The dissection of motor learning using an engineering systems framework


November 24, 2014 - 4:00pm
Maxwell Dworkin G115
About the Speaker
Maurice Smith (SEAS/CBS)

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 not only successful movement, but survival. The human motor system, in particular, has a remarkable capacity for adaptive control during volitional movement. I will present some recent insights into the mechanisms by which we, as humans, achieve this adaptive control based on analysis of the formation and maintenance of the motor memories that support it in an engineering systems framework. I will begin by showing how the contributions of fast and slow adaptive processes interact during motor learning. We find that these processes display very different learning rates and contribute to distinct memory stores that display different modes of forgetting, that they compete against one another in adaptive strength, and that a computational model of these competitive interactions provides an intriguing quantitatively-accurate account of the well-known but poorly understood advantage of trial spacing during learning. Recent work has suggested that fast and slow learning rely on distinct neuroanatomical underpinnings, giving new insight into neurologic diseases that affect motor learning. We also examine the relationship between motor variability and learning, showing how internal estimates of motor variability dynamically regulate motor execution allowing for adaptive control that maintains a fixed statistical confidence in the face of varying levels of environmental variability.