DocumentCode
3107791
Title
How to Test the Quality of Reconstructed Sources in Independent Component Analysis (ICA) of EEG/MEG Data
Author
Grosse-Wentrup, Moritz ; Harmeling, Stefan ; Zander, Thorsten ; Hill, Jason ; Scholkopf, Bernhard
Author_Institution
Dept. Empirical Inference, Max Planck Inst. for Intell. Syst., Tubingen, Germany
fYear
2013
fDate
22-24 June 2013
Firstpage
102
Lastpage
105
Abstract
We provide a simple method, based on volume conduction models, to quantify the neurophysiological plausibility of independent components (ICs) reconstructed from EEG/MEG data. We evaluate the method on EEG data recorded from 19 subjects and compare the results with two established procedures for judging the quality of ICs. We argue that our procedure provides a sound empirical basis for the inclusion or exclusion of ICs in the analysis of experimental data.
Keywords
electroencephalography; independent component analysis; magnetoencephalography; medical signal processing; neurophysiology; signal reconstruction; EEG data; ICA; MEG data; independent component analysis; neurophysiological plausibility; reconstructed sources; volume conduction models; Brain models; Data models; Electroencephalography; Integrated circuit modeling; Surfaces; EEG; ICA; Independent Component Analysis; MEG;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition in Neuroimaging (PRNI), 2013 International Workshop on
Conference_Location
Philadelphia, PA
Type
conf
DOI
10.1109/PRNI.2013.35
Filename
6603567
Link To Document