A striking convergence in advanced brains has endowed those structures of the brains in insects and mammals that analyse olfactory information with close similarities (Hildebrand and Shepherd, 1997). In both, segregated modules of neuropile called glomeruli each receive input from the axons of olfactory receptor neurons (ORNs), each of which in turn expresses predominantly a single olfactory receptor gene (Gao et al., 2000; Vosshall et al., 2000). ORNs in the adult fruit fly Drosophila melanogaster belong to one of four classes of sensilla that form a regular pattern on the third segment of the fly’s antenna and maxillary palp (Vosshall and Stocker, 2007). Compared with the ~5×10⁶ ORNs (Kawagishi et al., 2014) that innervate the ~1800 glomeruli in the mouse olfactory bulb (Royet et al., 1988), the different regions of the olfactory system in Drosophila signal with fewer cell types using fewer odorant receptor molecules. Thus, only 1300 ORNs that express 62 odorant receptor proteins (Vosshall and Stocker, 2007) innervate a mere ~50 modular glomeruli (Grabe et al., 2015), the first relay of the insect olfactory system (Stocker, 1994; Laissue et al., 1999; Gao et al., 2000; Vosshall et al., 2000; Benton et al., 2009; Grabe et al., 2015).

Each of the ~50 glomeruli has been individually identified (Laissue et al., 1999; Benton et al., 2009; Silbering et al., 2011) and mapped, both in vitro, after dissection (Stocker et al., 1983; Laissue et al., 1999; Couto et al., 2005; Endo et al., 2007); Silbering et al., 2011) and in vivo (Grabe et al., 2015). Output from the glomeruli is made by the antennal lobe projection neurons (PNs), some of which relay olfactory information to higher-order olfactory centres, the mushroom body and lateral horn (Wong et al., 2002; Marin et al., 2002; Yasuyama et al., 2002; Yasuyama et al., 2003) via three main antennal lobe tracts (ALTs), medial, mediolateral and lateral (mALT, mlALT and lALT).

The cellular composition of the antennal lobe has also been extensively reported, both from early back-fill studies (Stocker et al., 1990) and more recent genetic reporter lines (e.g. Tanaka et al., 2012), and the numbers, types and patterns of innervation these receive from ORNs has likewise been identified from such lines (e.g. Couto et al., 2005). Among the PNs, Tanaka et al. (2012) have identified eleven classes, four in the medial, three in the mediolateral, and four in the lateral tracts. Amongst these, mPN1s project out of the antennal lobe along the mALT to the mushroom body and lateral horn (Tanaka et al., 2012). Relative to these, ORNs have been morphologically less well characterized but are recently catalogued for glomerulus DM6 (Tobin et al., 2017).

Little studied hitherto are the local interneurons (LNs), a major focus of our study. Tanaka has identified LNs of six types with cell bodies in different locations, which arborize in either single or multiple glomeruli and in the antennal lobe of either one or both sides (Table 1). Categorized by the glomeruli they innervate, Chou et al. (2010) identify at least ~100 different LNs for each side. Additional cell types identified include a single 5-HT neuron and several transverse (tALT) neurons (Tanaka et al., 2012).

Despite detailed knowledge of their cellular composition, the synaptic networks of the fly’s antennal lobe have been incompletely documented at the requisite level from electron microscopy (EM). The reasons for this are obvious: the difficulty of tracing the tiny neurites of Drosophila neurons, the labour required to do so, and the practical problems of targeting specific glomeruli for EM. Fluorescent pre- and postsynaptic markers provide proxies for claimed synaptic contacts (Mosca and Luo, 2014), but lack independent validation from EM. Two recent studies (Rybak et al., 2016; Tobin et al., 2017) report the synaptic networks of identified glomeruli. The first, a study of three glomeruli (DL5, DM2, and VA7: Laissue et al., 1999), has provided a significant map of synaptic connections and their numerical proportions, while the second, on glomerulus DM6 (Tobin et al., 2017), established many features of the PN. Neither study gave a comprehensive account of the varied synaptic inputs from and between LNs, however. Including the synaptic network of all LNs and PNs to generate an actual map of the complete synaptic network, or connectome (Lichtman and Sanes, 2008), for each glomerulus is thus a final step towards adopting functional connectomic approaches (Venken et al., 2011; Meinertzhagen and Lee, 2012) to the analysis of antennal lobe function.

We report the connectome of a single glomerulus VA1v of the right side of a female Drosophila antennal lobe (Figure 1), using dense reconstruction of an isotropic 8 nm voxel image stack (Figure 2), see Materials and methods, obtained by focused ion beam (FIB) milling scanning electron microscopy, FIB-SEM (Xu et al., 2017). VA1v is a sexually dimorphic fruitless-positive glomerulus responsive to fly odour (Sakurai et al., 2013), that signals the sex pheromones cis-vaccenyl acetate and methyl laurate (Kurtovic et al., 2007; Dweck et al., 2013), and is significantly larger in male flies than in females (Kondoh et al., 2003; Stockinger et al., 2005).

Figure 1

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Figure 2

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Figure 2—source data 1

List of quantitative features for all cells of the dataset.

Name - putative name based on Tanaka et al., 2012; Cell_ID - unique id given by NeuTu program; soma - location of soma, or soma tract (t); vol – volume of neurite in glomerulus; T-bars - number of presynaptic ribbons; Pre - targets of pre-synapse; Post – postsynaptic site; PSDs per T-bar – Average number of targets of pre-synapse; pre/post – ratio of targets of pre-synapses to postsynaptic site; T-bar/vol – number of T-bars per neurite vol (µm⁻³). Figure illustrates designation of pre- and postsynaptic sites.

https://doi.org/10.7554/eLife.37550.005

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Synapses

Each synapse comprised a T-bar ribbon at the presynaptic site opposite membrane densities at the postsynaptic dendrites (Figure 3A). Most commonly these numbered three per synapse, with an average of 3.4, most synapses thus forming triads or tetrads (Figure 2—source data 1), like those of the three glomeruli reported by Rybak et al. (2016). The range was from 1:1 to 1:9. The numbers of postsynaptic dendrites differed slightly for each presynaptic cell, ipsilateral ORN cells having 3.63 dendrites per synapse, LN1 and LN2L 3.17 and 3.06 respectively, and mPN1 had 3.54 postsynaptic dendrites (Figure 2—source data 1).

Figure 3

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The size and structural features of each synapse resembled those found between neurons in other Drosophila neuropiles, such as the optic lobe lamina and medulla (Meinertzhagen and O'Neil, 1991; Takemura et al., 2008). At each presynaptic site a T-bar was found with a clear pedestal; the electron density of the ribbon platform surmounting it was weak after the preparation methods adopted for FIB-SEM. Thus unlike transmission EM, TEM (Rybak et al., 2016), ribbons often lacked canonical T-bar profiles when seen in FIB-SEM images. This chiefly resulted because in our FIB-SEM images the grey level of the synapses was about twice that of the membranes. We therefore adjusted the electron density of images to increase membrane contrast, because this proved advantageous to enhance membrane continuity more reliably during later proof-reading steps (see Materials and methods), but rendered the platform of the T-bar ribbon often less distinct in our FIB-SEM images than when seen in TEM.

