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International Symposium on Neural Networks

ISNN 2006: Advances in Neural Networks - ISNN 2006 pp 560–565Cite as

Nonlinear Dynamics of EEG Signal Based on Coupled Network Lattice Model

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

Abstract

EEG signals were expressed as the typical non-stationary signal. More and more evidences were found that both EEG and ERP signals are also chaotic signal from the nonlinear dynamics system. A novel model based on the time-varying coupled map lattice model is proposed for investigating the nonlinear dynamics of EEG under specified cognitive tasks. Moreover, the time-variant largest Lyapunov exponent (LLE) is defined for the purpose of defining quantitative parameters to reveal the global characters of system and extract new information involved in the system. Both simulations and real ERP signals were examined in terms of LLE parameter for studying the signal’s dynamic structure. Several experimental results show that the brain chaos changes with time under different attention tasks of the information processing. The influence of the LLE with the different attention tasks occurs in P2 period.

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Author information

Authors and Affiliations

  1. College of Information Engineering, Guangdong University of Technology, Guangzhou, China

    Minfen Shen

  2. Key Lab. of Image Processing, Shantou University, Guangdong, China

    Guoliang Chang & Shuwang Wang

  3. School of System Engineering, Portsmouth University, Portsmouth, U.K.

    Patch J. Beadle

Authors
  1. Minfen Shen
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  2. Guoliang Chang
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  3. Shuwang Wang
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  4. Patch J. Beadle
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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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Shen, M., Chang, G., Wang, S., Beadle, P.J. (2006). Nonlinear Dynamics of EEG Signal Based on Coupled Network Lattice Model. 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_82

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  • DOI: https://doi.org/10.1007/11760191_82

  • 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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