Independent Component Analysis For EEG Source Localization In Realistic Head Models

Leonid Zhukov, David Weinstein and Chris Johnson Center for Scientific Computing and Imaging University of Utah

Abstract:

A pervasive problem in neuroscience is determining which regions of the brain are active, given voltage measurements at the scalp. If accurate solutions to such problems could be obtained, neurologists would gain non-invasive access to patient-specific cortical activity. Access to such data would ultimately increase the number of patients who could be effectively treated for neural pathologies such as multi-focal epilepsy.

However, estimating the location and distribution of electric current source within the brain from electroencephalographic (EEG) recordings is an ill-posed problem. Specifically, there is no unique solution and solutions do not depend continuously on the data. The ill-posedness of the problem makes finding the correct solution a challenging analytic and computational problem.

In this paper we consider a spatio-temporal method for sources localization, taking advantage of the entire EEG time series to reduce the configuration space we must evaluate. The EEG data is first decomposed into signal and noise subspaces using a Principal Component Analysis (PCA) decomposition. This partitioning allows us to easily discard the noise subspace, which has two primary benefits: the remaining signal is less noisy, and it has lower dimensionality. After PCA, we apply Independent Component Analysis (ICA) on the signal subspace. The ICA algorithm separates multichannel data into activation maps due to temporally independent stationary sources. For each activation map we perform an EEG source localization procedure, looking only for a single dipole per map. By localizing multiple dipoles independently, we substantially reduce our search complexity and increase the likelihood of efficiently converging on the correct solution.

Keywords: EEG, ICA, PCA, source localization, realistic head model

Zhukov Leonid

Fri Oct 8 13:55:47 MDT 1999

Revised: March , 2005