Literature DB >> 3801537

Habituation rules for a theory of the cerebellar cortex.

G Chauvet.   

Abstract

A quantitative model of cerebellar cortical function is described with a complete formalization based on (i) the topology of cerebellar cortical neuronal network, (ii) some particular synaptic properties of cell classes in cerebellum cortex, and (iii) the dynamics of excitation in this network. For (i), a construction of functional classes around one Purkinje cell is given and their existence is discussed. For (ii), as in Marr-Albus model, the modifiability of synapses between parallel fibres and Purkinje cell is assumed. But the formalization permits to consider the consequences of such a property at the level of glomerulus (with granule cells) which is known as a complex transformation system. For (iii) habituation rules are assumed. It is shown that this method leads to some interesting properties in the functioning of cerebellar cortex. Particularly, emitting frequency along a Purkinje cell axon results from a discrimination by the system between transformed input signals and an external "noise" due to all other "contexts," and learning could be considered as the result of a conflict between a set of patterns and the transformed input signals. This model could be a basis for future numerical simulations.

Mesh:

Year:  1986        PMID: 3801537     DOI: 10.1007/bf00341934

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  5 in total

1.  A two-pathway informon theory of conditioning and adaptive pattern recognition.

Authors:  A M Uttley
Journal:  Brain Res       Date:  1976-01-30       Impact factor: 3.252

2.  Quantitative histological analysis of the cerebellar cortex in the cat. IV. Mossy fiber-Purkinje cell numerical transfer.

Authors:  M Palkovits; P Magyar; J Szentágothai
Journal:  Brain Res       Date:  1972-10-13       Impact factor: 3.252

3.  A theory of cerebellar cortex.

Authors:  D Marr
Journal:  J Physiol       Date:  1969-06       Impact factor: 5.182

4.  Simulation of learning processes in neuronal networks of the cerebellum.

Authors:  D S Melkonian; H H Mkrtchian; V V Fanardjian
Journal:  Biol Cybern       Date:  1982       Impact factor: 2.086

5.  Adaptive filter model of the cerebellum.

Authors:  M Fujita
Journal:  Biol Cybern       Date:  1982       Impact factor: 2.086

  5 in total
  2 in total

1.  A neural network model of the cerebellar cortex performing dynamic associations.

Authors:  F Chapeau-Blondeau; G Chauvet
Journal:  Biol Cybern       Date:  1991       Impact factor: 2.086

2.  An n-level field theory of biological neural networks.

Authors:  G A Chauvet
Journal:  J Math Biol       Date:  1993       Impact factor: 2.259

  2 in total

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