Computational Principles Underlying the Learning of Sensorimotor Repertoires

Explore groundbreaking research on human movement and motor learning in this Stanford Center for Mind, Brain, Computation and Technology seminar presented by renowned neuroscientist Daniel Wolpert from Columbia University. Delve into the fundamental principles of how humans develop, store, and refine motor memories throughout their lifetime. Examine cutting-edge computational and experimental approaches to understanding human movement, with particular focus on the crucial role of context in organizing motor memories. Discover a revolutionary theory of motor learning based on contextual inference that challenges traditional single-context learning models and provides unified explanations for previously unexplained motor learning phenomena. Learn how this innovative research demonstrates that contextual inference serves as a fundamental principle in translating diverse experiences into motor behavior, supported by experimental evidence from Wolpert's laboratory studies. Gain insights from a distinguished researcher who has been recognized with numerous prestigious awards including Fellowship in the Royal Society and the Royal Society Ferrier medal for his contributions to neuroscience.