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' ( n = 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 ( n = 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 ( n = 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 ( n = 10), while a control group replicated the results of the first experiment ( n = 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. NEW & NOTEWORTHY 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.

The motor system’s ability to adapt to environmental changes is essential for maintaining accurate movements. Such adaptation recruits several distinct systems: cerebellar sensory-prediction error learning, success-based reinforcement, and explicit control. Although much work has focused on the relationship between cerebellar learning and explicit control, there is little research regarding how reinforcement and explicit control interact. To address this, participants first learnt a 20° visuomotor displacement. After reaching asymptotic performance, binary, hit-or-miss feedback (BF) was introduced either with or without visual feedback, the latter promoting reinforcement. Subsequently, retention was assessed using no-feedback trials, with half of the participants in each group being instructed to stop aiming off target. Although BF led to an increase in retention of the visuomotor displacement, instructing participants to stop re-aiming nullified this effect, suggesting explicit control is critical to BF-based reinforcement. In a second experiment, we prevented the expression or development of explicit control during BF performance, by either constraining participants to a short preparation time (expression) or by introducing the displacement gradually (development). Both manipulations strongly impaired BF performance, suggesting reinforcement requires both recruitment and expression of an explicit component. These results emphasise the pivotal role explicit control plays in reinforcement-based motor learning.

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Transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique, modulates neuronal excitability by the application of a small electrical current. The low cost and ease of the technique has driven interest in potential clinical applications. However, outcomes are highly sensitive to stimulation parameters, leading to difficulty maximizing the technique's effectiveness. Although reversing the polarity of stimulation often causes opposite effects, this is not always the case. Effective clinical application will require an understanding of how tDCS works; how it modulates a neuron; how it affects the local network; and how it alters inter-network signaling. We have summarized what is known regarding the mechanisms of tDCS from sub-cellular processing to circuit level communication with a particular focus on what can be learned from the polarity specificity of the effects.