Computational and circuit mechanisms underlying motor control

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Understanding the mechanisms that the nervous system uses to control movement is critical for understanding brain and behavior, and one of the fundamental questions in neuroscience. The control of movement emerges from the activity of different motor control centers, that converge onto output systems, mostly located in the spinal cord. While the spinal circuits that underlie different aspects of motor control have been relatively well characterized, the way by which these circuits are coordinated by supraspinal motor control centers remains elusive. In this project, we aim to understand the functional and computational logic of connectivity between a motor control centers, the motor cortex, and the spinal cord and muscle. We will anatomically and functionally characterize the role of projection-specific populations of corticospinal neurons during particular modes of motor control. Because even the simplest motor program requires the activation of many neuronal populations across multiple brain areas, we will also investigate the contribution of other cortical and subcortical areas to the output of the brain to the spinal cord, and to muscle activity. This understanding requires It also requires extracting the information that is carried between brain areas and neuronal cell types, and understanding the computations that are operated in the circuits in order to achieve specific patterns of muscle activation. We will extract computational principles governing the relation between brain activity and muscle activity that are conserved between rodents and , and will construct predictive models of . In order to achieve a mechanistic understanding of the brain circuits underlying motor control, we will dissect the contributions of activity in specific neural populations using closed-loop optogenetic manipulations. The level of understanding that we are seeking requires a dynamic back and forth between anatomical and functional mapping experiments, computational and conceptual models, and causal testing of predictions. We put together a a multidisciplinary team of PIs working in a tight network, sharing the latest technologies to measure and manipulate the brain through an Advanced Imaging and Instrumentation core, creating and refining circuit models based on data that generate testable predictions, and establishing real-time knowledge exchange between team members through a Data Science Core. Our U19BCP Motor Control team proposes a comprehensive and ambitious project to establish the computational and circuit mechanisms underlying classical modes of motor control based on cell-type specific connectivity between brain and spinal cord, novel technology to measure and manipulate functionally and genetically-defined neural populations, and state-of-the-art computational tools. primates multi-area dynamics during motor control