Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks
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- Shinichi Tamura
- NBL Technovator Co., Ltd., 631 Shindachimakino, Sennan 590-0522, Japan
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- Yoshi Nishitani
- Department of Radiology, Graduate School of Medicine, Osaka University, Suita 565-0871, Japan
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- Chie Hosokawa
- Biomedical Research Institute, AIST, Ikeda, Osaka 563-8577, Japan
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- Tomomitsu Miyoshi
- Department of Integrative Physiology, Graduate School of Medicine, Osaka University, Suita 565-0871, Japan
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- 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
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- http://creativecommons.org/licenses/by/4.0/
- DOI
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- 10.1155/2016/7186092
- 公開者
- Wiley
この論文をさがす
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>
収録刊行物
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- Computational Intelligence and Neuroscience
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Computational Intelligence and Neuroscience 2016 1-12, 2016
Wiley