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Chaotic Behavior in Neural Networks and FitzHugh-Nagumo Neuronal Model

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Neural Information Processing (ICONIP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3316))

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Abstract

There has been a lot of discussion about whether chaos theory can be applied to the dynamics of the brain. It is obvious that nonlinear mechanisms are crucial in neural systems and also it has been established from various experiments that neuronal activities and EEG recordings show many characteristics of chaotic behavior. Chaotic behavior of a three-dimensional neural network representing nonlinear dynamics of local-averaged spike-rate in neurons is investigated. The same study has been carried out to investigate chaos in FitzHugh-Nagumo neuronal model. It was found that these models exhibit chaotic dynamics at some parametric values.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, IIT Kanpur, 208 016, India

    Deepak Mishra, Abhishek Yadav & Prem K. Kalra

Authors
  1. Deepak Mishra
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  2. Abhishek Yadav
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  3. Prem K. Kalra
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Editor information

Editors and Affiliations

  1. Indian Statistical Institute, Electronics and Communication Sciences Unit, Kolkata, India

    Nikhil Ranjan Pal

  2. School of Computer and Information Sciences, Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, Private Bag 92006, Auckland, New Zealand

    Nik Kasabov

  3. Department of Instrumentation and Electronics Engineering, Jadavpur University, Salt-lake Campus, 700098, Calcutta, India

    Rajani K. Mudi

  4. Indian Statistical Institute, 203 B. T. Road, 700 108, Calcutta,  

    Srimanta Pal

  5. Indian Statistical Institute, Computer Vision and Pattern Recognition Unit, 700108, Kolkata, India

    Swapan Kumar Parui

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© 2004 Springer-Verlag Berlin Heidelberg

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Mishra, D., Yadav, A., Kalra, P.K. (2004). Chaotic Behavior in Neural Networks and FitzHugh-Nagumo Neuronal Model. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_133

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  • DOI: https://doi.org/10.1007/978-3-540-30499-9_133

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23931-4

  • Online ISBN: 978-3-540-30499-9

  • eBook Packages: Springer Book Archive

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