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Mining the Independent Source of ERP Components with ICA Decomposition

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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

Independent component analysis (ICA) can blindly separates the input ERP data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain regions. In this study, we use ICA to illustrate that the P300 components in two ERPs recorded under various conditions or tasks are both mainly contributed from a few independent sources. ICA decomposition also indicates a new method to compare P300 components between two ERPs induced by two related tasks. Our comparisons are made on those independent sources contributed to the P300 components, rather than on the ERP waveforms directly. This novel approach identifies not only the similar or common independent components in both conditions that bring about a common part in ERP time courses, but also those different components induced by the different parts in ERP waveforms. Our study suggests that the ICA method is a useful tool to study the brain dynamics.

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Author information

Authors and Affiliations

  1. College of Information Science and Technology, Beijing Normal University, Beijing, 100875, China

    Jia-Cai Zhang, Xiao-Jie Zhao & Li Yao

  2. McKnight Brain Institute, University of Florida, Gainesville, FL, 32610, USA

    Yi-Jun Liu

Authors
  1. Jia-Cai Zhang
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  2. Xiao-Jie Zhao
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  3. Yi-Jun Liu
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  4. Li Yao
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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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Zhang, JC., Zhao, XJ., Liu, YJ., Yao, L. (2006). Mining the Independent Source of ERP Components with ICA Decomposition. 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_87

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  • DOI: https://doi.org/10.1007/11760191_87

  • 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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