterior optic tubercle to the BU, relaying visual information to ring neurons and thereby the CX as a whole. TuBu neurons form two lineally segregated parallel channels, with DALcl1 establishing connections with ring neurons located in the peripheral domain of the EB via the BUs, and DALcl2 with central ring neurons via the BUi (Omoto, 2018).

Detailed functional studies are beginning to shed light on the circuitry involving ring neurons and their TuBu afferents and columnar efferents. Two-photon calcium imaging has revealed a discrete focus of neural activity, or 'bump,' within a population of columnar neurons ('E-PGs') that interconnect the EB, PB, and gall (GA) of the LAL. E-PG neurons encode an internal compass representation via the activity bump, which dynamically tracks the fly's heading. Additional columnar neuron populations that interconnect the PB, EB, and NO, called P-EN neurons, compute the animals' heading by controlling the movement of the bump in the clockwise or counter-clockwise direction. These findings suggest that the EB may operate as a critical hub in the CX, acting as an interface between neurons that transmit and distribute sensory information (TuBu and ring neurons), and circuits that encode and update a representation of heading direction (E-PG and P-EN neurons). In addition, internal state information is likely integrated into the EB network by additional ring neurons subclasses that signal physiological needs such as sleep and hunger drive (Omoto, 2018).

To make further inroads in understanding how the EB circuitry operates, a comprehensive knowledge of ring neurons and their upstream and downstream connectivity is required. Ultimately, a comprehensive analysis of single cells and their synaptic contacts on the light and electron microscopy level will yield complete coverage of the EB wiring diagram, and certainly inform understanding of how EB-related computations are implemented. However, a current description of subclass-specific projection patterns using genetic driver lines provides a framework to posit inter-class neural interactions that can then be tested physiologically and/or behaviorally, and will assist future efforts for such high-resolution anatomical maps. To this end, this study sought to expand on previous works using this genetic-anatomical approach to more thoroughly describe the EB neuropil. Gal4 driver lines that label ring neuron subclasses were screened and subsequently distinguished from each other based on defined criteria. Many drivers label populations corresponding to previously identified ring neuron subclasses, in addition to several, yet uncharacterized populations. The novel subclasses were given new names per the historical nomenclature system. Columnar elements were also incorporated into this anatomical framework. Based on the domain innervation pattern of each line, putative interactions between elements within the EB network are proposed. Finally, ring neuron drivers were subjected to the anterograde trans-synaptic labeling method, trans-Tango. Ring neurons occupying central domains of the EB commonly display homotypic interactions, such that neurons of a given subclass predominantly form synaptic interactions with other neurons in the same subclass. On the other hand, ring neurons occupying the peripheral domains typically display a larger degree of output into the columnar network. This highlights a fundamental difference in the connectivity, and potentially the functions, of ring neurons in different domains (Omoto, 2018).

This work serves to build upon previous anatomical studies by further clarifying the neuronal architecture of the Drosophila EB. Five definitive DN-cadherin domains constituting the EB neuropil provide fiducial landmarks with which neuron classes can be placed into spatial context. Based on this framework, this study reports several novel ring neuron subclasses and proposes potential interactions between ring, columnar, and neuromodulatory neurons in the EB. Lastly, putative postsynaptic partners of R-neurons were experimentally mapped using trans-Tango, revealing insight into how information may be distributed throughout the EB and the rest of the CX. In addition to the neuroanatomical description of different populations, the identification of driver lines enables genetic access to label or manipulate these populations. This provides an entry point for future studies to probe the functional properties of each class and test the interactions proposed herein. The following summarizes the primary findings, speculates on the functional significance of CX wiring principles, and places this study into a developmental-neuroanatomical context with previous works in Drosophila and homologous structures in other insects (Omoto, 2018).

The CX is viewed as a critical hub for goal-directed navigational behavior in insects. Streams of sensory information from different modalities must converge onto this center of sensorimotor integration to guide navigational decisions based on current trajectory, learned information, and motivational state. Central to this notion was the identification of a stable compass representation that tracks the flies heading in the E-PG neuron population. The robustness of this neural correlate of angular orientation, manifested as a single calcium activity 'bump' that moves around the EB, depends on both visual and proprioceptive cues (Seelig, 2015). Heavily relying upon studies in other insect species as a basis for comparison, recent progress has been made toward identifying the neural pathways that transmit sensory information to the Drosophila CX, with visual input being the most well characterized. The fly CX receives visual information via the anterior visual pathway (AVP), a circuit defined by three successive layers. Information is transmitted from the optic lobe medulla to the anterior optic tubercle, from the tubercle to the bulb (BU), and from there to the EB, via medullo-tubercular (MeTu), tuberculo-bulbar (TuBu), and DALv2 ring neurons (R-neurons), respectively. Parallel ensembles of TuBu neurons terminate in a topographically organized fashion onto the microglomerular dendrites of distinct R-neuron subclasses within the BU. Specific computations are implemented across successive layers in this pathway, such as the integration of recent visual history and self-motion, which may inform downstream behavior. Ring neurons transmit processed visual information concerning features and landmarks to the EB, likely as a stable allothetic reference to guide bump dynamics in E-PG neurons. The interaction between tangential elements of the EB and columnar neurons such as E-PG neurons has been suggested in other insects, and confirmed by GFP reconstitution across synaptic partners (GRASP) in Drosophila. Indeed, this study provides further evidence via trans-Tango that R2 neurons, which are tuned to visual features, provide direct presynaptic input to E-PG neurons. The calcium activity bump in E-PG neurons also shift in total darkness, demonstrating the existence of a proprioceptive input channel that can update the heading representation in the EB in the absence of visual input. It is posited that transmission of idiothetic cues to the CX is mediated in part by R1 and/or ExR4 neurons, as their neurite distribution and polarity suggests feedback from the LAL, a proposed motor signaling center (Omoto, 2018).

Conceivably, the information received by different R-neuron subclasses is transmitted to their ring-shaped neurites, and is processed via connections within the same subclass (homotypic interactions) and/or between subclasses (heterotypic interactions), the extent of which depends on the R-neuron subclass in question. As such, the R-neuron system likely displays recurrent connectivity to enable persistent activity required for memory processes, as has been shown for mushroom body circuits that support courtship memory. Indeed, inner ring neurons (likely R3d and R3p), which comprise a critical nucleus of visual working memory, display prominent homotypic interactions. Future work to define the mechanisms underlying intra-subclass interactions and experiments to perturb them, are required to assess the functional significance of these homotypic interactions (Omoto, 2018).

R-neurons, particularly subclasses of which occupy peripheral EB domains, provide input to several different columnar neuron populations. This study provides novel insight into the nature of subclass-specific, input-output communication between the ring and columnar networks. An important avenue of future work will be to elucidate the tuning properties of each R-neuron subclass and determine the contribution of each input to compass representation. Presumably, R-neuron subclasses that provide prominent, direct input to E-PG neurons, such as R2 or R4m, would exhibit the most influence over compass representation (Omoto, 2018).

Circuit flexibility is likely facilitated by neuromodulatory input on a moment-by-moment basis, which may reconfigure information flow through the network and thus the output of the system. Neuromodulation would likely occur at multiple processing stages, as evidenced by the wide-spread neurites of dopaminergic neurons. For example, a single PPM3 neuron, innervates the GA/LAL, BU, and EBoc/op. It is envisaged that neurite-specific signaling and plasticity may regulate distinct processing nodes, akin to what has been demonstrated for dopaminergic neurons that encode protein hunger. Similarly, 5-HT may also influence R-neuron activity as projections from the serotonergic neurons, ExR3 [corresponding to the posterior medial protocerebrum, dorsal cluster (PMPD)], most prominently innervate EBic. The effect of serotonin may be receptor and circuit specific; distinct 5-HT receptor isoforms are differentially expressed in specific R-neuron subclasses (Omoto, 2018).

For clarity, the five EB domains defined by the global marker DN-cadherin should be reconciled with previously used anatomical terminology of the EB. Frontal sections of the EB at different anteroposterior depths shows that DN-cadherin domains are distinct, annular entities. These domains correspond to 'layers' in other insects, and have sometimes been also referred to as layers in Drosophila as well. Therefore, N-cadherin EB domains are synonymous with layers. Each domain is best represented using a 'dorsal standard view': a horizontal section through the EB containing a lengthwise perspective of the EB canal. From this standard view, the N-cadherin domains are also clearly organized along the anteroposterior axis. Three anteroposterior subdivisions of the EB have been referred to as 'shells,' in line with terminology used for the FB. It is proposef that the anterior most shell encapsulates the anterior domain of the EB (EBa), and therefore consists of only one layer. The intermediate shell encapsulates the inner central (EBic) and outer central (EBoc) domains, and consists of two layers. Finally, the posterior shell encapsulates the inner posterior (EBip) and outer posterior (EBop) domains, and consists of two layers. For example, P-EN neurons occupy the EBop domain, which resides in the posterior EB shell (Omoto, 2018).

Previously, four substructures denoted as 'rings' [EBA (Anterior), EBO (Outer), EBC (Center), EBP (Posterior)], were based on anti-disks large (DLG) immunostaining and roughly correspond to the DN-cadherin domains. Like the DN-cadherin domains, each 'ring' was proposed to contain specific R-neuron subclasses. Based on the ring neuron subclasses to comprise each 'ring', it is inferred that EBA corresponds to EBa and EBic in the current classification system. Furthermore, EBO is EBoc, EBC is EBip, and EBP is EBop (Omoto, 2018).

How does the annular domain structure of the Drosophila EB compare to the lower division of the central body (CBL) described for other insects? Similar to the EB, the CBL represents a multilayered neuropil compartment formed by the neurite contributions of tangential and columnar elements. In insects such as locust (Schistocerca gregaria), which will be used as the primary basis for comparison in the following, the kidney bean or sausage-shaped CBL corresponds to the torus-shaped EB in Drosophila. In locusts, the CBL is effectively located ventrally of the upper division of the central body (CBU), whereas the homologous structures in Drosophila (EB and FB, respectively) are arranged in an antero-posterior fashion. This difference is reflective of a 60° anterior tilt of the locust neuraxis, as evidenced by the peduncle, which extends horizontally in flies but is oriented almost vertically in the locust. In the dung beetle (Scarabaeus lamarcki) and monarch butterfly (Danaus plexippus), the CBL are also sausage-shaped, but the neuraxis orientation is like that of Drosophila. Differences in neuraxis orientation influence the comparison between the internal architecture of the locust CBL and fly EB. The locust CBL is subdivided along the dorso-ventral axis into six horizontal layers (although not stacked seamlessly on top of one another). Based on the expression of global markers, the Drosophila EB is divided into toroidal domains (EBa/ic/oc/ip/op). Considering the tilt in neuraxis, it is posited that dorsal strata (layers 1-2) of the locust CBL roughly correspond to more posterior domains (EBip/op) of the fly EB, whereas ventral strata (layers 3-6) correspond to more anterior EB domains (EBa/ic/oc). Corroborating this notion is the fact that fly P-EN neurons innervate EBop, and the locust homologs (called CL2 neurons) innervate dorsal layers of the CBL (Omoto, 2018).

The EB and its domains, as well as other structures of the CX, are established by the neurite contributions of distinct neuronal populations. How is the neuronal diversity and connectivity of the CX developmentally established? The CX, and brain in general, is organized into structural-genetic modules called lineages; a lineage comprises the set of sibling neurons derived from an individual neural progenitor (neuroblasts). Each neuroblast forms a spatially discrete cluster of neurons with shared wiring properties; sibling neurons extend a limited number of fasciculated axon tract(s) and innervate specific brain compartments. Most brain lineages are 'type I' neuroblast lineages, whose neuroblasts undergo a series of asymmetric divisions each of which renews the neuroblast and produces a ganglion mother cell. Columnar neurons of the CX are generated from four type II lineages which are larger and more complex than type I, with neuroblasts first producing a set of intermediate progenitors which in turn, give rise to ganglion mother cells (Omoto, 2018).

While the columnar neurons contributing to the EB are derived from type II lineages, the tangential elements (R-neurons) are largely derived from a single paired type I neuroblast, forming the lineage DALv2 (also called EBa1). Neurons of the DALv2 lineage have been studied in developmental contexts in a number of previous works. Production of secondary neurons by DALv2 begin around 24 h after hatching. According to Kumar (2009), one of the DALv2 hemilineages undergoes apoptotic cell death, implying that the DALv2 R-neurons forming the adult EB represent a single hemilineage. Cursory heat-shock inducible single-cell clonal analysis carried out in the present study suggests that distinct R-neuron subclasses are born during specific time windows and therefore represent sublineages of DALv2 (Figure 4). Thus, clonal induction shortly after the onset of secondary neuroblast proliferation (20-48 h after hatching) yielded exclusively outer R-neurons of the R4m subclass. At increasingly later time points, these types of clones become rare, and disappeared entirely at induction times after 96 h. The converse is the case for inner ring neurons (R3d/m), which could be induced in increasing numbers with later time points of induction. Given that only a fraction of the overall number of R-neuron subclasses was represented among clones analyzed in this study, additional studies are required to settle the exact birth order of different R-neuron subclasses (Omoto, 2018).

The following provides a brief historical account of ring neuron definitions, attempt to resolve discrepancies in the literature when possible, and provide rationale for naming conventions used in this work (Omoto, 2018).

The R-neuron type corresponds to ring neurons of the DALv2 lineage, with four R-neuron subclasses described in an initial study (R1-4). Two other ring neuron types were designated as 'extrinsic ring neurons' (ExR-neurons), based on large projections outside of the EB; in this study, with this feature were pooled into a single type, the ExR-neurons. The first described type of extrinsic R-neuron (the ExR1 subclass) likely corresponds to helicon cells. The second type (the ExR2 subclass), due to its innervation of the caudal EB, ExR2 may correspond to the EBop-innervating PPM3 dopaminergic neuron. The serotonergic neurons that innervate the EB, corresponding to the PMPD neurons, designate in this study as ExR3. Therefore, ExR1-3 are posteriorly localized ExR-neurons, likely deriving from the DM3-6 lineages. Due to its wide arborization and non-DALv2 based origin, ring neurons of lineage BAmv1, with perikarya in the anterior cortex, were designated in this study a fourth type of ExR-neuron (ExR4); the possibility cannot be excluded that ExR2 from a previous study may correspond to ExR4-neurons, as they too innervate the caudal EB. Furthermore, the 'P'-neurons, described a previous study as having ventrally localized cell bodies and also innervate the caudal EB, likely correspond to what this study designates as ExR4-neurons (Omoto, 2018).

Driver line c105 was found in an earlier study to label R1 neurons, due to their centrifugal arborization pattern, inner ring localization, and extension into the posterior layers of the EB. However, c105-positive R1 neurons exhibit ventrally projecting neurites into the LAL and lack BU microglomeruli, in contrast to what was defined as R1 in a previous study. Due to R1 being the predominant designation this R-neuron subclass thereafter, this classification as R1 is retained in the current study (Omoto, 2018).

In more recent studies, the driver 38H02-Gal4 has been described as labeling R4 (or an R4-subset), in several studies. 38H02-Gal4 does in fact label R4m (based on BUa microglomeruli and centripetal EBoc innervation pattern), but also strongly labels R5. Two other drivers, 15B07-Gal4 and 28D01-Gal4, were used to target EB neurons required for visual-thermal associations in place learning, and were described as labeling 'R1 and R4,' or 'R1 alone,' respectively. Anatomical re-assessment of these drivers reveals that 15B07-Gal4 labels R3d, R3p, and R4d, whereas 28D01-Gal4 labels a neuron subclass indicative of R3m (Omoto, 2018).

In summary, the dorsal view of the EB in conjunction with DN-cadherin immunostaining provide criteria to more definitively identify ring neuron subclasses for future studies. The model organism Drosophila offers unique advantages to examine the circuit motifs that support the broadly relevant computations underlying the processes attributed to the CX; (1) the neurons comprising the CX are spatially and numerically confined, (2) genetic access to label, assess connectivity between, or functionally manipulate, specific neuron types within it, and (3) amenability to electro- or optophysiological recordings, oftentimes in the behaving animal. To fully leverage these advantages, this study provides a systematic description of the ring neuron subclasses comprising the EB, genetic tools to access them, and provide insight into their interactions with other neurons of the CX (Omoto, 2018).

Lineage-specific determination of ring neuron circuitry in the central complex of Drosophila

The ellipsoid body (EB) of the Drosophila central complex mediates sensorimotor integration and action selection for adaptive behaviours. Insights into its physiological function are steadily accumulating, however the developmental origin and genetic specification have remained largely elusive. This study identified two stem cells in the embryonic neuroectoderm as precursor cells of neuronal progeny that establish EB circuits in the adult brain. Genetic tracing of embryonic neuroblasts ppd5 and mosaic analysis with a repressible cell marker identified lineage-related progeny as Pox neuro (Poxn)-expressing EB ring neurons, R1-R4. During embryonic brain development, engrailed function is required for the initial formation of Poxn-expressing ppd5-derived progeny. Postembryonic determination of R1-R4 identity depends on lineage-specific Poxn function that separates neuronal subtypes of ppd5-derived progeny into hemi-lineages with projections either terminating in the EB ring neuropil or the superior protocerebrum (SP). Poxn knockdown in ppd5-derived progeny results in identity transformation of engrailed-expressing hemi-lineages from SP to EB-specific circuits. In contrast, lineage-specific knockdown of engrailed leads to reduced numbers of Poxn-expressing ring neurons. These findings establish neuroblasts ppd5-derived ring neurons as lineage-related sister cells that require engrailed and Poxn function for the proper formation of EB circuitry in the adult central complex of Drosophila (Bridi, 2019).

The Drosophila central complex is a composite of midline neuropils that include the protocerebral bridge, the fan-shaped body, the ellipsoid body (EB), the noduli and the lateral accessory lobes. These neuropils are interconnected in a modular way whereby columnar projection neurons leading to and from the central complex connect all its components that are themselves intersected by tangential layers of neural processes, which together form functional modules, each representing a segment of sensory space. Functional studies have identified specific roles for the central complex in higher motor control, courtship and orientation behaviours, visual memory and place learning, as well as sleep, attention, arousal and decision-making (Bridi, 2019).

In contrast to expanding insights into the physiological role of the central complex in regulating behaviour, its developmental origin and genetic specification has largely remained elusive. Earlier work described a primordial central complex at late larval/early pupal stages, which becomes fully formed by 48 h after puparium formation. Genetic studies have identified several alleles of as-yet unidentified genes, as well as orthodenticle, Pax6/eyeless, Pox neuro (Poxn), tay-bridge, roundabout, Pdm3 and semaphorin as genes involved in normal formation of central complex sub-structures (Bridi, 2019).

This study investigate the origin and formation of EB ring neurons R1-R4 in the developing and adult brain of Drosophila. Bilateral symmetric neuroblasts ppd5 were identified in the embryonic procephalic neuroectoderm as founder cells of neuronal progeny that constitute R1-R4 subtypes of tangential ring neurons in the adult EB. Mutant analysis and targeted genetic manipulations reveal a lineage-specific requirement of engrailed (en) and Poxn activity that determines the number and identity of ppd5-derived progeny and their EB ring-specific connectivity pattern in the adult central complex of Drosophila (Bridi, 2019).

Previous studies suggested the Drosophila EB -- as part of the central complex -- develops from precursor cells that differentiate during larval development and during pupal stages generate the EB neuropil. Lineage analysis demonstrates that at least part of its origin can be traced back to the embryonic procephalic neuroectoderm. This study identified Engrailed-expressing neuroblasts ppd5 as embryonic stem cells that give rise to Poxn-expressing progeny, which ultimately differentiate into EB ring neurons. Genetic tracing with en-Gal4 identified R1-R4 ring neurons, suggesting that embryonic neuroblasts ppd5 are the major source of Poxn-expressing progeny leading to EB ring neurons detected in this study. Based on their position, morphology, gene expression patterns and axonal fasciculation, these findings suggest that ppd5-derived larval lineages correspond to previously described larval lineages variously called 'EB-A1/P1', 'DALv2/3', 'MC1' or 'DM'. It was previously demonstrated that these larval lineages express Poxn and give rise to gamma-amino butyric acid (GABA)-ergic ring neurons in the central complex of the adult brain. It therefore is proposed to (re-) name them according to their embryonic origin (Bridi, 2019).

Subclass-specific Gal4 lines together with Poxn expression identifies these lineage-related, ppd5-derived sister cells as R1-R4 ring neurons. Moreover, brain-specific Poxn-Gal4 mediated labelling identifies ring neurons and their axonal projections covering all layers of the EB neuropil, thus suggesting neuroblasts ppd5 give rise to the majority, if not all, of ring neuron subtypes. The ontogenetic relationship between Engrailed-expressing neuroblasts ppd5 and Poxn-expressing EB ring neurons is affirmed by the fact that en-Gal4 and Poxn-Gal4-targeted RNAi-mediated knockdown of Poxn causes similar EB neuropil-specific phenotypes. Together, these data establish that ppd5-derived progeny are clonal units contributing to the EB ring neuron circuitry in the central complex in Drosophila (Bridi, 2019).

How are these units specified? In both insects and mammals, the patterning and specification of neural lineages is regulated by genetic programs from neurogenesis to neuronal differentiation. This study in Drosophila shows that the development and specification of EB-specific circuit elements is likewise dependent on the lineage-specific activity of developmental regulatory genes. Early formation and maintenance of Poxn-expressing ppd5 lineages requires engrailed function as revealed with a deficiency removing both engrailed orthologues, en and invected. Previous studies showed that, engrailed/invected are required for the specification of neuroblast identity in the developing nervous system, suggesting that engrailed is also required for the specification of ppd5. A later, lineage-specific function of engrailed was found in the specification of ring neuron numbers, onsistent with its transient expression in Poxn+ lineages in the embryonic brain but not at later developmental stages nor in adult ring neurons. engrailed codes for a homeodomain transcription factor mediating the activation and suppression of target genes, regulatory interactions that are required for neural lineage formation and specification in the procephalic neuroectoderm. In contrast, no function for Poxn in embryonic brain development has been reported, suggesting that Poxn is only during later stages of development required for lineage and/or neuronal specification in the central brain (Bridi, 2019).

