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Networking Property During Epileptic Seizure with Multi-channel EEG Recordings

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3973))

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Abstract

EEG recordings are widely used in epilepsy research. We intend to address a question whether small world network property exists in neural networks when epileptic seizures occur. In this paper, we introduce a bispectrum analysis to calculate the interaction between two EEG recordings; then, a suitable threshold is chosen to convert the interaction of the six channels at five frequency bands to a sparse graph (node: n=30, edge: k=4-7). Through analyzing a real EEG recording, it is found the clustering coefficient is similar to that of regular graph; however the path length is less than that of regular graph. Thus a primary suggestion can be made that neural networks possess small world network characteristic. During epileptic seizures, the small world property of neural network is more significant.

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Author information

Authors and Affiliations

  1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, China

    Huihua Wu, Xiaoli Li & Xinping Guan

Authors
  1. Huihua Wu
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  2. Xiaoli Li
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  3. Xinping Guan
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Wu, H., Li, X., Guan, X. (2006). Networking Property During Epileptic Seizure with Multi-channel EEG Recordings. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_84

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  • DOI: https://doi.org/10.1007/11760191_84

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34482-7

  • Online ISBN: 978-3-540-34483-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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