Dissecting circuit and cellular mechanisms for limb motor control

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Motor neurons connect to muscles and comprise the major output of the nervous system. Patterns of neural activity in motor neurons cause temporally precise muscle contractions, producing coordinated and flexible behavior. These patterns are shaped by the connectivity and physiology of premotor circuits in the spinal cord that synapse onto the motor neurons. Premotor circuits combine descending motor commands with sensory feedback signals to drive motor neuron activity. How premotor networks are structured to control motor output is not well understood, due in part to an incomplete inventory of spinal cell types, and to the difficulties of recording neural activity in behaving animals. To address this gap, this project aims to use Drosophila melanogaster as a model for investigating motor control and premotor neural circuits. With an accessible and numerically compact nervous system, a large and growing suite of genetic tools, and agile, limbed locomotion, Drosophila has the potential to provide insight into fundamental problems of motor control. We introduce a task in which flies learn to generate specific amounts of force to position the femur-tibia joint in different targets. The joint is controlled by twelve neurons which can be genetically labeled for targeted neural recordings. Electrophysiological recordings will reveal how the complete population of motor neurons function together to dynamically position the leg and to sustain a given force output. These data will address long-standing hypotheses about how premotor circuits recruit subsets of motor neurons and the degree to which that control is flexible. Then, a new electron-microscopy level reconstruction of central locomotor circuits will allow identification of key premotor neurons. Electrophysiological recordings of those premotor neurons during the behavioral task will reveal their contributions to processing sensory feedback and to controlling leg force. These results will provide a foundation for understanding how descending commands interact with internal models of body state to control locomotion, a critical step toward achieving the long-term goals of designing interventions for neuromuscular disorders and algorithms for controlling engineered systems.