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Moussa, A. J.

Publications and source records attributed to Moussa, A. J..

3 recordsLinked to original sources

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. MN activity is coordinated by complex premotor networks that allow individual muscles to contribute to many different behaviors. Here, we use connectomics to analyze 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. In contrast, wing premotor networks lack proportional synaptic connectivity, which may allow wing steering muscles to be recruited 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.

neuroscience↗

Tools for comprehensive reconstruction and analysis of Drosophila motor circuits

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.

neuroscience↗

Cell-type specific transcriptomic signatures of neocortical circuit organization and their relevance to autism

A prevailing challenge in neuroscience is understanding how diverse neuronal cell types select their synaptic partners to form circuits. In the neocortex, major classes of excitatory projection neurons and inhibitory interneurons are conserved across functionally distinct regions. There is evidence these classes form canonical circuit motifs that depend primarily on their identity; however, regional cues likely also influence their choice of synaptic partners. We mined the Allen Institutes single-cell RNA-sequencing database of mouse cortical neurons to study the expression of genes necessary for synaptic connectivity and maintenance in two regions: the anterior lateral motor cortex (ALM) and the primary visual cortex (VISp). We used the Allens metadata to parse cells by clusters representing major excitatory and inhibitory classes that are common to both ALM and VISp. We then performed two types of pairwise differential gene expression analysis: 1) between different neuronal classes within the same brain region (ALM or VISp), and 2) between the same neuronal class in ALM and VISp. We filtered our results for differentially expressed circuit connectivity related genes and developed a novel bioinformatic approach to determine the sets uniquely enriched in each neuronal class in ALM, VISp, or both. This analysis provides an organized set of genes that may regulate circuit formation in a cell-type-specific manner. Furthermore, it identifies candidate mechanisms for the formation of circuits that are conserved across functionally distinct cortical regions or that are region dependent. Finally, we used the SFARI Human Gene Module to identify genes from this analysis that are related to risk for autism spectrum disorder (ASD). Our analysis provides clear molecular targets for future studies to understand neocortical circuit organization and abnormalities that underly autistic phenotypes.

neuroscience↗