Neural Adaptation: Motor Control

This lecture by Mackenzie Mathis explores how animals and agents learn to adapt through the study of adaptive motor control. The presentation covers topics such as task goals, noise, motor commands, control policies, internal forward models, sensory feedback, and the role of the somatosensory cortex in motor learning. The research delves into the mechanisms behind motor adaptation, the impact of sensory prediction errors, and the essential role of the forelimb S1 area in learning. Through experiments with mice and theoretical models, the lecture sheds light on the neural computations and internal models involved in adaptive behaviors, aiming to guide the development of adaptive AI.