a1 Department of Physiology, Northwestern University Medical School, Chicago, IL 60611 Electronic mail: email@example.com
a2 Department of Computer Science, University of Massachusetts, Amherst, MA 01003 Electronic mail: firstname.lastname@example.org
a3 Department of Computer Science, University of Massachusetts, Amherst, MA 01003 Electronic mail: email@example.com
This article reviews models of the cerebellum and motor learning, from the landmark papers by Marr and Albus through those of the present time. The unique architecture of the cerebellar cortex is ideally suited for pattern recognition, but how is pattern recognition incorporated into motor control and learning systems? The present analysis begins with a discussion of exactly what the cerebellar cortex needs to regulate through its anatomically defined projections to premotor networks. Next, we examine various models showing how the microcircuitry in the cerebellar cortex could be used to achieve its regulatory functions. Having thus defined what it is that Purkinje cells in the cerebellar cortex must learn, we then evaluate theories of motor learning. We examine current models of synaptic plasticity, credit assignment, and the generation of training information, indicating how they could function cooperatively to guide the processes of motor learning.