Reviewer #1 (Public Review): A Connectome of the Male Drosophila Ventral Nerve Cord
Shin-ya TakemuraKenneth J. HayworthGary B. HuangMichał JanuszewskiZhiyuan LuElizabeth C. MarinStephan PreibischC. Shan XuJohn BogovicAndrew ChampionHan SJ CheongMarta CostaKatharina EichlerWilliam KatzChristopher KnechtFeng LiBilly J MorrisChristopher OrdishPatricia K. RivlinPhilipp SchlegelKazunori ShinomiyaTomke StürnerTing ZhaoGriffin BadalamenteDennis BaileyPaul BrooksBrandon S CaninoJody ClementsMichael CookOctave DuclosChristopher R DunneKelli FairbanksSiqi FangSamantha Finley-MayAudrey FrancisReed GeorgeMarina GkantiaKyle HarringtonGary Patrick HopkinsJoseph HsuPhilip M. HubbardAlexandre JavierDagmar KainmuellerWyatt KorffJulie KovalyakDominik KrzemińskiShirley A LauchieAlanna LohffCharli MaldonadoEmily A ManleyCaroline MooneyErika NeaceMatthew NicholsOmotara OgundeyiNneoma OkeomaTyler PatersonElliott PhillipsEmily M PhillipsCaitlin RibeiroSean M RyanJon Thomson RymerAnne K ScottAshley L ScottDavid ShepherdAya ShinomiyaClaire SmithNatalie SmithAlia SuleimanSatoko TakemuraIris TalebiImaan FM TamimiEric T. TrautmanLowell UmayamJohn J WalshTansy YangGerald M. RubinLouis K. SchefferJan FunkeStephan SaalfeldHarald F. HessStephen M. PlazaGwyneth M CardGregory S.X.E. JefferisStuart Berg
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Animal behavior is principally expressed through neural control of muscles. Therefore understanding how the brain controls behavior requires mapping neuronal circuits all the way to motor neurons. We have previously established technology to collect large-volume electron microscopy data sets of neural tissue and fully reconstruct the morphology of the neurons and their chemical synaptic connections throughout the volume. Using these tools we generated a dense wiring diagram, or connectome, for a large portion of the Drosophila central brain. However, in most animals, including the fly, the majority of motor neurons are located outside the brain in a neural center closer to the body, i.e. the mammalian spinal cord or insect ventral nerve cord (VNC). In this paper, we extend our effort to map full neural circuits for behavior by generating a connectome of the VNC of a male fly.Keywords:
Ventral nerve cord
The connectome provides the structural substrate facilitating communication between brain regions. We aimed to establish whether accounting for polysynaptic communication in structural connectomes would improve prediction of interindividual variation in behavior as well as increase structure-function coupling strength. Connectomes were mapped for 889 healthy adults participating in the Human Connectome Project. To account for polysynaptic signaling, connectomes were transformed into communication matrices for each of 15 different network communication models. Communication matrices were (a) used to perform predictions of five data-driven behavioral dimensions and (b) correlated to resting-state functional connectivity (FC). While FC was the most accurate predictor of behavior, communication models, in particular communicability and navigation, improved the performance of structural connectomes. Communication also strengthened structure-function coupling, with the navigation and shortest paths models leading to 35–65% increases in association strength with FC. We combined behavioral and functional results into a single ranking that provides insight into which communication models may more faithfully recapitulate underlying neural signaling patterns. Comparing results across multiple connectome mapping pipelines suggested that modeling polysynaptic communication is particularly beneficial in sparse high-resolution connectomes. We conclude that network communication models can augment the functional and behavioral predictive utility of the human structural connectome.
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The connectome provides a structural substrate facilitating communication between brain regions. We aimed to establish whether accounting for polysynaptic communication paths in structural connectomes would improve prediction of interindividual variation in behavior as well as increase structure-function coupling strength. Structural connectomes were mapped for 889 healthy adults participating in the Human Connectome Project. To account for polysynaptic signaling, connectomes were transformed into communication matrices for each of 15 different network communication models. Communication matrices were (i) used to perform predictions of five data-driven behavioral dimensions and (ii) correlated to interregional resting-state functional connectivity (FC). While FC was the most accurate predictor of behavior, network communication models, in particular communicability and navigation, improved the performance of structural connectomes. Accounting for polysynaptic communication also significantly strengthened structure-function coupling, with the navigation and shortest paths models leading to 35-65% increases in association strength with FC. Combining behavioral and functional results into a single ranking of communication models positioned navigation as the top model, suggesting that it may more faithfully recapitulate underlying neural signaling patterns. We conclude that network communication models augment the functional and behavioral predictive utility of the human structural connectome and contribute to narrowing the gap between brain structure and function.
