Skip to contentSkip to filters

We use cookies for analytics.

Topic: Learning Theories

Seminar
1 seminar

In Computational Neuroscience and Computer Science

Seminar · Computational Neuroscience

Generalizing theories of cerebellum-like learning

Ashok Litwin Kumar · Columbia University

Fri, Mar 19, 2021 · 15:00 UTC

Since the theories of Marr, Ito, and Albus, the cerebellum has provided an attractive well-characterized model system to investigate biological mechanisms of learning. In recent years, theories have been developed that provide a normative account for many features of the anatomy and function of cerebellar cortex and cerebellum-like systems, including the distribution of parallel fiber-Purkinje cell synaptic weights, the expansion in neuron number of the granule cell layer and their synaptic in-degree, and sparse coding by granule cells. Typically, these theories focus on the learning of random