TY - GEN
T1 - Robust MEG source localization of event related potentials
T2 - 28th Symposium of the German Association for Pattern Recognition, DAGM 2006
AU - Breun, Peter
AU - Grosse-Wentrup, Moritz
AU - Utschick, Wolfgang
AU - Buss, Martin
PY - 2006
Y1 - 2006
N2 - Independent Component Analysis (ICA) is a frequently used preprocessing step in source localization of MEG and EEC data. By decomposing the measured data into maximally independent components (ICs), estimates of the time course and the topographies of neural sources are obtained. In this paper, we show that when using estimated source topographies for localization, correlations between neural sources introduce an error into the obtained source locations. This error can be avoided by reprojecting ICs onto the observation space, but requires the identification of relevant ICs. For Event Related Potentials (ERPs), we identify relevant ICs by estimating their non-Gaussianity. The efficacy of the approach is tested on auditory evoked potentials (AEPs) recorded by MEG. It is shown that ten trials are sufficient for reconstructing all important characteristics of the AEP, and source localization of the reconstructed ERP yields the same focus of activity as the average of 250 trials.
AB - Independent Component Analysis (ICA) is a frequently used preprocessing step in source localization of MEG and EEC data. By decomposing the measured data into maximally independent components (ICs), estimates of the time course and the topographies of neural sources are obtained. In this paper, we show that when using estimated source topographies for localization, correlations between neural sources introduce an error into the obtained source locations. This error can be avoided by reprojecting ICs onto the observation space, but requires the identification of relevant ICs. For Event Related Potentials (ERPs), we identify relevant ICs by estimating their non-Gaussianity. The efficacy of the approach is tested on auditory evoked potentials (AEPs) recorded by MEG. It is shown that ten trials are sufficient for reconstructing all important characteristics of the AEP, and source localization of the reconstructed ERP yields the same focus of activity as the average of 250 trials.
UR - http://www.scopus.com/inward/record.url?scp=33750259888&partnerID=8YFLogxK
U2 - 10.1007/11861898_40
DO - 10.1007/11861898_40
M3 - Conference contribution
AN - SCOPUS:33750259888
SN - 3540444122
SN - 9783540444121
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 394
EP - 403
BT - Pattern Recognition - 28th DAGM Symposium, Proceedings
PB - Springer Verlag
Y2 - 12 September 2006 through 14 September 2006
ER -