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International Conference on Theory and Application in Nonlinear Dynamics (ICAND 2012) pp 101–112Cite as

Asynchronous Cellular Automaton Based Modeling of Nonlinear Dynamics of Neuron

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Part of the book series: Understanding Complex Systems ((UCS))

Abstract

A modeling approach of nonlinear dynamics of neurons by an asynchronous cellular automaton is introduced. It is shown that an asynchronous cellular automaton neuron model can realize not only typical nonlinear response characteristics of neurons but also their underlying occurrence mechanisms (i.e., bifurcation scenarios). The model can be implemented as an asynchronous sequential logic circuit, whose control parameter is the pattern of wires that can be dynamically updated in a dynamic reconfigurable FPGA. An on-FPGA learning algorithm (i.e., on-FPGA rewiring algorithm) is presented and is used to tune the model so that it reproduces nonlinear response characteristics of a neuron.

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Author information

Authors and Affiliations

  1. Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-cho, Toyonaka, Osaka,  560-8531, Japan

    Hiroyuki Torikai & Takashi Matsubara

Authors
  1. Hiroyuki Torikai
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  2. Takashi Matsubara
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Corresponding author

Correspondence to Hiroyuki Torikai .

Editor information

Editors and Affiliations

  1. Code 71730, Spawar Systems Center, San Diego, California, USA

    Visarath In

  2. Department of Mathematics, San Diego State University, San Diego, California, USA

    Antonio Palacios

  3. Code 71730, Spawar Systems Center, San Diego, California, USA

    Patrick Longhini

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Torikai, H., Matsubara, T. (2014). Asynchronous Cellular Automaton Based Modeling of Nonlinear Dynamics of Neuron. In: In, V., Palacios, A., Longhini, P. (eds) International Conference on Theory and Application in Nonlinear Dynamics (ICAND 2012). Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-02925-2_9

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