Postdoctoral T32 in Integrated Computational and Experimental Sensorimotor Control - We propose to establish a training program in Integrated Computational and Experimental Sensorimotor Control to support 10 postdoctoral trainees over 5 years, each for 2 years. Movement is fundamental to human existence, yet impairments of human movement, due to stroke, degenerative disease, and developmental disorders, affect 5% of the population over their lifespan. To understand the underlying brain processes that control human movement, and their malfunction in disease, requires a major interdisciplinary effort using the latest scientific developments and technological tools that combine theoretical and experimental approaches. Our objective is to provide integrated training in the methods- and knowledgebase of several disciplines, to focus a range of modern experimental and computational methods on the fundamental problem of how the brain controls the body. The Zuckerman Mind Brain Behavior Institute houses all 16 participating faculty mentors within a single building; 5 are theoretical neuroscientists and 11 are primarily experimentalists. Their work on the control of movement spans multiple species (fly, mouse, bird, monkey and human) and techniques (theory, tools, behavior and circuits). The Zuckerman Institute is perhaps unparalleled in the breadth and depth of work in sensorimotor control. Our long- term objective is to train the next generation of scientists who will be versed in the scientific disciplines, analytic tools and experimental methods that will be required for the next generation to advance the field. The rationale for the program arises because of the rapid advance of the field at multiple levels: (1) the ability of deep learning techniques to extract motor behavior at unprecedented spatial and temporal resolution in all species; (2) the ability to record muscle (e.g. myomatrix) and neural activity (e.g. neuropixels) on thousands of channels in multiple areas, and the resulting range of new analytical tools; (3) rapid advances in methods to develop motor tasks from robotic interfaces and virtual reality to new holographic neural stimulation methods; and (4) rapid advances in theoretical tools from Bayesian approaches, through recurrent neural networks, to deep learning. It has become increasingly hard for trainees to master all the skills necessary to be well versed in the field and take advantage of these developments without a comprehensive, targeted training program. Our trainees will be co-mentored by a theory and experimental mentor and the project will be a true collaboration between the groups. Key activities include new didactic and research-based training to fill skills gaps for experimentalists and theoreticians and to extend their current skill sets. These include (i) a new 4 month core course in sensorimotor control as well as several new program-wide activities that include monthly (ii) experimental designs sessions and (iii) journal club, (iv) quarterly data analysis Hackathon; annual (v) experimental Hackathon, (vi) project planning meeting and (vii) project progress meeting. The outcome of this integrated training will be a new generation of scientists versed in both computational and experimental approaches, equipped with the core skills necessary to manage their own laboratories and possess the ability to integrate knowledge across different species and techniques.