Occasional synapses were bidirectional, with a T-bar ribbon on either side of the synaptic cleft. Synapse sizes also varied more widely than for tetrad synapses in the lamina (Fröhlich, 1985; Meinertzhagen and O'Neil, 1991). Occasional autapses were seen amongst PN axons, at which the neuron was presynaptic to itself. These typically numbered about 1% of all the PN axon’s synapses, about the same relative number as reported for medulla neurons (Takemura et al., 2015). Synaptic vesicles were not well resolved after FIB-SEM imaging at 8 nm. In addition to synapses with what appear to be small, clear vesicles, dark vesicles having a dense core of between 50 and 100 nm in diameter appeared in the profiles of most LNs. An additional reconstruction which closely resembled the cell called 5-HT1 (Tanaka et al., 2012), and was neither an ORN, PN nor LN, was full of large dark vesicles (84 ± 12 nm in diameter) and had few synapses with what appear to be small clear vesicles (Figure 3B–D) not obviously visible after FIB-SEM imaging. Its axon exited via the mediolateral tract (mlT). Spinules (Gruber et al., 2018), interesting membrane invaginations visible in most cell profiles, fall in the vicinity of synapses, but were neither invariably close nor obviously related to synapses; they may represent regions of temporary membrane disequilibrium at sites of vesicle exo- or endocytosis.

Identified neurons from dense reconstruction in VA1v

We reconstructed 192 neuron bodies (Figure 4), each of which had >50 contacts in glomerulus VA1v. These 192 ( Figure 4—source data 1, Figure 4—source data 2, Figure 4—source data 3, Figure 4—source data 4) constituted most of the neurons of that glomerulus, which was thus densely reconstructed (Figure 2). Occasional orphan elements (Figure 2; Figure 4—source data 4) may have constituted an additional cell but were disconnected and had membranes too obscure to trace with greater certainty. Otherwise dense reconstruction provided reassurance that no cell could hide undetected within the neuropile (Figure 2). A total of 87.9% of VA1v synaptic connections have been assigned to these neurons, the remainder being those of orphan neurites or neurons with fewer than 50 contacts. Overall, glomerulus VA1v had a neuropile volume of 4,858 µm³ and the 192 neuron bodies constituted 87% of the volume. Neurons were additionally traced sparsely beyond the borders of the glomerulus where possible, in order to connect to cell bodies, and project via the three ALT tracts, antennal nerve, and commissural tract. The total neurite length traced was 15.8 cm.

Figure 4

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Figure 4—source data 1

Library of reconstructed ORNs.

https://doi.org/10.7554/eLife.37550.008

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Figure 4—source data 2

Library of reconstructed PNs, some partially so.

https://doi.org/10.7554/eLife.37550.009

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Figure 4—source data 3

Library of partially reconstructed LNs.

https://doi.org/10.7554/eLife.37550.010

Download elife-37550-fig4-data3-v2.pdf

Figure 4—source data 4

Library of other reconstructed cells.

https://doi.org/10.7554/eLife.37550.011

Download elife-37550-fig4-data4-v2.pdf

We reconstructed the neurons and compared their reconstructed shapes within the glomerulus, and their wider axon trajectories within the antennal lobe, with those revealed by comprehensive mapping using Gal4 enhancer-trap strains (Tanaka et al., 2012). This enabled us to identify them cell-by-cell as one of the three main classes of neurons: input ORNs, output PNs, and local interneuron LNs (Figure 4). The provisional identification of cells relative to published trajectories of cells in reporter lines is listed in Table 1.

A total of 51 ORNs originated in the ipsilateral antennal nerve with a further 56 that entered in the commissure from the contralateral lobe.

We have identified an unanticipated large number of 18 PNs that lay within the region containing glomerulus VA1v. They fall into the three groups that exit the three main tracts of the antennal lobe (tract nomenclature from Ito et al., 2014): (a) Within the group that exits the medial tract we found three tightly interwoven monoglomerular PNs, the mPN1s (Figure 4; Figure 4—source data 2). (In a previous study Yu et al., 2010 identified five mPN cells in VA1lm, which we interpret to reveal the PNs of two glomeruli, one with 3 mPN1 and its neighbour with 2) We also identified three other mPN1s with a few projections within the ROI but these were in two other glomeruli. These are labeled mPN1 external (see Figure 4—source data 2i–n). b) In the group that exits the mediolateral tract there was a total of eight neurons: (i) two mlPN1s which are monoglomerular; (ii) three mlPN2s which are multiglomerular but only extending neurites to select glomeruli (one having a less widespread projection pattern in VA1v) and one other, mlPN2, which is mainly external to Va1v; and (iii) two mlPN3s which are multiglomerular and have a much sparser projection. For all of these, see Figure 4—source data 2o–v. c) In the group that exits the lateral tract we identified eight neurons: (i) three lPN4s that project mainly to VA1v and its sister glomerulus VA1d; (ii) four lPN2s which are multiglomerular and bilateral; and (iii) one cell called lPN2_Comm which resembles lPNS but does not exit in the lateral tract, instead entering from the commissure (see Figure 4—source data 2b–h).

One additional cell, AL-AST3 reported by Tanaka et al., 2012, with few pre- and postsynaptic contacts, had an axon that exits at the posterior of the antennal lobe and a cell body close to the antennal nerve.

We also identified no fewer than 56 LNs that innervated our glomerulus, of the >150 previously reported for the entire antennal lobe (Chou et al., 2010). As previously reported (Chou et al., 2010; Das et al., 2011; Liu and Wilson, 2013), these are morphologically diverse, possibly reflecting the three developmental modes of their origin, as residual larval LNs, as adult-specific LNs emerging before associated sensory and projection neurons, and as LNs that emerge after synaptic connections are established (Liou et al., 2018). As a whole, we find they have a wide range in the numbers of their synaptic contacts. LNs were traced comprehensively in VA1v and also via their axon to their soma; thus although most are panglomerular (Chou et al., 2010), our reconstructed LNs are therefore partial. Their morphologies are illustrated fully in Figure 4—source data 3. Within the different LN groups, some have many synaptic contacts within VA1v. We could assign most to the six morphological classes identified by Tanaka et al., 2012, as follows: (a) The most noteworthy LN is a single largely uniglomerular cell that we identified as LN2V. Although superficially resembling a PN, it does not project to any of the three tracts and has a small neurite which extends towards the ventral cortex of cell bodies but which extends beyond the field of view. This is remarkable in three ways that distinguish it from multiglomerular LNs: in arborizing predominantly within a single glomerulus, in being highly directed (with predominant output to PNs), and in the numbers of its synaptic contacts in glomerulus VA1v. Multiglomerular LNs (Tanaka et al., 2012), by contrast, all have fewer synaptic contacts and lack clear directionality.From their morphology and connectivity, we could recognise at least five other types of LNs: (b) Two major groups previously reported are LN1 and LN2L, which share the same soma locations and enter by the same tract. We distinguish them by whether they made contact with ORNs (LN2L: having 24 cells) or not (LN1: having 17 cells) (Figure 5—figure supplement 1). LN3 (one cell) and LN4 (one cell) both have somata ventrolateral to the antennal lobe and project to the commissure, LN4 arborizing in only a few glomeruli, and LN6 (two cells each) have few connections in VA1v. In addition a further four bilateral cells send neurites into VA1v via the commissure; their somata are located on the contralateral side. These types are hard to differentiate further without knowing their contralateral arbor. (c) We found in addition LNV (three cells) and LN_LV (three cells), were not easily reconciled with the report of Tanaka et al., 2012. The cells called LNV enter the antennal lobe close to the lateral tract and branch profusely; we could not identify these further because we could not find their cell bodies. Three cells we call LN_LV have axons that exit close to the lateral tract and originate from cell bodies close to the antennal nerve; one has an identified axon to the commissure (Figure 4—source data 3) and could therefore be LN3. We could not find the tract to the commissure to know whether this cell might be bilateral. d) Four cells with axons that arrive or exit in the commissure are LN commissure cells. These could also be PNs.

