INTRODUCTION A brainwide, synaptic-resolution connectivity map—a connectome—is essential for understanding how the brain generates behavior. However because of technological constraints imaging entire brains with electron microscopy (EM) and reconstructing circuits from such datasets has been challenging. To date, complete connectomes have been mapped for only three organisms, each with several hundred brain neurons: the nematode C. elegans , the larva of the sea squirt Ciona intestinalis , and of the marine annelid Platynereis dumerilii . Synapse-resolution circuit diagrams of larger brains, such as insects, fish, and mammals, have been approached by considering select subregions in isolation. However, neural computations span spatially dispersed but interconnected brain regions, and understanding any one computation requires the complete brain connectome with all its inputs and outputs. RATIONALE We therefore generated a connectome of an entire brain of a small insect, the larva of the fruit fly, Drosophila melanogaster. This animal displays a rich behavioral repertoire, including learning, value computation, and action selection, and shares homologous brain structures with adult Drosophila and larger insects. Powerful genetic tools are available for selective manipulation or recording of individual neuron types. In this tractable model system, hypotheses about the functional roles of specific neurons and circuit motifs revealed by the connectome can therefore be readily tested. RESULTS The complete synaptic-resolution connectome of the Drosophila larval brain comprises 3016 neurons and 548,000 synapses. We performed a detailed analysis of the brain circuit architecture, including connection and neuron types, network hubs, and circuit motifs. Most of the brain’s in-out hubs (73%) were postsynaptic to the learning center or presynaptic to the dopaminergic neurons that drive learning. We used graph spectral embedding to hierarchically cluster neurons based on synaptic connectivity into 93 neuron types, which were internally consistent based on other features, such as morphology and function. We developed an algorithm to track brainwide signal propagation across polysynaptic pathways and analyzed feedforward (from sensory to output) and feedback pathways, multisensory integration, and cross-hemisphere interactions. We found extensive multisensory integration throughout the brain and multiple interconnected pathways of varying depths from sensory neurons to output neurons forming a distributed processing network. The brain had a highly recurrent architecture, with 41% of neurons receiving long-range recurrent input. However, recurrence was not evenly distributed and was especially high in areas implicated in learning and action selection. Dopaminergic neurons that drive learning are amongst the most recurrent neurons in the brain. Many contralateral neurons, which projected across brain hemispheres, were in-out hubs and synapsed onto each other, facilitating extensive interhemispheric communication. We also analyzed interactions between the brain and nerve cord. We found that descending neurons targeted a small fraction of premotor elements that could play important roles in switching between locomotor states. A subset of descending neurons targeted low-order post-sensory interneurons likely modulating sensory processing. CONCLUSION The complete brain connectome of the Drosophila larva will be a lasting reference study, providing a basis for a multitude of theoretical and experimental studies of brain function. The approach and computational tools generated in this study will facilitate the analysis of future connectomes. Although the details of brain organization differ across the animal kingdom, many circuit architectures are conserved. As more brain connectomes of other organisms are mapped in the future, comparisons between them will reveal both common and therefore potentially optimal circuit architectures, as well as the idiosyncratic ones that underlie behavioral differences between organisms. Some of the architectural features observed in the Drosophila larval brain, including multilayer shortcuts and prominent nested recurrent loops, are found in state-of-the-art artificial neural networks, where they can compensate for a lack of network depth and support arbitrary, task-dependent computations. Such features could therefore increase the brain’s computational capacity, overcoming physiological constraints on the number of neurons. Future analysis of similarities and differences between brains and artificial neural networks may help in understanding brain computational principles and perhaps inspire new machine learning architectures. The connectome of the Drosophila larval brain. The morphologies of all brain neurons, reconstructed from a synapse-resolution EM volume, and the synaptic connectivity matrix of an entire brain. This connectivity information was used to hierarchically cluster all brains into 93 cell types, which were internally consistent based on morphology and known function.
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A multilayer circuit architecture for the generation of distinct locomotor behaviors in Drosophila
Animals generate diverse motor behaviors, yet how the same motor neurons (MNs) generate two distinct or antagonistic behaviors remains an open question. Here, we characterize Drosophila larval muscle activity patterns and premotor/motor circuits to understand how they generate forward and backward locomotion. We show that all body wall MNs are activated during both behaviors, but a subset of MNs change recruitment timing for each behavior. We used TEM to reconstruct a full segment of all 60 MNs and 236 premotor neurons (PMNs), including differentially-recruited MNs. Analysis of this comprehensive connectome identified PMN-MN ‘labeled line’ connectivity; PMN-MN combinatorial connectivity; asymmetric neuronal morphology; and PMN-MN circuit motifs that could all contribute to generating distinct behaviors. We generated a recurrent network model that reproduced the observed behaviors, and used functional optogenetics to validate selected model predictions. This PMN-MN connectome will provide a foundation for analyzing the full suite of larval behaviors.
