Conserved neural circuit structure across Drosophila larval development revealed by comparative connectomics

Transsynaptic BMP Signaling Regulates Fine-Scale Topography between Adjacent Sensory Neurons

Sensory axons projecting to the central nervous system are organized into topographic maps that represent the locations of sensory stimuli. In some sensory systems, even adjacent sensory axons are arranged topographically, forming "fine-scale" topographic maps. Although several broad molecular gradients are known to instruct coarse topography, we know little about the molecular signaling that regulates fine-scale topography at the level of two adjacent axons. Here, we provide evidence that transsynaptic bone morphogenetic protein (BMP) signaling mediates local interneuronal communication to regulate fine-scale topography in the nociceptive system of Drosophila larvae. We first show that the topographic separation of the axon terminals of adjacent nociceptors requires their common postsynaptic target, the A08n neurons. This phenotype is recapitulated by knockdown of the BMP ligand, Decapentaplegic (Dpp), in these neurons. In addition, removing the Type 2 BMP receptors or their effector (Mad transcription factor) in single nociceptors impairs the fine-scale topography, suggesting the contribution of BMP signaling originated from A08n. This signaling is likely mediated by phospho-Mad in the presynaptic terminals of nociceptors to ensure local interneuronal communication. Finally, reducing Dpp levels in A08n reduces the nociceptor-A08n synaptic contacts. Our data support that transsynaptic BMP signaling establishes the fine-scale topography by facilitating the formation of topographically correct synapses. Local BMP signaling for synapse formation may be a developmental strategy that independently regulates neighboring axon terminals for fine-scale topography.

Dimensionality of locomotor behaviors in developing C. elegans

Adult animals display robust locomotion, yet the timeline and mechanisms of how juvenile animals acquire coordinated movements and how these movements evolve during development are not well understood. Recent advances in quantitative behavioral analyses have paved the way for investigating complex natural behaviors like locomotion. In this study, we tracked the swimming and crawling behaviors of the nematode Caenorhabditis elegans from postembryonic development through to adulthood. Our principal component analyses revealed that adult C. elegans swimming is low dimensional, suggesting that a small number of distinct postures, or eigenworms, account for most of the variance in the body shapes that constitute swimming behavior. Additionally, we found that crawling behavior in adult C. elegans is similarly low dimensional, corroborating previous studies. Further, our analysis revealed that swimming and crawling are distinguishable within the eigenworm space. Remarkably, young L1 larvae are capable of producing the postural shapes for swimming and crawling seen in adults, despite frequent instances of uncoordinated body movements. In contrast, late L1 larvae exhibit robust coordination of locomotion, while many neurons crucial for adult locomotion are still under development. In conclusion, this study establishes a comprehensive quantitative behavioral framework for understanding the neural basis of locomotor development, including distinct gaits such as swimming and crawling in C. elegans.

Toolkits for detailed and high-throughput interrogation of synapses in C. elegans

Visualizing synaptic connectivity has traditionally relied on time-consuming electron microscopy-based imaging approaches. To scale the analysis of synaptic connectivity, fluorescent protein-based techniques have been established, ranging from the labeling of specific pre- or post-synaptic components of chemical or electrical synapses to transsynaptic proximity labeling technology such as GRASP and iBLINC. In this paper, we describe WormPsyQi, a generalizable image analysis pipeline that automatically quantifies synaptically localized fluorescent signals in a high-throughput and robust manner, with reduced human bias. We also present a resource of 30 transgenic strains that label chemical or electrical synapses throughout the nervous system of the nematode Caenorhabditis elegans, using CLA-1, RAB-3, GRASP (chemical synapses), or innexin (electrical synapse) reporters. We show that WormPsyQi captures synaptic structures in spite of substantial heterogeneity in neurite morphology, fluorescence signal, and imaging parameters. We use these toolkits to quantify multiple obvious and subtle features of synapses - such as number, size, intensity, and spatial distribution of synapses - in datasets spanning various regions of the nervous system, developmental stages, and sexes. Although the pipeline is described in the context of synapses, it may be utilized for other 'punctate' signals, such as fluorescently tagged neurotransmitter receptors and cell adhesion molecules, as well as proteins in other subcellular contexts. By overcoming constraints on time, sample size, cell morphology, and phenotypic space, this work represents a powerful resource for further analysis of synapse biology in C. elegans.

Puckered and JNK signaling in pioneer neurons coordinates the motor activity of the Drosophila embryo

Central nervous system organogenesis is a complex process that obeys precise architectural rules. The impact that nervous system architecture may have on its functionality remains, however, relatively unexplored. To clarify this problem, we analyze the development of the Drosophila embryonic Ventral Nerve Cord (VNC). VNC morphogenesis requires the tight control of Jun kinase (JNK) signaling in a subset of pioneer neurons, exerted in part via a negative feedback loop mediated by the dual specificity phosphatase Puckered. Here we show that the JNK pathway autonomously regulates neuronal electrophysiological properties without affecting synaptic vesicle transport. Manipulating JNK signaling activity in pioneer neurons during early embryogenesis directly influences their function as organizers of VNC architecture and, moreover, uncovers a role in the coordination of the embryonic motor circuitry that is required for hatching. Together, our data reveal critical links, mediated by the control of the JNK signaling cascade by Puckered, between the structural organization of the VNC and its functional optimization.

Linking neural circuits to the mechanics of animal behavior in Drosophila larval locomotion

The motions that make up animal behavior arise from the interplay between neural circuits and the mechanical parts of the body. Therefore, in order to comprehend the operational mechanisms governing behavior, it is essential to examine not only the underlying neural network but also the mechanical characteristics of the animal's body. The locomotor system of fly larvae serves as an ideal model for pursuing this integrative approach. By virtue of diverse investigation methods encompassing connectomics analysis and quantification of locomotion kinematics, research on larval locomotion has shed light on the underlying mechanisms of animal behavior. These studies have elucidated the roles of interneurons in coordinating muscle activities within and between segments, as well as the neural circuits responsible for exploration. This review aims to provide an overview of recent research on the neuromechanics of animal locomotion in fly larvae. We also briefly review interspecific diversity in fly larval locomotion and explore the latest advancements in soft robots inspired by larval locomotion. The integrative analysis of animal behavior using fly larvae could establish a practical framework for scrutinizing the behavior of other animal species.

