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PubMed · 17228710

[Multiple dipole source localization from spatio-temporal EEG data by Quasi-Newton-ICA method].

Ling Zou·Shan'an Zhu·Bin He
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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.

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BrainBrain MappingComputer SimulationData Interpretation, StatisticalElectroencephalographyHumansModels, StatisticalEnglish AbstractJournal Article

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Ling Zou, Shan'an Zhu, Bin He. 2006. [Multiple dipole source localization from spatio-temporal EEG data by Quasi-Newton-ICA method].. https://pubmed.ncbi.nlm.nih.gov/17228710/

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