The Rules of Cerebellar Learning: Around the Ito Hypothesis.

Journal Article (Journal Article;Review)

As a tribute to Masao Ito, we propose a model of cerebellar learning that incorporates and extends his original model. We suggest four principles that align well with conclusions from multiple cerebellar learning systems. (1) Climbing fiber inputs to the cerebellum drive early, fast, poorly-retained learning in the parallel fiber to Purkinje cell synapse. (2) Learned Purkinje cell outputs drive late, slow, well-retained learning in non-Purkinje cell inputs to neurons in the cerebellar nucleus, transferring learning from the cortex to the nucleus. (3) Recurrent feedback from Purkinje cells to the inferior olive, through interneurons in the cerebellar nucleus, limits the magnitude of fast, early learning in the cerebellar cortex. (4) Functionally different inputs are subjected to plasticity in the cerebellar cortex versus the cerebellar nucleus. A computational neural circuit model that is based on these principles mimics a large amount of neural and behavioral data obtained from the smooth pursuit eye movements of monkeys.

Full Text

Duke Authors

Cited Authors

  • Lisberger, SG

Published Date

  • May 10, 2021

Published In

Volume / Issue

  • 462 /

Start / End Page

  • 175 - 190

PubMed ID

  • 32866603

Pubmed Central ID

  • PMC7914257

Electronic International Standard Serial Number (EISSN)

  • 1873-7544

Digital Object Identifier (DOI)

  • 10.1016/j.neuroscience.2020.08.026


  • eng

Conference Location

  • United States