Human sensorimotor learning: adaptation, skill, and beyond

Recent studies of upper limb movements have provided insights into the computations, mechanisms, and taxonomy of human sensorimotor learning. Motor tasks differ with respect to how they weight different learning processes. These include adaptation, an internal-model based process that reduces sensory-prediction errors in order to return performance to pre-perturbation levels, use-dependent plasticity, and operant reinforcement. Visuomotor rotation and force-field tasks impose systematic errors and thereby emphasize adaptation. In skill learning tasks, which for the most part do not involve a perturbation, improved performance is manifest as reduced motor variability and probably depends less on adaptation and more on success-based exploration. Explicit awareness and declarative memory contribute, to varying degrees, to motor learning. The modularity of motor learning processes maps, at least to some extent, onto distinct brain structures.

► Human sensorimotor learning is comprised of several component processes. ► Adaptation is updating of internal model based on sensory prediction errors. ► Skill learning is improvement in a controller through trial-and-error reinforcement. ► Use-dependent plasticity is induced by movement repetition and induces biases. ► Explicit and implicit processes influence skill learning.