Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks

  • Shinichi Tamura
    NBL Technovator Co., Ltd., 631 Shindachimakino, Sennan 590-0522, Japan
  • Yoshi Nishitani
    Department of Radiology, Graduate School of Medicine, Osaka University, Suita 565-0871, Japan
  • Chie Hosokawa
    Biomedical Research Institute, AIST, Ikeda, Osaka 563-8577, Japan
  • Tomomitsu Miyoshi
    Department of Integrative Physiology, Graduate School of Medicine, Osaka University, Suita 565-0871, Japan
  • Hajime Sawai
    College of Health and Human Sciences, Osaka Prefecture University, Habikino, Osaka 583-8555, Japan

書誌事項

公開日
2016
資源種別
journal article
権利情報
  • http://creativecommons.org/licenses/by/4.0/
DOI
  • 10.1155/2016/7186092
公開者
Wiley

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説明

<jats:p>It has been shown that, in cultured neuronal networks on a multielectrode, pseudorandom-like sequences (codes) are detected, and they flow with some spatial decay constant. Each cultured neuronal network is characterized by a specific spectrum curve. That is, we may consider the spectrum curve as a “signature” of its associated neuronal network that is dependent on the characteristics of neurons and network configuration, including the weight distribution. In the present study, we used an integrate-and-fire model of neurons with intrinsic and instantaneous fluctuations of characteristics for performing a simulation of a code spectrum from multielectrodes on a 2D mesh neural network. We showed that it is possible to estimate the characteristics of neurons such as the distribution of number of neurons around each electrode and their refractory periods. Although this process is a reverse problem and theoretically the solutions are not sufficiently guaranteed, the parameters seem to be consistent with those of neurons. That is, the proposed neural network model may adequately reflect the behavior of a cultured neuronal network. Furthermore, such prospect is discussed that code analysis will provide a base of communication within a neural network that will also create a base of natural intelligence.</jats:p>

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