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Multiple Signal Classification Based on Chaos Optimization Algorithm for MEG Sources Localization

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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

How to localize the neural activation sources effectively and precisely from the magnetoencephalographic (MEG) recording is a critical issue for the clinical neurology and the study on brain functions. Multiple signal classification (MUSIC) algorithm and its extension referred to as recursive MUSIC algorithm are widely used to localize multiple dipolar sources from the MEG data. The drawback of these algorithms is that they run very slowly when scanning a three-dimensional head volume globally. In order to solve this problem, a novel MEG source localization method based on chaos optimization algorithm is proposed. This method uses the property of ergodicity of chaos to estimate the rough source location. Then combining with grids in small area, the accurate dipolar source localization is performed. Experimental results show that this method can improve the speed of source localization greatly and its accuracy is satisfactory.

This research was supported by the grant from the National Natural Science Foundation of China (No. 30370392).

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Author information

Authors and Affiliations

  1. Department of Electronics Engineering, Fudan University, Shanghai, 200433, China

    Jie-Ming Ma, Bin Wang & Li-Ming Zhang

  2. Department of Physiology and Biophysics, School of Life Science, Fudan University, Shanghai, 200433, China

    Yang Cao

Authors
  1. Jie-Ming Ma
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  2. Bin Wang
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  3. Yang Cao
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  4. Li-Ming Zhang
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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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Ma, JM., Wang, B., Cao, Y., Zhang, LM. (2006). Multiple Signal Classification Based on Chaos Optimization Algorithm for MEG Sources Localization. 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_88

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  • DOI: https://doi.org/10.1007/11760191_88

  • 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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