Neural substrates of cold nociception in Drosophila larva

Metazoans detect and differentiate between innocuous (non-painful) and/or noxious (harmful) environmental cues using primary sensory neurons, which serve as the first node in a neural network that computes stimulus specific behaviors to either navigate away from injury-causing conditions or to perform protective behaviors that mitigate extensive injury. The ability of an animal to detect and respond to various sensory stimuli depends upon molecular diversity in the primary sensors and the underlying neural circuitry responsible for the relevant behavioral action selection. Recent studies in Drosophila larvae have revealed that somatosensory class III multidendritic (CIII md) neurons function as multimodal sensors regulating distinct behavioral responses to innocuous mechanical and nociceptive thermal stimuli. Recent advances in circuit bases of behavior have identified and functionally validated Drosophila larval somatosensory circuitry involved in innocuous (mechanical) and noxious (heat and mechanical) cues. However, central processing of cold nociceptive cues remained unexplored. We implicate multisensory integrators (Basins), premotor (Down-and-Back) and projection (A09e and TePns) neurons as neural substrates required for cold-evoked behavioral and calcium responses. Neural silencing of cell types downstream of CIII md neurons led to significant reductions in cold-evoked behaviors and neural co-activation of CIII md neurons plus additional cell types facilitated larval contraction (CT) responses. We further demonstrate that optogenetic activation of CIII md neurons evokes calcium increases in these neurons. Collectively, we demonstrate how Drosophila larvae process cold stimuli through functionally diverse somatosensory circuitry responsible for generating stimulus specific behaviors.

Distinctive features of the central synaptic organization of Drosophila larval proprioceptors

Proprioceptive feedback is critically needed for locomotor control, but how this information is incorporated into central proprioceptive processing circuits remains poorly understood. Circuit organization emerges from the spatial distribution of synaptic connections between neurons. This distribution is difficult to discern in model systems where only a few cells can be probed simultaneously. Therefore, we turned to a relatively simple and accessible nervous system to ask: how are proprioceptors' input and output synapses organized in space, and what principles underlie this organization? Using the Drosophila larval connectome, we generated a map of the input and output synapses of 34 proprioceptors in several adjacent body segments (5-6 left-right pairs per segment). We characterized the spatial organization of these synapses, and compared this organization to that of other somatosensory neurons' synapses. We found three distinguishing features of larval proprioceptor synapses: (1) Generally, individual proprioceptor types display segmental somatotopy. (2) Proprioceptor output synapses both converge and diverge in space; they are organized into six spatial domains, each containing a unique set of one or more proprioceptors. Proprioceptors form output synapses along the proximal axonal entry pathway into the neuropil. (3) Proprioceptors receive few inhibitory input synapses. Further, we find that these three features do not apply to other larval somatosensory neurons. Thus, we have generated the most comprehensive map to date of how proprioceptor synapses are centrally organized. This map documents previously undescribed features of proprioceptors, raises questions about underlying developmental mechanisms, and has implications for downstream proprioceptive processing circuits.

Whole-brain annotation and multi-connectome cell typing quantifies circuit stereotypy in Drosophila

The fruit fly Drosophila melanogaster combines surprisingly sophisticated behaviour with a highly tractable nervous system. A large part of the fly's success as a model organism in modern neuroscience stems from the concentration of collaboratively generated molecular genetic and digital resources. As presented in our FlyWire companion paper 1 , this now includes the first full brain connectome of an adult animal. Here we report the systematic and hierarchical annotation of this ~130,000-neuron connectome including neuronal classes, cell types and developmental units (hemilineages). This enables any researcher to navigate this huge dataset and find systems and neurons of interest, linked to the literature through the Virtual Fly Brain database 2 . Crucially, this resource includes 4,552 cell types. 3,094 are rigorous consensus validations of cell types previously proposed in the hemibrain connectome 3 . In addition, we propose 1,458 new cell types, arising mostly from the fact that the FlyWire connectome spans the whole brain, whereas the hemibrain derives from a subvolume. Comparison of FlyWire and the hemibrain showed that cell type counts and strong connections were largely stable, but connection weights were surprisingly variable within and across animals. Further analysis defined simple heuristics for connectome interpretation: connections stronger than 10 unitary synapses or providing >1% of the input to a target cell are highly conserved. Some cell types showed increased variability across connectomes: the most common cell type in the mushroom body, required for learning and memory, is almost twice as numerous in FlyWire as the hemibrain. We find evidence for functional homeostasis through adjustments of the absolute amount of excitatory input while maintaining the excitation-inhibition ratio. Finally, and surprisingly, about one third of the cell types proposed in the hemibrain connectome could not yet be reliably identified in the FlyWire connectome. We therefore suggest that cell types should be defined to be robust to inter-individual variation, namely as groups of cells that are quantitatively more similar to cells in a different brain than to any other cell in the same brain. Joint analysis of the FlyWire and hemibrain connectomes demonstrates the viability and utility of this new definition. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open source toolchain for brain-scale comparative connectomics.

High-Speed Automated Reconstruction of Drosophila Larval Brain from Volumetric EM Data

To uncover the relationship between neural activity and behavior, it is essential to reconstruct neural circuits. However, methods typically used for neuron reconstruction from volumetric electron microscopy (EM) dataset are often time-consuming and require extensive manual proofreading, making it difficult to reproduce in a typical laboratory setting. To address this challenge, we have developed a set of acceleration techniques that build upon the Flood Filling Network (FFN), significantly reducing the time required for this task. These techniques can be easily adapted to other similar datasets and laboratory settings. To validate our approach, we tested our pipeline on a dataset of Drosophila larval brain serial section EM images at synaptic-resolution level. Our results demonstrate that our pipeline significantly reduces the inference time compared to the FFN baseline method and greatly reduces the time required for reconstructing the 3D morphology of neurons.

Bisected graph matching improves automated pairing of bilaterally homologous neurons from connectomes

Graph matching algorithms attempt to find the best correspondence between the nodes of two networks. These techniques have been used to match individual neurons in nanoscale connectomes-in particular, to find pairings of neurons across hemispheres. However, since graph matching techniques deal with two isolated networks, they have only utilized the ipsilateral (same hemisphere) subgraphs when performing the matching. Here, we present a modification to a state-of-the-art graph matching algorithm that allows it to solve what we call the bisected graph matching problem. This modification allows us to leverage the connections between the brain hemispheres when predicting neuron pairs. Via simulations and experiments on real connectome datasets, we show that this approach improves matching accuracy when sufficient edge correlation is present between the contralateral (between hemisphere) subgraphs. We also show how matching accuracy can be further improved by combining our approach with previously proposed extensions to graph matching, which utilize edge types and previously known neuron pairings. We expect that our proposed method will improve future endeavors to accurately match neurons across hemispheres in connectomes, and be useful in other applications where the bisected graph matching problem arises.

