Motor control is the study of how organisms make accurate goal-directed movements. Here we consider two problems that the motor system must solve in order to achieve such control. The first problem is that sensory feedback is noisy and delayed, which can make movements inaccurate and unstable. The second problem is that the relationship between a motor command and the movement it produces is variable, as the body and the environment can both change. A solution is to build adaptive internal models of the body and the world. The predictions of these internal models, called forward models because they transform motor commands into sensory consequences, can be used to both produce a lifetime of calibrated movements, and to improve the ability of the sensory system to estimate the state of the body and the world around it. Forward models are only useful if they produce unbiased predictions. Evidence shows that forward models remain calibrated through motor adaptation: learning driven by sensory prediction errors.

Motor skills can take weeks to months to acquire and can diminish over time in the absence of continued practice. Thus, strategies that enhance skill acquisition or retention are of great scientific and practical interest. Here we investigated the effect of noninvasive cortical stimulation on the extended time course of learning a novel and challenging motor skill task. A skill measure was chosen to reflect shifts in the task's speed-accuracy tradeoff function (SAF), which prevented us from falsely interpreting variations in position along an unchanged SAF as a change in skill. Subjects practiced over 5 consecutive days while receiving transcranial direct current stimulation (tDCS) over the primary motor cortex (M1). Using the skill measure, we assessed the impact of anodal (relative to sham) tDCS on both within-day (online) and betweenday (offline) effects and on the rate of forgetting during a 3-month follow-up (long-term retention). There was greater total (online plus offline) skill acquisition with anodal tDCS compared to sham, which was mediated through a selective enhancement of offline effects. Anodal tDCS did not change the rate of forgetting relative to sham across the 3-month follow-up period, and consequently the skill measure remained greater with anodal tDCS at 3 months. This prolonged enhancement may hold promise for the rehabilitation of brain injury. Furthermore, these findings support the existence of a consolidation mechanism, susceptible to anodal tDCS, which contributes to offline effects but not to online effects or long-term retention.long-term retention ͉ motor cortex ͉ motor learning ͉ transcranial direct current stimulation (tDCS) ͉ transcranial magnetic stimulation (TMS) A ccurate motor performance is essential to almost everything we do, from typing, to driving, to playing sports. Having a motor skill implies a level of performance in a given task that is only achievable through practice (1). Evidence indicates that motor skill learning can continue over a prolonged time period (2-5). Within-session performance improvements (online effects) occur in the minutes or hours of a single training session and continue over days and weeks of repeated training sessions until performance nears asymptotic levels. Changes in performance can also occur between training sessions (offline effects), i.e., performance at the beginning of session n ϩ 1 is different from performance at the end of session n (6, 7). We have intentionally chosen to avoid the use of the term ''offline learning'' because it has been used to refer to both a physiological process (consolidation) (6) and a particular measurement result (a positive offline effect) (8). Offline effects could also be negative, presumably because of forgetting processes (7). Skills can be retained to varying degrees over weeks to months after the completion of training (long-term retention) (5). Here we investigated the effect of noninvasive cortical stimulation on measurements of these 3 temporal components of skill learning (online effects, of...

Visuomotor adaptation has been thought to be an implicit process that results when a sensory-prediction error signal is used to update a forward model. A striking feature of human competence is the ability to receive verbal instructions and employ strategies to solve tasks; such explicit processes could be used during visuomotor adaptation. Here, we used a novel task design that allowed us to obtain continuous verbal reports of aiming direction while participants learned a visuomotor rotation. We had two main hypotheses: the contribution of explicit learning would be modulated by instruction and the contribution of implicit learning would be modulated by the form of error feedback. By directly assaying aiming direction, we could identify the time course of the explicit component and, via subtraction, isolate the implicit component of learning. There were marked differences in the time courses of explicit and implicit contributions to learning. Explicit learning, driven by target error, was achieved by initially large then smaller explorations of aiming direction biased toward the correct solution. In contrast, implicit learning, driven by a sensory-prediction error, was slow and monotonic. Continuous error feedback reduced the amplitude of explicit learning and increased the contribution of implicit learning. The presence of instruction slightly increased the rate of initial learning and only had a subtle effect on implicit learning. We conclude that visuomotor adaptation, even in the absence of instruction, results from the interplay between explicit learning driven by target error and implicit learning of a forward model driven by prediction error.

The relationship between implicit and explicit processes during motor learning, and for visuomotor adaptation in particular, is poorly understood. We set up a conflict between implicit and explicit processes by instructing subjects to counter a visuomotor rotation using a cognitive strategy in a pointing task. Specifically, they were told the exact nature of the directional perturbation, a rotation that directed them 45°counterclockwise from the desired target, and they were instructed to counter it by aiming for the neighboring clockwise target, 45°away. Subjects were initially successful in completely negating the rotation with this strategy. Surprisingly, however, they were unable to sustain explicit control and made increasingly large errors to the desired target. The cognitive strategy failed because subjects simultaneously adapted unconsciously to the rotation to the neighboring target. Notably, the rate of implicit adaptation to the neighboring target was not significantly different from rotation adaptation in the absence of an opposing explicit strategy. These results indicate that explicit strategies cannot substitute for implicit adaptation to a visuomotor rotation and are in fact overridden by the motor planning system. This suggests that the motor system requires that planned and executed trajectories remain congruous in visual space, and enforces this correspondence even at the expense of an opposing explicit task goal.