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Neural network model of selective visual attention using Hodgkin–Huxley equation

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Abstract

We propose a mathematical model of selective visual attention using a two-layered neural network with neurons described by the Hodgkin–Huxley equation in order to investigate part of the assumption proposed by Desimone and Duncan. The neural network consists of a layer of hippocampal formation and of visual cortex. A frequency of firing and a firing time for each neuron and also a correlation of the firing times between neurons are calculated numerically to clarify an attention state, a nonattention state, and an attention shift. We find that synchronous phenomena occur not only for the frequency but also for the firing time between the neurons in the hippocampal formation and those in a part of the visual cortex in our model. It also turns out that the attention shift is performed quickly in our model.

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Authors and Affiliations

  1. Research Institute of Electrical Communication, Tohoku University, Sendai, 980-8577, Japan

    Katsuki Katayama & Masafumi Yano

  2. Department of Computer and Mathematical Sciences, Graduate School of Information Sciences, Tohoku University, Sendai, 980-8579, Japan

    Tsuyoshi Horiguchi

Authors
  1. Katsuki Katayama
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  2. Masafumi Yano
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  3. Tsuyoshi Horiguchi
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Corresponding author

Correspondence to Katsuki Katayama.

Additional information

Acknowledgements We are grateful to T. Omori for his valuable discussions and comments. K. K. was partially supported by Research Fellowships of the Japan Society for the Promotion of Science for Young Scientists. This work was partially supported by Grant-In-Aid for Scientific Research No. 13680383 from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan.

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Katayama, K., Yano, M. & Horiguchi, T. Neural network model of selective visual attention using Hodgkin–Huxley equation. Biol. Cybern. 91, 315–325 (2004). https://doi.org/10.1007/s00422-004-0504-4

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  • DOI: https://doi.org/10.1007/s00422-004-0504-4

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