A Quantitative Analysis of Locomotor Patterns in Developing C. elegans

Adult animals display robust locomotion, yet the timeline and mechanisms of how juvenile animals acquire coordinated movements and how these movements evolve during development are not well understood. Recent advances in quantitative behavioral analyses have paved the way for investigating complex natural behaviors like locomotion. In this study, we tracked the swimming and crawling behaviors of the nematode Caenorhabditis elegans from postembryonic development through to adulthood. Our principal component analyses revealed that adult C. elegans swimming is low dimensional, suggesting that a small number of distinct postures, or eigenworms, account for most of the variance in the body shapes that constitute swimming behavior. Additionally, we found that crawling behavior in adult C. elegans is similarly low dimensional, corroborating previous studies. However, our analysis revealed that swimming and crawling are distinct gaits in adult animals, clearly distinguishable within the eigenworm space. Remarkably, young L1 larvae are capable of producing the postural shapes for swimming and crawling seen in adults, despite frequent instances of uncoordinated body movements. In contrast, late L1 larvae exhibit robust coordination of locomotion, while many neurons crucial for adult locomotion are still under development. In conclusion, this study establishes a comprehensive quantitative behavioral framework for understanding the neural basis of locomotor development, including distinct gaits such as swimming and crawling in C. elegans.

Comparative connectomics and escape behavior in larvae of closely related Drosophila species

Evolution has generated an enormous variety of morphological, physiological, and behavioral traits in animals. How do behaviors evolve in different directions in species equipped with similar neurons and molecular components? Here we adopted a comparative approach to investigate the similarities and differences of escape behaviors in response to noxious stimuli and their underlying neural circuits between closely related drosophilid species. Drosophilids show a wide range of escape behaviors in response to noxious cues, including escape crawling, stopping, head casting, and rolling. Here we find that D. santomea, compared with its close relative D. melanogaster, shows a higher probability of rolling in response to noxious stimulation. To assess whether this behavioral difference could be attributed to differences in neural circuitry, we generated focused ion beam-scanning electron microscope volumes of the ventral nerve cord of D. santomea to reconstruct the downstream partners of mdIV, a nociceptive sensory neuron in D. melanogaster. Along with partner interneurons of mdVI (including Basin-2, a multisensory integration neuron necessary for rolling) previously identified in D. melanogaster, we identified two additional partners of mdVI in D. santomea. Finally, we showed that joint activation of one of the partners (Basin-1) and a common partner (Basin-2) in D. melanogaster increased rolling probability, suggesting that the high rolling probability in D. santomea is mediated by the additional activation of Basin-1 by mdIV. These results provide a plausible mechanistic explanation for how closely related species exhibit quantitative differences in the likelihood of expressing the same behavior.

Cross-modal modulation gates nociceptive inputs in Drosophila

Animals' response to a stimulus in one sensory modality is usually influenced by other modalities.1 One important type of multisensory integration is the cross-modal modulation, in which one sensory modality modulates (typically inhibits) another. Identification of the mechanisms underlying cross-modal modulations is crucial for understanding how sensory inputs shape animals' perception and for understanding sensory processing disorders.2,3,4 However, the synaptic and circuit mechanisms that underlie cross-modal modulation are poorly understood. This is due to the difficulty of separating cross-modal modulation from multisensory integrations in neurons that receive excitatory inputs from two or more sensory modalities5-in which case it is unclear what the modulating or modulated modality is. In this study, we report a unique system for studying cross-modal modulation by taking advantage of the genetic resources in Drosophila. We show that gentle mechanical stimuli inhibit nociceptive responses in Drosophila larvae. Low-threshold mechanosensory neurons inhibit a key second-order neuron in the nociceptive pathway through metabotropic GABA receptors on nociceptor synaptic terminals. Strikingly, this cross-modal inhibition is only effective when nociceptor inputs are weak, thus serving as a gating mechanism for filtering out weak nociceptive inputs. Our findings unveil a novel cross-modal gating mechanism for sensory pathways.

Generative network modeling reveals quantitative definitions of bilateral symmetry exhibited by a whole insect brain connectome

Comparing connectomes can help explain how neural connectivity is related to genetics, disease, development, learning, and behavior. However, making statistical inferences about the significance and nature of differences between two networks is an open problem, and such analysis has not been extensively applied to nanoscale connectomes. Here, we investigate this problem via a case study on the bilateral symmetry of a larval Drosophila brain connectome. We translate notions of 'bilateral symmetry' to generative models of the network structure of the left and right hemispheres, allowing us to test and refine our understanding of symmetry. We find significant differences in connection probabilities both across the entire left and right networks and between specific cell types. By rescaling connection probabilities or removing certain edges based on weight, we also present adjusted definitions of bilateral symmetry exhibited by this connectome. This work shows how statistical inferences from networks can inform the study of connectomes, facilitating future comparisons of neural structures.

Nociception in fruit fly larvae

Nociception, the process of encoding and processing noxious or painful stimuli, allows animals to detect and avoid or escape from potentially life-threatening stimuli. Here, we provide a brief overview of recent technical developments and studies that have advanced our understanding of the Drosophila larval nociceptive circuit and demonstrated its potential as a model system to elucidate the mechanistic basis of nociception. The nervous system of a Drosophila larva contains roughly 15,000 neurons, which allows for reconstructing the connectivity among them directly by transmission electron microscopy. In addition, the availability of genetic tools for manipulating the activity of individual neurons and recent advances in computational and high-throughput behavior analysis methods have facilitated the identification of a neural circuit underlying a characteristic nocifensive behavior. We also discuss how neuromodulators may play a key role in modulating the nociceptive circuit and behavioral output. A detailed understanding of the structure and function of Drosophila larval nociceptive neural circuit could provide insights into the organization and operation of pain circuits in mammals and generate new knowledge to advance the development of treatment options for pain in humans.

The connectome of an insect brain

Brains contain networks of interconnected neurons and so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an entire insect brain (Drosophila larva) with rich behavior, including learning, value computation, and action selection, comprising 3016 neurons and 548,000 synapses. We characterized neuron types, hubs, feedforward and feedback pathways, as well as cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain's most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled state-of-the-art deep learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.

Drosophila postembryonic nervous system development: a model for the endocrine control of development

During postembryonic life, hormones, including ecdysteroids, juvenile hormones, insulin-like peptides, and activin/TGFβ ligands act to transform the larval nervous system into an adult version, which is a fine-grained mosaic of recycled larval neurons and adult-specific neurons. Hormones provide both instructional signals that make cells competent to undergo developmental change and timing cues to evoke these changes across the nervous system. While touching on all the above hormones, our emphasis is on the ecdysteroids, ecdysone and 20-hydroxyecdysone (20E). These are the prime movers of insect molting and metamorphosis and are involved in all phases of nervous system development, including neurogenesis, pruning, arbor outgrowth, and cell death. Ecdysteroids appear as a series of steroid peaks that coordinate the larval molts and the different phases of metamorphosis. Each peak directs a stereotyped cascade of transcription factor expression. The cascade components then direct temporal programs of effector gene expression, but the latter vary markedly according to tissue and life stage. The neurons read the ecdysteroid titer through various isoforms of the ecdysone receptor, a nuclear hormone receptor. For example, at metamorphosis the pruning of larval neurons is mediated through the B isoforms, which have strong activation functions, whereas subsequent outgrowth is mediated through the A isoform through which ecdysteroids play a permissive role to allow local tissue interactions to direct outgrowth. The major circulating ecdysteroid can also change through development. During adult development ecdysone promotes early adult patterning and differentiation while its metabolite, 20E, later evokes terminal adult differentiation.

