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Conditioning and the Cerebellum

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Dynamic Interactions in Neural Networks: Models and Data

Part of the book series: Research Notes in Neural Computing ((NEURALCOMPUTING,volume 1))

Abstract

Mathematical models of learning that describe the effects of training with no regard for motor output are incomplete and consequently difficult to represent within natural systems. This chapter summarizes our efforts to reconcile a model that describes real-time topographical features of the classically conditioned nictitating membrane response (NMR) of the rabbit with knowledge about the cerebellum, the brain region thought to be most crucial for NMR conditioning. The NMR is a protective response resulting from retraction of the eyeball and the passive sweeping of the NM over the eye. The conditioned NMR is a graded, adaptive response.

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Authors and Affiliations

  1. University of Massachusetts, Amherst, Massachusetts, USA

    John W. Moore & Diana E. J. Blazis

Authors
  1. John W. Moore
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  2. Diana E. J. Blazis
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Editor information

Editors and Affiliations

  1. Center for Neural Engineering, University of Southern California, Los Angeles, CA, 90089-0782, USA

    Michael A. Arbib

  2. Department of Mathematical Engineering and Instrumentation Physics, University of Tokyo, Tokyo, 113, Japan

    Shun-ichi Amari

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© 1989 Springer-Verlag New York Inc.

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Moore, J.W., Blazis, D.E.J. (1989). Conditioning and the Cerebellum. In: Arbib, M.A., Amari, Si. (eds) Dynamic Interactions in Neural Networks: Models and Data. Research Notes in Neural Computing, vol 1. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4536-0_16

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  • DOI: https://doi.org/10.1007/978-1-4612-4536-0_16

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-96893-3

  • Online ISBN: 978-1-4612-4536-0

  • eBook Packages: Springer Book Archive

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