Prediction signals in the cerebellum: beyond supervised motor learning

Elife. 2020 Mar 30;9:e54073. doi: 10.7554/eLife.54073.

Abstract

While classical views of cerebellar learning have suggested that this structure predominantly operates according to an error-based supervised learning rule to refine movements, emerging evidence suggests that the cerebellum may also harness a wider range of learning rules to contribute to a variety of behaviors, including cognitive processes. Together, such evidence points to a broad role for cerebellar circuits in generating and testing predictions about movement, reward, and other non-motor operations. However, this expanded view of cerebellar processing also raises many new questions about how such apparent diversity of function arises from a structure with striking homogeneity. Hence, this review will highlight both current evidence for predictive cerebellar circuit function that extends beyond the classical view of error-driven supervised learning, as well as open questions that must be addressed to unify our understanding cerebellar circuit function.

Keywords: cerebellum; motor learning; neural circuits; neuroscience.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Animals
  • Cerebellum / physiology*
  • Humans
  • Learning*
  • Mice
  • Models, Neurological
  • Movement