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)


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.


Visual Cortex Lyapunov Exponent External Input Hippocampal Formation Attention Shift 
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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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