Indeed, experiments identify a postembryonic requirement of Poxn in the specification of ppd5-derived progeny. Previous studies showed that zygotic mutations of Poxn perturb EB neuropil formation, in that presumptive ring neurons are unable to project their axons across the midline and as a consequence, the EB ring neuropil is not formed. In the present study, en-Gal4-targeted knockdown of Poxn reveals Engrailed-expressing cells that project across the midline and form a ring-like neuropil instead of their normal ipsilateral projections to the SP. Significantly, no ppd5-derived GFP-labelled cells were observed that project ipsilaterally towards the SP, neurons that are normally detectable with en-Gal4 targeted GFP expression in the adult brain. Furthermore, en>Poxn-IR-targeted, EB neuron-like projections do not form a torroidal ring but are rather characterised by a ventral cleft. These en>Poxn-IR cells aberrantly retain Engrailed expression even though their axonal projection and connectivity pattern clearly identify them as ring neurons that are normally devoid of Engrailed but instead express Poxn. Together these data suggest that, based on their morphology, Engrailed expression, axogenesis and ring-specific projection patterns, en>GFP cells normally projecting to the SP have been transformed into EB ring neurons in en>mCD8::GFP,Dcr2,Poxn-IR flies (Bridi, 2019).

The resulting additional ring neurons in en>mCD8::GFP,Dcr2,Poxn-IR flies are accompanied with a ventrally open EB ring neuropil. A comparable phenotype is seen in brains of Poxn(757)>Poxn-IR flies which are characterised by an increased number of Poxn(757)-Gal4-targeted ring neurons, suggesting that increasing numbers of EB ring neurons lead to an arch-like neuropil reminiscent of the arch-like EB seen in the majority of arthropods. In support of this notion, previous work has demonstrated that in vivo amplification of ppd5-derived progenitor cells can lead to fully differentiated supernumerary GABAergic ring neurons that form functional connections often characterised by a ventrally open EB ring neuropil. Together, these data identify differential roles of Poxn activity during neuroblast lineage formation, in that Poxn is required for cell identity determination of ppd5-derived progeny, as well as for the specification of cell numbers and terminal neuronal projections of EB ring neurons (Bridi, 2019).

These Poxn functions in ppd5-derived brain lineages are reminiscent of Poxn activity in the peripheral nervous system (PNS) which mediates the specification of sensory organ precursor (SOP) cell lineages giving rise to external sense organs, the tactile and gustatory bristles, respectively. In these SOP lineages, differential Poxn activity determines progeny fate between chemosensory (gustatory) or mechanosensory (tactile) neuronal identities. Furthermore, SOP lineage-specific Poxn function specifies the number of these neurons and their connectivity pattern. The apparent functional commonalities between Poxn-mediated specification of ppd5 neuroblast-derived lineages in the brain and SOP lineages in the PNS, suggest that evolutionarily-conserved mechanisms underlie the development and specification of clonal units as cellular substrates for neural circuit and sensory organ formation (Bridi, 2019).

The cytoarchitecture of both the insect and mammalian brain are characterised by neural lineages generated during development by repeated asymmetric divisions of neural stem and progenitor cells. These ontogenetic clones are thought to constitute building blocks of the insect and mammalian brain. In support of this notion, lineage-related progeny constitutes sets of circuit elements of the mushroom bodies and antennal lobes in Drosophila. Clonal relationship also characterises the lineage-dependent circuit assembly in the mammalian brain, where stem cell-like radial glia give rise to clonally-related neurons that synapse onto each other, as has been shown for cortical columns and GABAergic interneurons in the neocortex and for striatal compartments of the basal ganglia. The current study in Drosophila shows that a pair of bilateral symmetric, engrailed-expressing embryonic stem cells, neuroblasts ppd5, give rise to R1-R4 subtypes of tangential ring neurons that contribute to the layered EB neuropil. Thus, ppd5 neuroblast lineages constitute complete sets of circuit elements intrinsic to the adult central complex in Drosophila (Bridi, 2019).

It has been suggested that clonal expansion of neural lineages contributed to the evolution of complex brains and behaviours. Key to this hypothetical scenario are ancestral circuit elements in the form of genetically encoded stem cell-derived clonal units, like the ones described in the current study. In such a scenario, lineage-related ancestral circuit elements might have been multiplied and co-opted or diversified during the course of evolution. Multiplication and co-option have been suggested for the evolution of the multiple-loop architecture of the basal ganglia that allows processing of cognitive, emotional and motor information. In line with this hypothesis, quantitative control of the transcription factor Prospero is sufficient to cause clonal expansion of ring-neuron circuitry in Drosophila (Shaw, 2018), which has been implicated in cognitive and motor information processing and resembles extensive correspondences to vertebrate basal ganglia, ranging from comparable developmental genetics to behavioural manifestations and disease-related dysfunctions (Bridi, 2019).

In contrast to multiplication and co-option, the diversification of stem cell lineages can equally contribute to neural circuit evolution. The current results identify differential and tightly regulated spatio-temporal functions of engrailed and Poxn that lead to the differentiation of ppd5 progeny into hemi-lineage specific identities in the adult brain. Loss of engrailed affects the formation of precursors cells, whereas its lineage-specific knockdown affects the number of Poxn expressing ring neurons. Correspondingly, en-Gal4-driven lineage-specific knockdown of Poxn results in an identity transformation of Engrailed-expressing neurons in the adult brain in that they no longer project to the SP, but instead reveal an EB ring-neuron identity. These data indicate a binary switch of hemi-lineage identities as the result of a feed-forward mechanism between engrailed and Poxn. engrailed may activate transcription (directly or indirectly) of Poxn, which in turn represses engrailed to permit differentiation of R1-R4 neurons, thereby regulating the specification of neuronal identities in ppd5 hemi-lineages. This hypothesis is consistent with lineage tracing and MARCM experiments, as well as the transient expression of engrailed in embryonic ppd5 lineages but not in adult EB ring neurons. However, further studies are required to elucidate the nature and extend of these putative regulatory interactions between Engrailed and Poxn (Bridi, 2019).

In summary, these findings establish a causal relationship between a pair of bilateral symmetric embryonic stem cells, neuroblasts ppd5 and the lineage-related assembly of their EB ring neuron progeny as structural units of the central complex in Drosophila. Based on these observations it is proposed that amplification and diversification of ontogenetic clones together with the repurposed use or exaptation of resulting circuitries, is a likely mechanism for the evolution of complex brains and behaviours (Bridi, 2019).

Developmentally arrested precursors of pontine neurons establish an embryonic blueprint of the Drosophila central complex

Serial electron microscopic analysis shows that the Drosophila brain at hatching possesses a large fraction of developmentally arrested neurons with a small soma, heterochromatin-rich nucleus, and unbranched axon lacking synapses. All 802 'small undifferentiated' (SU) neurons were digitally reconstructed and assigned to the known brain lineages. By establishing the coordinates and reconstructing trajectories of the SU neuron tracts, a framework is provided of landmarks for the ongoing analyses of the L1 brain circuitry. To address the later fate of SU neurons, focus was placed on the 54 SU neurons belonging to the DM1-DM4 lineages, which generate all columnar neurons of the central complex. Regarding their topologically ordered projection pattern, these neurons form an embryonic nucleus of the fan-shaped body ('FB pioneers'). Fan-shaped body pioneers survive into the adult stage, where they develop into a specific class of bi-columnar elements, the pontine neurons. Later born, unicolumnar DM1-DM4 neurons fasciculate with the fan-shaped body pioneers. Selective ablation of the fan-shaped body pioneers altered the architecture of the larval fan-shaped body primordium but did not result in gross abnormalities of the trajectories of unicolumnar neurons, indicating that axonal pathfinding of the two systems may be controlled independently. This comprehensive spatial and developmental analysis of the SU neurons adds to understanding of the establishment of neuronal circuitry (Andrade, 2019).

The central complex (CX) of the insect brain plays an important role in a variety of different behaviors, including the fine control of motor movement and spatial orientation. Recent studies indicate that the CX harbors dynamic neural activity that integrates the animal's external and internal environment. Anatomical studies have started to reveal the neuronal connectivity that underlies CX function. The CX is comprised of four major compartments, including (from anterior to posterior) the ellipsoid body (EB), fan-shaped body (FB) with noduli (NO), and protocerebral bridge (PB). CX circuitry is dominated by an orthogonal scaffold of transversally oriented ('tangential') widefield neurons, and longitudinally oriented columnar small field neurons. Tangential neurons, whose fibres are directed parallel to the length axis of the CX neuropils, provide input to the CX from other brain areas. Best understood among these input neurons are the TL-neurons in locust and their Drosophila counterparts, the R-neurons, that conduct retinotopically ordered visual information to the ellipsoid body. Columnar neurons, which interconnect the different CX neuropils along the antero-posterior axis, are characterized by highly localized dendritic and axonal endings in narrow volumes ('columns') of the respective compartments. Most classes of columnar neurons, within a given CX neuropil, are confined to a single column ('unicolumnar neurons'). Projections are characterized by a strict homotopic order, whereby columns within the lateral half of the PB are connected to columns of the ipsilateral PB and EB, and medial PB columns project to the contralateral FB and EB. One class of columnar neurons, the so-called pontine neurons of the fan-shaped body, behave differently. Their projection is restricted to the FB, interconnecting two FB columns located on either side of the midline ('bicolumnar neurons') (Andrade, 2019).

Developmental studies provide a valuable approach to unravel the circuitry of the brain, including the central complex. A hallmark of the Drosophila brain is its composition of invariant neuronal and glial lineages, originating from stem cells (neuroblasts) that appear in the early embryo. Embryonic neuroblasts express specific combinations of transcription factors (TFs), which are thought to provide each lineage with the information needed to shape the connectivity of its neurons. As a result, lineages become structural modules: Neurons of the same lineage generally project together in one or two fiber tracts, and form synapses in specific, spatially restricted brain compartments. Neuron classes of the CX conform well to the lineage principle. For example, the R-neurons of the ellipsoid body are derived from one lineage, DALv (also called EBa1). Sublineages of DALv born at different times further tile the bulb (BU) and EB into discrete layers. The columnar neurons of the CX are produced by four pairs of lineages located in the dorsomedial brain, called DM1/DPMm1, DM2/DPMpm1, DM3/DPMpm2, DM4/CM (called DM1-DM henceforward). The spatial pattern of these lineages is reflected in the position at which their corresponding tracts enter and terminate within the CX. In this manner, the four lineages subdivide the CX neuropils into four evenly sized quadrants (Andrade, 2019).

The brain of Drosophila and other holometabolous insects arises in two distinct phases. During the first phase, neuroblasts of the embryo produce a relatively small set of primary neurons which differentiate and form the larval brain. Most neuroblasts then enter a dormant phase that lasts towards the end of the first larval instar. Subsequently they reactivate and produce secondary, adult specific neurons. These cells form axon bundles that form a 'blue print' of connections later established within the adult brain. Differentiation is delayed until metamorphosis, when secondary neurons, along with re-modeled primary neurons, extend axonal and dendritic branches and form synapses. In general, primary and secondary neurons of a given lineage show fundamental structural similarities, whereby projections of secondary neurons follow those of earlier formed primary neurons. Remarkably, the central complex, as defined anatomically for the adult, is the one major set of compartments of the fly brain that lacks an obvious counterpart in the larva. Thus, all tangential and columnar neurons with their highly ordered connections outlined above are secondary neurons born in the larva, prompting the question of what guidance mechanisms control CX connectivity, and what part primary neurons play during this process (Andrade, 2019).

Previous work described a set of embryonically born (i.e., primary) neurons belonging to the DM1-4 lineages. These neurons, visualized by the expression of R45F08-Gal4, form a commissural tract that becomes incorporated into the fan-shaped body. Along with the emerging tracts and filopodia extended by secondary neurons of DM1-4 the R45F08-Gal4-positive neurons form a 'fan-shaped body primordium' (prFB). This study undertook a detailed analysis of the structure, differentiative fate, and developmental role of the primary neurons that form the fan-shaped body primordium, using serial electron microscopy of the early larval brain in combination with confocal analysis of all stages covering early larva to adult. The neurons of the fan-shaped body primordium, that will be called fan-shaped body pioneers (FB pioneers) in the following, form part of a much larger population of early larval brain neurons that are arrested in development, projecting a simple, thin, unbranched process into the neuropil. The large majority of these neurons entirely lack synaptic contacts; in a small number of them, a few presynaptic sites are seen. Aside from their undifferentiated neurite arbor, these neurons differ from regular, mature neurons by the small size of their cytoplasm and nucleus, and the abundance of heterochromatin. Virtually every brain lineage possesses a complement of the small undifferentiated (SU) neurons. The data show further that SU neurons differentiate in the late larva and pupa and give rise to distinct adult neuron populations; FB pioneers produce the pontine neurons of the fan-shaped body. Later born secondary neurons of the DM1-4 lineages, destined to form the various classes of unicolumnar neurons of the central complex, fasciculate with the FB pioneers on their pathway towards and across the midline. However, selective ablation of FB pioneers did not result in gross abnormalities of the trajectories of unicolumnar neurons, suggesting that the initial axonal pathfinding of the two system of columnar neurons may be controlled independently (Andrade, 2019).

This analysis demonstrates that a large fraction of the neurons of the early Drosophila larval brain does not elaborate a branched neurite arbor and synaptic connections. This finding came as a surprise; it had been well established that the large number of neurons produced during the secondary, larval phase of neurogenesis remain undifferentiated until the onset of metamorphosis, resembling in many ways the SU neurons described in this study, but the same was not assumed for so many of the embryonically generated primary neurons. Previous studies had shown that in the thoracic ganglia, a subset of presumptive adult peptidergic neurons and motor neurons show a SU phenotype, extending a truncated axon into the peripheral nerve, but failing to form synaptic connections to the musculature. These embryonically born neurons, which transiently express the transcription factor Broad-Z3, differentiate along with the larvally born motor neurons and form dendritic and axonal branches and synapses in the pupa. Due to their delayed differentiation, typical for secondary neurons, these embryonically born thoracic SU neurons have been termed 'embryonically born secondary neurons'. To avoid confusion, this study will stick to the convention that defines all neurons born during the embryonic period as primary neurons, and call them 'primary SU neurons' (Andrade, 2019).

The existence of SU neurons (primary or secondary) is most likely tied to the holometabolous life cycle of Drosophila where, in terms of structure and function, the larval body (formed in the embryo) differs strongly from the adult body (formed in the larva and pupa). The proliferation of adult-specific cells and organs that takes place in the larva is separated from the differentiated larval structures, possibly in order to prevent interference between novel growth and organ function. In case of the musculature, for example, proliferating adult myoblasts form clusters of cells attached to the peripheral nerves or imaginal discs, outside the larval musculature. Neuroblasts generating adult specific neurons are part of the larval brain, but their progeny are arrested in the immature SU state until the onset of metamorphosis, when, under the influence of ecdysone signals, all neurons start branching and generating synaptic connections. If that were not the case, that is, if secondary neurons would continuously differentiate according to their birth date (like regular primary neurons in the embryo), they would constantly and in growing numbers intrude into existing larval circuits, possibly leading to disruptions in functioning of these circuits. It is conceivable that the occurrence of primary SU neurons can be explained by the same reasoning. Based on their (mostly) superficial position, it is assumed that primary SU neurons are born during the final rounds of embryonic neuroblast divisions. It could be speculated further that there is a 'cut-off' line that limits neurons' ability to commence differentiation, and that this cut-off line falls before the time interval during which primary SU neurons are born, thereby preventing the latter from differentiating (Andrade, 2019).

In support of the notion that the presence of SU neurons is an attribute of holometabolous insects, such cells have not been observed in locusts or other hemitabolans for which neuro- developmental observations have been made. A good number of central neurons of the brain and VNC that were followed throughout development show continuous growth and arborization of their neurite tree. This also includes the unicolumnar neurons of the central complex which, in Drosophila, are all born as secondary neurons and undergo a phase of developmental arrest in the larva. In grasshopper, the homologous neurons mature continuously between mid- and late embryonic stages, to form part of a functional central complex right after hatching of the embryo (Andrade, 2019).

Drosophila SU neurons described in this paper exhibit structural characteristics that are similar to those described for neuronal precursors in the developing vertebrate brain. Thus, postmitotic neuronal precursors of the neocortex or hippocampus, while migrating along radial glia, are small, electron-dense cells with hetero-chromatin-rich nuclei and scant cytoplasm. Typically, they exhibit a bipolar shape, extending a leading and trailing process that are in contact with the radial glia. The same phenotype is observed in neuronal precursors ('D-cells') that are generated in the subgranular zone of the hippocampus in adult mammals. As neurons mature, forming dendrites and axons, nuclear and cytoplasmic size increase, and cells become transcriptionally more active, with a concurrent reduction in heterochromatin. Experimental studies have shown that a variety of signaling pathways and receptors for neurotrophic factors become activated by proteins forming part of the complex cell cycle-controlling molecular machinery. However, the specific mechanism that drives the transition from small, heterochromatin-richneural precursor to differentiated neuron is little understood. In human and mouse, mutations in the MECP2 protein, which encodes a transcriptional repressor, is associated with a reduction or delay of neuronal maturation (Rett Syndrome). The gene network (of which MECP2 may form part) that accompanies neural precursor maturation has not been established. In Drosophila, this mechanism is embedded into the ecdysone hormonal cycle that controls larval growth and metamorphosis in general. It has been shown that different isoforms of the ecdysone receptor (EcR) are expressed and required for different developmental changes that occur in the nervous system. The EcRB1 and EcRB2 isoforms are expressed in primary neurons that undergo remodeling, including the gamma neurons of the mushroom body, and blocking this receptor will result in defects of remodeling. In contrast, EcR-A appears to be more dedicated to guide secondary neurons through their maturation and maintenance. The level of ecdysone and its receptors are under the control of developmental paracrine signals, such as in case of the mushroom body cells which produce an activin signal to maintain EcR-B1 levels. In addition, intrinsic determinants expressed sequentially in the dividing neuroblasts form part of a feed-back mechanism with the ecdysone cycle. SU neurons in the Drosophila larval brain may present a favorable paradigm to study the process of neuronal maturation downstream of the ecdysone cycle. SU neurons represent a major population at the early larval stage (primary SU neurons) and late larval stage (primary and secondary SU neurons), and can be labeled by specifically expressed factors (e.g., Broad-Z3), which should make them amenable to FACS sorting and systematic gene expression screens (Andrade, 2019).

Most neuropil compartments of the adult Drosophila brain have a corresponding larval counterpart; outgrowing fibers of secondary neurons, which form much of the volume of the adult compartments, follow their primary siblings and establish dendritic and axonal branches around this primary scaffold. This principle does not apply to the secondary neurons forming the central complex, for which no anatomically defined larval counterpart exists. Small primordia of the different compartments of the central complex and associated structures (i.e., the bulb and anterior optic tubercle, which relay input to the central complex) can be first detected at the late larval stage. These larval primordia of the central complex compartments are formed by the fiber bundles and associated filopodia of the secondary lineages which will develop into the central complex of the adult brain. The minute early larval prFB, formed by the FB pioneers described in the present paper, represent an exceptional case. Thus, FB pioneers are primary neurons whose axons extend during the late embryonic phase and gather into a tight commissural bundle located in the center of the crossing fiber masses that constitute the supraesophageal commissure of the early larval brain. Several aspects of the prFB deserve special comment (Andrade, 2019).

(1) From late embryonic stages onward the FB pioneer axons are enclosed by an exclusive glial layer formed by the so called interhemispheric ring gli. Several pairs of primary glia, located close to the brain midline, make up the interhemispheric ring. Processes of these glial cells assemble into an invariant pattern of sheaths around several individual commissural bundles. Posteriorly, glial processes form two channels, a ventral one containing the great commissure, and a dorsal one, dedicated to the prFB. This dorsal channel conducting the prFB stands out by a pair of glial nuclei attached to its posterior-medial wall; this study could unequivocally identify a pair of glial nuclei at that position in the serial EM stack. As the larva grows and secondary tracts of DM1-4 are added to the FB pioneer bundle, the glial channel widens (Andrade, 2019).

This volumetric increase continues throughout metamorphosis, and eventually the interhemispheric ring glia accommodates the entire fan-shaped body. Similar to other primary neuropil glia, the interhemispheric ring undergoes apoptotic cell death during mid-pupal stages, and is replaced by a much larger number of small secondary glia that surround the adult fan-shaped body. Genetic studies indicate that interhemispheric glia does play a role in the morphogenesis of the fan-shaped body, even though this role may be relatively minor, or occur late in development. Thus, genetic ablation of glia, or loss of function of molecular factors expressed specifically in the interhemispheric ring, result in defective shapes of the adult FB and EB. However, the pathways of DM1- lineages at the late larval stage did not display major defects (Andrade, 2019).

(2) FB pioneers differentiate into the pontine neurons of the adult central complex. Pontine neurons differ in their projection from all other columnar neurons, because they connect two columns on either side of the midline. For example, pontine neurons of the right hemispheric DM4 lineage connect the right lateral column of the FB with its left medial column, thereby crossing the midline. In contrast, axons of other, unicolumnar neurons of the right DM4 remain ipsilaterally, connecting only to the right lateral column of the FB. The trajectories of the FB pioneers reflect this pontine-typical behavior already in the early larva. Thus, the majority of DM4 SU axons reach the midline and terminate just after crossing it; DM3 axons project slightly further, followed by DM2 and DM1, which reach more than 20μm into the contralateral hemisphere (Andrade, 2019).

Outgrowing secondary DM1-4 tracts, even though they initially follow the FB pioneers, show their own characteristic pattern of termination. In particular, secondary axon tracts of DM4 and DM3 do not cross the midline, but form terminal filopodial tufts in the lateral and medial half, respectively, of the ipsilateral prFB (Andrade, 2019).

(3) Even though primary FB pioneers and their secondary follower tracts are in close contact to each other throughout larval development, ablation of the former does not result in gross structural abnormalities of the latter. Thus, the characteristic trajectories and branching pattern of the Neurotactin-positive secondary tracts of DM1-4 in the late larva lacking FB pioneers appeared indistinguishable from the control. Filopodial tufts of secondary tracts in ablated specimens still assembled into regularly sized globular structures, representing the forerunners of fan-shaped body columns. These findings imply that separate guidance systems act on the early born pontine neurons and later born unicolumnar neurons. Nothing is known about the molecular nature of global or local signaling systems controlling the highly ordered architecture of the DM1-4 unicolumnar connections within the central complex. Given that neither ablation of glia, nor loss of primary FB pioneers, causes major changes in this architecture, at least at the initial phase of axonal pathfinding, it is likely that local interactions among the different DM1-4 lineages and sublineages plays a predominant role. For example, local repulsion in between neurons of these lineages could be instrumental in specifying the separate, largely non-overlapping medio-lateral domains within the the FB and EB where neurons terminate. Similarly, interactions occurring in between sequentially born sublineages within a given DM lineage could determine the projection to different territories along the anterior-posterior axis. It is not yet known how the different classes of DM neurons distinguished by projection (e.g., PB-FB vs PB-EB vs FB-NO etc) relate to their pedigree, that is, the time they are born, or the sublineage they belong to. It stands to reason that the different intermediate progenitors born from the type II DM neuroblasts are responsible to generate structurally different classes of neurons, but this remains to be confirmed by detailed clonal analysis. If proven correct, one could surmise that intrinsic factors expressed by a given intermediate progenitor provides its progeny with a specific 'projection identity'. Neurons descended from a hypothetical intermediate progenitor A might recognize a more posterior territory within the prFB as their proper destination, whereas neurons formed by a (later born) progenitor B are repelled by the A neurons, and are forced to terminate in more anterior territory. The former class would develop into PB-FB neurons, the later into PB-EB neurons. That repulsive interactions in between sublineages are important has been experimentally proven by a recent analysis of semaphorin signaling in the ellipsoid body. Here, repulsion among DALv R-2 neurons, born at different times, is instrumental for the proper central>peripheral projection of axons within the EB (Andrade, 2019).