Axon-axon interactions determine modality-specific wiring and subcellular synaptic specificity in a somatosensory circuit

Synaptic connections between neurons are often formed in precise subcellular regions of dendritic arbors with implications for information processing within neurons. Cell-cell interactions are widely important for circuit wiring; however, their role in subcellular specificity is not well understood. We studied the role of axon-axon interactions in precise targeting and subcellular wiring of Drosophila somatosensory circuitry. Axons of nociceptive and gentle touch neurons terminate in adjacent, non-overlapping layers in the central nervous system (CNS). Nociceptor and touch receptor axons synapse onto distinct dendritic regions of a second-order interneuron, the dendrites of which span these layers, forming touch-specific and nociceptive-specific connectivity. We found that nociceptor ablation elicited extension of touch receptor axons and presynapses into the nociceptor recipient region, supporting a role for axon-axon interactions in somatosensory wiring. Conversely, touch receptor ablation did not lead to expansion of nociceptor axons, consistent with unidirectional axon-axon interactions. Live imaging provided evidence for sequential arborization of nociceptive and touch neuron axons in the CNS. We propose that axon-axon interactions and modality-specific timing of axon targeting play key roles in subcellular connection specificity of somatosensory circuitry.

Regulated alternative splicing of Dscam2 is required for somatosensory circuit wiring

Axon and dendrite placement and connectivity is guided by a wide range of secreted and surface molecules in the developing nervous system. Nevertheless, the extraordinary complexity of connections in the brain requires that this repertoire be further diversified to precisely and uniquely regulate cell-cell interactions. One important mechanism for molecular diversification is alternative splicing. Drosophila Down syndrome cell adhesion molecule (Dscam2) undergoes cell type-specific alternative splicing to produce two isoform-specific homophilic binding proteins. Regulated alternative splicing of Dscam2 is important for dendrite and axon patterning, but how this translates to circuit wiring and animal behavior is not well understood. Here, we examined the role of cell-type specific expression of Dscam2 isoforms in regulating synaptic partner selection in the larval somatosensory system. We found that synaptic partners in the nociceptive circuit express different Dscam2 isoforms. Forcing synaptic partners to express a common isoform resulted in nociceptive axon patterning defects and attenuated nocifensive behaviors, indicating that a role for Dscam2 alternative splicing is to ensure that synaptic partners do not express matching isoforms. These results point to a model in which regulated alternative splicing of Dscam2 across populations of neurons restricts connectivity to specific partners and prevents inappropriate synaptic connections.

Electrophysiological Validation of Monosynaptic Connectivity between Premotor Interneurons and the aCC Motoneuron in the Drosophila Larval CNS

The Drosophila connectome project aims to map the synaptic connectivity of entire larval and adult fly neural networks, which is essential for understanding nervous system development and function. So far, the project has produced an impressive amount of electron microscopy data that has facilitated reconstructions of specific synapses, including many in the larval locomotor circuit. While this breakthrough represents a technical tour de force, the data remain underutilized, partly because of a lack of functional validation of reconstructions. Attempts to validate connectivity posited by the connectome project, have mostly relied on behavioral assays and/or GFP reconstitution across synaptic partners (GRASP) or GCaMP imaging. While these techniques are useful, they have limited spatial or temporal resolution. Electrophysiological assays of synaptic connectivity overcome these limitations. Here, we combine patch-clamp recordings with optogenetic stimulation in male and female larvae, to test synaptic connectivity proposed by connectome reconstructions. Specifically, we use multiple driver lines to confirm that several connections between premotor interneurons and the anterior corner cell motoneuron are, as the connectome project suggests, monosynaptic. In contrast, our results also show that conclusions based on GRASP imaging may provide false-positive results regarding connectivity between cells. We also present a novel imaging tool, based on the same technology as our electrophysiology, as a favorable alternative to GRASP imaging. Finally, of eight Gal4 lines tested, five are reliably expressed in the premotor interneurons they are targeted to. Thus, our work highlights the need to confirm functional synaptic connectivity, driver line specificity, and use of appropriate genetic tools to support connectome projects.SIGNIFICANCE STATEMENT The Drosophila connectome project aims to provide a complete description of connectivity between neurons in an organism that presents experimental advantages over other models. It has reconstructed hundreds of thousands of synaptic connections of the fly larva by manual identification of anatomic landmarks present in serial section transmission electron microscopy (ssTEM) volumes of the larval CNS. We use a highly reliable electrophysiological approach to verify these connections, providing useful insight into the accuracy of work based on ssTEM. We also present a novel imaging tool for validating excitatory monosynaptic connections between cells and show that several genetic driver lines designed to target neurons of the larval connectome exhibit nonspecific and/or unreliable expression.

nAdder: A scale-space approach for the 3D analysis of neuronal traces

Tridimensional microscopy and algorithms for automated segmentation and tracing are revolutionizing neuroscience through the generation of growing libraries of neuron reconstructions. Innovative computational methods are needed to analyze these neuronal traces. In particular, means to characterize the geometric properties of traced neurites along their trajectory have been lacking. Here, we propose a local tridimensional (3D) scale metric derived from differential geometry, measuring for each point of a curve the characteristic length where it is fully 3D as opposed to being embedded in a 2D plane or 1D line. The larger this metric is and the more complex the local 3D loops and turns of the curve are. Available through the GeNePy3D open-source Python quantitative geometry library (https://genepy3d.gitlab.io), this approach termed nAdder offers new means of describing and comparing axonal and dendritic arbors. We validate this metric on simulated and real traces. By reanalysing a published zebrafish larva whole brain dataset, we show its ability to characterize different population of commissural axons, distinguish afferent connections to a target region and differentiate portions of axons and dendrites according to their behavior, shedding new light on the stereotypical nature of neurites' local geometry.

Imaging whole-brain activity to understand behavior

The brain evolved to produce behaviors that help an animal inhabit the natural world. During natural behaviors, the brain is engaged in many levels of activity from the detection of sensory inputs to decision-making to motor planning and execution. To date, most brain studies have focused on small numbers of neurons that interact in limited circuits. This allows analyzing individual computations or steps of neural processing. During behavior, however, brain activity must integrate multiple circuits in different brain regions. The activities of different brain regions are not isolated, but may be contingent on one another. Coordinated and concurrent activity within and across brain areas is organized by (1) sensory information from the environment, (2) the animal's internal behavioral state, and (3) recurrent networks of synaptic and non-synaptic connectivity. Whole-brain recording with cellular resolution provides a new opportunity to dissect the neural basis of behavior, but whole-brain activity is also mutually contingent on behavior itself. This is especially true for natural behaviors like navigation, mating, or hunting, which require dynamic interaction between the animal, its environment, and other animals. In such behaviors, the sensory experience of an unrestrained animal is actively shaped by its movements and decisions. Many of the signaling and feedback pathways that an animal uses to guide behavior only occur in freely moving animals. Recent technological advances have enabled whole-brain recording in small behaving animals including nematodes, flies, and zebrafish. These whole-brain experiments capture neural activity with cellular resolution spanning sensory, decision-making, and motor circuits, and thereby demand new theoretical approaches that integrate brain dynamics with behavioral dynamics. Here, we review the experimental and theoretical methods that are being employed to understand animal behavior and whole-brain activity, and the opportunities for physics to contribute to this emerging field of systems neuroscience.

