Contribution of explicit processes to reinforcement-based motor learning

Abstract

<p class="first" id="d713367e154">Despite increasing interest in the role of reward in motor learning, the underlying mechanisms remain ill defined. In particular, the contribution of explicit processes to reward-based motor learning is unclear. To address this, we examined subjects’ ( <i>n</i> = 30) ability to learn to compensate for a gradually introduced 25° visuomotor rotation with only reward-based feedback (binary success/failure). Only two-thirds of subjects ( <i>n</i> = 20) were successful at the maximum angle. The remaining subjects initially followed the rotation but after a variable number of trials began to reach at an insufficiently large angle and subsequently returned to near-baseline performance ( <i>n</i> = 10). Furthermore, those who were successful accomplished this via a large explicit component, evidenced by a reduction in reach angle when they were asked to remove any strategy they employed. However, both groups displayed a small degree of remaining retention even after the removal of this explicit component. All subjects made greater and more variable changes in reach angle after incorrect (unrewarded) trials. However, subjects who failed to learn showed decreased sensitivity to errors, even in the initial period in which they followed the rotation, a pattern previously found in parkinsonian patients. In a second experiment, the addition of a secondary mental rotation task completely abolished learning ( <i>n</i> = 10), while a control group replicated the results of the first experiment ( <i>n</i> = 10). These results emphasize a pivotal role of explicit processes during reinforcement-based motor learning, and the susceptibility of this form of learning to disruption has important implications for its potential therapeutic benefits. </p><p id="d713367e171"> <b>NEW &amp; NOTEWORTHY</b> We demonstrate that learning a visuomotor rotation with only reward-based feedback is principally accomplished via the development of a large explicit component. Furthermore, this form of learning is susceptible to disruption with a secondary task. The results suggest that future experiments utilizing reward-based feedback should aim to dissect the roles of implicit and explicit reinforcement learning systems. Therapeutic motor learning approaches based on reward should be aware of the sensitivity to disruption. </p>