TY - JOUR
T1 - Analysis of induced components in electroencephalograms using a multiple correlation method.
AU - Graichen, Uwe
AU - Witte, Herbert
AU - Haueisen, Jens
N1 - Funding Information:
This work was supported by the Deutsche Forschungsgemeinschaft (Ha 2899/8-1, Ha 2899/5-1 and Wi 1166/9-1) and the Bundesministerium für Bildung und Forschung (03IP605).
PY - 2009
Y1 - 2009
N2 - BACKGROUND: Evoked and induced activities are two typical components in the EEG and MEG time series after a stimulation. While evoked activity is phase-locked to the stimulus, induced activity is not. Present analysis methods are able to detect non-phase-locked parts of the signal, however, they do not improve the signal-to-noise ratio (SNR) of these signal components. RESULTS: We present a new method for estimating induced activation in EEG multi-trial data sets. It is based on the multiple correlation of single trials. Our method not only detects induced components within the EEG signal, it also improves their SNR. The method is successfully tested with artificial data sets. Application to real data is exemplified using EEG data recorded in a photic driving experiment. CONCLUSION: We show that the SNR of the induced activity is enhanced by our method, and the method found longer lasting induced activity after the end of stimulation compared with a conventional method.
AB - BACKGROUND: Evoked and induced activities are two typical components in the EEG and MEG time series after a stimulation. While evoked activity is phase-locked to the stimulus, induced activity is not. Present analysis methods are able to detect non-phase-locked parts of the signal, however, they do not improve the signal-to-noise ratio (SNR) of these signal components. RESULTS: We present a new method for estimating induced activation in EEG multi-trial data sets. It is based on the multiple correlation of single trials. Our method not only detects induced components within the EEG signal, it also improves their SNR. The method is successfully tested with artificial data sets. Application to real data is exemplified using EEG data recorded in a photic driving experiment. CONCLUSION: We show that the SNR of the induced activity is enhanced by our method, and the method found longer lasting induced activity after the end of stimulation compared with a conventional method.
UR - http://www.scopus.com/inward/record.url?scp=74049140826&partnerID=8YFLogxK
U2 - 10.1186/1475-925X-8-21
DO - 10.1186/1475-925X-8-21
M3 - Journal article
C2 - 19778443
AN - SCOPUS:74049140826
SN - 1475-925X
VL - 8
SP - 21
JO - BioMedical Engineering Online
JF - BioMedical Engineering Online
ER -