Variability, reference frames, and generalization in motor learning

The ability to control movement is perhaps *the* central function of the nervous system, and the ability to optimize this control through learning can be absolutely essential for successful movement. The human motor system, in particular, has a remarkable capacity for adaptive control. I will present some recent insights into the mechanisms by which humans achieve this adaptive control during voluntary movement. We will begin by looking at recent work on the mechanisms for spatial representations in motor learning and the generalization of learning to untrained conditions. We will then focus on the relationship between motor variability and learning, showing how estimates of motor variability evolve during exposure to a novel environment, and how both inter-individual and task-related differences in learning ability are related to the structure of motor output variability. We will conclude by demonstrating how the structure of motor output variability can be adaptively reshaped to optimize learning ability.

Speaker: Maurice Smith, Harvard

Room 5101