Most cells formed both pre- and postsynaptic contacts (Figure 6). However, ORNs were predominantly presynaptic, ipsilateral ORNs carrying more synapses than contralateral ORNs, and most of the reconstructed neurites from VA1v PNs were predominantly postsynaptic, as also recently reported from ssEM for other glomeruli (Rybak et al., 2016; Tobin et al., 2017)(Figures 5 and 6). LNs had about equal numbers of both pre- and postsynaptic contacts and, despite some details (Rybak et al., 2016), these have not previously been reported comprehensively (Figure 2—source data 1). A log/log plot of post- and presynaptic contacts for each cell shows that the predominantly presynaptic ORNs cluster beneath the corresponding values for LNs; having more outputs than inputs (Figure 6).

Figure 5 with 1 supplement see all

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Figure 5—source data 1

Connectivity matrix as an Excel spreadsheet file for all 192 antennal lobe glomerulus VA1v cells having >50 contacts.

Data are the same as contribute to the matrix in Figure 5, but presented cell by cell. Register of cells with presynaptic sites (x axis, ordinate) plotted against the same cells having postsynaptic sites and colour-coded intercepts denoting the number of synaptic contacts between each pair (key), and thus the anatomical strength of their connection. Cells are arranged from the top left origin as, first, outputs (PNs), then interneurons (INs), and finally inputs (ORNs), and further organized within those groups by the particular cell. Among the total of 192 cells, dense pathways occupy few intercepts, mostly concentrated in ORN to PN, and PN to LN intercepts. Only cells with more than 50 pre- or postsynaptic contacts are included.

https://doi.org/10.7554/eLife.37550.014

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Figure 6

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ORN, PN and LN cells exhibit a wide range of synaptic loads, most obvious for the PNs which cluster less tightly, and three of which, all mlPNs, lack all presynaptic sites (Figure 6). The three tightly clustered mPN1s by contrast have both pre- and postsynaptic sites, as also reported from ssEM for other glomeruli (Rybak et al., 2016; Tobin et al., 2017). Means for the numbers of synapses are given for each cell and cell type in Figure 2—source data 1.

We can set these features in synaptic organisation in the context of known responses of glomeruli to odours and odour mixtures: Relative to ORN and PN cells, LNs exhibit far greater synaptic diversity (Seki et al., 2010). The synaptic summary we present indicates that LNs are anatomically qualified to relay information within and between glomeruli, and given that each glomerulus processes information about only a single olfactant (e.g. Silbering and Galizia, 2007), are therefore qualified as a substrate to make comparisons between different olfactants. Comparison between ipsi- and contralateral inputs to PNs may provide a pathway for Drosophila to signal the direction of olfactants while PN responses to olfactant mixtures provide evidence for interglomerular inhibition (Silbering and Galizia, 2007).

Connectivity features of the network

If we summarize the numerical features of the network (Figures 5 and 7) we see that the output from ORNs numerically dominates the connectome, with 59.8% of all pre- connections, of which 39.5% go to the PN’s, 14.5% to LNs, and 5.9% to other ORNs (Figure 7A). Much output from the local interneurons is thought to be inhibitory (Wilson and Laurent, 2005) and anatomically this output accounts for a further 27.8% of synapses, distributed evenly amongst the three classes of target cells: 10.4% to PNs, 7.8% to ORNs, and 9.6% to other LNs. PN output is rare within the glomerulus, with 6.4% to LNs, 4.1% to PNs and only 1.8% to ORNs, but of course most output is predicted to lie among the target circuits in the mushroom body calyx (Yasuyama et al., 2002); Leiss et al., 2009; Butcher et al., 2012) and higher olfactory centres. Many cells are multiglomerular, and generate a complex interglomerular network inferred mostly from light microscopy and thus not at synapse level. Thus inhibitory LN output to other LNs is predicted to generate disinhibition, and is further expected to constitute part of a widespread weak interglomerular inhibitory network. Glomeruli innervated by OSNs expressing a narrowly tuned olfactory receptor may have more PNs and fewer LNs, suggesting that these glomeruli perform less lateral processing.

Figure 7

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Looking at the network’s features more specifically, we see that the largest input extends from ORNs, those from ipsilateral ORNs constituting 70% of the total ORN input (Figure 7B). Some ORN synapses are made between an ORN and its neighbouring olfactory receptor neurons. Most of the ORN inputs are made to the three mPN1 neurons (25%), however, although input also falls upon other PNs. A total of 76% of ipsilateral ORN input to PNs goes to the three classes of monoglomerular PNs, mPN1 and mlPN1 and lPN4. The latter projects mainly to VA1v but also its sister VA1d glomerulus (Tanaka et al., 2012). Of the 76%, 43% goes to mPN1. The only other PN class to receive major input is the multiglomerular mlPN2 which receives 18.5% of the total ipsilateral ORN input. Thus, very little of the ipsilateral ORN input goes to the remaining PNs. (ii) Cell LN2V is anomalous. Its pattern of connections resembles that of a PN more than that of the other LNs, receiving its input from ipsilateral ORNs and providing most of its output to PNs. This pattern does not resemble in all details any of the cells previously reported by Tanaka et al., 2012. It appears to be predominantly monoglomerular in VA1v but has sparse projections to other glomeruli. (iii)Unusual among LNs, LN6 is almost entirely presynaptic, with weak output to other LNs and a single strong output to LNv not identified by Tanaka et al., 2012. Possibly these two neurons are not LNs at all, but the arbors of receptor neurons from the maxillary palps. Their axons enter the glomerulus from the posterior antennal lobe, compatible with an entry from the antenno-suboesophageal tract, which was not clearly identifiable in our reconstructions; against this possibility, however, ORNs from the maxillary palps are not reported to enter VA1v (Couto et al., 2005). (iv) Neurons that project to many glomeruli, as identified from reporters (Couto et al., 2005; Tanaka et al., 2012), form few connections in VA1v. (v) Six orphans that lack a soma or identified projections outside the glomerulus are included in the matrix. They have very fine neurites we were unable to trace completely, for which reason we have recorded them as orphans, and they are most likely to be the disconnected parts of recorded LNs.

Synaptic reciprocity

Some connections between neurons are made reciprocally, and many LN cell pairs in particular are so connected, but weakly so (Figure 8). The numerical ratios of synapses formed between different cell types differ. Of 1540 possible pairs of neurons having >2 contacts, only 442 (29%) were reciprocal, 380 (25%) of which met a criterion for strong reciprocity in which there were at least four times as many synapses in one direction as the other (a pre:post ratio of either 4 or 0.25: Figure 8).

