Abstract
Determining the location of cortical activity from electroencephalographic (EEG) data is important theoretically and clinically. Estimating the location of electric current source from EEG recordings is not well-posed mathematically because different internal source configurations can produce an identical external electromagnetic field. In this paper we propose a new method for EEG source localization using Independent Residual Analysis (IRA). First, we apply Independent Residual Analysis on EEG data to divide the raw signals into the independent components. Then for each component, we employ the least square method to locate the dipole. By localizing multiple dipoles independently, we greatly reduce our search complexity and improve the localization accuracy. Computer simulation is also presented to show the effectiveness of the proposed method.
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Tan, G., Zhang, L. (2004). EEG Source Localization Using Independent Residual Analysis. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_70
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DOI: https://doi.org/10.1007/978-3-540-28648-6_70
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22843-1
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