(4) It is an open question what, if any, role the primary neurons of DM1-4 (both differerentiated neurons and other [non-prFB] SU neurons) play in the adult central complex. It is quite possible that these neurons do not contribute at all to this structure; in case of another lineage, DALv2, that has been shown to be the case: secondary DALv2 neurons form the ellipsoid body of the adult brain, but primary DALv neurons arborize in the lateral accessory complex (LAL) and inferior protocerebrum (IPa) of the larva and adult, but do not become part of the ellipsoid body. The same may be true for the primary neurons of DM1-4. On the other hand, at least a (small) subset of DM4 definitely will be incorporated into the central complex: the dopaminergic neurons of the PPM3 cluster, which profusely innervate the central complex and its associated structures (LAL, BU) have been identified as primary neurons of DM. The arborization pattern and connectivity of primary DM1-4 neurons (as that of primary neurons in general) will be worked out in the near future, based on the same serial EM stack that served as the basis for the current work; however, additional markers that remain continuously expressed in primary neurons from larval to adult stages will help solving the puzzle of how these neurons are reorganized during metamorphosis and what fate awaits these neurons in the adult brain. Aside from pioneering the fan-shaped body primordium, SU neurons form part of almost all lineages of the early larval brain, but it is not yet known what fate awaits these neurons. In view of the case represented by the FB pioneers, it is surmised that other SU neurons also survive and differentiate during metamorphosis. The axonal projection of SU neurons of a given lineage prefigures (generally in a rudimentary way) the pathway formed by later born secondary neurons of that lineage. Markers similar to the one provided by R45F08-Gal4 are required to establish what type of adult neurons the different SU neurons give rise to. Of particular interest are SU neurons of lineages that, like DM1-4, contribute to the adult central complex. In case of DALv2, which generates all of the R-neurons of the EB, a single SU neuron exists in each hemisphere. This neuron projects a short axon along the primary tract, but does not reach the EB primordium described for the late larval stage in previous works. Two other lineages, DALcl1 and DALcl2, contribute a large number of secondary neurons to the anterior visual pathway, which provides input to the central complex. Both lineages are composed of two hemilineages, DALcl1/2d (dorsal) and DALcl1/2v (ventral). DALcl1/2d differentiate into small neurons whose proximal dendrites innervate the anterior optic tubercle, and distal axons the bulb, where they target the dendrites of DALv2 neurons. DALcl1/2 form a relatively large number of SU neurons which for the most part follow the dorsal pathway, suggesting that they belong to the DALcl1/2d hemilineage. As outlined above, secondary neurons of DALcl1/2 innervate the anterior optic tubercle and the bulb of the adult brain. Do the earlier born primary SU neurons form early larval primordia of these compartments, analogous to the prFB established by SU neurons of DM1-4. Most DALcl1/2 SU neurons extend relatively short axons that follow the differentiated DALcl1/2d neurons, cross the peduncle of the mushroom body, and terminate shortly thereafter. A few other DALcl1/2 SU neurons project further, but terminate at different locations along the primary tract. In other words, a spatially restricted territory that houses all DALcl1/2d SU terminations, and that might therefore be considered a forerunner of the bulb, does not exist in the early larva. Similarly, no projections of SU neurons are concentrated in a region that might correspond to the primordium of the anterior optic tubercle. In conclusion, SU neurons of lineages DM1-4 may represent a rare case where primary neurons establish a blueprint for an adult-specific brain compartment (Andrade, 2019).

A neural heading estimate is compared with an internal goal to guide oriented navigation

Goal-directed navigation is thought to rely on the activity of head-direction cells, but how this activity guides moment-to-moment actions remains poorly understood. This study characterize how heading neurons in the Drosophila central complex guide moment-to-moment navigational behavior. An innate, heading-neuron-dependent, tethered navigational behavior was established where walking flies maintain a straight trajectory along a specific angular bearing for hundreds of body lengths. While flies perform this task, chemogenetics was used to transiently rotate their neural heading estimate and observe that the flies slow down and turn in a direction that aims to return the heading estimate to the angle it occupied before stimulation. These results support a working model in which the fly brain quantitatively compares an internal estimate of current heading with an internal goal heading and uses the sign and magnitude of the difference to determine which way to turn, how hard to turn and how fast to walk forward (Green, 2019).

Generation of stable heading representations in diverse visual scenes

Many animals rely on an internal heading representation when navigating in varied environments. How this representation is linked to the sensory cues that define different surroundings is unclear. In the fly brain, heading is represented by 'compass' neurons that innervate a ring-shaped structure known as the ellipsoid body. Each compass neuron receives inputs from 'ring' neurons that are selective for particular visual features; this combination provides an ideal substrate for the extraction of directional information from a visual scene. This study combines two-photon calcium imaging and optogenetics in tethered flying flies with circuit modelling and shows how the correlated activity of compass and visual neurons drives plasticity, which flexibly transforms two-dimensional visual cues into a stable heading representation. This study describes how this plasticity enables the fly to convert a partial heading representation, established from orienting within part of a novel setting, into a complete heading representation. The results provide mechanistic insight into the memory-related computations that are essential for flexible navigation in varied surroundings (Kim, 2019).

Many animals rely on an internal heading representation when navigating in varied environments. How this representation is linked to the sensory cues that define different surroundings is unclear. In the fly brain, heading is represented by 'compass' neurons that innervate a ring-shaped structure known as the ellipsoid body. Each compass neuron receives inputs from 'ring' neurons that are selective for particular visual features; this combination provides an ideal substrate for the extraction of directional information from a visual scene. This study combines two-photon calcium imaging and optogenetics in tethered flying flies with circuit modelling, and shows how the correlated activity of compass and visual neurons drives plasticity, which flexibly transforms two-dimensional visual cues into a stable heading representation. This study also describes how this plasticity enables the fly to convert a partial heading representation, established from orienting within part of a novel setting, into a complete heading representation. These results provide mechanistic insight into the memory-related computations that are essential for flexible navigation in varied surroundings (Kim, 2019).

This study has shown how inhibitory Hebbian plasticity can rapidly transform visual feature information into an attractor-driven internal representation. Angular velocity input to the attractor converts an emerging mapping on the basis of limited views of a scene into a complete and consistent heading representation, a potentially critical function in animal navigation. The induction of inverse maps emphasizes the notable flexibility of the system. A key issue that remains unresolved is the nature of bump dynamics during translation in a two-dimensional environment. Mammalian head-direction cells are unaffected by translation1, but this Drosophila model suggests that the compass circuit tracks the angle between the orientation of the fly and an object in the visual scene without correcting for translation-potentially making it a local compass. However, the plasticity that this study has identified required only a few minutes, and may be even faster under natural conditions when the system can co-opt an existing mapping from ring to compass neurons. In simulations, this timescale prevented nearby objects and transient stimuli-such as neighbouring conspecifics that would not move coherently with the bearing of the fly-from being mapped, but tethered the compass to distant objects that moved coherently with the turns of the fly (Kim, 2019).

The locus of plasticity is likely to be synapses between ring and compass neurons; An accompanying article (Fisher, 2019), presents electrophysiological evidence that is consistent with plasticity altering inhibitory visual inputs to individual compass neurons. At a synaptic and biophysical level, it remains to be seen how the Hebbian mechanism that is proposed in this study relates to, and interacts with, other forms of plasticity such as spike-timing-dependent plasticity, or with plasticity-inducing mechanisms such as nitric oxide signalling in the ellipsoid body, dopaminergic modulation (as seen in the fly mushroom body) or plateau potentials (as seen during remapping of hippocampal place cells) (Kim, 2019).

The results support a model in which plasticity is constantly active to allow rapid adaptation to new settings, enabling the ring attractor to generate a single heading direction even in a complex environment. Such stable sensorimotor representations probably enable animals to overcome transient uncertainties in their surroundings as they pursue diverse behavioural goals (Kim, 2019).

Sensorimotor experience remaps visual input to a heading-direction network

In the Drosophila brain, 'compass' neurons track the orientation of the body and head (the fly's heading) during navigation. In the absence of visual cues, the compass neuron network estimates heading by integrating self-movement signals over time. When a visual cue is present, the estimate of the network is more accurate. Visual inputs to compass neurons are thought to originate from inhibitory neurons called R neurons (also known as ring neurons); the receptive fields of R neurons tile visual space. The axon of each R neuron overlaps with the dendrites of every compass neuron, raising the question of how visual cues are integrated into the compass. Using in vivo whole-cell recordings, this study shows that a visual cue can evoke synaptic inhibition in compass neurons and that R neurons mediate this inhibition. Each compass neuron is inhibited only by specific visual cue positions, indicating that many potential connections from R neurons onto compass neurons are actually weak or silent. It was also shown that the pattern of visually evoked inhibition can reorganize over minutes as the fly explores an altered virtual-reality environment. Using ensemble calcium imaging, it was demonstrated that this reorganization causes persistent changes in the compass coordinate frame. Taken together, these data suggest a model in which correlated pre- and postsynaptic activity triggers associative long-term synaptic depression of visually evoked inhibition in compass neurons. These findings provide evidence for the theoretical proposal that associative plasticity of sensory inputs, when combined with attractor dynamics, can reconcile self-movement information with changing external cues to generate a coherent sense of direction (Fisher, 2019).

The compass neurons in the Drosophila brain exhibit some resemblance to the head-direction cells of the mammalian brain. Visual cues stabilize the tuning preferences of mammalian head-direction cells, and when a visual cue is rotated to a new horizontal position, the preferences of all of the head-direction neurons rotate together. It has been proposed that the mammalian head-direction system represents a ring attractor-a network in which global dynamics exhibit multiple stable states that unfold in a repeated sequence in response to an input. However, it is not known how visual cues anchor the mammalian head-direction system at a mechanistic level. It has been suggested that Hebbian synaptic plasticity of visual inputs enforces the correct mapping between sensory cues and attractor network states (Fisher, 2019).

Similar to mammalian head-direction cells, Drosophila compass neurons (called E-PG neurons) have properties of a ring attractor. Indeed, the dendrites of E-PG neurons are arranged in a ring in the brain. At any point in time, there is one 'bump' of activity in the E-PG ensemble, which rotates as the fly turns. This network receives continuous input from brain regions that track the rotational velocity of the fly via optic flow signals, proprioceptive signals and/or motor efference signals. These rotational velocity inputs push the bump around the circle. Visual cues make the position of the bump more accurate and stable. It is not known whether visual inputs to E-PG neurons are plastic: the offset between the E-PG bump and the visual world is different in different individuals and it can occasionally change unpredictably within an individual; however, network instability alone does not provide evidence for synaptic plasticity (Fisher, 2019).

It is proposed that correlated pre- and postsynaptic activity triggers associative long-term synaptic depression of R-to-E-PG inhibition. This learning rule would explain why visual receptive fields and heading tuning are typically aligned in E-PG neurons. When an individual R neuron is activated by a visual cue, it should push the bump of activity towards the E-PG neurons that it inhibits most weakly. If the full ring attractor network agrees with this outcome, then long-term synaptic depression will occur and those weak R-to-E-PG synapses will become even weaker, further reinforcing this outcome. To ensure network stability, long-term synaptic depression should be balanced by long-term potentiation at R-to-E-PG synapses; the co-existence of long-term synaptic depression and long-term potentiation would also explain why bidirectional changes are found in visual receptive fields after training. These learning rules should produce a doubled pattern of R-to-E-PG synaptic weights after training in a two-cue world, reflecting the twofold symmetry of visuomotor correlations (Fisher, 2019).

The key result of this study-that visual inputs to E-PG neurons are plastic-supports theoretical models that describe how a network can progressively establish a spatial map of the world by incorporating information about consistent sensory cues during exploration. In robotics, this process is called simultaneous localization and mapping. Ther results provide direct experimental evidence for this type of unsupervised learning at the level of synaptic potentials in vivo (Fisher, 2019).

In a simultaneous localization and mapping framework, visual cues are often local, meaning that they can change in size and apparent angle as they are approached; by contrast, this study chose to use visual cues that could not be approached, simplifying the relationship between heading and visual cues. This choice was motivated by the known receptive field properties of R2 or R4d neurons, which seem adapted to detect the position of the Sun (or Moon). Specifically, R2 or R4d neurons have large inhibitory surrounds, meaning that they only respond robustly to isolated visual objects such as the Sun. The Sun is an ideal compass cue because it is effectively at infinity (Fisher, 2019).

It is proposed that plasticity at R-to-E-PG synapses allows the position of the Sun to be flexibly associated with other compass cues, such as the pattern of linearly polarized light in the sky, sky-wide chromatic and intensity gradients, and wind. In other insects, the E-PG network responds to multiple sorts of compass cues, and navigation behaviour can depend on arbitrary learned associations between compass cues. In a companion study, Kim (2019) provides evidence in favour of the idea that plasticity could be used to learn a complex conjunction of visual objects; in the future, to test this idea, it will be interesting to see whether any complex scene can generate a progressively more-stable heading representation (offset) during training. It will also be important to extend the approach that was taken in this study to simulate a more naturalistic virtual world, to study how multiple types of cues influence the behaviour of this network and the organism (Fisher, 2019).

A multi-regional network encoding heading and steering maneuvers in Drosophila

Navigation in many animals involves an internal sense of heading direction. Such a sense of heading is thought to be mediated by neurons that are specifically active when the animal is orienting toward the neuron's preferred direction. These head direction cells reside in multiple brain regions and interact with each other as well as with other neurons, including cells encoding angular velocity (Shiozaki, 2020).

In Drosophila melanogaster, two types of columnar neurons innervating the ellipsoid body (EB) and the protocerebral bridge (PB), subregions of the central complex (CX), encode heading direction. As with head direction cells in mammalian brains, columnar neurons encode heading as the identity of active neurons among the population. This heading representation can be updated by visual and self-motion cues via interactions between specific types of columnar neurons. These cell type-specific analyses have provided support for computational models of heading direction encoding, originally proposed for rodent neurons, where angular information is integrated through recurrent excitation. However, the CX is comprised of four highly interconnected subregions that likely function coordinately, and how information related to heading is represented and further processed in other subregions, especially in downstream areas, remains unexplored (Shiozaki, 2020).

The fan-shaped body (FB), another subregion of the CX, is anatomically considered to be an area downstream of columnar neurons in the EB. A functional connectivity study suggested that columnar neurons in the EB, albeit indirectly, influence the activity of certain FB neurons. In addition, the FB directly receives input from outside the CX and is involved in various aspects of navigation, such as visual memory, locomotor handedness, and processing of optic flow. Therefore, the FB is well positioned to receive heading signals from columnar neurons in the EB and integrate them with other types of signals to guide navigation. However, it remains unclear whether and how neurons in the FB encode information about directional heading in behaving animals (Shiozaki, 2020).

Two-photon calcium imaging in the FB was carried out while flies were flying in visual virtual reality as well as in darkness. Specific types of columnar neurons in the FB show characteristic population dynamics that are prominent during flight but not in quiescence. These dynamics multiplexed information about ongoing turning behavior and heading direction. Activity of these FB neurons was coordinated with that of columnar neurons in the EB, which also encoded turning behavior and heading direction. Despite these similarities, columnar neurons in the FB and EB showed distinct activity in their branches in the noduli (NO), a subregion of the CX, where FB but not EB neurons flipped turn preference depending on the visual environment. These results therefore suggest that the heading direction system of Drosophila is composed of columnar neuron networks spanning the EB and the FB, where heading and angular signals from the EB are combined with information about visual context in FB neurons (Shiozaki, 2020).

This study analyzed neural dynamics in the navigation system of Drosophila by performing cell type-specific calcium imaging during flight. Columnar neurons in the FB and the EB showed coordinated population dynamics that encode ongoing turning behavior and, in short timescales, heading direction. A group of FB neurons flipped the preference for turn direction depending on the visual environment, whereas analogous neurons in the EB showed invariant turn tuning. These data suggest that the heading direction system in Drosophila is composed of multiple interacting circuits that distinctly integrate visual and self-motion information (Shiozaki, 2020).

Silencing of neurons in the FB impairs aspects of navigation, such as memory-guided flight orientation. However, little was known about the information encoded by FB neurons aside from flight-dependent change in visual and baseline calcium signals. The current data show that a population of columnar neurons in the FB encodes flight turning behavior as circular dynamics. The position and velocity of the activity bump in the FB were correlated with a fly's turning behavior. Moreover, the bump position was also correlated with a fly's heading in short timescales. Thus, columnar neurons in the FB multiplex information about two aspects of animal navigation (Shiozaki, 2020).

This population activity in the FB was coordinated with that in the EB, suggesting that they carry similar information. Indeed, columnar neurons in the EB encoded turning behavior and heading as in the FB. Unlike a previous study reporting that the movement of the bump in E-PG neurons is uncorrelated with flight turns in darkness, this study found that turning behavior is correlated with the position and velocity of activity bump in E-PG neurons even in darkness. This apparent discrepancy likely resulted in part from differences in prior experience in closed-loop flight because E-PG neurons did not show turn-related activity in darkness when the flies performed flight with a visual pattern and a bar in advance, as in the previous study. This study also found that the bump position was influenced more by turning behavior than visual cues, unlike in walking flies, where visual but not motor cues dictate the bump position. Together, the activity bump of columnar neurons encodes different types of information depending on experience and behavioral states. On a relevant note, experimental and computational studies have proposed that the association between bump position and visual landmarks is formed through experience-dependent synaptic plasticity. For these proposed models to work, turning behavior must drive the movement of the bump, which was observed in the CX of flying flies as in walking flies (Shiozaki, 2020).

The bump position of columnar neurons in the FB and the EB was correlated with heading only for several seconds during flight with a visual pattern, suggesting that the offset between bump position and heading drifted away over the course of the recordings. Such a strong drift was not observed for E-PG neurons in walking flies. A previous study has shown that the offset can be unstable when the visual scene contains multiple identical objects. Thus, the stronger drift in the current study might stem from the visual pattern, which contained an array of identical bars. Consistent with this idea, the drift was weaker during flight with a single bar. It is likely that heading representations are stable in flies navigating in natural environments where visual scenes contain more features to identify heading than the scenes in the current study (Shiozaki, 2020).

In the FB and EB, the bump position was correlated with turning behavior with a delay of around 1 s. Thus, these turn signals potentially contribute to flight behavior operating on a timescale of seconds. Notably, menotaxis, a behavior that requires columnar neurons in the EB, involves changes in heading on such a timescale. However, it remains to be investigated whether and how the turn signals encoded as the bump position contribute to guiding flight (Shiozaki, 2020).

How are heading circuits organized in the CX? The data show that columnar neurons in the FB and EB coordinately encode heading and turning behavior during flight. It is proposed that this coordination originates in the communication from columnar neurons in the EB to those in the FB for two reasons. First, P-F-R and P-FN neurons have dendrites in the PB, where axons of E-PG neurons reside. Second, E-PG neurons can activate a type of local neuron in the PB, Δ7 neurons, whose activation can influence the activity of P-FN neurons. Therefore, columnar neurons in the FB might inherit heading signals from the EB, where heading is thought to be computed through recurrent connections among columnar neurons (Shiozaki, 2020).

However, information encoded by columnar neurons in the FB and EB are not identical. This study found that P-FN but not P-EN neurons flipped the preference for turning behavior between flight in darkness and with a visual pattern, suggesting that two types of neurons are differentially influenced by visual input. This difference might reflect signals conveyed from visually responsive neurons that have dendrites outside of the CX and axons either in the EB (ring neurons) or in the FB (e.g., ExFl1 neurons). In addition, P-FN and P-EN neurons innervate different compartments in the NO, where axons of different sets of neurons projecting from the lateral accessory lobe terminate. Although the mechanism underlying this difference awaits further investigation, the current results suggest that columnar neurons in the FB likely do not just relay heading signals but integrate them with other inputs. Consistent with this idea, silencing of neurons in the FB and the EB have different effects on navigation (Shiozaki, 2020).

Although P-FN neurons flipped their turn preference in the NO depending on the visual environment, their branches in the FB did not (i.e., the sign of the correlation between turn direction and bump rotation was invariant). This suggests that calcium signals in the NO branches of P-FN neurons are modulated sub-cellularly, as in the EB branches of P-EN neurons (Shiozaki, 2020).

Columnar neurons showed turn-related activity in darkness, indicating that it derives from non-visual cues. One possibility is that the activity represents an efference copy because the CX receives input from putative pre-motor regions, including the lateral accessory lobe and the posterior slope. Alternatively, turn signals might reflect sensory feedback from, for example, mechanosensory neurons in the antennae, which are active during flight. Although the columnar neurons in the EB also encode turns during walking in darkness, its neural underpinnings likely differ from those during flight because the two modes of locomotion involve distinct patterns of neural activation in motor and sensory systems (Shiozaki, 2020).

Activity of P-F-R neurons increased during flight as in other types of CX neurons. This activity might be inherited from neurons in the optic lobe, whose activity increases during flight. Alternatively, this phenomenon might be mediated by octopaminergic neurons innervating the CX because octopamine regulates flight-dependent neural modulation in the optic lobe. Beyond mechanisms, it will be important to determine whether and how flight-dependent neural modulation contributes to sensory processing and behavior (Shiozaki, 2020).

Networks of columnar neurons in the FB are upstream of the motor system; a type of columnar neurons in the FB, PF-LCre neurons, send axons to the lateral accessory lobe, where dendrites of descending neurons reside. Because PF-LCre neurons are considered to be a primary output channel of the CX, the FB likely plays a unique role in modulating locomotion. In fact, suppressing the activity of columnar neurons in the FB influences walking behaviors in Drosophila, and electrical stimulation of the FB modifies walking in cockroaches. Because E-PG neurons are necessary for adopting arbitrary heading relative to a visual landmark but are dispensable for phototaxis, the FB might modulate elementary motor programs based on spatial information computed within the CX (Shiozaki, 2020).

