Mechanisms of Trial-by-Trial Error Correction During Goal-Directed Arm Movements

Sensorimotor adaptation is a form of motor learning whereby performance errors are compensated implicitly from one movement to the next. This project uses systems identification and time series analysis techniques to model trial-by-trial adaptive responses to mechanical perturbations during reaching. Our approach injects "information" into human learners by randomly changing perturbations opposing reaching movements to reveal how people use memories to predict and compensate for changing loads. We have developed a MR-safe robot and functional MRI analysis techniques to visualize neural mechanisms supporting error compensation during trial-to-trial adaptation, finding that multiple neural systems known to be involved in motor learning {basal ganglia, cerebellum, hippocampus} contribute to adapting sensorimotor control from one movement to the next.

Even in the simplest actions such as reaching, corrections for performance errors are comprised of separate components attributable to implicit sensorimotor adaptation and explicit strategic re-aiming. Both implicit and explicit mechanisms utilize memories of prior performance features to improve subsequent performance. This project introduces a new way to assess the contributions of explicit and implicit mechanisms to sensorimotor learning: Subjects grasp the handle of a planar robot while making rapid out-and-back reaches to a single visuospatial target. The robot opposes motion with spring-like loads that changed unpredictably from one reach to the next. Between movements, we sometimes require subjects to recall and report the hand's location at the moment of peak movement extent on the most recent trial; these self-assessments are used to provide visibility into explicit memory of kinematic performance (i.e. reach error). We use stepwise multilinear regression to fit models of sensorimotor adaptation to data from trial blocks performed with and without self-assessments to compare the contributions of implicit and explicit memories to the trial-by-trial compensation for variable environmental loads. We are testing the extent to which implicit and explicit memories both contribute meaningfully to the adaptation of kinematic performance during repeated practice of goal-directed reaching.