Figure 8

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Figure 8—source data 1

Reciprocity matrix for all 192antennal lobeglomerulus VA1v cells having >50 contacts.

https://doi.org/10.7554/eLife.37550.018

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We next consider reciprocity between particular cell pairs (Figure 8). There is considerable reciprocity with the two main LN classes (LN1 and LN2L): a) Between types LN1 and mPN1, 74% of pairs are reciprocal with 93% of pairs having a direction of mPN1 (pre) to LN1 (post) and an average ratio of 2.2; and b) between LN2L and mPN1, for which 84% of pairs are reciprocal, with 87% of those pairs being mPN1 (pre) to LN2L (post) and having an average ratio of 1.5. The mPN1 are all highly reciprocal on each other with an average connection strength of 9.9.

LN2L forms many reciprocal connections to other partners, too. Pairs of cells comprising LNs as one partner constitute 85% of the total of all reciprocal cell pairs in the matrix. LN reciprocity is widely observed between many LN pairs but mostly undirected, and with relatively few synapses in either direction. These are likely to be inhibitory (Wilson and Laurent, 2005) and feedback from LNs may therefore serve to suppress, or curtail signalling in both LN partners, and thus be disinhibitory, rather than to shorten transmission in the forward direction. Such reciprocal partnerships form connections on average of 6.7 ± 4.8 synapses (8.1 ± 5.2 in the stronger direction and 4.7 ± 3.1 in the weaker). In comparison, the average connection strength of ipsilateral ORNs to mPN1 is 21.6 ± 7.7 and for contralateral ORNs to mPN1 is 9.2 ± 4.6 synapses, compared with a recent report (Tobin et al., 2017) which found an average of 23 synapses from ipsilateral ORNs.

Our study reports the complete synaptic connectome for all three cell types, ORN, LN and PN, of a single large glomerulus of the Drosophila antennal lobe, providing a proof of principle for the remaining 50 glomeruli. It complements two contemporary EM studies for different glomeruli (Rybak et al., 2016; Tobin et al., 2017), augmenting these by including important synaptic circuits of the LNs, which had not previously been known in any detail at synaptic level yet which constitute nearly half the cells of the glomerulus. Our data are notable for comprehensively documenting synaptic partnerships, and for having overcome the challenge of reconstructing the dense multidirectional arbors of antennal lobe local neurons, aided by the superior z-axis resolution of FIB-SEM compared with ssEM. Unlike PNs and their ORN inputs, and except LN2V, we find that LNs have three main characteristics: they have fewer synapses on average than PNs and ORNs; these are heterogeneous, and they form undirected, reciprocal synaptic networks which are inhibitory.

The connectome we report is essential to promote functional analyses using genetic dissection methods (Venken et al., 2011). In particular it will enable the interpretation of future analyses of network function made possible: first, by imaging methods, either in vitro, especially using genetically encoded calcium (e.g. Tian et al., 2012) or voltage (e.g. Antic et al., 2016) indicators; or second, during intact behaviour in vivo (e.g. Grover et al., 2016), in response to single odours or their combinations (e.g. Yasuyama et al., 2002). Our data also support computational approaches to insect olfaction.

The volumetric packing density of synapses, one site per 2.29 µm³ of neuropile, corresponds approximately to the differently computed values reported from TEM by Rybak et al. (2016) for glomerulus VA7, but is less than the density of synapses in the first and second optic neuropiles, the lamina and medulla (Meinertzhagen, 2014). We may speculate that the more densely packed visual synapses also employ higher rates of transmitter release and are consequently more energetically demanding, but deeper comparisons are hard to make.

We provide the complete connectome from a sensory neuropile in Drosophila, augmenting previous reports on other brain regions, the optic medulla (Takemura et al., 2015) and the mushroom body, both the calyx to which the PN axons project (Butcher et al., 2012) and their Kenyon cell output neurons in the alpha lobe (Takemura et al., 2017). Both the present report and the previous medulla connectome reveal only part of their neuropile as a whole however, for glomerulus VA1v, a single glomerulus in the antennal lobe, and for seven columns only of the optic medulla (Takemura et al., 2015). Like the latter, for all it is comprehensive the connectome of this single fruitless-positive glomerulus lacks most of the circuits of any of the approximately 50 other glomeruli, even of its neighbours, to which most of the local interneurons, those that are multiglomerular, also extend.

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 5, 8 and Figure 2-source data 1. Grayscale and segmentation data are hosted at a Janelia website: http://emdata.janelia.org/AL-VA1v. Data can be viewed in a web browser using neuroglancer. Please see the readme file on how to access the data programmatically using dvid and DICED (this can be accessed by clicking on "AL-VA1v" (hyperlinked) at http://emdata.janelia.org/AL-VA1v).

1. 1. Horne JA
   2. Langille C
   3. McLin A
   4. Wiederman M
   5. Lu Z
   6. Xu CS
   7. Plaza SM
   8. Scheffer L
   9. Hess HF
   10. Meinertzhagen IA

   (2018) FlyEM

   Greyscale and segmentation data.

   http://emdata.janelia.org/AL-VA1v

1. 1. Antic SD
   2. Empson RM
   3. Knöpfel T

   (2016) Voltage imaging to understand connections and functions of neuronal circuits

   Journal of Neurophysiology 116:135–152.

   https://doi.org/10.1152/jn.00226.2016

   • PubMed
   • Google Scholar
2. 1. Bennett MV
   2. Goodenough DA

   (1978)

   Gap junctions, electrotonic coupling, and intercellular communication

   Neurosciences Research Program Bulletin 16:1–486.

   • PubMed
   • Google Scholar
3. 1. Benton R
   2. Vannice KS
   3. Gomez-Diaz C
   4. Vosshall LB

   (2009) Variant ionotropic glutamate receptors as chemosensory receptors in Drosophila

   Cell 136:149–162.

   https://doi.org/10.1016/j.cell.2008.12.001

   • PubMed
   • Google Scholar
4. 1. Butcher NJ
   2. Friedrich AB
   3. Lu Z
   4. Tanimoto H
   5. Meinertzhagen IA

   (2012) Different classes of input and output neurons reveal new features in microglomeruli of the adult Drosophila mushroom body calyx

   Journal of Comparative Neurology 520:2185–2201.

   https://doi.org/10.1002/cne.23037

   • PubMed
   • Google Scholar
5. 1. Chklovskii DB
   2. Vitaladevuni S
   3. Scheffer LK

   (2010) Semi-automated reconstruction of neural circuits using electron microscopy

   Current Opinion in Neurobiology 20:667–675.

   https://doi.org/10.1016/j.conb.2010.08.002

   • PubMed
   • Google Scholar
6. 1. Chou YH
   2. Spletter ML
   3. Yaksi E
   4. Leong JC
   5. Wilson RI
   6. Luo L

   (2010) Diversity and wiring variability of olfactory local interneurons in the Drosophila antennal lobe

   Nature Neuroscience 13:439–449.

   https://doi.org/10.1038/nn.2489

   • PubMed
   • Google Scholar
7. 1. Couto A
   2. Alenius M
   3. Dickson BJ

   (2005) Molecular, anatomical, and functional organization of the Drosophila olfactory system

   Current Biology 15:1535–1547.

   https://doi.org/10.1016/j.cub.2005.07.034

   • PubMed
   • Google Scholar
8. 1. Das A
   2. Chiang A
   3. Davla S
   4. Priya R
   5. Reichert H
   6. VijayRaghavan K
   7. Rodrigues V

   (2011) Identification and analysis of a glutamatergic local interneuron lineage in the adult Drosophila olfactory system

   Neural Systems & Circuits 1:4.