By gathering the knowledge acquired in various insects, recent work proposed a computational model of the CX network that is capable of performing path integration. In this model, E-PG and P-FN neurons have distinct functions; E-PG neurons encode heading, whereas P-FN neurons integrate heading and speed signals over time to calculate the direction and distance an animal has traveled. Although this study has analyzed just one of a few types of P-FN neurons, the results suggest that P-FN neurons encode heading and turning behavior in a manner similar to E-PG neurons. Monitoring the activity of various types of P-FN neurons in flies engaged in behaviors that require path integration would provide data for direct tests of the model (Shiozaki, 2020).

Neurons innervating the dorsal part of the FB promote sleep, during which locomotion is suppressed. In the current study, neurons in this part did not show circular dynamics, suggesting that these sleep-promoting neurons do not encode spatial information in the same way as FB columnar neurons. It is tempting to speculate that the sleep circuit might rather inhibit locomotion by downregulating the activity of FB columnar neurons; for example, through the EB. Similar processing may shape other behaviors requiring the FB, such as memory-guided flight orientatio, courtship memory, protein seeking, nociceptive avoidance, and aggression, because locomotion is a key building block of these behaviors. The FB might mediate the interaction between spatial representations and the internal state to dictate when and in which direction an animal moves (Shiozaki, 2020).

A comprehensive wiring diagram of the protocerebral bridge for visual information processing in the Drosophila brain

How the brain perceives sensory information and generates meaningful behavior depends critically on its underlying circuitry. The protocerebral bridge (PB) is a major part of the insect central complex (CX), a premotor center that may be analogous to the human basal ganglia. By deconstructing hundreds of PB single neurons and reconstructing them into a common three-dimensional framework, this study has constructed a comprehensive map of PB circuits with labeled polarity and predicted directions of information flow. The analysis reveals a highly ordered information processing system that involves directed information flow among CX subunits through 194 distinct PB neuron types. Circuitry properties such as mirroring, convergence, divergence, tiling, reverberation, and parallel signal propagation were observed; their functional and evolutional significance is discussed. This layout of PB neuronal circuitry may provide guidelines for further investigations on transformation of sensory (e.g., visual) input into locomotor commands in fly brains (Lin, 2014: PubMed).

Ring attractor dynamics in the Drosophila central brain

Ring attractors are a class of recurrent networks hypothesized to underlie the representation of heading direction. Such network structures, schematized as a ring of neurons whose connectivity depends on their heading preferences, can sustain a bump-like activity pattern whose location can be updated by continuous shifts along either turn direction. A population of fly neurons in the ellipsoid body has been shown to represent the animal's heading via bump-like activity dynamics (see Bump attractors and spontaneous pattern formation). This study combined two-photon calcium imaging in head-fixed flying flies with optogenetics to overwrite the existing population representation with an artificial one, which was then maintained by the circuit with naturalistic dynamics. A network with local excitation and global inhibition enforces this unique and persistent heading representation. Ring attractor networks have long been invoked in theoretical work; this study provides physiological evidence of their existence and functional architecture (Kim 2017).

Studies of neural circuits near the sensory periphery have produced deep mechanistic insights into circuit functions. However, it has been more challenging to understand circuit functions in central brain regions dominated by recurrent networks, which often produce complex neural activity patterns. These dynamics play a major role in shaping cognitive functions, such as the maintenance of heading information during navigation. A heading representation must be unique (because an animal can face only one direction at a given time) and persistent (to allow an animal to keep its bearings in darkness), yet must allow updating that matches the magnitude and speed of heading changes expected from the animal's movements. Theoretically, this can be accomplished by ring attractor networks (see, for example, Balanced neural architecture and the idling brain), wherein the position of a localized subset of active neurons in a topological ring represents the animal's heading direction. However, whether the brain uses these hypothesized networks is still unknown. A recent study reported that a population of neurons, called E-PG neurons [to signify their predominantly spiny (and, thus, putatively post-synaptic) projections within the ellipsoid body ('E-') and their predominantly bouton-like projections within the protocerebral bridge ('-P') and the gall ('G')], in the Drosophila melanogaster ellipsoid body (EB) appears to use bump-like neural activity dynamics to represent the animal's heading in visual environments and in darkness. This study establishes essential properties of the network that enables this representation (Kim 2017).

Whether the E-PG population activity bump tracks the fly's heading direction relative to its visual surroundings during tethered flight was determined first. Two-photon imaging with the genetically encoded calcium indicator GCaMP6f was performed to record dendritic calcium activity of the entire E-PG population in the EB while the fly was flying in a virtual-reality LED arena. The azimuthal velocity of the visual scene was proportional to the fly's yaw velocity. As with walking flies, E-PG population activity during flight was organized into a single bump, whether the visual scene contained a single bar or a more complex pattern. The activity bump closely tracked the fly's heading in flight and persisted in darkness. However, unlike in walking, the activity bump seldom tracked the fly's motor actions in darkness, potentially because tethering deprives the fly of normal sensory feedback about its rotational movements from its halteres. Although the location of the activity bump eventually drifted in some flies, the bump's movement was, on average, uncorrelated to the animal's turning movements in darkness. These findings suggest that the representation of heading in the E-PG population has intact, visually driven dynamics as well as persistence, but is largely uncoupled from updating by self-motion cues during tethered flight (Kim 2017).

To test whether the fly's compass network enforces a unique bump within the EB, advantage was taken of the relative persistence of the visually evoked activity bump in darkness, and asked whether this bump could coexist with an 'artificial' bump of activity. Localized optogenetic stimulation was used to create artificial activity bumps in different locations within the E-PG population. Using a transgenic fly line in which E-PG neurons coexpressed CsChrimsonand GCaMP6f, alternating two-photon laser scan lines of excitation (higher laser intensity) and imaging (normal laser intensity) were used to monitor changes in E-PG population dynamics in response to an optogenetically created spot of local activity. By varying the intensity of stimulation light delivered to the target location, bumps were created of increased calcium activity. As the new bump formed, activity at the previous location began to decline and eventually disappeared without significantly perturbing the fly's behavior. When the optogenetic excitation was terminated, the amplitude of the artificially created bump settled at levels typically evoked by sensory stimuli and did not disappear; it either stayed in the induced location for several seconds or slowly drifted away (Kim 2017).

The bump's uniqueness may arise through either recurrent mutual suppression or an indirect mechanism whereby strong bump activity in the EB functionally inhibits feedforward sensory inputs to other E-PG neurons. To discriminate between these alternatives, two locations on the EB ring were simultaneously excited. A reference location was excited at a fixed laser power, and a second, spatially offset location was excited at increasing levels of laser power. The reference bump could always be suppress by increasing laser power at the second location above a certain threshold, consistent with mutual suppression (Kim 2017).

Recurrent suppression can ensure a unique activity bump through a simple winner-take-all (WTA) circuit. However, an animal's representation of its angular orientation should favor more continuous updates based on turning actions. Such gradual, ordered drift to nearby locations would be more consistent with continuous, or ring, attractor models. This study therefore examined changes in the location of an artificially created bump after the stabilization of its peak activity at the 'natural' level. The experiments were performed in darkness to untether the bump from any potentially lingering visual input. If EB dynamics were driven by a WTA network, bumps would be expected to disappear at times and to jump to random distant locations. In contrast, the bump drifted gradually around the EB; this finding suggests that the fly's heading representation is updated through functionally excitatory interactions between neighboring E-PG neurons, consistent with a ring attractor model. These observations together rule out the possibility that network dynamics in darkness result purely from cell-intrinsic mechanisms or slowly decaying visual input. Most important, direct manipulation of E-PG neuron activity changed the network state, which implies that E-PG neurons do not merely mirror dynamics occurring in a different circuit, but are themselves an important component of the ring attractor (Kim 2017).

The next area of focus was the effective connectivity pattern underlying ring attractor dynamics in the E-PG population. A wide range of network structures can, in principle, implement ring attractors. This study focused efforts to a model space between two extreme network architectures that are analytically solvable: (1) a 'global model' based on global cosine-shaped interactions and (ii) a 'local model' based on relatively local excitatory interactions. Under constraints of a fixed bump width of 90° to match physiological observations and an assumption of effectively excitatory visual input without any negative bias, both models could explain the basic properties of bump dynamics, including its uniqueness and its persistence in darkness. The network's response to more artificial conditions, such as abrupt visual stimulus shifts, was therefore probed (Kim 2017).

How the E-PG population responded to unnatural, abrupt visual shifts was examined experimentally first. Depending on the distance of the shift, the E-PG bump either 'flowed' continuously (shorter shift distances) or 'jumped' to the new location (longer shift distances). In simulations, both models predicted a mixture of jump and flow responses, depending on the strength and width of the abruptly shifting visual input. For example, weak wide input induced flows and strong narrow input evoked jumps. However, the jump-flow balance predicted by the two models differed and was more consistent with the local model in several aspects. First, the visual input strength inferred from normal conditions was much weaker than required by the global model for bump jumps. Second, the global model required a much-wider-than-normal range of visual input strengths to explain jumps at multiple distances. Third, using parameters consistent with the rest of the findings, it was possible to reproduce the jump-flow ratio that was observed with the local model but not with the global model (Kim 2017).

To obtain more concrete evidence, model predictions were compared to experimentally observed bump dynamics, under conditions in which input strength, polarity, and shift distance were controlled through optogenetic stimulation. To simulate moderate and large input shift distances, two small regions were sequentially stimulated in the EB-each with an angular width of 22.5°-separated by either 90° or 180°. The stimulation laser power was varied to detect the threshold required for the bump to jump. The laser power required to elicit a jump was not significantly different between the two different shift distances, favoring the local model. The strength of input to the network was then inferred by comparing the amplitude of the optogenetically evoked bump to natural bump amplitudes in darkness. The optogenetic input strength required to induce jumps was smaller than the global model's prediction but matched that of the local model and the range of the inferred visual input strength under normal conditions. Finally, intermediate models that lie between the extremes of the local and global models were then test; any model that exhibited the observed jumps in response to a weak 22.5°-wide input had narrow connectivity profiles was then found. All these observations were once again consistent with the local model (Kim 2017).

In mammals, heading representations are thought to be distributed across multiple neural populations and multiple brain areas. In Drosophila as well, the compass system likely involves multiple cell types, including neurons in the protocerebral bridge (PB). Further, occasional changes observed in the dynamics suggest network modulation by other factors not yet known. For example, sometimes sudden changes were observed in E-PG dynamics, as when the amplitude of the sensory-evoked activity bump changed depending on whether or not the tethered fly was flying and, occasionally, during flight. Nonetheless, the E-PG population provides a powerful physiological handle on the internal representation of heading: a single activity bump moving through topographically arranged neurons. The experimental approach this enabled provides one avenue for investigating which of multiple populations are key circuit components of a computation and which simply read out the results of that computation. It was found that the artificial bump created by directly manipulating E-PG population activity displays natural dynamics, which indicates that these neurons are a key component of the heading circuit (Kim 2017).

The finding that the uniqueness of the E-PG activity bump is ensured via global competition strengthens the conclusion that this population encodes an abstract internal representation of the fly's heading direction. Such abstract representations permit an animal to untether its actions from the grasp of its immediate sensory environment and thereby confer flexibility in both time and behavioral use. Combining an analysis of artificially induced bump dynamics with theoretical modeling allowed interrogation of this recurrent circuit architecture. It was found that the effective network connectivity profile was consistent with ring attractor models characterized by narrow local excitation and flat long-range inhibition. This neural circuit motif of local excitation and long-range inhibition is ubiquitous across many brain areas and across animal taxa. Such observations support the idea that common circuit motifs might be evolutionarily adapted to serve as crucial building blocks of cognitive function (Kim 2017).

Neural dynamics for landmark orientation and angular path integration

Many animals navigate using a combination of visual landmarks and path integration. In mammalian brains, head direction cells integrate these two streams of information by representing an animal's heading relative to landmarks, yet maintaining their directional tuning in darkness based on self-motion cues. This study used two-photon calcium imaging in head-fixed Drosophila melanogaster walking on a ball in a virtual reality arena to demonstrate that landmark-based orientation and angular path integration are combined in the population responses of neurons whose dendrites tile the ellipsoid body, a toroidal structure in the centre of the fly brain. The neural population encodes the fly's azimuth relative to its environment, tracking visual landmarks when available and relying on self-motion cues in darkness. When both visual and self-motion cues are absent, a representation of the animal's orientation is maintained in this network through persistent activity, a potential substrate for short-term memory. Several features of the population dynamics of these neurons and their circular anatomical arrangement are suggestive of ring attractors, network structures that have been proposed to support the function of navigational brain circuits (Seelig, 2015).

Visual landmarks can provide animals with a reliable indicator of their whereabouts. In the absence of such cues, many animals track their position relative to a reference point by continuously monitoring their own motion, a process called path integration. Estimates of position based purely on self-motion cues, however, can accumulate error over time. Successful navigation then, requires animals to flexibly combine these distinct sources of information. In mammalian brains this process of integration is evident in head direction cells, which are neurons sensitive to an animal's heading relative to visual cues in its surroundings that maintain their representation of heading in total darkness using self-motion cues. With their smaller brains and identifiable neurons, insects offer tractable systems to examine the integrative neural computations underlying navigation. Indeed, many insects (for example, desert ants and honeybees) are known to navigate using landmarks and path integration. Experiments in a variety of insects indicate the involvement of the central complex (CX)-a brain region conserved across insects-in such behaviour. In the fruitfly, behavioural genetics experiments have suggested that the CX is required for several components of navigation, including memory for visual landmarks, patterns and places, and directional motor control. Electrophysiological recordings in immobilized locusts and butterflies have revealed a map-like representation for the orientation of electric field vectors of polarized light, which may enable sun-compass navigation. Extracellular recordings from CX neurons in tethered walking cockroaches have shown encodings of turning direction and of wide-field optic flow, a potential cue for self-motion. However, previous studies of visual responses in the CX were conducted under conditions in which insects passively viewed visual stimuli. This study sought to uncover integrative neural processes relevant to navigation in the CX by allowing a tethered fly to control and respond to visual stimuli while simultaneously recording its neural activity and behaviour (Seelig, 2015).

Two-photon imaging was used with the genetically encoded calcium indicator GCaMP6f to monitor neural responses in the CX while a head-fixed fly walked on an air-supported ball within a light-emitting-diode (LED) arena. In previous experiments, a subset of neurons was identified with projections to the CX, and specifically to rings of the ellipsoid body (EB), that show strong tuning to localized visual features including vertical stripes, a class of stimuli that also induce innate fixational responses in flies. To probe how such visual information might be used within the CX this study focused on a class of columnar neurons of the CX, each of which sends dendrites to a specific wedge of the EB. These neurons are termed EBw.s neurons. The dendritic responses of the entire EBw.s population were monitored in the EB during walking, both under closed-loop virtual reality conditions in which the rotation of visual patterns was driven by the fly's turning movement on the ball and in darkness (Seelig, 2015).

This network was found to use information from both landmark-based and angular path integration systems to create a compass-like representation of the animal's orientation in the environment. Previous studies have described static visual maps in the CX. Such maps may allow navigating insects to maintain a sun-compass-based heading direction. This study found that EBw.s neurons track the fly's orientation relative to visual landmarks in a variety of different visual environments, suggesting that the CX dynamically adapts to estimate the fly's orientation within its visual surroundings. Subsets of ring neurons are likely to bring information about spatially localized visual features to specific rings of the ellipsoid body. It is not yet clear how this information is converted into an abstract and flexible representation of the animal's orientation relative to landmarks, but EBw.s responses in a symmetric environment with two indistinguishable cues hint at an underlying winner-take-all process for landmark selection. Combining landmark orientation with information about the animal's movement effectively creates an internal reference frame for the animal in its surroundings. Many of the proposed functions of the CX in directed locomotion, visual place learning, and action-selection, may rely on this internal reference. Although the EBw.s population tracks the fly's rotational movements in darkness, it is not yet known where and how translational motion, an important component of a complete navigational system, is incorporated. Additionally, although the calcium sensor that was chosen for imaging experiments has the temporal resolution necessary to capture EBw.s representations of the fly's angular rotation, it lacks the precision necessary for determination of whether EBw.s activity represents the fly's predicted future orientation or its estimate of current orientation (Seelig, 2015).

The observation that EBw.s activity was maintained in the absence of self-motion suggests that internal dynamics play a significant role in shaping neural activity in the fly brain, much as they do in the brains of larger animals. Persistent activity in the CX can maintain compass information when the fly is standing in darkness for 30 s - two orders of magnitude longer than might be explained by calcium sensor decay kinetics. Persistent activity has been shown to support maintenance of eye position in the goldfish and has been proposed to underlie working memory in mammals. In the CX, this activity may allow the fly to retain a short-term orientation memory even when landmarks are temporarily out of sight. Consistent with this notion, the EBw.s activity bump largely remained tethered to the position of one landmark even in the presence of another identical landmark in front of the fly. The bump also did not always shift instantaneously following an abrupt displacement of visual landmarks, as if temporarily retaining the original orientation reference before locking on to its new position (Seelig, 2015).

Several models have been proposed to explain how visual landmark and self-motion cues are integrated at the level of head direction cell activity in mammals. Most rely on circuits organized as ring attractors: neurons are schematized as being arranged in a circle based on their preferred directions, with connection strengths that depend on their angular separation. With initial sensory input and an appropriate balance of recurrent excitation and inhibition, such a circuit can generate and sustain a localized activity bump. The bump's position on the circle corresponds to the animal's heading which is then updated by directional drive from self-motion signalling neurons. Direct experimental evidence in support of these models has been difficult to obtain in mammals owing to the distributed nature of the underlying circuits. Although the functional connectivity between EBw.s neurons is not yet known, several of the expected features of ring attractor models were observed in the dynamics of this population of CX neurons: organization of activity into a localized bump, movement of the bump to neighbouring wedges based on self-motion, drift in bump location in darkness, persistent activity, and both abrupt jumps and gradual transitions of the activity bump when triggered by strong visual input. Cell-intrinsic mechanisms could also underlie some of these features, including, for example, persistent activity. The genetic tools available in Drosophila to target and manipulate the activity of identified cell types should allow different models for visually guided orientation and angular path integration to be discriminated at the level of synaptic, cellular and network mechanism (Seelig, 2015).

Visual input to the Drosophila central complex by developmentally and functionally distinct neuronal populations

The Drosophila central brain consists of developmental-structural units of macrocircuitry formed by the sibling neurons of single neuroblasts. Lineage guides the connectivity and function of neurons, providing input to the central complex, a collection of neuropil compartments important for visually guided behaviors. The ellipsoid body (EB) is formed largely by the axons of ring (R) neurons, all of which are generated by a single lineage, DALv2. Two further lineages, DALcl1 and DALcl2, produce neurons that connect the anterior optic tubercle, a central brain visual center, with R neurons. Finally, DALcl1/2 receive input from visual projection neurons of the optic lobe medulla, completing a three-legged circuit that is called the anterior visual pathway (AVP). The AVP bears a fundamental resemblance to the sky-compass pathway, a visual navigation circuit described in other insects. DALcl1 and DALcl2 form two parallel channels, establishing connections with R neurons located in the peripheral and central domains of the EB, respectively. Although neurons of both lineages preferentially respond to bright objects, DALcl1 neurons have small ipsilateral, retinotopically ordered receptive fields, whereas DALcl2 neurons share a large excitatory receptive field in the contralateral hemifield. DALcl2 neurons become inhibited when the object enters the ipsilateral hemifield and display an additional excitation after the object leaves the field of view. Thus, the spatial position of a bright feature, such as a celestial body, may be encoded within this pathway (Omoto, 2017).

Functional divisions for visual processing in the central brain of flying Drosophila

Although anatomy is often the first step in assigning functions to neural structures, it is not always clear whether architecturally distinct regions of the brain correspond to operational units. Whereas neuroarchitecture remains relatively static, functional connectivity may change almost instantaneously according to behavioral context. This study imaged panneuronal responses to visual stimuli in a highly conserved central brain region in the fruit fly, Drosophila, during flight. In one substructure, the fan-shaped body, automated analysis reveals three layers that are unresponsive in quiescent flies but become responsive to visual stimuli when the animal is flying. The responses of these regions to a broad suite of visual stimuli suggest that they are involved in the regulation of flight heading. To identify the cell types that underlie these responses, activity was imaged in sets of genetically defined neurons with arborizations in the targeted layers. The responses of this collection during flight also segregate into three sets, confirming the existence of three layers, and they collectively account for the panneuronal activity. These results provide an atlas of flight-gated visual responses in a central brain circuit (Weir, 2015).

The visual orientation memory of Drosophila requires Foraging (PKG) upstream of Ignorant (RSK2) in ring neurons of the central complex

Orientation and navigation in a complex environment requires path planning and recall to exert goal-driven behavior. Walking Drosophila flies possess a visual orientation memory for attractive targets which is localized in the central complex of the adult brain. This study shows that this type of working memory requires the cGMP-dependent protein kinase encoded by the foraging gene in just one type of ellipsoid-body ring neurons. Moreover, genetic and epistatic interaction studies provide evidence that Foraging functions upstream of the Ignorant Ribosomal-S6 Kinase 2, thus revealing a novel neuronal signaling pathway necessary for this type of memory in Drosophila (Kuntz, 2012).

For signaling has previously been implicated in different types of memories; however, in contrast to the working memory in the detour paradigm, these memories require a longer time frame to be established. In mammals, nitric oxide, the initiating molecule of the cGMP/PKG-pathway, is thought to act as a retrograde messenger during the induction of long-term potentiation (LTP). A LTP enhancement has been reported after adding PKG activators and a long-term depression after the addition of PKG inhibitors. Mice carrying a knock-out for the Pkg gene show reduced ability of motor learning due to a loss of synaptic plasticity in the cerebellum. Furthermore, mice lacking Pkg in the amygdala exhibit an impairment in fear conditioning and cGMP/PKG signaling in the hippocampus is required for novel object recognition. In insects, For is involved in different types of food searching behavior and associative memories in which establishing the learning traces takes at least seconds. In contrast, the orientation memory observed in the detour paradigm presented in this study represents a form of working memory which has to be updated continuously in fractions of seconds. Whereas the phosphorylation and activation of For and Ignorant might be the mechanism by which these kinases affect longer-lasting memories, it is thought unlikely that this mechanism is involved in the constantly and rapidly changing orientation memory. Both kinases would have to be activated or inactivated in an online fashion during every turn of the fly. On the other hand, RSK2 has been implicated in multiple cellular processes and transcriptional control. It is therefore speculated that the biochemical pathway both kinases work in is necessary to endow the ring neurons with the capacity to efficiently change signaling rapidly to encode orientation. For instance, ring neurons might need a higher density of synaptic release sites and/or dendritic neurotransmitter receptors to exert their specific function (Kuntz, 2012).