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C. elegans locomotes in an undulatory fashion, generating thrust by propagating dorsoventral bends along its body. Although central pattern generators (CPGs) are typically involved in animal locomotion, their presence in C. elegans has been questioned, mainly because there has been no evident circuit that supports intrinsic network oscillations. With a fully reconstructed connectome, the question of whether it is possible to have a CPG in the ventral nerve cord (VNC) of C. elegans can be answered through computational models. We modeled a repeating neural unit based on segmentation analysis of the connectome. We then used an evolutionary algorithm to determine the unknown physiological parameters of each neuron so as to match the features of the neural traces of the worm during forward and backward locomotion. We performed 1,000 evolutionary runs and consistently found configurations of the neural circuit that produced oscillations matching the main characteristic observed in experimental recordings. In addition to providing an existence proof for the possibility of a CPG in the VNC, we suggest a series of testable hypotheses about its operation. More generally, we show the feasibility and fruitfulness of a methodology to study behavior based on a connectome, in the absence of complete neurophysiological details.
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Abstract Animal behavior is principally expressed through neural control of muscles. Therefore understanding how the brain controls behavior requires mapping neuronal circuits all the way to motor neurons. We have previously established technology to collect large-volume electron microscopy data sets of neural tissue and fully reconstruct the morphology of the neurons and their chemical synaptic connections throughout the volume. Using these tools we generated a dense wiring diagram, or connectome, for a large portion of the Drosophila central brain. However, in most animals, including the fly, the majority of motor neurons are located outside the brain in a neural center closer to the body, i.e. the mammalian spinal cord or insect ventral nerve cord (VNC). In this paper, we extend our effort to map full neural circuits for behavior by generating a connectome of the VNC of a male fly.
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Kinorhynchs are ecdysozoan animals with a phylogenetic position close to priapulids and loriciferans. To understand the nature of segmentation within Kinorhyncha and to infer a probable ancestry of segmentation within the last common ancestor of Ecdysozoa, the musculature and the nervous system of the allomalorhagid kinorhynch Pycnophyes kielensis were investigated by use of immunohistochemistry, confocal laser scanning microscopy, and 3D reconstruction software. The kinorhynch body plan comprises 11 trunk segments. Trunk musculature consists of paired ventral and dorsal longitudinal muscles in segments 1–10 as well as dorsoventral muscles in segments 1–11. Dorsal and ventral longitudinal muscles insert on apodemes of the cuticle inside the animal within each segment. Strands of longitudinal musculature extend over segment borders in segments 1–6. In segments 7–10, the trunk musculature is confined to the segments. Musculature of the digestive system comprises a strong pharyngeal bulb with attached mouth cone muscles as well as pharyngeal bulb protractors and retractors. The musculature of the digestive system shows no sign of segmentation. Judged by the size of the pharyngeal bulb protractors and retractors, the pharyngeal bulb, as well as the introvert, is moved passively by internal pressure caused by concerted action of the dorsoventral muscles. The nervous system comprises a neuropil ring anterior to the pharyngeal bulb. Associated with the neuropil ring are flask-shaped serotonergic somata extending anteriorly and posteriorly. A ventral nerve cord is connected to the neuropil ring and runs toward the anterior until an attachment point in segment 1, and from there toward the posterior with one ganglion in segment 6. Segmentation within Kinorhyncha likely evolved from an unsegmented ancestor. This conclusion is supported by continuous trunk musculature in the anterior segments 1–6, continuous pharyngeal bulb protractors and retractors throughout the anterior segments, no sign of segmentation within the digestive system, and the absence of ganglia in most segments. The musculature shows evidence of segmentation that fit the definition of an anteroposteriorly repeated body unit only in segments 7–10.
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Summary Like the vertebrate spinal cord, the insect ventral nerve cord (VNC) mediates limb sensation and motor control. Here, we apply automated tools for electron microscopy volume alignment, neuron segmentation, and synapse prediction toward creating a connectome of an adult female Drosophila VNC. To interpret a connectome, it is crucial to know its relationship with the rest of the body. We therefore mapped the muscle targets of leg and wing motor neurons in the connectome by comparing their morphology to genetic driver lines, dye fills, and X-ray nano-tomography of the fly leg and wing. Knowing the outputs of the connectome allowed us to identify neural circuits that coordinate the wings and legs during escape takeoff. We provide the reconstruction of VNC circuits and motor neuron atlas, along with tools for programmatic and interactive access, as community resources to support experimental and theoretical studies of how the fly nervous system controls behavior.
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