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- Award ID(s):
- 1707398
- NSF-PAR ID:
- 10174294
- Date Published:
- Journal Name:
- eLife
- Volume:
- 8
- ISSN:
- 2050-084X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Spinal motor neurons (MNs) integrate sensory stimuli and brain commands to generate movements. In vertebrates, the molecular identities of the cardinal MN types such as those innervating limb versus trunk muscles are well elucidated. Yet the identities of finer subtypes within these cell populations that innervate individual muscle groups remain enigmatic. Here we investigate heterogeneity in mouse MNs using single-cell transcriptomics. Among limb-innervating MNs, we reveal a diverse neuropeptide code for delineating putative motor pool identities. Additionally, we uncover that axial MNs are subdivided into three molecularly distinct subtypes, defined by mediolaterally-biased Satb2, Nr2f2 or Bcl11b expression patterns with different axon guidance signatures. These three subtypes are present in chicken and human embryos, suggesting a conserved axial MN expression pattern across higher vertebrates. Overall, our study provides a molecular resource of spinal MN types and paves the way towards deciphering how neuronal subtypes evolved to accommodate vertebrate motor behaviors.
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ABSTRACT In complex nervous systems, neurons must identify their correct partners to form synaptic connections. The prevailing model to ensure correct recognition posits that cell-surface proteins (CSPs) in individual neurons act as identification tags. Thus, knowing what cells express which CSPs would provide insights into neural development, synaptic connectivity, and nervous system evolution. Here, we investigated expression of Dpr and DIP genes, two CSP subfamilies belonging to the immunoglobulin superfamily, in Drosophila larval motor neurons (MNs), muscles, glia and sensory neurons (SNs) using a collection of GAL4 driver lines. We found that Dpr genes are more broadly expressed than DIP genes in MNs and SNs, and each examined neuron expresses a unique combination of Dpr and DIP genes. Interestingly, many Dpr and DIP genes are not robustly expressed, but are found instead in gradient and temporal expression patterns. In addition, the unique expression patterns of Dpr and DIP genes revealed three uncharacterized MNs. This study sets the stage for exploring the functions of Dpr and DIP genes in Drosophila MNs and SNs and provides genetic access to subsets of neurons.more » « less
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Navigation requires steering and propulsion, but how spinal circuits contribute to direction control during ongoing locomotion is not well understood. Here, we use drifting vertical gratings to evoke directed “fictive” swimming in intact but immobilized larval zebrafish while performing electrophysiological recordings from spinal neurons. We find that directed swimming involves unilateral changes in the duration of motor output and increased recruitment of motor neurons, without impacting the timing of spiking across or along the body. Voltage-clamp recordings from motor neurons reveal increases in phasic excitation and inhibition on the side of the turn. Current-clamp recordings from premotor interneurons that provide phasic excitation or inhibition reveal two types of recruitment patterns. A direction-agnostic pattern with balanced recruitment on the turning and nonturning sides is primarily observed in excitatory V2a neurons with ipsilateral descending axons, while a direction-sensitive pattern with preferential recruitment on the turning side is dominated by V2a neurons with ipsilateral bifurcating axons. Inhibitory V1 neurons are also divided into direction-sensitive and direction-agnostic subsets, although there is no detectable morphologic distinction. Our findings support the modular control of steering and propulsion by spinal premotor circuits, where recruitment of distinct subsets of excitatory and inhibitory interneurons provide adjustments in direction while on the move.
SIGNIFICANCE STATEMENT Spinal circuits play an essential role in coordinating movements during locomotion. However, it is unclear how they participate in adjustments in direction that do not interfere with coordination. Here we have developed a system using larval zebrafish that allows us to directly record electrical signals from spinal neurons during “fictive” swimming guided by visual cues. We find there are subsets of spinal interneurons for coordination and others that drive unilateral asymmetries in motor neuron recruitment for direction control. Our findings suggest a modular organization of spinal premotor circuits that enables uninterrupted adjustments in direction during ongoing locomotion. -
null (Ed.)The American lobster, Homarus americanus, cardiac neuromuscular system is controlled by the cardiac ganglion (CG), a central pattern generator consisting of four premotor and five motor neurons. Here, we show that the premotor and motor neurons can establish independent bursting patterns when decoupled by a physical ligature. We also show that mRNA encoding myosuppressin, a cardioactive neuropeptide, is produced within the CG. We thus asked whether myosuppressin modulates the decoupled premotor and motor neurons, and if so, how this modulation might underlie the role(s) that these neurons play in myosuppressin’s effects on ganglionic output. Although myosuppressin exerted dose-dependent effects on burst frequency and duration in both premotor and motor neurons in the intact CG, its effects on the ligatured ganglion were more complex, with different effects and thresholds on the two types of neurons. These data suggest that the motor neurons are more important in determining the changes in frequency of the CG elicited by low concentrations of myosuppressin, whereas the premotor neurons have a greater impact on changes elicited in burst duration. A single putative myosuppressin receptor (MSR-I) was previously described from the Homarus nervous system. We identified four additional putative MSRs (MSR-II–V) and investigated their individual distributions in the CG premotor and motor neurons using RT-PCR. Transcripts for only three receptors (MSR-II–IV) were amplified from the CG. Potential differential distributions of the receptors were observed between the premotor and motor neurons; these differences may contribute to the distinct physiological responses of the two neuron types to myosuppressin. NEW & NOTEWORTHY Premotor and motor neurons of the Homarus americanus cardiac ganglion (CG) are normally electrically and chemically coupled, and generate rhythmic bursting that drives cardiac contractions; we show that they can establish independent bursting patterns when physically decoupled by a ligature. The neuropeptide myosuppressin modulates different aspects of the bursting pattern in these neuron types to determine the overall modulation of the intact CG. Differential distribution of myosuppressin receptors may underlie the observed responses to myosuppressin.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7554/eLife.51781