Neural coding in the visual system of Drosophila melanogaster: How do small neural populations support visually guided behaviours?

All organisms wishing to survive and reproduce must be able to respond adaptively to a complex, changing world. Yet the computational power available is constrained by biology and evolution, favouring mechanisms that are parsimonious yet robust. This study investigated the information carried in small populations of visually responsive neurons in Drosophila melanogaster. These so-called 'ring neurons', projecting to the ellipsoid body of the central complex, are reported to be necessary for complex visual tasks such as pattern recognition and visual navigation. Recently the receptive fields of these neurons have been mapped, allowing an investigation of how well they can support such behaviours. For instance, in a simulation of classic pattern discrimination experiments, this study shows that the pattern of output from the ring neurons matches observed fly behaviour. However, performance of the neurons (as with flies) is not perfect and can be easily improved with the addition of extra neurons, suggesting the neurons' receptive fields are not optimised for recognising abstract shapes, a conclusion which casts doubt on cognitive explanations of fly behaviour in pattern recognition assays. Using artificial neural networks, it was then assessed how easy it is to decode more general information about stimulus shape from the ring neuron population codes. These neurons were shown to be well suited for encoding information about size, position and orientation, which are more relevant behavioural parameters for a fly than abstract pattern properties. This leads to a suggestion that in order to understand the properties of neural systems, one must consider how perceptual circuits put information at the service of behaviour (Dewar, 2017).

Specific kinematics and motor-related neurons for aversive chemotaxis in Drosophila

Chemotaxis, the ability to direct movements according to chemical cues in the environment, is important for the survival of most organisms. The vinegar fly, Drosophila melanogaster, displays robust olfactory aversion and attraction, but how these behaviors are executed via changes in locomotion remains poorly understood. In particular, it is not clear whether aversion and attraction bidirectionally modulate a shared circuit or recruit distinct circuits for execution. Using a quantitative behavioral assay, this study has determined that both aversive and attractive odorants modulate the initiation and direction of turns but display distinct kinematics. Using genetic tools to perturb these behaviors, specific populations of neurons were identified that are required for aversion, but not for attraction. Inactivation of these populations of cells affects the completion of aversive turns, but not their initiation. Optogenetic activation of the same populations of cells triggers a locomotion pattern resembling aversive turns. Perturbations in both the ellipsoid body and the ventral nerve cord, two regions involved in motor control, were shown to result in defects in aversion. It is concluded that aversive chemotaxis in vinegar flies triggers ethologically appropriate kinematics distinct from those of attractive chemotaxis and requires specific motor-related neurons (Gao, 2013).

This study is the first direct demonstration that odorants modulate turn initiation and direction in freely walking insects. Moreover, aversive and attractive turns involve distinct kinematics. Intuitively, these quantitative analyses reveal that flies speed up and follow straighter trajectories after turning away from a noxious smell, which should shorten their exposure to potential harm. Such a strategy is not employed for attraction. Chemotaxis has been studied in tethered adult flies, paradigms in which mimicking the olfactory inputs a freely moving fly would encounter proved challenging. For example, in one group of studies, a 'fly-on-the-ball' paradigm, aversion was not triggered even using a strong repellent. In another study, flying flies responded symmetrically to aversive and attractive odorants. The current more naturalistic approach provides new insights into the relationship between aversive and attractive chemotaxes (Gao, 2013).

In bacteria, aversion and attraction are achieved through bidirectional modulation of the same mechanism. Similarly, in C. elegans, aversion and attraction are thought to utilize a push-pull mechanism on one set of antagonizing command neurons (Faumont, 2012). Genetic inactivation experiments suggest that, in flies, aversion is executed through specific neurons distinct from attraction. In this study. two candidate circuit components, the EB and a subset of the VNC neurons, were identified that appear redundantly necessary for aversive chemotaxis. The EB is part of the central complex, defects in which are associated with uncoordinated walking. In grasshoppers and cockroaches, activating central complex neurons induces specific kinematics. In the VNC, dTdc2+ neurons are prominent candidates for mediating aversion, although other neurons might be involved. These othere neurons are homologous to dorsal/ventral unpaired median neurons in other insects because they are octopaminergic and show similar projection patterns]. The activity in these neurons is correlated with specific aspects of locomotion in locusts, crickets, and moths. Given that 441 > shits1 flies display defects in aversive turn completion but not initiation, it is postulated that the current genetic manipulation does not interfere with the perception, processing, decision-making, or even initiation steps of aversive chemotaxis, but rather the execution of motor programs specifically necessary for this behavior. These discoveries bridge the extensive investigation of olfactory processing in insects such as honeybees and moths with studies focused on motor control mechanisms in species such as cockroaches and stick insects (Gao, 2013).

It is intriguing that part of the aversion-specific circuit resides in the VNC, and can be artificially activated to generate a pattern similar to aversive turns. Although the larval VNC is sufficient for substrate exploration, VNC autonomy in motor pattern generation in adult flies has only been established for escape flight and courtship song, both highly specialized for certain ethological functions. When a fly continuously explores the environment and updates its walking pattern, the division of labor between the brain and the VNC is less clear. Conceptually, one possibility is that circuit modules in the VNC only encode basic elements of locomotion. For example, right turns may always involve the same VNC circuit, and the only difference is their embedding within different sequences of actions based on the combination of descending signals from the brain. Alternatively, VNC circuit modules could be task-specific; once a descending signal specifies the task, the details of the motor output will unfold according to a pre-wired VNC circuit. The current findings support the latter possibility in the context of aversive chemotaxis. In both vertebrates and invertebrates, artificial activation of neurons in the spinal cord or the VNC generates specific motor outputs, but rarely have these neurons been demonstrated to be necessary for specific sensory-driven tasks. It would be interesting to test the generality of having autonomous motor-related circuits specifically responsive to certain sensory triggers (Gao, 2013).

Two clusters of GABAergic ellipsoid body neurons modulate olfactory labile memory in Drosophila

In Drosophila, aversive olfactory memory is believed to be stored in a prominent brain structure, the mushroom body (MB), and two pairs of MB intrinsic neurons, the dorsal paired medial (DPM) and the anterior paired lateral (APL) neurons, are found to regulate the consolidation of middle-term memory (MTM). This study reports that another prominent brain structure, the ellipsoid body (EB), is also involved in the modulation of olfactory MTM. Activating EB R2/R4m neurons does not affect the learning index, but specifically eliminates anesthesia-sensitive memory (ASM), the labile component of olfactory MTM. It was further demonstrated that approximately two-thirds of these EB neurons are GABAergic and are responsible for the suppression of ASM. Using GRASP (GFP reconstitution across synaptic partners), potential synaptic connections were revealed between the EB and MB in regions covering both the presynaptic and postsynaptic sites of EB neurons, suggesting the presence of bidirectional connections between these two important brain structures. These findings suggest the existence of direct connections between the MB and EB, and provide new insights into the neural circuit basis for olfactory labile memory in Drosophila (Zhang, 2014).

Previous studies have shown that the EB plays an essential role in visual pattern memory, orientation memory and place learning (Pan, 2009; Ofstad, 2011; Kuntz, 2012), and thus it is usually considered to be a center of visual learning and mem- ory. Interestingly, one study on NMDA receptors reported that the EB is required for olfactory long-term memory (LTM) consolidation; however, the underlying neural circuits remain uninvestigated. The current results reveal that a group of EB neurons, the c819-labeled R2/R4m neurons, plays an inhibitory role in the modulation of MTM but not the immediate memory. This points to a new function of the EB in olfactory cognition and further demonstrates that the EB could be involved in the process of olfactory aversive learning and memory from an earlier stage than previously thought (Zhang, 2014).

The presence of dense GABA-like immunoreactivity has been demonstrated in the EB ring and RF tract suggesting that the bulk of EB neurons are GABAergic. Although this finding has been confirmed by several other studies, the function of these GABAergic neurons in cognition is still unclear. The current results further reveal that approximately two-thirds of the c819-EB neurons are GABAergic, and they play an inhibitory role in ASM modulation. The GABAA receptor, resistant to dieldrin (RDL), has been shown to be highly expressed in the MB lobes and the EB. It is thus possible that these EB GABAergic neurons function through RDL receptors (Zhang, 2014).

As a component of MTM, ASM has been suggested to be stored in the MB and to be modulated by MB intrinsic APL and DPM neurons, of which the neural terminals are restricted to the MB. This study reports the EB, a brain structure separate from the MB, is also involved in the modulation of ASM. WEB neurons may be both presynaptic and postsynaptic to MB neurons, suggesting that they may suppress 3 h ASM via putative direct connections between the EB and MB. That the MB and EB are two discrete but possibly interconnected and interacting brain regions, suggests that it is important to study the process of learning and memory over a more widely distributed neural network. However, the interaction between neurons from different structures may endow the network with greater capacity for more complex activities (Zhang, 2014).

It is also interesting to discover that activating c819-EB GABAergic neurons during training impaired 3 h ASM instead of immediate learning performance. Recently it has been reported that blocking two pairs of dopaminergic neurons during intertrial intervals in spaced training suppresses the formation of 24 h LTM by interfering with the slow oscillations in these dopaminergic neurons. Since this study has shown that bidirectional connections may exist between the EB and MB, it is proposed that there may be a small feedback circuit between the EB and MB, which may have prolonged oscillations and therefore affect 3 h ASM consolidation. Further functional imaging studies may provide more clues on how this neural circuit functions (Zhang, 2014).

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

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).

A transcriptional reporter of intracellular Ca(2+) in Drosophila

Intracellular Ca(2+) is a widely used neuronal activity indicator. This study describes a transcriptional reporter of intracellular Ca(2+) (TRIC) in Drosophila that uses a binary expression system to report Ca(2+)-dependent interactions between calmodulin and its target peptide. In vitro assays predicted in vivo properties of TRIC. TRIC signals in sensory systems were show to depend on neuronal activity. TRIC was able to quantitatively monitor neuronal responses that changed slowly, such as those of neuropeptide F-expressing neurons to sexual deprivation and neuroendocrine pars intercerebralis (PI) cells to food and arousal. Furthermore, TRIC-induced expression of a neuronal silencer in nutrient-activated cells enhanced stress resistance, providing a proof of principle that TRIC can be used for circuit manipulation. Thus, TRIC facilitates the monitoring and manipulation of neuronal activity, especially those reflecting slow changes in physiological states that are poorly captured by existing methods. TRIC's modular design should enable optimization and adaptation to other organisms (Gao, 2015).

Using cultured cells and multiple in vivo assays, this study found that TRIC reports changes in Ca2+ levels under diverse conditions in visual, olfactory and neuromodulatory systems. The results provide quantitative assessments for choosing TRIC variants with appropriate sensitivity and stringency, and proof of principle that TRIC can be used to express a circuit manipulator. Thus, TRIC acts as a useful complement to functional Ca2+ imaging by integrating changes in activity over long periods of time and offering genetic access to neurons on the basis of their activity (Gao, 2015).

Vertebrate immediate-early-gene (IEGs) which evolved to be expressed in a high signal-to-baseline ratio in response to neuronal activation, are widely used to report neuronal activity. However, as they rely on endogenous signaling networks, their response properties and cell-type biases are difficult to modify. TRIC can be considered a rationally designed IEG, by exogenously introducing a protein-peptide interaction to detect Ca2+. The modular design of TRIC renders it more amenable to optimization. TRIC reports a rise in nuclear Ca2+ levels, which have previously been used to monitor pan-neuronal activity in C. elegans, and also accompanies neuronal activation in mammalian neurons likely shuttled by Ca2+-binding proteins. The current experiments indicate that nuclear Ca2+ correlates with activity in diverse neuronal classes in flies. It is likely that not all cell types have the same efficiency in converting cytoplasmic Ca2+ signal to nuclear Ca2+ signal. Thus, TRIC efficiency and optimization may differ for different neuronal types (Gao, 2015).

While this manuscript was in review, a Ca2+ integrator (CaMPARI) was reported in which the ultraviolet conversion of emission spectrum of a fluorescent protein was engineered to be contingent on Ca2+ concentration. CaMPARI can capture neuronal activity on a shorter time scale than TRIC or IEG. However, access of neurons to ultraviolet may limit the use of CaMPARI in deep tissues, at least in large animals, whereas TRIC and IEG report neuronal activity in the entire nervous system non-invasively. Notably, unlike CaMPARI or IEG, TRIC offers genetic access to active neurons, allowing activity-based circuit manipulation (Gao, 2015).

The results underscore the importance of optimizing TRIC for specific neuronal types. In this study, TRIC was optimized for multiple cell types, and many variants were described that can help users in other cells. It is recommended that users begin with CaM/MKII-mediated TRIC in their neurons of interest. If TRIC signal is detected, the users can attempt QA-mediated or FLP-mediated regulation of the timing of TRIC onset. The signal-to-baseline ratio can be further improved by titrating expression of TRIC using QA, choosing reporters with different stabilities, or switching to nlsLexADBDo or the MKIIK11A variant. Stoichiometry can also be leveraged to boost TRIC signal (Gao, 2015).

With the current version of TRIC, the signal accumulates and decays over many hours. To detect shorter periods of neuronal activity, an important future goal is to increase signal strength while avoiding saturation by basal Ca2+ concentrations. One solution to this problem would be to restrict TRIC to a narrower time window than that offered by the QA- or the FLP-mediated strategy. For example, TRIC could be split into DBD-X, Y-target peptide and CaM-AD, where X and Y are two interacting modules controlled by light. One could then synchronize TRIC with a specific manipulation, or even trigger TRIC repetitively with specific behavioral features using feedback from automated tracking. To preserve phasic information about neuronal activity, reporters with faster decays than CD8::GFP could be used or the TRIC components could be destabilized with tags for protein degradation. Given that the current TRIC was able to interact with endogenous CaM and its target peptides, another important direction is to 'isolate' TRIC by co-engineering the CaM and MKII components to lose binding to their endogenous partners, but maintain their mutual interaction. Future TRIC optimization could be achieved using high throughput screens in cultured cells, which can predict in vivo performance (Gao, 2015).

Previous studies used Ilp2 immunostaining, epitope-tagged Ilp2 or a secreted GFP as indirect indicators of PI activity. The major conclusions of these studies were validated using TRIC. After enhancing the dynamic range of TRIC, additional insight was gained into how PI activity is regulated. In particular, given that PI cells affect diverse processes, how do these cells determine their output according to all relevant inputs? For example, an animal may encounter conflicting metabolic needs, such as conserving energy versus defending territory in an impoverished environment. Nutrient and OA comparison could be viewed as a minimal model of such a dilemma, as OA contributes to arousal and is necessary for 'fight or flight' in insects. PI cells exhibited graded, yet more readily saturated, responses to such events. In contrast, the linear PI response to nutrients extended over a wider range. These distinctions, as well as the additive interaction between yeast and OA, point to the independent operation of these two categories of inputs. To further survey the input landscape, one could genetically manipulate candidate receptors autonomously or candidate upstream neurons non-autonomously while monitoring PI activity using TRIC (Gao, 2015).

The physiological states of flies can change over hours to days and can be accompanied by changes in the activities of neurons expressing modulatory neurotransmitters or neuropeptides. Although previous work has focused on the targets of modulatory neurotransmitters, inputs to these cells remain largely unknown. In addition, there are ~75 predicted neuropeptides in flies, only a small subset of which have been examined. TRIC can be applied to neurons expressing specific transmitters or neuropeptides and tested in different physiological states (for example, the NPF neurons). It is noted that the current TRIC variants might not fit the dynamic range of all neuronal types, and it might be necessary to test other AD/DBD ratios or other MKII mutants following the examples in this paper of optimization for PI cells (Gao, 2015).

Finally, TRIC can report a rise of intracellular Ca2+ that accompanies any cellular, developmental or physiological processes in flies and can be adapted for similar use in other model organisms. TRIC modules can be introduced as transgenes or by viral vectors, and specific stoichiometry can be achieved by specifying the number of AD and DBD sequences in multi-cistronic constructs. TRIC expression can be made contingent on recombinase or other binary systems in model organisms, such as mice, where many Cre lines are available for spatiotemporal control, which can help refine activity monitoring and circuit manipulation in specific cell types (Gao, 2015).

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

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).

Sleep drive is encoded by neural plastic changes in a dedicated circuit

Prolonged wakefulness leads to an increased pressure for sleep, but how this homeostatic drive is generated and subsequently persists is unclear. From a neural circuit screen in Drosophila, this study identified a subset of ellipsoid body (EB) neurons whose activation generates sleep drive. Patch-clamp analysis indicates these EB neurons are highly sensitive to sleep loss, switching from spiking to burst-firing modes. Functional imaging and translational profiling experiments reveal that elevated sleep need triggers reversible increases in cytosolic Ca(2+) levels, NMDA receptor expression, and structural markers of synaptic strength, suggesting these EB neurons undergo 'sleep-need'-dependent plasticity. Strikingly, the synaptic plasticity of these EB neurons is both necessary and sufficient for generating sleep drive, indicating that sleep pressure is encoded by plastic changes within this circuit. These studies define an integrator circuit for sleep homeostasis and provide a mechanism explaining the generation and persistence of sleep drive (Liu, 2016).

Operation of a homeostatic sleep switch

In Drosophila, a crucial component of the machinery for sleep homeostasis is a cluster of neurons innervating the dorsal fan-shaped body (dFB) of the central complex. dFB neurons in sleep-deprived flies tend to be electrically active, with high input resistances and long membrane time constants, while neurons in rested flies tend to be electrically silent. This study demonstrates state switching by dFB neurons, identifies dopamine as a neuromodulator that operates the switch, and delineates the switching mechanism. Arousing dopamine causes transient hyperpolarization of dFB neurons within tens of milliseconds and lasting excitability suppression within minutes. Both effects are transduced by Dop1R2 receptors and mediated by potassium conductances. The switch to electrical silence involves the downregulation of voltage-gated A-type currents carried by Shaker and Shab, and the upregulation of voltage-independent leak currents through a two-pore-domain potassium channel that was termed Sandman. Sandman is encoded by the CG8713 gene and translocates to the plasma membrane in response to dopamine. dFB-restricted interference with the expression of Shaker or Sandman decreases or increases sleep, respectively, by slowing the repetitive discharge of dFB neurons in the ON state or blocking their entry into the OFF state. Biophysical changes in a small population of neurons are thus linked to the control of sleep-wake state (Pimentel, 2016).

Recordings were made from dFB neurons (which were marked by R23E10-GAL4 or R23E10-lexA-driven green fluorescent protein (GFP) expression) while head-fixed flies walked or rested on a spherical treadmill. Because inactivity is a necessary correlate but insufficient proof of sleep, the analysis was restricted to awakening, which is defined as a locomotor bout after >5 min of rest, during which the recorded dFB neuron had been persistently spiking. To deliver wake-promoting signals, the optogenetic actuator CsChrimson was expressed under TH-GAL4 control in the majority of dopaminergic neurons, including the PPL1 and PPM3 clusters, whose fan-shaped body (FB)-projecting members have been implicated in sleep control. Illumination at 630 nm, sustained for 1.5 s to release a bolus of dopamine, effectively stimulated locomotion. dFB neurons paused in successful (but not in unsuccessful) trials, and their membrane potentials dipped by 2-13 mV below the baseline during tonic activity. When flies bearing an undriven CsChrimson transgene were photostimulated, neither physiological nor behavioural changes were apparent. The tight correlation between the suppression of dFB neuron spiking and the initiation of movement might, however, merely mirror a causal dopamine effect elsewhere, as TH-GAL4 labels dopaminergic neurons throughout the brain. Because localized dopamine applications to dFB neuron dendrites similarly caused awakening, this possibility is considered remote (Pimentel, 2016).

Flies with enhanced dopaminergic transmission exhibit a short-sleeping phenotype that requires the presence of a D1-like receptor in dFB neurons, suggesting that dopamine acts directly on these cells. dFB-restricted RNA interference (RNAi) confirmed this notion and pinpointed Dop1R2 as the responsible receptor, a conclusion reinforced by analysis of the mutant Dop1R2MI08664 allele. Previous evidence that Dop1R1, a receptor not involved in regulating baseline sleep, confers responsiveness to dopamine when expressed in the dFB indicates that either D1-like receptor can fulfill the role normally played by Dop1R2. Loss of Dop1R2 increased sleep during the day and the late hours of the night, by prolonging sleep bouts without affecting their frequency. This sleep pattern is consistent with reduced sensitivity to a dopaminergic arousal signal (Pimentel, 2016).

To confirm the identity of the effective transmitter, avoid dopamine release outside the dFB, and reduce the transgene load for subsequent experiments, optogenetic manipulations of the dopaminergic system were replaced with pressure ejections of dopamine onto dFB neuron dendrites. Like optogenetically stimulated secretion, focal application of dopamine hyperpolarized the cells and suppressed their spiking. The inhibitory responses could be blocked at several nodes of an intracellular signalling pathway that connects the activation of dopamine receptors to the opening of potassium conductances: by RNAi-mediated knockdown of Dop1R2; by the inclusion in the patch pipette of pertussis toxin (PTX), which inactivates heterotrimeric G proteins of the Gi/o family; and by replacing intracellular potassium with caesium, which obstructs the pores of G-protein-coupled inward-rectifier channels. Elevating the chloride reversal potential above resting potential left the polarity of the responses unchanged, corroborating that potassium conductances mediate the bulk of dopaminergic inhibition (Pimentel, 2016).

Coupling of Dop1R2 to Gi/o, although documented in a heterologous system, represents a sufficiently unusual transduction mechanism for a predicted D1-like receptor to prompt verification of its behavioural relevance. Like the loss of Dop1R2, temperature-inducible expression of PTX in dFB neurons increased overall sleep time by extending sleep bout length (Pimentel, 2016).

While a single pulse of dopamine transiently hyperpolarized dFB neurons and inhibited their spiking, prolonged dopamine applications (50 ms pulses at 10 Hz, or 20 Hz optogenetic stimulation, both sustained for 2-10 min) switched the cells from electrical excitability (ON) to quiescence (OFF). The switching process required dopamine as well as Dop1R2, but once the switch had been actuated the cells remained in the OFF state-and flies, awake-without a steady supply of transmitter. Input resistances and membrane time constants dropped to 53.3 ± 1.8 and 24.0 ± 1.3% of their initial values (means ± s.e.m.), and depolarizing currents no longer elicited action potentials (15 out of 15 cells). The biophysical properties of single dFB neurons, recorded in the same individual before and after operating the dopamine switch, varied as widely as those in sleep-deprived and rested flies (Pimentel, 2016).