Transformation of an early-established motor circuit during maturation in zebrafish

Locomotion is mediated by spinal circuits that generate movements with a precise coordination and vigor. The assembly of these circuits is defined early during development; however, whether their organization and function remain invariant throughout development is unclear. Here, we show that the first established fast circuit between two dorsally located V2a interneuron types and the four primary motoneurons undergoes major transformation in adult zebrafish compared with what was reported in larvae. There is a loss of existing connections and establishment of new connections combined with alterations in the mode, plasticity, and strength of synaptic transmission. In addition, we show that this circuit no longer serves as a swim rhythm generator, but instead its components become embedded within the spinal escape circuit and control propulsion following the initial escape turn. Our results thus reveal significant changes in the organization and function of a motor circuit as animals develop toward adulthood.

Synaptic counts approximate synaptic contact area in Drosophila

The pattern of synaptic connections among neurons defines the circuit structure, which constrains the computations that a circuit can perform. The strength of synaptic connections is costly to measure yet important for accurate circuit modeling. Synaptic surface area has been shown to correlate with synaptic strength, yet in the emerging field of connectomics, most studies rely instead on the counts of synaptic contacts between two neurons. Here we quantified the relationship between synaptic count and synaptic area as measured from volume electron microscopy of the larval Drosophila central nervous system. We found that the total synaptic surface area, summed across all synaptic contacts from one presynaptic neuron to a postsynaptic one, can be accurately predicted solely from the number of synaptic contacts, for a variety of neurotransmitters. Our findings support the use of synaptic counts for approximating synaptic strength when modeling neural circuits.

Presynaptic contact and activity opposingly regulate postsynaptic dendrite outgrowth

The organization of neural circuits determines nervous system function. Variability can arise during neural circuit development (e.g. neurite morphology, axon/dendrite position). To ensure robust nervous system function, mechanisms must exist to accommodate variation in neurite positioning during circuit formation. Previously, we developed a model system in the Drosophila ventral nerve cord to conditionally induce positional variability of a proprioceptive sensory axon terminal, and used this model to show that when we altered the presynaptic position of the sensory neuron, its major postsynaptic interneuron partner modified its dendritic arbor to match the presynaptic contact, resulting in functional synaptic input (Sales et al., 2019). Here, we investigate the cellular mechanisms by which the interneuron dendrites detect and match variation in presynaptic partner location and input strength. We manipulate the presynaptic sensory neuron by (a) ablation; (b) silencing or activation; or (c) altering its location in the neuropil. From these experiments we conclude that there are two opposing mechanisms used to establish functional connectivity in the face of presynaptic variability: presynaptic contact stimulates dendrite outgrowth locally, whereas presynaptic activity inhibits postsynaptic dendrite outgrowth globally. These mechanisms are only active during an early larval critical period for structural plasticity. Collectively, our data provide new insights into dendrite development, identifying mechanisms that allow dendrites to flexibly respond to developmental variability in presynaptic location and input strength.

Characterisation of geometric variance in the epithelial nerve net of the ctenophore Pleurobrachia pileus

Neuroscience lacks a diverse repertoire of model organisms, resulting in an incomplete understanding into the general principles of neural function. Ctenophores display many neurobiological and experimental features which make them a promising candidate to fill this gap. They possess a nerve net distributed across their body surface, in the epithelial layer. There is a long-held assumption that nerve nets are 'simple' and lack distinct organisational principles. We want to challenge this assumption and determine how stereotyped the structure of this network is. We estimated body surface area in Pleurobrachia pileus using custom Optical Projection Tomography and Light Sheet Morphometry imaging systems. Using an antibody against tyrosinated α-tubulin we visualised the nerve net in situ and quantified the geometric properties using an automated segmentation approach. We characterised organisational rules of the epithelial nerve net in animals of different sizes and at different regions of the body. We found that specific morphological features within the nerve net are largely unchanged during growth. These properties must be essential to the functionality of the nervous system and therefore are maintained during a change in body size. We have also established the principles of organisation of the network and showed that some of the geometric properties are variable across different parts of the body. This suggests that there may be different functions occurring in regions with different structural characteristics. This is the most comprehensive structural description of a ctenophore nerve net to date and demonstrates the amenability of P. pileus for whole organism network analysis. This article is protected by copyright. All rights reserved.

cAMP controls a trafficking mechanism that maintains the neuron specificity and subcellular placement of electrical synapses

Electrical synapses are established between specific neurons and within distinct subcellular compartments, but the mechanisms that direct gap junction assembly in the nervous system are largely unknown. Here, we show that a developmental program tunes cAMP signaling to direct the neuron-specific assembly and placement of electrical synapses in the C. elegans motor circuit. We use live-cell imaging to visualize electrical synapses in vivo and an optogenetic assay to confirm that they are functional. In ventral A class (VA) motor neurons, the UNC-4 transcription factor blocks expression of cAMP antagonists that promote gap junction miswiring. In unc-4 mutants, VA electrical synapses are established with an alternative synaptic partner and are repositioned from the VA axon to soma. cAMP counters these effects by driving gap junction trafficking into the VA axon for electrical synapse assembly. Thus, our experiments establish that cAMP regulates gap junction trafficking for the biogenesis of functional electrical synapses.

A general principle of dendritic constancy: A neuron's size- and shape-invariant excitability

Reducing neuronal size results in less membrane and therefore lower input conductance. Smaller neurons are thus more excitable, as seen in their responses to somatic current injections. However, the impact of a neuron's size and shape on its voltage responses to dendritic synaptic activation is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs in unbranched cables, showing that these are entirely independent of dendritic length. For a given synaptic density, neuronal responses depend only on the average dendritic diameter and intrinsic conductivity. This remains valid for a wide range of morphologies irrespective of their arborization complexity. Spiking models indicate that morphology-invariant numbers of spikes approximate the percentage of active synapses. In contrast to spike rate, spike times do depend on dendrite morphology. In summary, neuronal excitability in response to distributed synaptic inputs is largely unaffected by dendrite length or complexity.

