title: [Multiple dipole source localization from spatio-temporal EEG data by Quasi-Newton-ICA method].
abstract: We have investigated spatio-temporal source modeling (STSM) of the electroencephalogram (EEG) by using a Quasi-Newton method based on Independent Component Analysis (ICA) for localization of multiple dipole sources from the scalp EEG. The problem of multiple dipole localization was transformed into several single dipole localization problems. Another benefit of the present method is that the number of independent sources can be estimated. Computer simulation studies were conducted to evaluate the performance of this approach. The present simulation results indicate that the ICA-based method is superior to the conventional nonlinear methods in localization accuracy, computation time and anti-noise performance, for multiple dipole localization when the sources are stationary over the period of interest.
authors.affiliation: Department of Computer Science and Technology, Jiangsu Polytechnic University, Changzhou 213016, China. zoluingme@yahoo.com.cn
authors.forename: Ling
authors.initials: L
authors.lastname: Zou
authors.forename: Shan'an
authors.initials: S
authors.lastname: Zhu
authors.forename: Bin
authors.initials: B
authors.lastname: He
mesh_terms: D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical