Phase-Based Cerebellar Learning of Dynamic Signals

Author

Witali L. Dunin-Barkowski
Donald C. Wunsch, Missouri University of Science and TechnologyFollow

Abstract

Recently, it has been shown that cerebellar Purkinje cell can acquire (memorize) the signals, which come to the climbing fiber cell from external sources [4,5]. The memorizing mechanism is based on using phase of climbing fiber firing. In preceding papers two major points were unclear: (1) how the system behaves in a case of non-stationary signals, and (2) how information transformation in cells of cerebellar nuclei affects model behavior. Herewith in computer simulation experiments, we demonstrate that the phase-based cerebellar system is well suited for acquisition of non-stationary signals. The system is also capable to perform signal interpolation as well as acquisition of randomly presented relations. Mathematical analysis, supported with computer simulations, also demonstrate that signal transformation in cerebellar nuclei is consistent with the proposed model and yields same results as the simplified network. (C) 2000 Elsevier Science B.V. All rights reserved.

Recommended Citation

W. L. Dunin-Barkowski and D. C. Wunsch, "Phase-Based Cerebellar Learning of Dynamic Signals," Neurocomputing, vol. 32 thru 33, pp. 709 - 725, Elsevier, Jun 2000.

The definitive version is available at https://doi.org/10.1016/S0925-2312(00)00236-8

Department(s)

Electrical and Computer Engineering

Second Department

Computer Science

Comments

National Science Foundation, Grant -9413120

Keywords and Phrases

Cerebellar nuclei; Cerebellum; Inferior olives; Information storage; Phase-Based systems; Purkinje cell

International Standard Serial Number (ISSN)

0925-2312

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Elsevier, All rights reserved.

Publication Date

01 Jun 2000