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The universal fuzzy logical framework of neural circuits and its application in modeling primary visual cortex

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Abstract

Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells’ dynamical equations. Although there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.

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Authors and Affiliations

  1. Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100080, China

    Hong Hu & ZhongZhi Shi

  2. Laboratory of Visual Information Processing, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China

    Su Li, YunJiu Wang & XiangLin Qi

Authors
  1. Hong Hu
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  2. Su Li
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  3. YunJiu Wang
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  4. XiangLin Qi
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  5. ZhongZhi Shi
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Corresponding author

Correspondence to Hong Hu.

Additional information

Supported by the National Natural Science Foundation of China (Grant Nos. 60435010 and 60675010), 863 National High-Tech Program (Grant No. 2006AA01Z128), National Basic Research Priorities Programme (Grant No. 2007CB311004)

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Hu, H., Li, S., Wang, Y. et al. The universal fuzzy logical framework of neural circuits and its application in modeling primary visual cortex. SCI CHINA SER C 51, 902–912 (2008). https://doi.org/10.1007/s11427-008-0114-9

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  • DOI: https://doi.org/10.1007/s11427-008-0114-9

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