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Synchronous Phenomena for Two-Layered Neural Network with Chaotic Neurons

  • Katsuki Katayama
  • Masafumi Yano
  • Tsuyoshi Horiguchi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3316)

Abstract

We propose a mathematical model of visual selective attention using a two-layered neural network, based on an assumption proposed by Desimone and Duncan. We use a spiking neuron model proposed by Hayashi and Ishizuka, which generates periodic spikes, quasiperiodic spikes and chaotic spikes. The neural network consists of a layer of hippocampal formation and that of visual cortex. In order to clarify an attention shift, we solve numerically a set of the first-order ordinary differential equations, which describe a time-evolution of neurons. The visual selective attention is considered as the synchronous phenomena between the firing times of the neurons in the hippocampal formation and those in a part of the visual cortex in the present model.

Keywords

Visual Cortex Lyapunov Exponent External Input Hippocampal Formation Attention Shift 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Katsuki Katayama
    • 1
  • Masafumi Yano
    • 1
  • Tsuyoshi Horiguchi
    • 2
  1. 1.Research Institute of Electrical CommunicationTohoku UniversitySendaiJapan
  2. 2.Department of Computer and Mathematical Sciences, GSISTohoku UniversitySendaiJapan

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