A neuropeptidergic circuit gates selective escape behavior of Drosophila larvae

Animals display selective escape behaviors when faced with environmental threats. Selection of the appropriate response by the underlying neuronal network is key to maximizing chances of survival, yet the underlying network mechanisms are so far not fully understood. Using synapse-level reconstruction of the Drosophila larval network paired with physiological and behavioral readouts, we uncovered a circuit that gates selective escape behavior for noxious light through acute and input-specific neuropeptide action. Sensory neurons required for avoidance of noxious light and escape in response to harsh touch, each converge on discrete domains of neuromodulatory hub neurons. We show that acute release of hub neuron-derived insulin-like peptide 7 (Ilp7) and cognate relaxin family receptor (Lgr4) signaling in downstream neurons are required for noxious light avoidance, but not harsh touch responses. Our work highlights a role for compartmentalized circuit organization and neuropeptide release from regulatory hubs, acting as central circuit elements gating escape responses.

On PDE Characterization of Smooth Hierarchical Functions Computed by Neural Networks

Neural networks are versatile tools for computation, having the ability to approximate a broad range of functions. An important problem in the theory of deep neural networks is expressivity; that is, we want to understand the functions that are computable by a given network. We study real, infinitely differentiable (smooth) hierarchical functions implemented by feedforward neural networks via composing simpler functions in two cases: (1) each constituent function of the composition has fewer inputs than the resulting function and (2) constituent functions are in the more specific yet prevalent form of a nonlinear univariate function (e.g., tanh) applied to a linear multivariate function. We establish that in each of these regimes, there exist nontrivial algebraic partial differential equations (PDEs) that are satisfied by the computed functions. These PDEs are purely in terms of the partial derivatives and are dependent only on the topology of the network. Conversely, we conjecture that such PDE constraints, once accompanied by appropriate nonsingularity conditions and perhaps certain inequalities involving partial derivatives, guarantee that the smooth function under consideration can be represented by the network. The conjecture is verified in numerous examples, including the case of tree architectures, which are of neuroscientific interest. Our approach is a step toward formulating an algebraic description of functional spaces associated with specific neural networks, and may provide useful new tools for constructing neural networks.

Connectomes across development reveal principles of brain maturation

An animal's nervous system changes as its body grows from birth to adulthood and its behaviours mature^1-8. The form and extent of circuit remodelling across the connectome is unknown^3,9-15. Here we used serial-section electron microscopy to reconstruct the full brain of eight isogenic Caenorhabditis elegans individuals across postnatal stages to investigate how it changes with age. The overall geometry of the brain is preserved from birth to adulthood, but substantial changes in chemical synaptic connectivity emerge on this consistent scaffold. Comparing connectomes between individuals reveals substantial differences in connectivity that make each brain partly unique. Comparing connectomes across maturation reveals consistent wiring changes between different neurons. These changes alter the strength of existing connections and create new connections. Collective changes in the network alter information processing. During development, the central decision-making circuitry is maintained, whereas sensory and motor pathways substantially remodel. With age, the brain becomes progressively more feedforward and discernibly modular. Thus developmental connectomics reveals principles that underlie brain maturation.

Aversive teaching signals from individual dopamine neurons in larval Drosophila show qualitative differences in their temporal "fingerprint"

Dopamine serves many functions, and dopamine neurons are correspondingly diverse. We use a combination of optogenetics, behavioral experiments, and high-resolution video-tracking to probe for the functional capacities of two single, identified dopamine neurons in larval Drosophila. The DAN-f1 and the DAN-d1 neuron were recently found to carry aversive teaching signals during Pavlovian olfactory learning. We enquire into a fundamental feature of these teaching signals, namely their temporal "fingerprint". That is, receiving punishment feels bad, whereas being relieved from it feels good, and animals and humans alike learn with opposite valence about the occurrence and the termination of punishment (the same principle applies in the appetitive domain, with opposite sign). We find that DAN-f1 but not DAN-d1 can mediate such timing-dependent valence reversal: presenting an odor before DAN-f1 activation leads to learned avoidance of the odor (punishment memory), whereas presenting the odor upon termination of DAN-f1 activation leads to learned approach (relief memory). In contrast, DAN-d1 confers punishment memory only. These effects are further characterized in terms of the impact of the duration of optogenetic activation, the temporal stability of the memories thus established, and the specific microbehavioral patterns of locomotion through which they are expressed. Together with recent findings in the appetitive domain and from adult Drosophila, our results suggest that heterogeneity in the temporal fingerprint of teaching signals might be a more general principle of reinforcement processing through dopamine neurons.

Neurodevelopment: Comparative connectomics and the study of circuit assembly

A new study reveals the effects of specific single cell type perturbations on the assembly and function of a mechanosensory circuit in the Drosophila melanogaster larva with synaptic resolution. This work paves the way for the use of comparative connectomics to understand general principles governing the development of wiring specificity.

A quick and versatile protocol for the 3D visualization of transgene expression across the whole body of larval Drosophila

Larval Drosophila are used as a genetically accessible study case in many areas of biological research. Here we report a fast, robust and user-friendly procedure for the whole-body multi-fluorescence imaging of Drosophila larvae; the protocol has been optimized specifically for larvae by systematically tackling the pitfalls associated with clearing this small but cuticularized organism. Tests on various fluorescent proteins reveal that the recently introduced monomeric infrared fluorescent protein (mIFP) is particularly suitable for our approach. This approach comprises an effective, low-cost clearing protocol with minimal handling time and reduced toxicity in the reagents employed. It combines a success rate high enough to allow for small-scale screening approaches and a resolution sufficient for cellular-level analyses with light sheet and confocal microscopy. Given that publications and database documentations typically specify expression patterns of transgenic driver lines only within a given organ system of interest, the present procedure should be versatile enough to extend such documentation systematically to the whole body. As examples, the expression patterns of transgenic driver lines covering the majority of neurons, or subsets of chemosensory, central brain or motor neurons, are documented in the context of whole larval body volumes (using nsyb-Gal4, IR76b-Gal4, APL-Gal4 and mushroom body Kenyon cells, or OK371-Gal4, respectively). Notably, the presented protocol allows for triple-color fluorescence imaging with near-infrared, red and yellow fluorescent proteins.

Establishment and Maintenance of Neural Circuit Architecture

The ability to sense the world, process information, and navigate the environment depends on the assembly and continuous function of neural circuits in the brain. Within the past two decades, new technologies have rapidly advanced our understanding of how neural circuits are wired during development and how they are stably maintained, often for years. Electron microscopy reconstructions of model organism connectomes have provided a map of the stereotyped (and variable) connections in the brain; advanced light microscopy techniques have enabled direct observation of the cellular dynamics that underlie circuit construction and maintenance; transcriptomic and proteomic surveys of both developing and mature neurons have provided insights into the molecular and genetic programs governing circuit establishment and maintenance; and advanced genetic techniques have allowed for high-throughput discovery of wiring regulators. These tools have empowered scientists to rapidly generate and test hypotheses about how circuits establish and maintain connectivity. Thus, the set of principles governing circuit formation and maintenance have been expanded. These principles are discussed in this review.