Dopamine-induced changes in input resistance and membrane time constant occurred from similar baselines in all genotypes and followed single-exponential kinetics with time constants of 1.07-1.10 min. The speed of conversion points to post-translational modification and/or translocation of ion channels between intracellular pools and the plasma membrane as the underlying mechanism(s). In 7 out of 15 cases, recordings were held long enough to observe the spontaneous recommencement of spiking, which was accompanied by a rise to baseline of input resistance and membrane time constant, after 7-60 min of quiescence (mean ± s.e.m. = 25.86 ± 7.61 min). The temporary suspension of electrical output is thus part of the normal activity cycle of dFB neurons and not a dead end brought on by the experimental conditions (Pimentel, 2016).

dFB neurons in the ON state expressed two types of potassium current: voltage-dependent A-type (rapidly inactivating) and voltage-independent non-A-type currents. The current-voltage (I-V) relation of iA resembled that of Shaker, the prototypical A-type channel: no current flowed below -50 mV, the approximate voltage threshold of Shaker; above -40 mV, peak currents increased steeply with voltage and inactivated with a time constant of 7.5 ± 2.1 ms (mean ± s.e.m.). Non-A-type currents showed weak outward rectification with a reversal potential of -80 mV, consistent with potassium as the permeant ion, and no inactivation (Pimentel, 2016).

Switching the neurons OFF changed both types of potassium current. iA diminished by one-third, whereas inon-A nearly quadrupled when quantified between resting potential and spike threshold. The weak rectification of inon-A in the ON state vanished in the OFF state, giving way to the linear I-V relationship of an ideal leak conductance. dFB neurons thus upregulate iA in the sleep-promoting ON state. When dopamine switches the cells OFF, voltage-dependent currents are attenuated and leak currents augmented. This seesaw form of regulation should be sensitive to perturbations of the neurons' ion channel inventory: depletion of voltage-gated A-type (KV) channels (which predominate in the ON state) should tip the cells towards the OFF state; conversely, loss of leak channels (which predominate in the OFF state) should favour the ON state. To test these predictions, sleep was examined in flies carrying R23E10-GAL4-driven RNAi transgenes for dFB-restricted interference with individual potassium channel transcripts (Pimentel, 2016).

RNAi-mediated knockdown of two of the five KV channel types of Drosophila (Shaker and Shab) reduced sleep relative to parental controls, while knockdown of the remaining three types had no effect. Biasing the potassium channel repertoire of dFB neurons against A-type conductances thus tilts the neurons' excitable state towards quiescence, causing insomnia, but leaves transient and sustained dopamine responses unaffected. The seemingly counterintuitive conclusion that reducing a potassium current would decrease, not increase, action potential discharge is explained by a requirement for A-type channels in generating repetitive activity of the kind displayed by dFB neurons during sleep. Depleting Shaker from dFB neurons shifted the interspike interval distribution towards longer values, as would be expected if KV channels with slow inactivation kinetics replaced rapidly inactivating Shaker as the principal force opposing the generation of the next spike. These findings identify a potential mechanism for the short-sleeping phenotypes caused by mutations in Shaker, its β subunit Hyperkinetic, or its regulator sleepless (Pimentel, 2016).

Leak conductances are typically formed by two-pore-domain potassium (K2P) channels. dFB-restricted RNAi of one member of the 11-strong family of Drosophila K2P channels, encoded by the CG8713 gene, increased sleep relative to parental controls; interference with the remaining 10 K2P channels had no effect. Recordings from dFB neurons after knockdown of the CG8713 gene product, which this study termed Sandman, revealed undiminished non-A-type currents in the ON state and intact responses to a single pulse of dopamine but a defective OFF switch: during prolonged dopamine applications, inon-A failed to rise, input resistances and membrane time constants remained at their elevated levels, and the neurons continued to fire action potentials (7 out of 7 cells). Blocking vesicle exocytosis in the recorded cell with botulinum neurotoxin C (BoNT/C) similarly disabled the OFF switch. This, combined with the absence of detectable Sandman currents in the ON state, suggests that Sandman is internalized in electrically active cells and recycled to the plasma membrane when dopamine switches the neurons OFF (Pimentel, 2016).

Because dFB neurons lacking Sandman spike persistently even after prolonged dopamine exposure, voltage-gated sodium channels remain functional in the OFF state. The difficulty of driving control cells to action potential threshold in this state must therefore be due to a lengthening of electrotonic distance between sites of current injection and spike generation. This lengthening is an expected consequence of a current leak, which may uncouple the axonal spike generator from somatodendritic synaptic inputs or pacemaker currents when sleep need is low (Pimentel, 2016).

The two kinetically and mechanistically distinct actions of dopamine on dFB neurons-instant, but transient, hyperpolarization and a delayed, but lasting, switch in excitable state-ensure that transitions to vigilance can be both immediate and sustained, providing speedy alarm responses and stable homeostatic control. The key to stability lies in the switching behaviour of dFB neurons, which is driven by dopaminergic input accumulated over time. Unlike bistable neurons, in which two activity regimes coexist for the same set of conductances, dFB neurons switch regimes only when their membrane current densities change. This analysis of how dopamine effects such a change, from activity to silence, has uncovered elements familiar from other modulated systems: simultaneous, antagonistic regulation of multiple conductances; reduction of iA; and modulation of leak currents. Currently little is known about the reverse transition, from silence to activity, except that mutating the Rho-GTPase-activating protein Crossveinless-c locks dFB neurons in the OFF state, resulting in severe insomnia and an inability to correct sleep deficits. Discovering the signals and processes that switch sleep-promoting neurons back ON will hold important clues to the vital function of sleep (Pimentel, 2016).

Drosophila acquires a long-lasting body-size memory from visual feedback

Implicit knowledge of peripersonal space in humans is first acquired during infancy but will be continuously updated throughout life. In contrast, body size of holometabolous insects does not change after metamorphosis; nevertheless, they do have to learn their body reaches at least once. The body size of Drosophila imagines can vary by about 15% depending on environmental factors like food quality and temperature. To investigate how flies acquire knowledge about and memorize their body size, their decisions to either refrain from or initiate climbing over gaps exceeding their body size were studied. Naive (dark-reared) flies overestimate their size and have to learn it from the parallax motion of the retinal images of objects in their environment while walking. Naive flies can be trained in a striped arena and manipulated to underestimate their size, but once consolidated, this memory seems to last for a lifetime. Consolidation of this memory is stress sensitive only in the first 2 h after training but cannot be retrieved for the next 12 h. This study has identified a set of intrinsic, lateral neurons of the protocerebral bridge of the central complex that depend on dCREB2 transcriptional activity for long-term memory consolidation and maintenance (Krause, 2019).

Sleep-promoting effects of threonine link amino acid metabolism in Drosophila neuron to GABAergic control of sleep drive

Emerging evidence indicates the role of amino acid metabolism in sleep regulation. This study demonstrates sleep-promoting effects of dietary threonine (SPET) in Drosophila. Dietary threonine markedly increased daily sleep amount and decreased the latency to sleep onset in a dose-dependent manner. High levels of synaptic GABA or pharmacological activation of metabotropic GABA receptors (GABAB-R) suppressed SPET. By contrast, synaptic blockade of GABAergic neurons or transgenic depletion of GABAB-R in the ellipsoid body R2 neurons enhanced sleep drive non-additively with SPET. Dietary threonine reduced GABA levels, weakened metabotropic GABA responses in R2 neurons, and ameliorated memory deficits in plasticity mutants. Moreover, genetic elevation of neuronal threonine levels was sufficient for facilitating sleep onset. Taken together, these data define threonine as a physiologically relevant, sleep-promoting molecule that may intimately link neuronal metabolism of amino acids to GABAergic control of sleep drive via the neuronal substrate of sleep homeostasis (Ki, 2019).

The circadian clock and sleep homeostasis are two key regulators that shape daily sleep behaviors in animals. In stark contrast to the homeostatic nature of sleep, the internal machinery of sleep is vulnerable to external (e.g., environmental change) or internal conditions (e.g., genetic mutation) that lead to adaptive changes in sleep behaviors. Sleep behavior is conserved among mammals, insects, and even lower eukaryotes. Since the identification of the voltage-gated potassium channel Shaker as a sleep-regulatory gene in Drosophila, fruit flies have been one of the most advantageous genetic models to dissect molecular and neural components that are important for sleep homeostasis and plasticity (Ki, 2019).

To date, a number of sleep-regulatory genes and neurotransmitters have been identified in animal models as well as in humans. For instance, the inhibitory neurotransmitter gamma-aminobutyric acid (GABA) is known to have a sleep-promoting role that is conserved in invertebrates and vertebrates. Hypomorphic mutations in mitochondrial GABA-transaminase (GABA-T) elevate GABA levels and lengthen baseline sleep in flies (Chen, 2015). The long sleep phenotype in GABA-T mutants accompanies higher sleep consolidation and shorter latency to sleep onset, consistent with the observations that pharmacological enhancement of GABAergic transmission facilitates sleep in flies and mammals, including humans. In addition, resistance to dieldrin (Rdl), a Drosophila homolog of the ionotropic GABA receptor, suppresses wake-promoting circadian pacemaker neurons in adult flies to exert sleep-promoting effects. Similarly, 4,5,6,7-tetrahydroisoxazolo[5,4 c]pyridin-3-ol (THIP), an agonist of the ionotropic GABA receptor, promotes sleep in insects and mammals (Ki, 2019).

Many sleep medications modulate GABAergic transmission. A prominent side effect of anti-epileptic drugs relevant to GABA is causing drowsiness. Conversely, glycine supplements improve sleep quality in a way distinct from traditional hypnotic drugs, minimizing deleterious cognitive problems or addiction. In fact, glycine or D-serine acts as a co-agonist of N-methyl-D-aspartate receptors (NMDARs) and promotes sleep through the sub-type of ionotropic glutamate receptors. Emerging evidence further supports the roles of amino acid transporters and metabolic enzymes in sleep regulation. In particular, it has been demonstrated that starvation induces the expression of metabolic enzymes for serine biosynthesis in Drosophila brains, and elevates free serine levels to suppress sleep via cholinergic signaling (Sonn, 2018). These observations prompted a hypothesis that other amino acids may also display neuro-modulatory effects on sleep behaviors (Ki, 2019).

The molecular and neural machinery of sleep regulation intimately interacts with external (e.g., light, temperature) and internal sleep cues (e.g., sleep pressure, metabolic state) to adjust the sleep architecture in animals. Using a Drosophila genetic model, this study has investigated whether dietary amino acids could affect sleep behaviors, through this investigation SPET was discovered. Previous studies have demonstrated that the wake-promoting circadian pacemaker neurons are crucial for timing sleep onset after lights-off in LD cycles. In addition, WAKE-dependent silencing of clock neurons and its collaborative function with RDL have been suggested as a key mechanism in the circadian control of sleep onset. However, the current evidence indicates that SPET facilitates sleep onset in a manner independent of circadian clocks. It was further elucidated that SPET operates likely via the down-regulation of metabotropic GABA transmission in R2 EB neurons, a neural locus for generating homeostatic sleep drive (Ki, 2019).

Both food availability and nutritional quality substantially affect sleep behaviors in Drosophila. Sucrose contents in food and their gustatory perception dominate over dietary protein to affect daily sleep. Starvation promotes arousal in a manner dependent on the circadian clock genes Clock and cycle as well as neuropeptide F (NPF), which is a fly ortholog of mammalian neuropeptide Y. On the other hand, protein is one of the nutrients that contribute to the postprandial sleep drive in Drosophila and this observation is possibly relevant to SPET. While Leucokinin (Lk) and Lk receptor (Lkr) play important roles in dietary protein-induced postprandial sleepand in starvation-induced arousal, comparable SPET was observed between hypomorphic mutants of Lk or Lkr and their heterozygous controls. Therefore, SPET and its neural basis reveal a sleep-regulatory mechanism distinct from those involved in sleep plasticity relevant to food intake (Ki, 2019).

What will be the molecular basis of SPET? Given the general implication of GABA in sleep promotion, a simple model will be that a molecular sensor expressed in a subset of GABAergic neurons (i.e., LN) directly responds to an increase in threonine levels, activates GABA transmission, and thereby induces sleep. Several lines of evidence, however, favored the other model that dietary threonine actually down-regulates metabotropic GABA transmission in R2 EB neurons, de-represses the neural locus for generating homeostatic sleep drive, and thereby enhances sleep drive. The latter model does not necessarily conflict with sleep-promoting effects of genetic or pharmacological conditions that generally elevate GABA levels or enhance GABAergic transmission since those effects will be the net outcome of activated GABA transmission via various sub-types of GABA receptors expressed in either wake- or sleep-promoting neurons and their (Ki, 2019).

The structural homology among threonine, GABA, and their metabolic derivatives (e.g., alpha-ketobutyrate and gamma-hydroxybutyrate) led to the hypothesis that these relevant chemicals may act as competitive substrates in enzymatic reactions for their overlapping metabolism. Consequently, dietary threonine may limit the total flux of GABA-glutamate-glutamine cycle possibly through substrate competition, decreases the size of available GABA pool, and thereby down-scales GABA transmission for SPET. This accounts for why genetic or pharmacological elevation of GABA levels rather suppresses SPET. Threonine, GABA, and their derivatives may also act as competitive ligands for metabotropic GABA receptors, explaining weak GABA responses in R2 EB neurons of threonine-fed flies. Biochemical and neural evidence supportive of this hypothesis is quite abundant. It has been previously shown that alpha-ketobutyrate, GABA, and the ketone body beta-hydroxybutyrate act as competitive substrates in common enzymatic reactions. Moreover, functional interactions of beta-hydroxybutyrate or gamma-hydroxybutyrate with GABAergic signaling have been well documented. Finally, threonine and GABA derivatives have anti-convulsive effects, which further support their common structural and functional relevance to GABAergic signaling (Ki, 2019).

The removal of the amino group is the initial step for amino acid metabolism, and various transaminases mediate its transfer between amino acids and alpha-keto acids. On the other hand, a group of amino acids (i.e., glutamate, glycine, serine, and threonine) has their own deaminases that can selectively remove the amino group. The presence of these specific deaminases is indicative of active mechanisms that individually fine-tune the baseline levels of these amino acids in metabolism, and possibly in the context of other physiological processes as well. This idea is further supported by the conserved roles of glutamate, glycine, and serine as neurotransmitters or neuromodulators important for brain function, including sleep regulation. In fact, serine, glycine, and threonine constitute a common metabolic pathway, and threonine may contribute indirectly to glycine- or serine-dependent activation of sleep-promoting NMDAR. Nonetheless, this study found that sleep-modulatory effects of dietary glycine were distinct from SPET and thus, it is speculated that threonine may act as an independent neuromodulator, similar to other amino acids with their dedicated deaminases (Ki, 2019).

While several lines of the data support that threonine is likely to be an endogenous sleep driver in fed conditions, it wa recently demonstrated that starvation induces serine biosynthesis in the brain and neuronal serine subsequently suppresses sleep via cholinergic signaling (Sonn, 2018). These two pieces of relevant works establish a compelling model that the metabolic pathway of serine-glycine-threonine functions as a key sleep-regulatory module in response to metabolic sleep cues (e.g., food ingredients and dietary stress). It is further hypothesized that the adaptive control of sleep behaviors by select amino acids and their conserved metabolic pathway suggests an ancestral nature of their sleep regulation. Future studies should address if the serine-glycine-threonine metabolic pathway constitutes the sleep homeostat that can sense and respond to different types of sleep needs. In addition, it will be interesting to determine if this metabolic regulation of sleep is conserved among other animals, including humans (Ki, 2019).

A serotonin-modulated circuit controls sleep architecture to regulate cognitive function independent of total sleep in Drosophila

Both the structure and the amount of sleep are important for brain function. Entry into deep, restorative stages of sleep is time dependent; short sleep bouts selectively eliminate these states. Fragmentation-induced cognitive dysfunction is a feature of many common human sleep pathologies. Whether sleep structure is normally regulated independent of the amount of sleep is unknown. This study shows that in Drosophila melanogaster, activation of a subset of serotonergic neurons fragments sleep without major changes in the total amount of sleep, dramatically reducing long episodes that may correspond to deep sleep states. Disruption of sleep structure results in learning deficits that can be rescued by pharmacologically or genetically consolidating sleep. Two reciprocally connected sets of ellipsoid body neurons were identified that form the heart of a serotonin-modulated circuit that controls sleep architecture. Taken together, these findings define a circuit essential for controlling the structure of sleep independent of its amount (Liu, 2019).

This study describes a circuit that regulates of sleep structure without affecting the total amount of sleep. 5HT acts to enhance the response of 5HT7-GAL4+ neurons to basally active excitatory inputs. 5HT-dependent calcium signals are blocked by TTX, while its ability to increase cAMP is not, supporting the existence of these active excitatory inputs to 5HT7-GAL4+ cells. In contrast, VT-GAL4+ cells do not have basally active excitatory inputs. 5HT modulation of the circuit likely occurs primarily via inputs to 5HT7-GAL4+ neurons since the response of VT038828-GAL4 (VT-GAL4)+ neurons is weaker and lower affinity. Whether there are other, perhaps situationally active, inputs to this circuit is currently unknown (Liu, 2019).

Within the ellipsoid body (EB) the circuit is complex. VT-GAL4+ neurons are functionally connected with the 5HT7-GAL4+ group. VT-GAL4+ neurons provide feedback inhibition to a subset of 5HT7-GAL4+ neurons, which enhances fragmentation, likely via output to non-central complex regions. How inhibition of a subset of the 5HT7-GAL4+ cells acts to modulate the behavioral output of the rest of the population is not yet clear, but it is noted that many of the 5HT7-GAL4+ cells are GABAergic. While all the details of the circuit's complex dynamics remain to be discovered, it is clear that this circuit has a profound and selective effect on sleep architecture (Liu, 2019).

The circuit described in this study is modulated by 5HT, a neurochemical known to be important for regulation of behavioral states in many species. While 5HT in mammals is important in a wide variety of contexts, it was controversial for nearly half a century whether it promoted sleep or wakefulness. In Drosophila, 5HT has only been thought to promote sleep. The current data show that upregulation of serotonergic signaling can also induce sleep fragmentation, suggesting that 5HT's role in sleep in flies exhibits a complexity similar to that of its roles in mammals. The genesis of this apparently conserved complexity may be the extensive involvement of 5HT in non-sleep processes. For an animal in the wild, sleep has inherent risks: predation and loss of opportunities for mating or feeding are just a few. Sleep/wake systems in the brain must control arousal state in collaboration with systems that assess competing needs. 5HT, because it is central to so many critical behavioral circuits, is ideally poised to be an integration point for sleep and the general state of the animal. The diverse, circuit-specific, roles in sleep that 5HT exhibits across phyla may be a result of its ubiquity (Liu, 2019).

The role this study has uncovered for 5HT as a regulator of sleep architecture aligns well with this idea. The daily neuronal activity profile reported by Tric-LUC, a calcium sensor that drives luciferase expression in response to neuronal activity, in sleep fragmentation-generating neurons maps to dawn and dusk, when crepuscular organisms such as fruit flies are most active. Fragmentation of sleep at these times would presumably be beneficial since flies would not enter into deep sleep states at times when they should be feeding and mating. Interestingly, the circuit described in this study accomplishes this feat by increasing P(doze), the probability of falling asleep from a wake state, leaving the scaling of P(wake), a parameter associated with dopamine and arousal, free to be modulated by other factors (e.g., danger from predation, appearance of potential mates). The fact that long sleep bouts can be prevented without putting the animal into a hyperaroused state is advantageous, allowing flexible responsiveness to changing conditions. The involvement of P(Doze), a parameter associated with sleep drive, is also congruent with the sleep-promoting role of 5HT in other brain regions (Liu, 2019).

While controlled sleep fragmentation appears to assist in active period behavior, there is also a need for consolidated sleep. In both mammals and Drosophila, sleep has electrophysiologically distinct substrates with progressively higher arousal thresholds that appear in an ordered fashion during a sleep episode. The deeper sleep stages in mammals, REM and slow wave sleep, are strongly associated with maintenance of cognitive function. Fragmentation of sleep, because it truncates sleep episodes before deeper stages are reached, can result in a selective deprivation of deep sleep stages even when total sleep is not changed. In this study, it was demonstrated that decreasing sleep consolidation, without changing the amount of sleep, can disrupt associative learning. These results suggest that in Drosophila, like in mammals, there are time-dependent changes in the depth of sleep that are important for its beneficial effects. This idea is also supported by modeling and analysis of the structure of fly sleep, which indicate that there are time-dependent changes in the probability of sleep-wake transitions consistent with the existence of deep sleep stages that are only accessed in long sleep episodes (Liu, 2019).

Fragmentation of sleep induced by activation of 5HT inputs to the EB also produced an increase in sleep after the activation was terminated. Excess sleep in the recovery day after a perturbation is a hallmark of a homeostatic process. Homeostatic regulation of total sleep time has been previously demonstrated in Drosophila, but the data suggest that there is also homeostatic regulation of sleep quality. In mammals, individual sleep substates have been demonstrated to be homeostatically regulated- selective deprivation of REM or slow wave sleep, in the absence of loss of total sleep time, drive rebound increases of the deprived stage and mechanical sleep fragmentation has been shown to lead to an increase in total sleep. The ability of the EB circuit in Drosophila to selectively modulate sleep structure, without changing the total amount of sleep, has allowed for the first time the selective probing of the cognitive importance of long sleep bouts and deep sleep stages in the fly. The fact that fragmentation triggers rebound sleep implies that these long sleep bouts may also be important for the general health benefits of sleep (Liu, 2019).

A computational model of the integration of landmarks and motion in the insect central complex

The insect central complex (CX) has been implicated in a wide range of behaviours. Recent experimental evidence from Drosophila and the cockroach (Blaberus discoidalis) has demonstrated the existence of neural activity corresponding to the animal's orientation within a virtual arena (a neural 'compass'), and this provides an insight into one component of the CX structure. There are two key features of the compass activity: an offset between the angle represented by the compass and the true angular position of visual features in the arena, and the remapping of the 270 degrees visual arena onto an entire circle of neurons in the compass. This study presents a computational model which can reproduce this experimental evidence in detail, and predicts the computational mechanisms that underlie the data. It is predicted that both the offset and remapping of the fly's orientation onto the neural compass can be explained by plasticity in the synaptic weights between segments of the visual field and the neurons representing orientation. Furthermore, it is predicted that this learning is reliant on the existence of neural pathways that detect rotational motion across the whole visual field and uses this rotation signal to drive the rotation of activity in a neural ring attractor. This model also reproduces the 'transitioning' between visual landmarks seen when rotationally symmetric landmarks are presented. This model can provide the basis for further investigation into the role of the central complex, which promises to be a key structure for understanding insect behaviour, as well as suggesting approaches towards creating fully autonomous robotic agents (Cope, 2017).

