Connectomic reconstruction of a female Drosophila ventral nerve cord.

A deep understanding of how the brain controls behaviour requires mapping neural circuits down to the muscles that they control. Here, we apply automated tools to segment neurons and identify synapses in an electron microscopy dataset of an adult female Drosophila melanogaster ventral nerve cord (VNC)1, which functions like the vertebrate spinal cord to sense and control the body. We find that the fly VNC contains roughly 45 million synapses and 14,600 neuronal cell bodies. To interpret the output of the connectome, we mapped the muscle targets of leg and wing motor neurons using genetic driver lines2 and X-ray holographic nanotomography3. With this motor neuron atlas, we identified neural circuits that coordinate leg and wing movements during take-off. We provide the reconstruction of VNC circuits, the motor neuron atlas and tools for programmatic and interactive access as resources to support experimental and theoretical studies of how the nervous system controls behaviour.

Synaptic architecture of leg and wing premotor control networks in Drosophila.

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles1. MN activity is coordinated by complex premotor networks that facilitate the contribution of individual muscles to many different behaviours2-6. Here we use connectomics7 to analyse the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. By contrast, wing premotor networks lack proportional synaptic connectivity, which may enable more flexible recruitment of wing steering muscles. Through comparison of the architecture of distinct motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

Divergent neural circuits for proprioceptive and exteroceptive sensing of the Drosophila leg.

Somatosensory neurons provide the nervous system with information about mechanical forces originating inside and outside the body. Here, we use connectomics to reconstruct and analyze neural circuits downstream of the largest somatosensory organ in the Drosophila leg, the femoral chordotonal organ (FeCO). The FeCO has been proposed to support both proprioceptive sensing of the fly's femur-tibia joint and exteroceptive sensing of substrate vibrations, but it remains unknown which sensory neurons and central circuits contribute to each of these functions. We found that different subtypes of FeCO sensory neurons feed into distinct proprioceptive and exteroceptive pathways. Position- and movement-encoding FeCO neurons connect to local leg motor control circuits in the ventral nerve cord (VNC), indicating a proprioceptive function. In contrast, signals from the vibration-encoding FeCO neurons are integrated across legs and transmitted to auditory regions in the brain, indicating an exteroceptive function. Overall, our analyses reveal the structure of specialized circuits for processing proprioceptive and exteroceptive signals from the fly leg. They also demonstrate how analyzing patterns of synaptic connectivity can distill organizing principles from complex sensorimotor circuits.

Synaptic architecture of leg and wing motor control networks in Drosophila.

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles. Because individual muscles may be used in many different behaviors, MN activity must be flexibly coordinated by dedicated premotor circuitry, the organization of which remains largely unknown. Here, we use comprehensive reconstruction of neuron anatomy and synaptic connectivity from volumetric electron microscopy (i.e., connectomics) to analyze the wiring logic of motor circuits controlling the Drosophila leg and wing. We find that both leg and wing premotor networks are organized into modules that link MNs innervating muscles with related functions. However, the connectivity patterns within leg and wing motor modules are distinct. Leg premotor neurons exhibit proportional gradients of synaptic input onto MNs within each module, revealing a novel circuit basis for hierarchical MN recruitment. In comparison, wing premotor neurons lack proportional synaptic connectivity, which may allow muscles to be recruited in different combinations or with different relative timing. By comparing the architecture of distinct limb motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

The evolutionary trajectory of drosophilid walking.

Neural circuits must both execute the behavioral repertoire of individuals and account for behavioral variation across species. Understanding how this variation emerges over evolutionary time requires large-scale phylogenetic comparisons of behavioral repertoires. Here, we describe the evolution of walking in fruit flies by capturing high-resolution, unconstrained movement from 13 species and 15 strains of drosophilids. We find that walking can be captured in a universal behavior space, the structure of which is evolutionarily conserved. However, the occurrence of and transitions between specific movements have evolved rapidly, resulting in repeated convergent evolution in the temporal structure of locomotion. Moreover, a meta-analysis demonstrates that many behaviors evolve more rapidly than other traits. Thus, the architecture and physiology of locomotor circuits can execute precise individual movements in one species and simultaneously support rapid evolutionary changes in the temporal ordering of these modular elements across clades.

Apical-Basal Polarity Signaling Components, Lgl1 and aPKCs, Control Glutamatergic Synapse Number and Function.

Normal synapse formation is fundamental to brain function. We show here that an apical-basal polarity (A-BP) protein, Lgl1, is present in the postsynaptic density and negatively regulates glutamatergic synapse numbers by antagonizing the atypical protein kinase Cs (aPKCs). A planar cell polarity protein, Vangl2, which inhibits synapse formation, was decreased in synaptosome fractions of cultured cortical neurons from Lgl1 knockout embryos. Conditional knockout of Lgl1 in pyramidal neurons led to reduction of AMPA/NMDA ratio and impaired plasticity. Lgl1 is frequently deleted in Smith-Magenis syndrome (SMS). Lgl1 conditional knockout led to increased locomotion, impaired novel object recognition and social interaction. Lgl1+/- animals also showed increased synapse numbers, defects in open field and social interaction, as well as stereotyped repetitive behavior. Social interaction in Lgl1+/- could be rescued by NMDA antagonists. Our findings reveal a role of apical-basal polarity proteins in glutamatergic synapse development and function and also suggest a potential treatment for SMS patients with Lgl1 deletion.

Local and Global Influences of Visual Spatial Selection and Locomotion in Mouse Primary Visual Cortex.

Sensory selection and movement locally and globally modulate neural responses in seemingly similar ways. For example, locomotion enhances visual responses in mouse primary visual cortex (V1), resembling the effects of spatial attention on primate visual cortical activity. However, interactions between these local and global mechanisms and the resulting effects on perceptual behavior remain largely unknown. Here, we describe a novel mouse visual spatial selection task in which animals either monitor one of two locations for a contrast change ("selective mice") or monitor both ("non-selective mice") and can run at will. Selective mice perform well only when their selected stimulus changes, giving rise to local electrophysiological changes in the corresponding hemisphere of V1 including decreased noise correlations and increased visual information. Non-selective mice perform well when either stimulus changes, giving rise to global changes across both hemispheres of V1. During locomotion, selective mice have worse behavioral performance, increased noise correlations in V1, and decreased visual information, while non-selective mice have decreased noise correlations in V1 but no change in performance or visual information. Our findings demonstrate that mice can locally or globally enhance visual information, but the interaction of the global effect of locomotion with local selection impairs behavioral performance. Moving forward, this mouse model will facilitate future studies of local and global sensory modulatory mechanisms and their effects on behavior.