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

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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 non-oscillatory 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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References

  • Block, H.D.: The perceptron: a model for brain functioning. I. Rev. Mod. Phys. 34, 123–135 (1962)

    Google Scholar 

  • Friesen, W.O., Stent, G.S.: Generation of a locomotory rhythm by a neural network with recurrent cyclic inhibition. Biol. Cybern. 28, 27–40 (1977)

    Google Scholar 

  • Fukushima, K.: Cognitron: a self-organizing multilayered neural network. Biol. Cybern. 20, 121–136 (1975)

    Google Scholar 

  • Fukushima, K.: Neocognitron: a self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in pattern. Biol. Cybern. 36, 193–202 (1980)

    Google Scholar 

  • Malsburg, Chr. von der: Self-organization of orientation sensitive cells in the striate cortex. Kybernetik 14, 85–100 (1973)

    Google Scholar 

  • Malsburg, Chr. von der: Development of ocularity domains and growth behaviour of axon terminals. Biol. Cybern. 32, 49–62 (1979)

    Google Scholar 

  • Mitchel, C.E., Friesen, W.O.: A neuromime system for neural circuit analysis. Biol. Cybern. 40, 127–137 (1981)

    Google Scholar 

  • Morishita, I., Yajima, A.: Analysis and simulation of networks of mutually inhibiting neurons. Kybernetik 11, 154–165 (1972)

    Google Scholar 

  • Nagano, T.: A model of visual development. Biol. Cybern. 26, 45–52 (1977)

    Google Scholar 

  • Nakano, K.: Assosiatron: a model of associative memory. IEEE Trans. Syst. Man Cybern. 2, 380–388 (1972)

    Google Scholar 

  • Pearson, K.: The control of walking. In: Vertebrates: Adaptation, pp. 55–65. Wessels, N.K. ed. San Francisco: Freeman 1979

    Google Scholar 

  • Stein, R.B., Leung, K.V., Mangeron, D., Oguztöreli, M.N.: Improved neuronal models for studying neural networks. Kybernetik 15, 1–9 (1974)

    Google Scholar 

  • Stein, R.B., Leung, K.V., Oguztöreli, M.N., Williams, D.W.: Properties of small neural networks. Kybernetik 14, 223–230 (1974)

    Google Scholar 

  • Thompson, R.S.: A model for basic pattern generating mechanisms in the lobster stomatogastric ganglian. Biol. Cybern. 43, 71–78 (1982)

    Google Scholar 

  • Tokura, T., Morishita, I.: Analysis and simulation of doublelayer neural networks with mutually inhibiting interconnections. Biol. Cybern. 25, 83–92 (1977)

    Google Scholar 

  • Wigström, H.: A neuron model with learning capability and its relation to mechanisms of association. Kybernetik 12, 204–215 (1973)

    Google Scholar 

  • Wigström, H.: A model for a neural network with recurrent inhibition. Kybernetik 16, 103–112 (1974)

    Google Scholar 

  • Wigström, H.: Associative recall and formation of stable modes of activity in neural network models. J. Neurosci. Res. 1, 287–313 (1975)

    Google Scholar 

  • Yagi, H.: Shinkeikei Johokogagu. Tokyo: Denkishoin 1974(in Japanese)

    Google Scholar 

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Tsutsumi, K., Matsumoto, H. A synaptic modification algorithm in consideration of the generation of rhythmic oscillation in a ring neural network. Biol. Cybern. 50, 419–430 (1984). https://doi.org/10.1007/BF00335199

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