ICA-Based EEG spatio-temporal dipole source localization: a model study

Authors:
Ling Zou;Shan-An Zhu;Bin He
Affiliations:
Department of Computer Science and Technology, Jiangsu Polytechnic University, China;College of Electrical Engineering, Zhejiang University, Hangzhou, China;Dept. of Biomedical Engineering, University of Minnesota, Minneapolis, MN
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Year:
2006

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Abstract

In this paper, we examine the performance of an Independent Component Analysis (ICA) based dipole localization approach to localize multiple source dipoles under noisy environment. Uncorrelated noise of up to 40% was added to scalp EEG signals. The performance of the ICA-based algorithm is compared with the conventional localization procedure using Simplex method. The present simulation results indicate the robustness of the ICA-based approach in localizing multiple dipoles of independent sources.