1. Prediction signals in the cerebellum: beyond supervised motor learning
- Author
-
Court Hull
- Subjects
Cerebellum ,cerebellum ,Computer science ,QH301-705.5 ,Science ,Movement ,Models, Neurological ,Review Article ,General Biochemistry, Genetics and Molecular Biology ,03 medical and health sciences ,Mice ,0302 clinical medicine ,medicine ,Biological neural network ,Animals ,Humans ,Learning ,Biology (General) ,neural circuits ,030304 developmental biology ,Cognitive science ,0303 health sciences ,General Immunology and Microbiology ,General Neuroscience ,Supervised learning ,Cognition ,General Medicine ,medicine.anatomical_structure ,Medicine ,Motor learning ,motor learning ,030217 neurology & neurosurgery ,Neuroscience - 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.
- Published
- 2019