Angular velocity integration in a fly heading circuit

Many animals maintain an internal representation of their heading as they move through their surroundings. Such a compass representation was recently discovered in a neural population in the Drosophila melanogaster central complex (see Anatomy suggests a potential circuit mechanism to update a compass representation), a brain region implicated in spatial navigation. This study used two-photon calcium imaging and electrophysiology in head-fixed walking flies to identify a different neural population that conjunctively encodes heading and angular velocity, and is excited selectively by turns in either the clockwise or counterclockwise direction. These mirror-symmetric turn responses combine with the neurons' connectivity to the compass neurons to create an elegant mechanism for updating the fly's heading representation when the animal turns in darkness. This mechanism, which employs recurrent loops with an angular shift, bears a resemblance to those proposed in theoretical models for rodent head direction cells. These results provide a striking example of structure matching function for a broadly relevant computation (Turner-Evans, 2017).

A stable internal representation of heading is fundamental to successful navigation. Neurons that maintain such a representation in darkness have been reported across various species. Several computational models have been proposed to explain how a population representation of heading might be updated using angular velocity signals from different neural populations, but identifying connections between neurons that carry and integrate these disparate signals has been challenging in mammals. This study took advantage of the small size, strong topography and well-described anatomy and cell types of the fly central complex to identify a candidate neuron population, P-ENs, which carry angular velocity signals. Cell-type-specific genetic tools were used to perform electrophysiological recordings from single P-EN neurons and two-photon calcium imaging from entire populations of both P-ENs and the previously described 'compass neurons' (E-PGs) in head-fixed walking flies to demonstrate how these neurons together create an elegant circuit mechanism to update a heading representation when the fly turns in darkness. The circuit motif underlying this mechanism shares some characteristics with past conceptual models of head-direction cell function (Turner-Evans, 2017).

The rate model that was implemented in this study was able to capture the essence of the observed network activity, reproducing physiological activity in response to an input that is specific to one side of the protocerebral bridge, but uniform otherwise. This suggests a level of control over moving the activity bump that is quite simple to implement in neural circuitry. In addition, the model is agnostic to the type of input that is needed to rotate the bump. It does, however, require inputs that are activated when the fly turns, with a strength proportional to the strength of the turn, and that such inputs preferentially innervate one hemisphere to create a mirror-symmetry in the system. This description anatomically matches at least one known cell type: PBG1/2-9.b-SPSi.s (Wolff, 2015). The model also requires inhibition to maintain a stationary bump and linear velocity integration. The widely arborizing and glutamatergic PB18.s-GxΔ7Gy.b neurons may provide such large-scale inhibition onto the P-EN neurons (Turner-Evans, 2017).

Some discrepancies remain between the proposed model and the experimental evidence presented in this study. The model assumes only one P-EN neuron per protocerebral bridge glomerulus (Wolff, 2015), which puts a strong constraint on the angular velocity integration properties of the circuit. In particular, although the circuit displays linear velocity integration within the typical range of angular velocities, the activity bump gets 'stuck' at individual P-EN neurons for small turns. That is, when the fly turns slowly, the corresponding small inputs to the circuit do not trigger bump movements. No such bump dynamics were observed in the imaging experiments, indicating that other, unexplored factors may help smooth bump movement in the actual circuit. Noise in the circuit, potential gap junctions and dendro-dendritic connections within and between E-PG and P-EN neurons, as well as the activity of other cell types in the circuit, such as the PBG1-8.s-EBt.b-D/Vgall.b neurons (Wolff, 2015), may all play a role in smoothing bump movement. These factors may also contribute to differences in bump shape and width between the model and experimental data. Further, the model suggests that E-PG activity is directly passed to the P-EN neurons in the protocerebral bridge, possibly with some anatomical offset and modulation through inhibition. Indeed, almost coincident bumps of activity were observed in the bridge for the two cell types. However, while functional connectivity showed a clear connection from the P-EN neurons to the E-PG neurons, the connectivity, electrophysiology, and imaging results suggested that the E-PG to P-EN connection might be more indirect and also recruit inhibition. In the functional connectivity experiments, very strong activation of the E-PG population reliably excited the P-EN neurons, but weaker excitation evoked a variety of responses. Electrophysiological recordings also revealed an unanticipated complexity in the tuning of the P-ENs' membrane potential. Membrane potential tuning curves generally showed a peak at the same heading as the spike rate tuning curves, but also a pronounced trough about 150° distant from that peak. That trough, likely a result of inhibition in the circuit, was not always evident in the spike rate tuning. Finally, in two-color imaging, offsets were observed of up to one glomerulus between the E-PG and P-EN activity on the ipsilateral side of the bridge, and unexpected P-EN activity on the contralateral side, also offset from the E-PG activity. These results were consistent for both color indicator pairings, as well as in experiments involving a second driver line, suggesting that the effects are not merely an artifact of indicator kinetics or co-expression in another population of neurons. It was noted that during slow rotations, when P-EN activity is low and the E-PG bump is weak, these offsets decreased and, depending on the driver line used, also differed between the ipsi- and contralateral side during a turn. These ae taken as indications that the connectivity between the E-PG and P-EN neurons in the protocerebral bridge may be partly indirect. Future studies will address how excitatory and inhibitory connectivity between these populations and others shape the circuit's compass function (Turner-Evans, 2017).

Still uncertain is whether an activity bump can be independently sustained in the P-EN and E-PG populations, or in the left vs. right P-EN subpopulations. The connections from P-ENs to E-PGs may be the substrate that sustains the maintenance of E-PG bump position in the ellipsoid body in the absence of both visual and self-motion cues (Seelig, 2015), as in the current model. The significant reduction seen in E-PG bump amplitude and PVA (population vector average) strength when synaptic transmission from P-ENs was blocked is supportive of such an idea. Whether E-PG input is similarly essential to the maintenance of P-EN bump strength is less clear, but P-EN heading tuning hints at a dependence on E-PG input. On the other hand, appropriate local connections between nearby neurons either in the ellipsoid body or in the protocerebral bridge may allow bumps of activity to be independently sustained in the E-PG neurons. Signs of such internal connections come, for example, from evidence of presynaptic specializations of E-PGs in the ellipsoid body. Bump persistence could also be achieved through long time-scale cellular biophysics. Future experiments and electron microscopy-based circuit reconstruction efforts should provide stronger constraints on the space of possible models, and clarify the functional and behavioral relevance of the actual circuit structure (Turner-Evans, 2017).

For a circuit mechanism in which phase relationships and conjunctive coding are important, calcium imaging may seem an unreliable arbiter of truth. Somatic single cell recordings, on the other hand, can be hard to interpret given the intricate projection patterns of fly neurons and the compartmentalization of information processing that this can produce. However, the results from calcium imaging and electrophysiology experiments in P-EN neurons were found to be in broad agreement. The electrical signature of P-EN responses to angular and forward velocity mirrored seem with calcium imaging in the noduli. The measured width of a single P-EN neuron's receptive field (~60°) was lower than that observed with calcium imaging (~110°), but this may arise from the slow decay kinetics of calcium indicators. One inconsistency between results, however, related to the imaging of neural activity in the protocerebral bridge. Based on imaging in the noduli and electrophysiology, it was expected that turns in one direction would evoke a steady decrease in activity on the other (contralateral) side of the bridge with increasing rotational velocity. Instead, imaging in the bridge showed a mild increase in activity at higher velocities, albeit while preserving the expected asymmetry between the ipsi- and contralateral side. It is hypothesized that this calcium signal might represent synaptic inputs to the P-ENs more than their spiking activity (Turner-Evans, 2017).

Blocking P-EN output using shiTS had two effects on the E-PG bump: Its amplitude was reduced and its position sometimes changed dramatically during small turns (visible as an increase in variability and low R2 for the correlation of changes in heading versus PVA. The bump amplitude decrease in shiTS flies at high temperature can be readily explained by the reduction in synaptic input to the E-PGs -- indeed, in the firing rate model P-EN input is essential to the maintenance of the E-PG bump. Several factors may explain why the E-PG bump did not completely disappear during this manipulation. First, cell-intrinsic properties of the E-PG neurons may contribute to the persistence of activity in those neurons even in the absence of external input. Second, the shiTS block may have been incomplete, meaning that there was sufficient P-EN drive even at high temperatures to keep the E-PG bump alive. Third, it the possibility of gap junctions between P-EN and E-PG neurons, which the experiments would not block, cannot be ruled out. Finally, other neuron types may also provide synaptic input to the E-PG population in the ellipsoid body. Some of these possibilities have been suggested in a recent study that used the anatomy of protocerebral bridge neurons to create a spiking model that generates ring attractor dynamics (Kakaria, 2017; Turner-Evans, 2017 and references therein).

Further, the conceptual and firing rate models would imply that if the P-EN to E-PG connections were entirely removed, E-PG activity would be unable to follow the fly's turns. However, the E-PG activity does still track the fly's turns at high temperature, when the P-EN synaptic output should be blocked. This may, once again, be the result of an incomplete block. It is speculated that one reason that the E-PG bump makes large movements across the ellipsoid body even during small turns is that a reduction in bump amplitude destabilizes the compass representation. Thus, fluctuations in the activity of the E-PGs elsewhere in the ellipsoid body may exert a greater influence on the movements of the bump than under normal conditions, when activity in distant E-PGs is likely to be suppressed. Yet another possibility that could explain the bump's movements is raised by a parallel study, which provides further evidence for P-ENs serving a role in angular integration and describes a second subtype of P-EN neurons that likely also influences the position of the E-PG bump (Green, 2017; Turner-Evans, 2017 and references therein).

The coordinated activity of the E-PG population and its control by the P-EN population when the fly turns are strongly evocative of a compass. The animal could, in principle, use such a neural compass to tether its actions to local landmarks or other sensory cues during navigation, and maintain its bearings in the temporary absence of such cues . Consistent with this idea, the PVA computed with E-PG population activity tracks the fly's heading quite accurately even in darkness. However, it is not yet known how downstream circuits read out E-PG population activity. Thus, although the PVA metric is a useful representation of E-PG compass-like activity, whether downstream circuits perform similar computations to extract the fly's heading is unclear. Further, the PVA was derived by combining the strength and angular position of activity in the E-PG population. Although both these features of E-PG activity likely influence downstream neurons, their specific influence on such neurons will depend on the precise connectivity of the circuit, something that a combination of functional connectivity studies and electron microscopy may reveal in time. Although there is considerable evidence across insects suggesting that CX neurons influence action initiation and turning movements , the connection of E-PG and P-EN neurons to the largely unidentified class of CX neurons that drive behavioral decisions is as yet unclear (Turner-Evans, 2017).

This study has focused on the effects of self-motion cues on bump movement, to which end most of the experiments were conducted with flies walking in the dark. However, E-PG activity is strongly influenced by visual cues, as evidenced by the fact that cue jumps can reset the bump position (Seelig, 2015; Kim, 2017). The angular velocity representation of P-EN neurons, by contrast, seemed unaffected by the presence of closed loop visual feedback. Thus, while a circuit mechanism was suggested for updating heading representation in the dark using self-motion signals, it is anticipated that strong sensory inputs, including those from visual cues, control updating in other circumstances. For example, it was previously observed that the ring neurons retinotopically respond to visual cues (Seelig, 2013). As the putative ring neuron axons arborize in the ellipsoid body along with the E-PG dendrites, it may be possible for them to convey visual information to the E-PG neurons, influencing the movement of the bump of activity. Further, it was suggested above that the E-PG to P-EN connection in the protocerebral bridge may be indirect and recruit sources of inhibition. There exist a few classes of bridge interneurons which may serve as intermediaries in E-PG to P-EN connections. Future studies should help clarify their role in the compass network (Turner-Evans, 2017).

Fly E-PG neurons share several characteristics with mammalian head direction cells. Both head direction cells and E-PG neurons maintain one stable bump of activity and both track the animal's heading in darkness, a feature that is well described by appropriately wired ring attractor models. Rodents that are deprived of proprioceptive and motor efference signals, as in passive transport experiments, show impaired heading representation. To update their heading in darkness, head direction cells in rodent thalamic nuclei and post-subiculum are thought to depend on angular velocity input from the vestibular system, mediated by the dorsal tegmental nucleus. Although 75% of neurons in this region were found to encode angular head velocity, only about a third of those did so in the mirror-symmetric, turn-direction-selective fashion of Drosophila P-EN neurons that were describe in this study (Turner-Evans, 2017).

Individual P-EN neurons were deterministic in their left-right mirror-symmetric rotation tuning, but diverse in the range of rotational velocities that their tuning curves spanned. Indeed, the measured bandwidth of individual P-ENs ranged anywhere between 30° and 270°/s. This diversity may reflect the diversity of tuning of the three to four P-EN neurons that innervate each protocerebral bridge glomerulus (estimated from cell body counts. Such a range of sensitivities and bandwidths would permit a more precise tracking of the flies' turns across a wide range of rotational velocities (Turner-Evans, 2017).

The origins of angular velocity responses in P-ENs are as yet unclear, but these responses show a latency relative to the fly's turning movements that are estimated to be ~150 ms, suggesting that they arise from proprioception rather than motor efference. Anatomically, both the two halves of the protocerebral bridge as well as the two noduli are mirror-symmetric structures innervated by a number of neuron types in a lateralized manner, making them likely candidates for receiving such rotation-tuned input. In the cockroach, neurons encoding angular as well as forward velocity have been recorded in the fan-shaped body, a substructure of the central complex that is evolutionarily conserved in flies. Of note, only one of the forty turn responsive neurons in the latter study showed bidirectional modulation, with excitation for turns in the preferred direction and inhibition for turns the other way, a hallmark of the P-EN neurons. These studies, which relied on extracellular recordings and did not identify cell types, found that changes in spike rate regularly preceded locomotor changes instead of tracking them as was found for the fly P-ENs. If it is assumed that neurons of the type recorded in the cockroach also exist in the fly, it is not yet clear whether the P-EN/E-PG compass network that is described in this article exploit advance information about expected changes in angular velocity (Turner-Evans, 2017).

A striking aspect of the fly compass system is its structural symmetry. Mirror symmetry is a prominent feature of the anatomical layout of the protocerebral bridge. The developmental origins of the anatomical positions of central complex neurons have been the focus of numerous studies. However, although the two sides of the protocerebral bridge and the noduli are tuned to rotations in opposite directions, maintaining symmetry at the large scale, the activity of the E-PGs and P-ENs at the scale of bridge glomeruli breaks this symmetry. During a turn, bumps of activity propagate through the left and right sides of the bridge in parallel, in a manner reminiscent of windshield wipers, rather than obeying mirror symmetry. This pattern of activity, together with the connectivity of protocerebral bridge glomeruli and ellipsoid body sectors ensures that the E-PG bump moves smoothly around the ellipsoid body when the fly turns (Turner-Evans, 2017).

More broadly, topographical organization is a striking feature of many sensory circuits, but structure often follows computational function in neural circuits in the central brain as well. The feedforward pathways to and from the Mauthner cell make clear these neurons role in rapid escape behavior, and the parallel delay loops of the barn owl auditory system and the electric fish point to their comparative roles in localizing prey. The anatomical shift of the P-EN neurons with respect to the E-PG neurons provided an immediate clue to a potential structure/function relationship, that of a mechanism for shifting the bump of E-PG activity to update their internal representation of heading. The fact that topography often matches topology in the small fly brain makes the system ideal for the identification of circuit mechanisms underlying complex computations. Only time -- and perhaps large scale circuit reconstruction efforts -- will tell whether such network motifs are also present, but perhaps better hidden, in the more distributed circuits of much larger brains (Turner-Evans, 2017).

The topographical mapping in Drosophila central complex network and its signal routing

Neural networks regulate brain functions by routing signals. Therefore, investigating the detailed organization of a neural circuit at the cellular levels is a crucial step toward understanding the neural mechanisms of brain functions. To study how a complicated neural circuit is organized, this study analyzed recently published data on the neural circuit of the Drosophila central complex, a brain structure associated with a variety of functions including sensory integration and coordination of locomotion. Except for a small number of 'atypical' neuron types, it was found that the network structure formed by the identified 194 neuron types can be described by only a few simple mathematical rules. Specifically, the topological mapping formed by these neurons can be reconstructed by applying a generation matrix on a small set of initial neurons. By analyzing how information flows propagate with or without the atypical neurons, it was found that while the general pattern of signal propagation in the central complex follows the simple topological mapping formed by the 'typical' neurons, some atypical neurons can substantially re-route the signal pathways, implying specific roles of these neurons in sensory signal integration. The present study provides insights into the organization principle and signal integration in the central complex (Chang, 2017).

A conserved plan for wiring up the fan-shaped body in the grasshopper and Drosophila

The central complex comprises an elaborate system of modular neuropils which mediate spatial orientation and sensory-motor integration. The neuroarchitecture of the largest of these modules, the fan-shaped body, is characterized by its stereotypic set of decussating fiber bundles. These are generated during development by axons from four homologous protocerebral lineages which enter the commissural system and subsequently decussate at stereotypic locations across the brain midline. It is not clear how the decussating bundles relate to individual lineages, or if the projection pattern is conserved across species. This study traced the axonal projections from the homologous central complex lineages into the commissural system of the embryonic and larval brains of both the grasshopper and Drosophila. Projections into the primordial commissures of both species are found to be lineage-specific and allow putatively equivalent fascicles to be identified. Comparison of the projection pattern before and after the commencement of axon decussation in both species reveals that equivalent commissural fascicles are involved in generating the columnar neuroarchitecture of the fan-shaped body. Further, the tract-specific columns in both the grasshopper and Drosophila can be shown to contain axons from identical combinations of central complex lineages, suggesting that this columnar neuroarchitecture is also conserved (Boyan, 2017).

In both the grasshopper S. gregaria and Drosophila, the fan-shaped body with its prominent columnar neuroarchitecture (see Wiring of the central complex subserves information processing) comprises the largest module of the adult central complex. In the grasshopper, this columnar neuroarchitecture develops from an initially orthogonal primary axon scaffold during the second half of embryogenesis and is functional at the time of hatching. The neuroarchitecture is generated when subsets of axons from four lineages (termed W, X, Y, Z) in each protocerebral hemisphere innervate the existing commissural system but then decussate from anterior to more posterior lying fascicles at stereotypic locations across the central brain in a process known as 'fascicle switching'. In Drosophila, decussation of axons from four putatively equivalent lineages to those of the grasshopper also occurs , but during the larval to pupal transition, so that the resulting neuroarchitecture is essentially an adult feature. Species comparisons reveal that fascicle switching is present at some stage of development in the central brain of all arthropods and so may be considered a conserved mode of axogenesis (Boyan, 2017).

A major drawback in understanding of axon decussation in the insect brain has been the lack of a systematic identification of the embryonic commissural fascicles involved. In the grasshopper, for example, although a map of all commissures for the adult brain has been available for some time, the embryonic commissures have to date only been superficially allocated into anterior (ac) and posterior (pc) subsets, in keeping with the nomenclature for the early ventral nerve cord. Further, while the pioneers of the w, x, y, and z tracts from each protocerebral hemisphere have been shown to project into the primary commissural fascicle of the brain just after its formation early in embryogenesis and then to fasciculate with its pioneers, the early axons from the W, X, Y, and Z lineages remain within the commissural fascicles they originally pioneer. Later, in growing axons from these same lineages, however, subsequently decussate but the commissural fascicles involved have remained undescribed. This study reconstructed the axon projections from representative lineages of the central complex into the commissural system of the brain at various developmental stages in both the grasshopper and Drosophila. At the same time, the commissural organization itself was analyzed at these stages using the nomenclature applicable to the grasshopperand Drosophila. This analysis leads to the conclusion that in setting up the columnar neuroarchitecture of the fan-shaped body, comparable choices are being made by subsets of axons from equivalent lineages in both the grasshopper and Drosophila, consistent with a conserved wiring plan for this brain region (Boyan, 2017).

In both Drosophila and the grasshopper, the axon scaffold of the embryonic brain comprises an orthogonal system of axonal projections around the stomodeum. Anterior to the stomodeum, this scaffold in Drosophila had earlier been resolved to the level of grouped anterior or posterior commissures, but not individual fascicles. Recent studies, using specific Gal-4 lines, on the other hand, have documented a large number of single projections from larval/pupal neurons of the protocerebrum to the protocerebral bridge and then to the fan-shaped body, ellipsoid body and noduli, many of a commissural nature. Such commissural elements may now be integrated into a plan equivalent to that developed for the grasshopper (Boyan, 2017).

The conserved nature of fan-shaped body neuroarchitecture in insects such as Drosophila and the grasshopper makes it likely that there is also a high degree of correspondence among their commissural fascicles. The current study now enables the development of the fan-shaped body to be understood at the level of individually identified commissural fascicles, and so provides the basis for interspecific comparisons of central complex development involving Drosophila, Tenebrio and the sightless dipluran Campodea where similar patterns of axon decussation are found. Equally, mutant analyses in Drosophila may allow the pattern of decussation present in the grasshopper to be understood with greater precision. For example, the topographic decussation of axons at stereotypic locations in both species suggests the presence of choice points across the midbrain similar to that reported for the ventral nerve cord. Although the mechanism has yet to be identified in the brain, a dysregulation of cell surface adhesion/recognition molecules in a graded manner across the midbrain represents one possibility. In the peripheral nervous system of Drosophila mutant for the cell surface molecule fasciclin III, for example, axons switch fascicles to an incorrect branch of the segmental nerve and so project to inappropriate body wall muscles, while in the visual system, relative expression levels of adhesion molecules have been found to regulate the wiring of neurite fascicles. Glia have also been shown to direct neuronal axogenesis in the CNS and midline glia are present in the both the grasshopper and Drosophila brain during commissure formation. In the karussell mutant (mutation affecting β-spectrin), for example, dysregulation of midline glia belonging to the pointed group results in commissural axons of the ventral nerve cord decussating between anterior and posterior fascicles, a neuroarchitecture not found in the wild type (Hummel, 1999).

Fan-shaped body neurons in the Drosophila brain regulate both innate and conditioned nociceptive avoidance

Multiple brain regions respond to harmful nociceptive stimuli. However, it remains unclear as to whether behavioral avoidance of such stimuli can be modulated within the same or distinct brain networks. This study found subgroups of neurons localized within a well-defined brain region capable of mediating both innate and conditioned nociceptive avoidance in Drosophila. Neurons in the ventral, but not the dorsal, of the multiple-layer organized fan-shaped body (FB) are responsive to electric shock (ES). Silencing ES-responsive neurons, but not non-responsive neurons, leads to reduced avoidance of harmful stimuli, including ES and heat shock. Activating these neurons consistently triggers avoidance and can serve as an unconditional stimulus in an aversive classical conditioning task. Among the three groups of responsive neurons identified, two also have reduced activity in ES-conditioned odor avoidance. These results demonstrate that both innate and conditioned nociceptive avoidance might be represented within neurons confined to a single brain region (Hu, 2018).

