Neural mechanisms of learning and control

A new theory was postulated that the cerebellum, the basal ganglia, and the cerebral cortex have evolved to implement different kinds of learning algorithms: the cerebellum for supervised learning, the basal ganglia for reinforcement learning, and the cerebral cortex for unsupervised learning. Here,...

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Bibliographic Details
Published inIEEE control systems Vol. 21; no. 4; pp. 42 - 54
Main Authors Doya, K., Kimura, H., Kawato, M.
Format Magazine Article
LanguageEnglish
Published New York IEEE 01.08.2001
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Animals
Basal ganglia
Biological control systems
Biological systems
Cerebral cortex
Control systems
Delay
Learning
Motor drives
Predictive models
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Summary:A new theory was postulated that the cerebellum, the basal ganglia, and the cerebral cortex have evolved to implement different kinds of learning algorithms: the cerebellum for supervised learning, the basal ganglia for reinforcement learning, and the cerebral cortex for unsupervised learning. Here, we introduce recent advances in motor control and learning, namely, the role of the basal ganglia in acquisition of goal-directed behaviors, learning of internal models by the cerebellum, and decomposition of complex tasks by the competition of predictive models.
Bibliography:ObjectType-Article-2
ObjectType-Feature-1
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SourceType-Magazines-1
ISSN:1066-033X
1941-000X
DOI:10.1109/37.939943