Useful road maps: studying Drosophila larva's central nervous system with the help of connectomics

The larva of Drosophila melanogaster is emerging as a powerful model system for comprehensive brain-wide understanding of the circuit implementation of neural computations. With an unprecedented amount of tools in hand, including synaptic-resolution connectomics, whole-brain imaging, and genetic tools for selective targeting of single neuron types, it is possible to dissect which circuits and computations are at work behind behaviors that have an interesting level of complexity. Here we present some of the recent advances regarding multisensory integration, learning, and action selection in Drosophila larva.

Achieving functional neuronal dendrite structure through sequential stochastic growth and retraction

Class I ventral posterior dendritic arborisation (c1vpda) proprioceptive sensory neurons respond to contractions in the Drosophila larval body wall during crawling. Their dendritic branches run along the direction of contraction, possibly a functional requirement to maximise membrane curvature during crawling contractions. Although the molecular machinery of dendritic patterning in c1vpda has been extensively studied, the process leading to the precise elaboration of their comb-like shapes remains elusive. Here, to link dendrite shape with its proprioceptive role, we performed long-term, non-invasive, in vivo time-lapse imaging of c1vpda embryonic and larval morphogenesis to reveal a sequence of differentiation stages. We combined computer models and dendritic branch dynamics tracking to propose that distinct sequential phases of stochastic growth and retraction achieve efficient dendritic trees both in terms of wire and function. Our study shows how dendrite growth balances structure-function requirements, shedding new light on general principles of self-organisation in functionally specialised dendrites.

Comparative Connectomics Reveals How Partner Identity, Location, and Activity Specify Synaptic Connectivity in Drosophila

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

A Neural Basis for Categorizing Sensory Stimuli to Enhance Decision Accuracy

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

Flexible neural connectivity under constraints on total connection strength

Neural computation is determined by neurons’ dynamics and circuit connectivity. Uncertain and dynamic environments may require neural hardware to adapt to different computational tasks, each requiring different connectivity configurations. At the same time, connectivity is subject to a variety of constraints, placing limits on the possible computations a given neural circuit can perform. Here we examine the hypothesis that the organization of neural circuitry favors computational flexibility: that it makes many computational solutions available, given physiological constraints. From this hypothesis, we develop models of connectivity degree distributions based on constraints on a neuron’s total synaptic weight. To test these models, we examine reconstructions of the mushroom bodies from the first instar larva and adult Drosophila melanogaster. We perform a Bayesian model comparison for two constraint models and a random wiring null model. Overall, we find that flexibility under a homeostatically fixed total synaptic weight describes Kenyon cell connectivity better than other models, suggesting a principle shaping the apparently random structure of Kenyon cell wiring. Furthermore, we find evidence that larval Kenyon cells are more flexible earlier in development, suggesting a mechanism whereby neural circuits begin as flexible systems that develop into specialized computational circuits.

High-throughput electron microscopic anatomical experiments have begun to yield detailed maps of neural circuit connectivity. Uncovering the principles that govern these circuit structures is a major challenge for systems neuroscience. Healthy neural circuits must be able to perform computational tasks while satisfying physiological constraints. Those constraints can restrict a neuron’s possible connectivity, and thus potentially restrict its computation. Here we examine simple models of constraints on total synaptic weights, and calculate the number of circuit configurations they allow: a simple measure of their computational flexibility. We propose probabilistic models of connectivity that weight the number of synaptic partners according to computational flexibility under a constraint and test them using recent wiring diagrams from a learning center, the mushroom body, in the fly brain. We compare constraints that fix or bound a neuron’s total connection strength to a simple random wiring null model. Of these models, the fixed total connection strength matched the overall connectivity best in mushroom bodies from both larval and adult flies. We also provide evidence suggesting that neural circuits are more flexible in early stages of development and lose this flexibility as they grow towards specialized function.

The Corazonin-PTTH Neuronal Axis Controls Systemic Body Growth by Regulating Basal Ecdysteroid Biosynthesis in Drosophila melanogaster

Steroid hormones play key roles in development, growth, and reproduction in various animal phyla [1]. The insect steroid hormone, ecdysteroid, coordinates growth and maturation, represented by molting and metamorphosis [2]. In Drosophila melanogaster, the prothoracicotropic hormone (PTTH)-producing neurons stimulate peak levels of ecdysteroid biosynthesis for maturation [3]. Additionally, recent studies on PTTH signaling indicated that basal levels of ecdysteroid negatively affect systemic growth prior to maturation [4-8]. However, it remains unclear how PTTH signaling is regulated for basal ecdysteroid biosynthesis. Here, we report that Corazonin (Crz)-producing neurons regulate basal ecdysteroid biosynthesis by affecting PTTH neurons. Crz belongs to gonadotropin-releasing hormone (GnRH) superfamily, implying an analogous role in growth and maturation [9]. Inhibition of Crz neuronal activity increased pupal size, whereas it hardly affected pupariation timing. This phenotype resulted from enhanced growth rate and a delay in ecdysteroid elevation during the mid-third instar larval (L3) stage. Interestingly, Crz receptor (CrzR) expression in PTTH neurons was higher during the mid- than the late-L3 stage. Silencing of CrzR in PTTH neurons increased pupal size, phenocopying the inhibition of Crz neuronal activity. When Crz neurons were optogenetically activated, a strong calcium response was observed in PTTH neurons during the mid-L3, but not the late-L3, stage. Furthermore, we found that octopamine neurons contact Crz neurons in the subesophageal zone (SEZ), transmitting signals for systemic growth. Together, our results suggest that the Crz-PTTH neuronal axis modulates ecdysteroid biosynthesis in response to octopamine, uncovering a regulatory neuroendocrine system in the developmental transition from growth to maturation.

Identifying neural substrates of competitive interactions and sequence transitions during mechanosensory responses in Drosophila

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

The astrocyte network in the ventral nerve cord neuropil of the Drosophila third-instar larva

Understanding neuronal function at the local and circuit level requires understanding astrocyte function. We have provided a detailed analysis of astrocyte morphology and territory in the Drosophila third-instar ventral nerve cord where there already exists considerable understanding of the neuronal network. Astrocyte shape varies more than previously reported; many have bilaterally symmetrical partners, many have a high percentage of their arborization in adjacent segments, and many have branches that follow structural features. Taken together, our data are consistent with, but not fully explained by, a model of a developmental growth process dominated by competitive or repulsive interactions between astrocytes. Our data suggest that the model should also include cell-autonomous aspects, as well as the use of structural features for growth. Variation in location of arborization territory for identified astrocytes was great enough that a standardized scheme of neuropil division among the six astrocytes that populate each hemi-segment is not possible at the third instar. The arborizations of the astrocytes can extend across neuronal functional domains. The ventral astrocyte in particular, whose territory can extend well into the proprioceptive region of the neuropil, has no obvious branching pattern that correlates with domains of particular sensory modalities, suggesting that the astrocyte would respond to neuronal activity in any of the sensory modalities, perhaps integrating across them. This study sets the stage for future studies that will generate a robust, functionally oriented connectome that includes both partners in neuronal circuits-the neurons and the glial cells, providing the foundation necessary for studies to elucidate neuron-glia interactions in this neuropil.