   https://doi.org/10.1186/2042-1001-1-4

   • PubMed
   • Google Scholar
9. 1. Dowling JE
   2. Boycott BB

   (1966) Organization of the primate retina: electron microscopy

   Proceedings of the Royal Society B: Biological Sciences 166:80–111.

   https://doi.org/10.1098/rspb.1966.0086

   • Google Scholar
10. 1. Dweck HK
    2. Ebrahim SA
    3. Kromann S
    4. Bown D
    5. Hillbur Y
    6. Sachse S
    7. Hansson BS
    8. Stensmyr MC

    (2013) Olfactory preference for egg laying on citrus substrates in Drosophila

    Current Biology 23:2472–2480.

    https://doi.org/10.1016/j.cub.2013.10.047

    • PubMed
    • Google Scholar
11. 1. Endo K
    2. Aoki T
    3. Yoda Y
    4. Kimura K
    5. Hama C

    (2007) Notch signal organizes the Drosophila olfactory circuitry by diversifying the sensory neuronal lineages

    Nature Neuroscience 10:153–160.

    https://doi.org/10.1038/nn1832

    • PubMed
    • Google Scholar
12. 1. Fröhlich A

    (1985) Freeze-fracture study of an invertebrate multiple-contact synapse: the fly photoreceptor tetrad

    The Journal of Comparative Neurology 241:311–326.

    https://doi.org/10.1002/cne.902410306

    • PubMed
    • Google Scholar
13. 1. Gao Q
    2. Yuan B
    3. Chess A

    (2000) Convergent projections of Drosophila olfactory neurons to specific glomeruli in the antennal lobe

    Nature Neuroscience 3:780–785.

    https://doi.org/10.1038/77680

    • PubMed
    • Google Scholar
14. 1. Grabe V
    2. Strutz A
    3. Baschwitz A
    4. Hansson BS
    5. Sachse S

    (2015) Digital in vivo 3D atlas of the antennal lobe of Drosophila melanogaster

    Journal of Comparative Neurology 523:530–544.

    https://doi.org/10.1002/cne.23697

    • PubMed
    • Google Scholar
15. 1. Grabe V
    2. Baschwitz A
    3. Dweck HKM
    4. Lavista-Llanos S
    5. Hansson BS
    6. Sachse S

    (2016) Elucidating the neuronal architecture of olfactory glomeruli in the Drosophila antennal lobe

    Cell Reports 16:3401–3413.

    https://doi.org/10.1016/j.celrep.2016.08.063

    • PubMed
    • Google Scholar
16. 1. Grover D
    2. Katsuki T
    3. Greenspan RJ

    (2016) Flyception: imaging brain activity in freely walking fruit flies

    Nature Methods 13:569–572.

    https://doi.org/10.1038/nmeth.3866

    • PubMed
    • Google Scholar
17. 1. Gruber L
    2. Rybak J
    3. Hansson BS
    4. Cantera R

    (2018) Synaptic Spinules in the Olfactory Circuit of Drosophila melanogaster

    Frontiers in Cellular Neuroscience 12:86.

    https://doi.org/10.3389/fncel.2018.00086

    • PubMed
    • Google Scholar
18. 1. Hamanaka Y
    2. Meinertzhagen IA

    (2010) Immunocytochemical localization of synaptic proteins to photoreceptor synapses of Drosophila melanogaster

    The Journal of Comparative Neurology 518:1133–1155.

    https://doi.org/10.1002/cne.22268

    • PubMed
    • Google Scholar
19. 1. Heisenberg M
    2. Böhl K

    (1979) Isolation of anatomical brain mutants of Drosophila by histological means

    Zeitschrift für Naturforschung C 34:143–147.

    https://doi.org/10.1515/znc-1979-1-228

    • Google Scholar
20. 1. Hildebrand JG
    2. Shepherd GM

    (1997) Mechanisms of olfactory discrimination: converging evidence for common principles across phyla

    Annual Review of Neuroscience 20:595–631.

    https://doi.org/10.1146/annurev.neuro.20.1.595

    • PubMed
    • Google Scholar
21. Preprint

    1. Huang GB
    2. Plaza S

    (2014) Identifying synapses using deep and wide multiscale recursive networks

    arXiv.

    https://arxiv.org/abs/1409.1789

    • Google Scholar
22. 1. Ignell R
    2. Root CM
    3. Birse RT
    4. Wang JW
    5. Nässel DR
    6. Winther AM

    (2009) Presynaptic peptidergic modulation of olfactory receptor neurons in Drosophila

    PNAS 106:13070–13075.

    https://doi.org/10.1073/pnas.0813004106

    • PubMed
    • Google Scholar
23. 1. Ito K
    2. Shinomiya K
    3. Ito M
    4. Armstrong JD
    5. Boyan G
    6. Hartenstein V
    7. Harzsch S
    8. Heisenberg M
    9. Homberg U
    10. Jenett A
    11. Keshishian H
    12. Restifo LL
    13. Rössler W
    14. Simpson JH
    15. Strausfeld NJ
    16. Strauss R
    17. Vosshall LB
    18. Insect Brain Name Working Group

    (2014) A systematic nomenclature for the insect brain

    Neuron 81:755–765.

    https://doi.org/10.1016/j.neuron.2013.12.017

    • PubMed
    • Google Scholar
24. 1. Jeanne JM
    2. Wilson RI

    (2015) Convergence, divergence, and reconvergence in a feedforward network improves neural speed and accuracy

    Neuron 88:1014–1026.

    https://doi.org/10.1016/j.neuron.2015.10.018

    • PubMed
    • Google Scholar
25. Software

    1. Katz WT
    2. Plaza S

    (2018) DVID

    Github.

    https://github.com/janelia-flyem/dvid
26. 1. Kawagishi K
    2. Ando M
    3. Yokouchi K
    4. Sumitomo N
    5. Karasawa M
    6. Fukushima N
    7. Moriizumi T

    (2014) Stereological quantification of olfactory receptor neurons in mice

    Neuroscience 272:29–33.

    https://doi.org/10.1016/j.neuroscience.2014.04.050

    • PubMed
    • Google Scholar
27. 1. Kazama H
    2. Wilson RI

    (2009) Origins of correlated activity in an olfactory circuit

    Nature Neuroscience 12:1136–1144.

    https://doi.org/10.1038/nn.2376

    • PubMed
    • Google Scholar
28. Book

    1. Klebanov LB

    (2003)

    Heavy Tailed Distributions

    Prague: Charles University.

