Literature DB >> 6487679

A synaptic modification algorithm in consideration of the generation of rhythmic oscillation in a ring neural network.

K Tsutsumi, H Matsumoto.   

Abstract

In consideration of the generation of bursts of nerve impulses (that is, rhythmic oscillation in impulse density) in the ring neural network, a synaptic modification algorithm is newly proposed. Rhythmic oscillation generally occurs in the regular ring network with feedback inhibition and in fact such signals can be observed in the real nervous system. Since, however, various additional connections can cause a disturbance which easily extinguishes the rhythmic oscillation in the network, some function for maintaining the rhythmic oscillation is to be expected to exist in the synapses if such signals play an important part in the nervous system. Our preliminary investigation into the rhythmic oscillation in the regular ring network has led to the selection of the parameters, that is, the average membrane potential (AMP) and the average impulse density (AID) in the synaptic modification algorithm, where the decrease of synaptic strength is supposed to be essential. This synaptic modification algorithm using AMP and AID enables both the rhythmic oscillation and the nonoscillatory state to be dealt with in the algorithm without distinction. Simulation demonstrates cases in which the algorithm catches and holds the rhythmic oscillation in the disturbed ring network where the rhythmic oscillation was previously extinguished.

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Year:  1984        PMID: 6487679     DOI: 10.1007/bf00335199

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


  14 in total

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Authors:  K Fukushima
Journal:  Biol Cybern       Date:  1975-11-05       Impact factor: 2.086

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Journal:  Biol Cybern       Date:  1979-02-02       Impact factor: 2.086

3.  Associative recall and formation of stable modes of activity in neural network models.

Authors:  H Wigström
Journal:  J Neurosci Res       Date:  1975       Impact factor: 4.164

4.  A model of a neural network with recurrent inhibition.

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Journal:  Kybernetik       Date:  1974

5.  A neuron model with learning capability and its relation to mechanisms of association.

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Journal:  Kybernetik       Date:  1973-05

6.  Properties of small neural networks.

Authors:  R B Stein; K V Leung; M N Oğuztöreli; D W Williams
Journal:  Kybernetik       Date:  1974-04-26

7.  Analysis and simulation of networks of mutually inhibiting neurons.

Authors:  I Morishita; A Yajima
Journal:  Kybernetik       Date:  1972-10

8.  Analysis and simulation of double-layer neural networks with mutually inhibiting interconnections.

Authors:  T Tokura; I Morishita
Journal:  Biol Cybern       Date:  1977-01-20       Impact factor: 2.086

9.  Neocognitron: a self organizing neural network model for a mechanism of pattern recognition unaffected by shift in position.

Authors:  K Fukushima
Journal:  Biol Cybern       Date:  1980       Impact factor: 2.086

10.  Generation of a locomotory rhythm by a neural network with reccurrent cyclic inhibition.

Authors:  W O Friesen; G S Stent
Journal:  Biol Cybern       Date:  1977-12-16       Impact factor: 2.086

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  3 in total

1.  Oscillations and chaos in neural networks: an exactly solvable model.

Authors:  L P Wang; E E Pichler; J Ross
Journal:  Proc Natl Acad Sci U S A       Date:  1990-12       Impact factor: 11.205

2.  Ring neural network qua a generator of rhythmic oscillation with period control mechanism.

Authors:  K Tsutsumi; H Matsumoto
Journal:  Biol Cybern       Date:  1984       Impact factor: 2.086

3.  A group-theoretic approach to rings of coupled biological oscillators.

Authors:  J J Collins; I Stewart
Journal:  Biol Cybern       Date:  1994       Impact factor: 2.086

  3 in total

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