Feedforward and feedback learning in human sensorimotor control
The human sensorimotor control system has exceptional abilities to perform skilful action despite ever changing conditions. I will discuss how this adaptability can result through intrinsic feedback mechanisms in two different ways: sensory feedback driving feedforward adaptation; and feedforward adaptation in turn adapting the feedback responses and tuning them to the environment. In the first part of my talk I will examine how prior sensorimotor cues can be used to learn independent motor memories. These results suggests that motor memories are encoded not simply as a mapping from current state to motor command but are encoded in terms of the recent history of sensorimotor states. However learning can also be used to adjust intrinsic feedback control. The second half of my talk will focus on a few recent studies examining feedback responses; demonstrating both how they are modulated for control and using them to probe the underlying mechanisms of visually guided reaching. Finally I will present work demonstrate that the visuomotor feedback gain shows a temporal evolution related to task demands (as predicted by optimal control) and that this evolution can be flexibly recomputed within 100 ms to accommodate online modifications to task goals.