    • Google Scholar
29. 1. Knott G
    2. Marchman H
    3. Wall D
    4. Lich B

    (2008) Serial section scanning electron microscopy of adult brain tissue using focused ion beam milling

    Journal of Neuroscience 28:2959–2964.

    https://doi.org/10.1523/JNEUROSCI.3189-07.2008

    • PubMed
    • Google Scholar
30. 1. Kondoh Y
    2. Kaneshiro KY
    3. Kimura K
    4. Yamamoto D

    (2003) Evolution of sexual dimorphism in the olfactory brain of Hawaiian Drosophila

    Proceedings of the Royal Society B: Biological Sciences 270:1005–1013.

    https://doi.org/10.1098/rspb.2003.2331

    • PubMed
    • Google Scholar
31. 1. Kreshuk A
    2. Straehle CN
    3. Sommer C
    4. Koethe U
    5. Cantoni M
    6. Knott G
    7. Hamprecht FA

    (2011) Automated detection and segmentation of synaptic contacts in nearly isotropic serial electron microscopy images

    PLoS One 6:e24899.

    https://doi.org/10.1371/journal.pone.0024899

    • PubMed
    • Google Scholar
32. 1. Kurtovic A
    2. Widmer A
    3. Dickson BJ

    (2007) A single class of olfactory neurons mediates behavioural responses to a Drosophila sex pheromone

    Nature 446:542–546.

    https://doi.org/10.1038/nature05672

    • PubMed
    • Google Scholar
33. 1. Lai SL
    2. Awasaki T
    3. Ito K
    4. Lee T

    (2008) Clonal analysis of Drosophila antennal lobe neurons: diverse neuronal architectures in the lateral neuroblast lineage

    Development 135:2883–2893.

    https://doi.org/10.1242/dev.024380

    • PubMed
    • Google Scholar
34. 1. Laissue PP
    2. Reiter C
    3. Hiesinger PR
    4. Halter S
    5. Fischbach KF
    6. Stocker RF

    (1999) Three-dimensional reconstruction of the antennal lobe in Drosophila melanogaster

    The Journal of Comparative Neurology 405:543–552.

    https://doi.org/10.1002/(SICI)1096-9861(19990322)405:4<543::AID-CNE7>3.0.CO;2-A

    • PubMed
    • Google Scholar
35. 1. Leiss F
    2. Groh C
    3. Butcher NJ
    4. Meinertzhagen IA
    5. Tavosanis G

    (2009) Synaptic organization in the adult Drosophila mushroom body calyx

    The Journal of Comparative Neurology 517:808–824.

    https://doi.org/10.1002/cne.22184

    • PubMed
    • Google Scholar
36. 1. Lichtman JW
    2. Sanes JR

    (2008) Ome sweet ome: what can the genome tell us about the connectome?

    Current Opinion in Neurobiology 18:346–353.

    https://doi.org/10.1016/j.conb.2008.08.010

    • PubMed
    • Google Scholar
37. 1. Lin S
    2. Lai SL
    3. Yu HH
    4. Chihara T
    5. Luo L
    6. Lee T

    (2010) Lineage-specific effects of Notch/Numb signaling in post-embryonic development of the Drosophila brain

    Development 137:43–51.

    https://doi.org/10.1242/dev.041699

    • PubMed
    • Google Scholar
38. 1. Liou NF
    2. Lin SH
    3. Chen YJ
    4. Tsai KT
    5. Yang CJ
    6. Lin TY
    7. Wu TH
    8. Lin HJ
    9. Chen YT
    10. Gohl DM
    11. Silies M
    12. Chou YH

    (2018) Diverse populations of local interneurons integrate into the Drosophila adult olfactory circuit

    Nature Communications 9:2232.

    https://doi.org/10.1038/s41467-018-04675-x

    • PubMed
    • Google Scholar
39. 1. Liu WW
    2. Wilson RI

    (2013) Glutamate is an inhibitory neurotransmitter in the Drosophila olfactory system

    PNAS 110:10294–10299.

    https://doi.org/10.1073/pnas.1220560110

    • PubMed
    • Google Scholar
40. 1. Marin EC
    2. Jefferis GS
    3. Komiyama T
    4. Zhu H
    5. Luo L

    (2002) Representation of the glomerular olfactory map in the Drosophila brain

    Cell 109:243–255.

    https://doi.org/10.1016/S0092-8674(02)00700-6

    • PubMed
    • Google Scholar
41. 1. Meinertzhagen IA
    2. Lee CH

    (2012) The genetic analysis of functional connectomics in Drosophila

    Advances in Genetics 80:99–151.

    https://doi.org/10.1016/B978-0-12-404742-6.00003-X

    • PubMed
    • Google Scholar
42. 1. Meinertzhagen IA
    2. O'Neil SD

    (1991) Synaptic organization of columnar elements in the lamina of the wild type in Drosophila melanogaster

    The Journal of Comparative Neurology 305:232–263.

    https://doi.org/10.1002/cne.903050206

    • PubMed
    • Google Scholar
43. 1. Meinertzhagen IA
    2. Sorra KE

    (2001) Synaptic organization in the fly's optic lamina: few cells, many synapses and divergent microcircuits

    Progress in Brain Research 131:53–69.

    https://doi.org/10.1016/S0079-6123(01)31007-5

    • PubMed
    • Google Scholar
44. 1. Meinertzhagen IA
    2. Takemura SY
    3. Lu Z
    4. Huang S
    5. Gao S
    6. Ting CY
    7. Lee CH

    (2009) From form to function: the ways to know a neuron

    Journal of Neurogenetics 23:68–77.

    https://doi.org/10.1080/01677060802610604

    • PubMed
    • Google Scholar
45. Book

    1. Meinertzhagen IA

    (2014)

    The anatomical organization of the compound eye visual system

    In: Dubnau J, editors. Handbook of Behavior Genetics of Drosophila melanogaster: Behavioral Phenotyping Protocols, 1. Cambridge University Press. pp. 1–19.

    • Google Scholar
46. 1. Meinertzhagen IA

    (2018)

    Of what use is connectomics? (Commentary)

    The Journal of Experimental Biology jeb164954.

    • Google Scholar
47. 1. Mosca TJ
    2. Luo L

    (2014) Synaptic organization of the Drosophila antennal lobe and its regulation by the Teneurins

    eLife 3:e03726.

    https://doi.org/10.7554/eLife.03726

    • PubMed
    • Google Scholar
48. 1. Okada R
    2. Awasaki T
    3. Ito K

    (2009) Gamma-aminobutyric acid (GABA)-mediated neural connections in the Drosophila antennal lobe

    The Journal of Comparative Neurology 514:74–91.

    https://doi.org/10.1002/cne.21971

    • PubMed
    • Google Scholar
49. 1. Parag T
    2. Chakraborty A
    3. Plaza S
    4. Scheffer L

    (2015) A context-aware delayed agglomeration framework for electron microscopy segmentation

    PLoS One 10:e0125825.

    https://doi.org/10.1371/journal.pone.0125825

    • PubMed
    • Google Scholar
50. 1. Plaza SM
    2. Scheffer LK
    3. Saunders M

    (2012) Minimizing manual image segmentation turn-around time for neuronal reconstruction by embracing uncertainty

    PLoS One 7:e44448.

    https://doi.org/10.1371/journal.pone.0044448

    • PubMed
    • Google Scholar
51. 1. Plaza SM
    2. Scheffer LK
    3. Chklovskii DB

    (2014) Toward large-scale connectome reconstructions

    Current Opinion in Neurobiology 25:201–210.

    https://doi.org/10.1016/j.conb.2014.01.019

    • PubMed
    • Google Scholar
52. 1. Rall W
    2. Shepherd GM
    3. Reese TS
    4. Brightman MW

    (1966) Dendrodendritic synaptic pathway for inhibition in the olfactory bulb

    Experimental Neurology 14:44–56.

    https://doi.org/10.1016/0014-4886(66)90023-9

    • PubMed
    • Google Scholar
53. 1. Royet JP
    2. Souchier C
    3. Jourdan F
    4. Ploye H

    (1988) Morphometric study of the glomerular population in the mouse olfactory bulb: numerical density and size distribution along the rostrocaudal axis

    Journal of Comparative Neurology 270:559–568.