Neural signatures of dynamic stimulus selection in Drosophila

Many animals orient using visual cues, but how a single cue is selected from among many is poorly understood. This study shows that Drosophila ring neurons-central brain neurons implicated in navigation-display visual stimulus selection. Using in vivo two-color two-photon imaging with genetically encoded calcium indicators, this study demonstrates that individual ring neurons inherit simple-cell-like receptive fields from their upstream partners. Stimuli in the contralateral visual field suppressed responses to ipsilateral stimuli in both populations. Suppression strength depended on when and where the contralateral stimulus was presented, an effect stronger in ring neurons than in their upstream inputs. This history-dependent effect on the temporal structure of visual responses, which was well modeled by a simple biphasic filter, may determine how visual references are selected for the fly's internal compass. This approach highlights how two-color calcium imaging can help identify and localize the origins of sensory transformations across synaptically connected neural populations (Sun, 2017).

Building a functional connectome of the Drosophila central complex

The central complex is a highly conserved insect brain region composed of morphologically stereotyped neurons that arborize in distinctively shaped substructures. The region is implicated in a wide range of behaviors and several modeling studies have explored its circuit computations. Most studies have relied on assumptions about connectivity between neurons based on their overlap in light microscopy images. This study presents an extensive functional connectome of Drosophila melanogaster's central complex at cell-type resolution. Using simultaneous optogenetic stimulation, calcium imaging and pharmacology, the connectivity was tested between 70 presynaptic-to-postsynaptic cell-type pairs. Numerous inputs to the central complex were identified, but only a small number of output channels (see The central complex neuropiles and the hypothesized flow of information based on overlap of arbors in light-microscopy images). Additionally, the connectivity of this highly recurrent circuit appears to be sparser than anticipated from light microscopy images. Finally, the connectivity matrix highlights the potentially critical role of a class of bottleneck interneurons. All data is provided for interactive exploration on a website (Franconville, 2018).

Sun navigation requires compass neurons in Drosophila

Despite their small brains, insects can navigate over long distances by orienting using visual landmarks, skylight polarization, and sun position. Although Drosophila are not generally renowned for their navigational abilities, mark-and-recapture experiments in Death Valley revealed that they can fly nearly 15 km in a single evening. To accomplish such feats on available energy reserves, flies would have to maintain relatively straight headings, relying on celestial cues. Cues such as sun position and polarized light are likely integrated throughout the sensory-motor pathway, including the highly conserved central complex. Recently, a group of Drosophila central complex cells (E-PG neurons) have been shown to function as an internal compass, similar to mammalian head-direction cells. Using an array of genetic tools, this study set out to test whether flies can navigate using the sun and to identify the role of E-PG cells in this behavior. Using a flight simulator, it was found that Drosophila adopt arbitrary headings with respect to a simulated sun, thus performing menotaxis, and individuals remember their heading preference between successive flights-even over several hours. Imaging experiments performed on flying animals revealed that the E-PG cells track sun stimulus motion. When these neurons are silenced, flies no longer adopt and maintain arbitrary headings relative to the sun stimulus but instead exhibit frontal phototaxis. Thus, without the compass system, flies lose the ability to execute menotaxis and revert to a simpler, reflexive behavior (Giraldo, 2018).

In the absence of normal E-PG function, flies might directly orient toward the sun, because they lack the ability to compare their instantaneous heading to a stored value of their directional preference. Such a loss of function in the compass network might unmask a simpler reflexive behavior, such as phototaxis, that does not require the elaborate circuitry of the central complex. Consistent with this hypothesis, stripe fixation was not different between control and experimental animals. This interpretation is compatible with a recent model that showed that frontal object fixation could result from a simple circuit involving two asymmetric wide-field motion integrators, without the need for the central complex (Giraldo, 2018).

The findings are consistent with an emerging model of a navigational circuit involving the central complex. E-PG cells have an excitatory relationship with another cell class in the central complex (protocerebral bridge to ellipsoid body and noduli, or P-EN, neurons), creating an angular velocity integrator that allows a fly to maintain its heading in the absence of visual landmarks. Furthermore, the E-PG neurons are homologous to the CL1 neurons described in locusts, monarchs, dung beetle, and bees and likely serve similar functions across taxa. Extracellular recordings from the central complex in cockroaches revealed neurons that act as head-direction cells relative to, or in the absence of, visual landmarks, although precise cell types were not identified. Inputs to E-PG neurons likely occur via the anterior visual pathway from the medulla to the anterior optic tubercle and on to the bulb. From there, tubercle-bulb neurons, one class of which is responsive to the azimuth and elevation of small bright spots, synapse onto ring neurons that project to the ellipsoid body, thus bringing visual information into the compass network. In a recent model of path integration in bees, CL1 neurons are part of a columnar circuit that provides instantaneous heading information to an array of self-excitatory networks that also receive convergent optic flow information, thereby storing a memory of distance traveled in each direction (Stone, 2017). This information is then retrieved as an animal returns home, by driving appropriate steering commands in another class of central complex neurons. The putative memory cells suggested by this model, CPU4 cells, could be homologous to protocerebral bridge-fan-shaped-body noduli (P-FN) neurons described for Drosophila. Furthermore, cells responsive to progressive optic flow are found throughout the central complex of flies, including neuropil in the fan-shaped body containing the P-FN cells. In addition to their role in path integration, the CPU4 network might also function to store the desired heading during sun navigation. Although the results do not directly test this model, they are consistent with the role of CL1 neurons in providing heading direction to circuits that generate steering commands toward an arbitrary orientation whose memory is stored in the network of CPU4 (P-FN) neurons (Giraldo, 2018).

Stripe fixation and sun navigation behaviors may represent two different flight modes in Drosophila. Stripe fixation is thought to be a short-range behavioral reflex to orient toward near objects, which, in free flight, is quickly terminated by collision avoidance or landing behaviors. In contrast, navigation using the sun is likely a component of long-distance dispersal behavior that could be used in conjunction with polarization vision either in a hierarchical or integrative manner. Individuals could differ in where they lie on the continuum of long-range dispersal to local search, which could explain the inter-individual variation observed in heading fidelity during sun orientation experiments. In general, dispersal is a condition-dependent behavior that is known to vary with hunger or other internal factors. Given the architectural similarity of the central complex among species, the celestial compass identified in Drosophila is likely one module within a conserved behavioral toolkit, allowing orientation and flight over long distances by integrating skylight polarization, the position of the sun or moon, and other visual cues. An independent study has recently found that the E-PG compass neurons are also necessary in walking flies for maintaining arbitrary headings relative to a small bright object. The expanding array of genetic tools developed for flies and the rapid growth in understanding of the neural circuitry involved in rientation and flight make this a promising system for exploring such essential and highly conserved behaviors (Giraldo, 2018).

Neuroarchitecture of the Drosophila central complex: A catalog of nodulus and asymmetrical body neurons and a revision of the protocerebral bridge catalog

The central complex, a set of neuropils in the center of the insect brain, plays a crucial role in spatial aspects of sensory integration and motor control. Stereotyped neurons interconnect these neuropils with one another and with accessory structures. Over 5000 Drosophila melanogaster GAL4 lines were screened for expression in two neuropils, the noduli (NO) of the central complex and the asymmetrical body (AB), and multicolor stochastic labelling was used to analyze the morphology, polarity and organization of individual cells in a subset of the GAL4 lines that showed expression in these neuropils. Nine NO and three AB cell types were identified and are described in this study. The morphology of the NO neurons suggests that they receive input primarily in the lateral accessory lobe and send output to each of the six paired noduli. The AB is demonstrated to be a bilateral structure which exhibits asymmetry in size between the left and right bodies. The AB neurons are shown to directly connect the AB to the central complex and accessory neuropils, that they target both the left and right ABs, and that one cell type preferentially innervates the right AB. It is proposed that the AB be considered a central complex neuropil in Drosophila. Finally, highly restricted GAL4 lines are presented for most identified protocerebral bridge, NO and AB cell types. These lines, generated using the split-GAL4 method, will facilitate anatomical studies, behavioral assays, and physiological experiments (Wolff, 2018).

Located at the center of the insect brain, the central complex is a set of highly interconnected neuropils that processes complex, multisensory information from the environment, integrates it with information about the insect's internal state and past experiences, and guides motor outputs that drive appropriate behavioral responses (Wolff, 2018).

One of the most studied roles of the insect central complex is the integration of sensory information, predominantly from visual input. The output of this sensory processing encompasses diverse motor and behavioral responses. In this capacity, the central complex regulates locomotor behaviors such as handedness, turn direction, initiation and termination of walking. The central complex is thought to play a key role in migration, navigation and orientation using input such as celestial cues and displays responses to looming stimuli suggestive of an involvement in generating escape responses in the locust and fly. The central complex has been suggested to contain a ring attractor network that maintains a representation of the fly's heading direction that may be useful for navigation and orientation in visual conditions as well as in darkness. The central complex is also involved in the formation and recall of short- and long-term visual memories, in the processing of olfactory and gustatory inputs and in maintaining information about the fly's satiety state (Wolff, 2018).

Understanding the core principles of operation of the central complex has been greatly enabled by the dissection of behavior at a single neuron level and the neuron-by-neuron assembly of circuits. A comprehensive anatomical atlas and genetic lines that enable manipulation of individual cell types are invaluable tools for this strategy. This study describes the neuronal composition of the NO and the AB, neither of which has been extensively studied in Drosophila. An understanding of the function of the noduli in behavior lags far behind that of the other central complex structures: the protocerebral bridge (PB), fan- shaped body (FB) and ellipsoid body (EB). The only documented roles for the NO in Drosophila are in the time course of walking activity and in influencing handedness during locomotion. The locust neurons that connect the PB, EB and NO and the PB, FB and NO are sensitive to polarized light. Most recently, recordings from optic-flow-sensitive neurons that connect the lateral accessory lobe (LAL) to the NO and other neurons that link the NO to the FB in the bee have demonstrated the NO are involved in path integration. Finally, the fact that this structure appears to be present only in the subclass of winged insects has led to the speculation that the noduli may regulate flight (Wolff, 2018).

Structural conservation of the central complex across insect species is strong, but not absolute. The discussion that follows focuses on the anatomy of the Drosophila neuropils. The PB, FB, EB and NO are midline structures and exhibit a stratified organization. The PB is a handlebar- shaped structure in the posterior dorsal brain. The EB is shaped like a torus and is tilted on its dorso-ventral axis such that its ventral border defines the anterior margin of the central complex. The FB lies between the PB and EB and represents the largest of the four central complex structures. The bilateral noduli, historically called ventral tubercles, are the most ventral neuropil of the central complex and are nestled beneath the FB. There are three pairs of noduli neatly stacked on top of one another from dorsal to ventral; each pair is bisected by the midline. The dorsal nodulus (NO 1) displays some hint of a transverse division whereas the medial (NO2) and ventral (NO3) noduli exhibit longitudinal segmentation. NO2 is divided into dorsal and ventral subdomains (NO2D and NO2V) and NO3 has three subdomains (Wolff, 2018).

The neuropils considered to be components of the central complex have evolved over time. Power's 1943 description of the central complex includes the FB, EB, and 'ventral tubercles', or NO. By the mid-1970s, the modern view of the central complex had emerged: Williams included the PB within the locust central complex, alongside the FB, EB and NO. The asymmetrical body (AB) is a relatively inconspicuous structure located at the midline, adjacent to the ventral FB. It was first described in the fly as a round, almost exclusively right-hemisphere structure. The AB was observed in both hemispheres in just 7.6% of 2,250 brains immunolabeled with an antibody against the Fasciclin II (Fas II) protein, which is expressed in this structure. Flies with bilateral ABs were reported to have disrupted long-term memory, leading to the suggestion that asymmetry of this structure is important for long-term, but not short-term, memory. Although thousands of GAL4 lines that drive expression in small subsets of neurons in the larval and adult fly brains have been examined, the AB is the only reported instance of an asymmetric structure in the adult fly brain (Wolff, 2018).

Elements with likely homology to the Drosophila AB have also been described in the grey flesh fly Neobellieria bullata and the blowfly Calliphora erythrocephala. In both species, these bodies occur bilaterally, and one of the two is consistently smaller and less densely innervated than the other. In addition, the smaller of the two appears fragmented. A previous study identified five GAL4 lines that show asymmetric innervation of the AB. That analysis revealed lines ranging from a strong right hemisphere bias in innervation to those with asymmetric but bilateral expression, with more conspicuous expression in the right AB. This study builds on the previous study by providing a systematic characterization of the neurons that target the AB, and leads to a proposal that the AB be added as the fifth neuropil of the Drosophila central complex (Wolff, 2018).

In this work, a characterization is presented of cell types of the NO and AB, including morphology, presumed polarity and population size. A set of split-GAL4 lines for NO and AB cell types, reagents was also generated and characterized that will greatly facilitate functional studies. In addition, since publication of a description of the neurons that arborize in the PB, this study has gained several new insights into the PB neurons. These include: 1) one new PB neuron family has been identified; 2) a neuron identified by in a previous study has since been found in the GAL4 collection and is characterized in this study using the multicolor flip-out technique (MCFO); and 3) a set of split-GAL4 lines was generated for PB cell types (Wolff, 2018).

The asymmetrical body: the fifth central complex structure The neuropils considered to be constituent components of the central complex have changed over the decades. The central body), included what became known as the ellipsoid body and the fan-shaped body. The noduli were known as the ventral tubercles. More recently, the central complex has been defined as 'a group of modular neuropils across the midline of the insect brain', '...interconnected neuropils and nuclei that populate the midline of the forebrain-midbrain boundary region', and 'a system of interconnected neuropils lying at, or about, the midline of the protocerebrum'. Although the modular architecture of the central complex structures is conspicuous (e.g. the glomeruli of the PB and the trajectory patterns of neurons that project to, from, and within the central complex structures), it is the assigned boundaries that encompass the central complex that seem to be the feature that defines these structures as members of the central complex (Wolff, 2018).

This study has illustrated that the Drosophila AB, which appears to be a structure that is distinct from the FB, meets the criteria outlined above for central complex neuropils: It is a midline neuropil; it falls within the boundaries of the central complex; and it is interconnected (to the FB and SLP) by a network of previously undocumented (with one exception) neurons (Wolff, 2018).

Since the AB meets all the criteria previously used to define neuropils as components of the central complex, it is proposed that the AB be added as a fifth neuropil of the central complex of Drosophila. The AB is not unique to Drosophila. A previous study describe the presence of likely homologous bilateral, asymmetrically sized ABs in N. bullata and C. erythrocephala. That work also identified a tangential FB neuron that bears a resemblance to the SLP-AB-FBl8 neuron described in this study (Wolff, 2018).

It remains to be determined if the AB is more widely represented in other insect orders. The right AB is significantly larger than the left. At a minimum, this difference is likely due to a combination of smaller arbors in the left AB and the lower frequency with which the left AB is targeted: only the ipsilateral-contralateral- projecting form of the SLP-AB neuron, which arborizes in both the left and right ABs, targets the left AB, whereas the ipsilateral and contralateral-projecting forms of the SLP-AB neuron target exclusively the right AB. Thus, the right AB appears to receive a disproportionately larger share of information from the SLP, although the right and left hemispheres appear to be equally represented as sources of input. Notably, this left-right bias is restricted to the AB, as a parallel preference is not shown for the SLP. The availability of genetic lines that target AB-specific cell types will enable experiments aimed at revealing the relevance of this left-right bias (Wolff, 2018).

Three unusual features distinguish the five most commonly seen NO neurons described from other central complex neurons. First, in contrast to the majority of PB neurons described to date, the projections of four of these five NO neurons are ipsilateral. Second, while anatomical features identify distinct input and output neuronal populations in other central complex neuropils, the noduli appear to be sites for receiving primarily input from other neuropils (boutons appear to be the predominant anatomical feature in the noduli in confocal micrographs of NO, PB-FB-NO and PB-EB-NO neurons). Golgi preparations and data from the likely locust equivalent of the PB-FB-NO neuron (the CPU4 neuron), however, indicate these NO arbors are mixed; perhaps the intensity of the dense populations of boutons masks the presence of spines in confocal preparations. Third, although the noduli do receive input from central complex neuropils (e.g. via the PB-FB-NO and PB-EB-NO neurons, from FB tangential neurons, etc.), the majority of direct input for this new set of neurons is provided by just one neuropil, the LAL. Such a restricted thoroughfare of communication is in stark contrast to the PB neurons, for example, which have a much broader and more diverse network of direct communication. The LAL.s-CREc.s-NO3 Pc.b cell type is distinct from the other four common NO neurons in that it delivers contralateral, rather than ipsilateral, input from the LAL and CRE to NO3P. The posterior compartment of NO3 is therefore unique in that it is the only nodulus subcompartment to communicate directly with the contralateral hemisphere. Given that NO3P (and NO3M) also receives ipsilateral terminals from the LAL via LAL.s-CREi.s-NO3P/Mi.b, this subcompartment may act as a limited integration center between the fly's left and right sensory fields (Wolff, 2018).

Physiological data from two neurons in the sweat bee offer insight into a likely role for the NO neurons described in this study. The TN1 and TN2 neurons ('noduli tangential neurons') share a high degree of anatomical homology with the LAL- NO neurons: TN1 and TN2 are ipsilateral neurons with input branches in the lateral central brain and blebbed branches in the noduli. Recordings from these two cells reveal they fire in response to simulated backward and forward flight, respectively, and that the rate of firing is dependent on the stimulus velocity, suggesting these neurons encode speed using optic- flow and can thereby track the distance traveled by the bee. Similar physiological features and path integration functions would not be unexpected for the apparent homologous Drosophila neurons. The LAL is the primary source of input for the NO neurons described in this study and its activity may provide additional insight into the roles of the LAL-NO neurons. It is a large, bilateral neuropil that is highly interconnected with neuropils of the central complex. Functionally, the LAL is considered to be a sensorimotor integration center, based on several lines of evidence in various insect species. For example, in crickets and moths, activity in LAL neurons is associated with walking. In the locust, assorted LAL neurons exhibit changes in activity in response to various aspects of flight, implicating this brain region in flight control. In Drosophila, LAL neurons involved in walking backwards have been documented (Wolff, 2018).

It has been suggested that the noduli are involved in walking and motor control in Drosophila. The neurons implicated in left-right turning bias in locomotion are the PB-FB-NO neurons, which have presumed input (fine terminals) in the PB, and presumed output (boutons) in the FB and NO. It has been speculated that the bias to turn in one direction or the other is influenced by an interplay between the nodulus subdomains that are targeted by the different PB-FB-NO cell types (Wolff, 2018).

Direct communication between the PB-FB-NO neurons and the LAL-NO neurons is not unexpected, as a previous study has shown synaptic contacts between the bumblebee equivalents of these two cells, the CPU4 and TN cells, respectively. Considering the sensorimotor contribution made by the LAL in various types of movement, the LAL-NO neurons described in this study are strong candidates to contribute to the circuits involved in turning (Wolff, 2018).

The catalog of NO neurons described in this study is incomplete. Analyses of other GAL4 lines has identified several large-field FB neurons that also arborize in the noduli, as well as other brain regions that are currently being characterized; some of these neurons are illustrated in the Golgi stains of a previous study. Other cell types with arbors in the noduli that have so far eluded identification. Finally, it seems likely that there would be output neurons from the NO, although such neurons have not been identified. Electron microscopic-level analysis should provide a path to identifying these neurons (Wolff, 2018).

The debate continues to swirl over what constitutes a distinct cell type. Morphology and function have long been accepted as reliable criteria to distinguish cell types. While morphology is a straightforward and easy means of classifying cell types, it can be misleading in that cells that appear identical may have functional differences. For example, a previous study describe clearly distinct physiological roles for two PB neurons that appear to have indistinguishable morphology at the light level (Wolff, 2018).

Morphological features evident with light microscope-level resolution will therefore likely be insufficient to distinguish all cell types, so knowledge of some combination of synaptic connectivity, functional properties and the genetic programs used to specify these attributes will be necessary to fully define cell types. Similar limitations confound the assignment of neuropil boundaries and sub-compartments (Wolff, 2018).

Synaptic density varies considerably across brain regions and this variation has provided landmarks used to define the neuropils of the fly brain. While the boundaries of some structures are unambiguous (e.g., the PB and EB), neuropil margins are not universally so clear-cut, with many neuropils appearing to meld seamlessly with adjacent neuropils. The opportunity to map the domains of arbors within neuropils identifies distinct regions that are not revealed by differences in synaptic density (e.g. wedge and tile domains in the EB). For example, the mushroom body lobes can be divided into a series of non-overlapping compartments with distinct functions by the extent of the arbors of dopaminergic input neurons and mushroom body output neurons. The LAL provides an example of one neuropil that may have functionally distinct subregions. It is a large neuropil with no obvious boundaries revealed by anti-Brp staining, yet the arbors of many neurons that target this neuropil exhibit strong regional preferences. Mapping the domains of these arbors may identify regions that are functionally distinct (Wolff, 2018).

Three major efforts aimed at cataloging all the neurons in the Drosophila brain are in progress. One, typified by this and others' work, characterizes one structure at a time using light microscopy in combination with the generation and analysis of highly specific GAL4 driver lines. The second method is a modern implementation of the Golgi approach of randomly labeling small numbers of neurons in order to describe their morphology. And the third, which is now becoming practical at the required scale, involves reconstruction of neuronal morphology and circuits through analysis of image volumes collected using electron microscopy. It is believed that such light and electron microscopic-level analyses will be highly synergistic. Light microscopy, with genetically marked cells, provides the ability to observe the morphology of hundreds of individual cells of the same cell type in many different individuals, providing insights on stereotypy. However, its dependence on GAL4 drivers means that completeness of coverage cannot be assured. Conversely, electron microscopic analysis, while usually limited to a single sample, not only ensures completeness but also enables visualization and quantification of synaptic connectivity. Moreover, since EM samples do not carry transgenes expressing ectopic membrane proteins that can interfere with development, wiring errors may be less likely. While only electron microscopy is likely to provide the complete wiring diagram of a circuit, light level analysis of genetic driver lines will be needed to provide the critical bridge between circuit maps and the tools required to precisely manipulate the activity of their individual components (Wolff, 2018).


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genes expressed in brain morphogenesis

Genes involved in organ development

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