Multiple dipole source localization from spatio-temporal EEG data by Quasi-Newton-ICA method / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1206-1212, 2006.
Article
in Chinese
| WPRIM
| ID: wpr-331446
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.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Physiology
/
Computer Simulation
/
Brain
/
Brain Mapping
/
Data Interpretation, Statistical
/
Models, Statistical
/
Electroencephalography
/
Methods
Type of study:
Risk factors
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2006
Type:
Article
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