    https://doi.org/10.1002/cne.902700409

    • PubMed
    • Google Scholar
54. 1. Ryan K
    2. Lu Z
    3. Meinertzhagen IA

    (2016) The CNS connectome of a tadpole larva of Ciona intestinalis (L.) highlights sidedness in the brain of a chordate sibling

    eLife 5:e16962.

    https://doi.org/10.7554/eLife.16962

    • PubMed
    • Google Scholar
55. 1. Rybak J
    2. Talarico G
    3. Ruiz S
    4. Arnold C
    5. Cantera R
    6. Hansson BS

    (2016) Synaptic circuitry of identified neurons in the antennal lobe of Drosophila melanogaster

    Journal of Comparative Neurology 524:1920–1956.

    https://doi.org/10.1002/cne.23966

    • PubMed
    • Google Scholar
56. 1. Sakurai A
    2. Koganezawa M
    3. Yasunaga K
    4. Emoto K
    5. Yamamoto D

    (2013) Select interneuron clusters determine female sexual receptivity in Drosophila

    Nature Communications 4:1825.

    https://doi.org/10.1038/ncomms2837

    • PubMed
    • Google Scholar
57. 1. Seki Y
    2. Rybak J
    3. Wicher D
    4. Sachse S
    5. Hansson BS

    (2010) Physiological and morphological characterization of local interneurons in the Drosophila antennal lobe

    Journal of Neurophysiology 104:1007–1019.

    https://doi.org/10.1152/jn.00249.2010

    • PubMed
    • Google Scholar
58. 1. Shannon P
    2. Markiel A
    3. Ozier O
    4. Baliga NS
    5. Wang JT
    6. Ramage D
    7. Amin N
    8. Schwikowski B
    9. Ideker T

    (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks

    Genome Research 13:2498–2504.

    https://doi.org/10.1101/gr.1239303

    • PubMed
    • Google Scholar
59. 1. Shaw SR
    2. Stowe S

    (1982)

    Freeze-fracture evidence for gap junctions connecting the axon terminals of dipteran photoreceptors

    Journal of Cell Science 53:115–141.

    • Google Scholar
60. Book

    1. Shepherd GM

    (1998)

    The Synaptic Organization of the Brain (4th Edn)

    New York: Oxford University Press.

    • Google Scholar
61. 1. Silbering AF
    2. Galizia CG

    (2007) Processing of odor mixtures in the Drosophila antennal lobe reveals both global inhibition and glomerulus-specific interactions

    Journal of Neuroscience 27:11966–11977.

    https://doi.org/10.1523/JNEUROSCI.3099-07.2007

    • PubMed
    • Google Scholar
62. 1. Silbering AF
    2. Rytz R
    3. Grosjean Y
    4. Abuin L
    5. Ramdya P
    6. Jefferis GS
    7. Benton R

    (2011) Complementary function and integrated wiring of the evolutionarily distinct Drosophila olfactory subsystems

    Journal of Neuroscience 31:13357–13375.

    https://doi.org/10.1523/JNEUROSCI.2360-11.2011

    • PubMed
    • Google Scholar
63. 1. Stocker RF
    2. Singh RN
    3. Schorderet M
    4. Siddiqi O

    (1983) Projection patterns of different types of antennal sensilla in the antennal glomeruli of Drosophila melanogaster

    Cell and Tissue Research 232:237–248.

    https://doi.org/10.1007/BF00213783

    • PubMed
    • Google Scholar
64. 1. Stocker RF
    2. Lienhard MC
    3. Borst A
    4. Fischbach KF

    (1990) Neuronal architecture of the antennal lobe in Drosophila melanogaster

    Cell and Tissue Research 262:9–34.

    https://doi.org/10.1007/BF00327741

    • PubMed
    • Google Scholar
65. 1. Stocker RF

    (1994) The organization of the chemosensory system in Drosophila melanogaster: a review

    Cell and Tissue Research 275:3–26.

    https://doi.org/10.1007/BF00305372

    • PubMed
    • Google Scholar
66. 1. Stockinger P
    2. Kvitsiani D
    3. Rotkopf S
    4. Tirián L
    5. Dickson BJ

    (2005) Neural circuitry that governs Drosophila male courtship behavior

    Cell 121:795–807.

    https://doi.org/10.1016/j.cell.2005.04.026

    • PubMed
    • Google Scholar
67. 1. Strube-Bloss MF
    2. Grabe V
    3. Hansson BS
    4. Sachse S

    (2017) Calcium imaging revealed no modulatory effect on odor-evoked responses of the Drosophila antennal lobe by two populations of inhibitory local interneurons

    Scientific Reports 7:7854.

    https://doi.org/10.1038/s41598-017-08090-y

    • PubMed
    • Google Scholar
68. 1. Takemura SY
    2. Lu Z
    3. Meinertzhagen IA

    (2008) Synaptic circuits of the Drosophila optic lobe: the input terminals to the medulla

    Journal of Comparative Neurology 509:493–513.

    https://doi.org/10.1002/cne.21757

    • PubMed
    • Google Scholar
69. 1. Takemura SY
    2. Bharioke A
    3. Lu Z
    4. Nern A
    5. Vitaladevuni S
    6. Rivlin PK
    7. Katz WT
    8. Olbris DJ
    9. Plaza SM
    10. Winston P
    11. Zhao T
    12. Horne JA
    13. Fetter RD
    14. Takemura S
    15. Blazek K
    16. Chang LA
    17. Ogundeyi O
    18. Saunders MA
    19. Shapiro V
    20. Sigmund C
    21. Rubin GM
    22. Scheffer LK
    23. Meinertzhagen IA
    24. Chklovskii DB

    (2013) A visual motion detection circuit suggested by Drosophila connectomics

    Nature 500:175–181.

    https://doi.org/10.1038/nature12450

    • PubMed
    • Google Scholar
70. 1. Takemura S
    2. Cs X
    3. Lu Z
    4. Rivlin PK
    5. Olbris DJ
    6. Parag T
    7. Plaza S
    8. Zhao T
    9. Katz WT
    10. Umayam L
    11. Weaver C
    12. Hess H
    13. Horne JA
    14. Nunez J
    15. Aniceto R
    16. Chang L-A
    17. Lauchie S
    18. Nasca A
    19. Ogundeyi O
    20. Sigmund C
    21. Takemura S
    22. Tran J
    23. Langille C
    24. Le Lacheur K
    25. McLin S
    26. Shinomiya A
    27. Chklovskii DB
    28. Meinertzhagen IA
    29. Scheffer LK

    (2015)

    Multi-column synaptic circuits and an analysis of their variations in the visual system of Drosophila

    PNAS 112:13711–13716.