Maintenance of cell type-specific connectivity and circuit function requires Tao kinase

Sensory circuits are typically established during early development, yet how circuit specificity and function are maintained during organismal growth has not been elucidated. To gain insight we quantitatively investigated synaptic growth and connectivity in the Drosophila nociceptive network during larval development. We show that connectivity between primary nociceptors and their downstream neurons scales with animal size. We further identified the conserved Ste20-like kinase Tao as a negative regulator of synaptic growth required for maintenance of circuit specificity and connectivity. Loss of Tao kinase resulted in exuberant postsynaptic specializations and aberrant connectivity during larval growth. Using functional imaging and behavioral analysis we show that loss of Tao-induced ectopic synapses with inappropriate partner neurons are functional and alter behavioral responses in a connection-specific manner. Our data show that fine-tuning of synaptic growth by Tao kinase is required for maintaining specificity and behavioral output of the neuronal network during animal growth.

Neurogenetic dissection of the Drosophila lateral horn reveals major outputs, diverse behavioural functions, and interactions with the mushroom body

Animals exhibit innate behaviours to a variety of sensory stimuli including olfactory cues. In Drosophila, one higher olfactory centre, the lateral horn (LH), is implicated in innate behaviour. However, our structural and functional understanding of the LH is scant, in large part due to a lack of sparse neurogenetic tools for this region. We generate a collection of split-GAL4 driver lines providing genetic access to 82 LH cell types. We use these to create an anatomical and neurotransmitter map of the LH and link this to EM connectomics data. We find ~30% of LH projections converge with outputs from the mushroom body, site of olfactory learning and memory. Using optogenetic activation, we identify LH cell types that drive changes in valence behavior or specific locomotor programs. In summary, we have generated a resource for manipulating and mapping LH neurons, providing new insights into the circuit basis of innate and learned olfactory behavior.

Regulation of subcellular dendritic synapse specificity by axon guidance cues

Neural circuit assembly occurs with subcellular precision, yet the mechanisms underlying this precision remain largely unknown. Subcellular synaptic specificity could be achieved by molecularly distinct subcellular domains that locally regulate synapse formation, or by axon guidance cues restricting access to one of several acceptable targets. We address these models using two Drosophila neurons: the dbd sensory neuron and the A08a interneuron. In wild-type larvae, dbd synapses with the A08a medial dendrite but not the A08a lateral dendrite. dbd-specific overexpression of the guidance receptors Unc-5 or Robo-2 results in lateralization of the dbd axon, which forms anatomical and functional monosynaptic connections with the A08a lateral dendrite. We conclude that axon guidance cues, not molecularly distinct dendritic arbors, are a major determinant of dbd-A08a subcellular synapse specificity.

The Hunchback temporal transcription factor determines motor neuron axon and dendrite targeting in Drosophila

The generation of neuronal diversity is essential for circuit formation and behavior. Morphological differences in sequentially born neurons could be due to intrinsic molecular identity specified by temporal transcription factors (henceforth called intrinsic temporal identity) or due to changing extrinsic cues. Here, we have used the Drosophila NB7-1 lineage to address this issue. NB7-1 generates the U1-U5 motor neurons sequentially; each has a distinct intrinsic temporal identity due to inheritance of different temporal transcription factors at its time of birth. We show that the U1-U5 neurons project axons sequentially, followed by sequential dendrite extension. We misexpressed the earliest temporal transcription factor, Hunchback, to create 'ectopic' U1 neurons with an early intrinsic temporal identity but later birth-order. These ectopic U1 neurons have axon muscle targeting and dendrite neuropil targeting that are consistent with U1 intrinsic temporal identity, rather than with their time of birth or differentiation. We conclude that intrinsic temporal identity plays a major role in establishing both motor axon muscle targeting and dendritic arbor targeting, which are required for proper motor circuit development.

Neuronal cell types in the fly: single-cell anatomy meets single-cell genomics

At around 150 000 neurons, the adult Drosophila melanogaster central nervous system is one of the largest species, for which a complete cellular catalogue is imminent. While numerically much simpler than mammalian brains, its complexity is still difficult to parse without grouping neurons into consistent types, which can number 1-1000 cells per hemisphere. We review how neuroanatomical and gene expression data are being used to discover neuronal types at scale. The correlation among multiple co-varying neuronal properties, including lineage, gene expression, morphology, connectivity, response properties and shared behavioral significance is essential to the definition of neuronal cell type. Initial studies comparing morphological and transcriptomic definitions of neuronal type suggest that these are highly consistent, but there is much to do to match these approaches brain-wide. Matched single-cell transcriptomic and morphological data provide an effective reference point to integrate other data types, including connectomics data. This will significantly enhance our ability to make functional predictions from brain wiring diagrams as well facilitating molecular genetic manipulation of neuronal types.

Convergence of monosynaptic and polysynaptic sensory paths onto common motor outputs in a Drosophila feeding connectome

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

WB. Verifying, Challenging, and Discovering New Synapses Among Fully EM-Reconstructed Neurons in the Leech Ganglion

Neural circuits underpin the production of animal behavior, largely based upon the precise pattern of synaptic connectivity among the neurons involved. For large numbers of neurons, determining such "connectomes" by direct physiological means is difficult, as physiological accessibility is ultimately required to verify and characterize the function of synapses. We collected a volume of images spanning an entire ganglion of the juvenile leech nervous system via serial blockface electron microscopy (SBEM). We validated this approach by reconstructing a well-characterized circuit of motor neurons involved in the swimming behavior of the leech by locating the synapses among them. We confirm that there are multiple synaptic contacts between connected pairs of neurons in the leech, and that these synapses are widely distributed across the region of neuropil in which the neurons' arbors overlap. We verified the anatomical existence of connections that had been described physiologically among longitudinal muscle motor neurons. We also found that some physiological connections were not present anatomically. We then drew upon the SBEM dataset to design additional physiological experiments. We reconstructed an uncharacterized neuron and one of its presynaptic partners identified from the SBEM dataset. We subsequently interrogated this cell pair via intracellular electrophysiology in an adult ganglion and found that the anatomically-discovered synapse was also functional physiologically. Our findings demonstrate the value of combining a connectomics approach with electrophysiology in the leech nervous system.