This seminar has been postponed due to unforseen circumstances. Please stay tuned for a rescheduled date for Dr. Saxena's visit!
Abstract: Our ability to record large-scale neural and behavioral data has substantially improved in the last decade. However, the inference of quantitative dynamical models for cognition and motor control remains challenging due to their unconstrained nature. Here, we incorporate constraints from anatomy and physiology to tame machine learning models of neural activity and behavior.
How does the motor cortex achieve generalizable and purposeful movements from the complex, nonlinear musculoskeletal system? I will introduce a deep reinforcement learning framework that trains recurrent neural network controllers to generate purposeful movements in anatomically accurate macaque and mouse musculoskeletal models. This framework mirrors biological neural strategies and aids in predicting and analyzing novel movements. Next, I will discuss ongoing work on integrating region-specific constraints in models of the cortico-basal ganglia-thalamic loop during timing tasks to gain insights into pathway-specific computations. Through these projects, we show that a constraints-based modeling approach allows us to predictively understand the relationship between neural activity and behavior.
Bio: Shreya Saxena is broadly interested in the neural control of complex, coordinated behavior. She is currently an Assistant Professor of Biomedical Engineering at the Center for Neurocomputation and Machine Intelligence at the Wu Tsai Institute at Yale University. During Shreya’s postdoctoral research at the Center for Theoretical Neuroscience at Columbia University’s Zuckerman Mind Brain Behavior Institute, she developed machine learning methods for interpretable modeling of neural and behavioral data. Her PhD in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT) dealt with performance limitations in sensorimotor control. Shreya received an M.S. in Biomedical Engineering from Johns Hopkins University, and a B.S. in Mechanical Engineering from the École Polytechnique Fédérale de Lausanne (EPFL). She is honored to have been selected as a Rising Star in both Electrical Engineering (2019) and Biomedical Engineering (2018).