    • Google Scholar
71. 1. Takemura SY
    2. Aso Y
    3. Hige T
    4. Wong A
    5. Lu Z
    6. Xu CS
    7. Rivlin PK
    8. Hess H
    9. Zhao T
    10. Parag T
    11. Berg S
    12. Huang G
    13. Katz W
    14. Olbris DJ
    15. Plaza S
    16. Umayam L
    17. Aniceto R
    18. Chang LA
    19. Lauchie S
    20. Ogundeyi O
    21. Ordish C
    22. Shinomiya A
    23. Sigmund C
    24. Takemura S
    25. Tran J
    26. Turner GC
    27. Rubin GM
    28. Scheffer LK

    (2017) A connectome of a learning and memory center in the adult Drosophila brain

    eLife 6:e26975.

    https://doi.org/10.7554/eLife.26975

    • PubMed
    • Google Scholar
72. 1. Tanaka NK
    2. Endo K
    3. Ito K

    (2012) Organization of antennal lobe-associated neurons in adult Drosophila melanogaster brain

    The Journal of Comparative Neurology 520:4067–4130.

    https://doi.org/10.1002/cne.23142

    • PubMed
    • Google Scholar
73. 1. Tian L
    2. Akerboom J
    3. Schreiter ER
    4. Looger LL

    (2012) Neural activity imaging with genetically encoded calcium indicators

    Progress in Brain Research 196:79–94.

    https://doi.org/10.1016/B978-0-444-59426-6.00005-7

    • PubMed
    • Google Scholar
74. 1. Tobin WF
    2. Wilson RI
    3. Lee WA
    4. W-Ca L

    (2017) Wiring variations that enable and constrain neural computation in a sensory microcircuit

    eLife 6:e24838.

    https://doi.org/10.7554/eLife.24838

    • PubMed
    • Google Scholar
75. 1. Venken KJ
    2. Simpson JH
    3. Bellen HJ

    (2011) Genetic manipulation of genes and cells in the nervous system of the fruit fly

    Neuron 72:202–230.

    https://doi.org/10.1016/j.neuron.2011.09.021

    • PubMed
    • Google Scholar
76. 1. Vosshall LB
    2. Wong AM
    3. Axel R

    (2000) An olfactory sensory map in the fly brain

    Cell 102:147–159.

    https://doi.org/10.1016/S0092-8674(00)00021-0

    • PubMed
    • Google Scholar
77. 1. Vosshall LB
    2. Stocker RF

    (2007) Molecular architecture of smell and taste in Drosophila

    Annual Review of Neuroscience 30:505–533.

    https://doi.org/10.1146/annurev.neuro.30.051606.094306

    • PubMed
    • Google Scholar
78. 1. Wilson RI
    2. Laurent G

    (2005) Role of GABAergic inhibition in shaping odor-evoked spatiotemporal patterns in the Drosophila antennal lobe

    Journal of Neuroscience 25:9069–9079.

    https://doi.org/10.1523/JNEUROSCI.2070-05.2005

    • PubMed
    • Google Scholar
79. 1. Wilson RI

    (2013) Early olfactory processing in Drosophila: mechanisms and principles

    Annual Review of Neuroscience 36:217–241.

    https://doi.org/10.1146/annurev-neuro-062111-150533

    • PubMed
    • Google Scholar
80. 1. Wong AM
    2. Wang JW
    3. Axel R

    (2002) Spatial representation of the glomerular map in the Drosophila protocerebrum

    Cell 109:229–241.

    https://doi.org/10.1016/S0092-8674(02)00707-9

    • PubMed
    • Google Scholar
81. 1. Xu CS
    2. Hayworth KJ
    3. Lu Z
    4. Grob P
    5. Hassan AM
    6. García-Cerdán JG
    7. Niyogi KK
    8. Nogales E
    9. Weinberg RJ
    10. Hess HF

    (2017) Enhanced FIB-SEM systems for large-volume 3D imaging

    eLife 6:e25916.

    https://doi.org/10.7554/eLife.25916

    • PubMed
    • Google Scholar
82. 1. Yasuyama K
    2. Meinertzhagen IA
    3. Schürmann FW

    (2002) Synaptic organization of the mushroom body calyx in Drosophila melanogaster

    Journal of Comparative Neurology 445:211–226.

    https://doi.org/10.1002/cne.10155

    • PubMed
    • Google Scholar
83. 1. Yasuyama K
    2. Meinertzhagen IA
    3. Schürmann FW

    (2003) Synaptic connections of cholinergic antennal lobe relay neurons innervating the lateral horn neuropile in the brain of Drosophila melanogaster

    Journal of Comparative Neurology 466:299–315.

    https://doi.org/10.1002/cne.10867

    • PubMed
    • Google Scholar
84. 1. Yu HH
    2. Kao CF
    3. He Y
    4. Ding P
    5. Kao JC
    6. Lee T

    (2010) A complete developmental sequence of a Drosophila neuronal lineage as revealed by twin-spot MARCM

    PLoS Biology 8:e1000461.

    https://doi.org/10.1371/journal.pbio.1000461

    • PubMed
    • Google Scholar
85. Preprint

    1. Zhao T
    2. Takemura S
    3. Huang G
    4. Horne JA
    5. Katz W
    6. Shinomiya K
    7. Scheffer L
    8. Meinertzhagen IA
    9. Rivlin P
    10. Plaza S

    (2015) Large-scale EM analysis of the Drosophila antennal lobe with automatically computed synapse point clouds

    arXiv.

    https://arxiv.org/abs/1508.06232

    • Google Scholar
86. Software

    1. Zhao T
    2. Olbris DJ
    3. Yu Y
    4. Plaza S

    (2018) NeuTu-EM

    Github.

    https://github.com/janelia-flyem/NeuTu

Author details

1. Jane Anne Horne

   Department of Psychology and Neuroscience, Life Sciences Centre, Dalhousie University, Halifax, Canada

   Contribution

   Data curation, Software, Formal analysis, Supervision, Methodology, Writing—original draft, Project administration, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9673-2692

2. Carlie Langille

   Department of Psychology and Neuroscience, Life Sciences Centre, Dalhousie University, Halifax, Canada

   Contribution

   Data curation, Validation

   Competing interests

   No competing interests declared

3. Sari McLin

   Department of Psychology and Neuroscience, Life Sciences Centre, Dalhousie University, Halifax, Canada

   Contribution

   Data curation, Validation

   Competing interests

   No competing interests declared

4. Meagan Wiederman

   Department of Psychology and Neuroscience, Life Sciences Centre, Dalhousie University, Halifax, Canada

   Contribution

   Data curation, Validation

   Competing interests

   No competing interests declared

5. Zhiyuan Lu

   1. Department of Psychology and Neuroscience, Life Sciences Centre, Dalhousie University, Halifax, Canada
   2. Janelia Research Campus, Howard Hughes Medical Institute, Virginia, United States

   Contribution

   Validation, Methodology, Ultramicrotomy

   Competing interests

   No competing interests declared

6. C Shan Xu

   Janelia Research Campus, Howard Hughes Medical Institute, Virginia, United States

   Contribution

   Visualization, Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8564-7836

7. Stephen M Plaza

   Janelia Research Campus, Howard Hughes Medical Institute, Virginia, United States

   Contribution

   Resources, Software, Methodology

   Competing interests

   No competing interests declared

8. Louis K Scheffer

   Janelia Research Campus, Howard Hughes Medical Institute, Virginia, United States

   Contribution

   Software, Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3289-6564

9. Harald F Hess

   Janelia Research Campus, Howard Hughes Medical Institute, Virginia, United States

   Contribution

   Visualization, Methodology

   Competing interests

   No competing interests declared

10. Ian A Meinertzhagen

    1. Department of Psychology and Neuroscience, Life Sciences Centre, Dalhousie University, Halifax, Canada
    2. Janelia Research Campus, Howard Hughes Medical Institute, Virginia, United States

    Contribution

    Writing—original draft, Writing—review and editing

    For correspondence

    I.A.Meinertzhagen@Dal.Ca

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-6578-4526

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