Analysis of induced components in electroencephalograms using a multiple correlation method.
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.


CONCLUSIONS
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.
TU Ilmenau, Faculty of Computer Science and Automation, Institute of Biomedical Engineering and Informatics, Gustav-Kirchhoff-Strasse 2, 98693 Ilmenau, Germany. uwe.graichen@tu-ilmenau.de
Uwe
U
Graichen
Herbert
H
Witte
Jens
J
Haueisen
D000328:Adult; D000465:Algorithms; D001698:Biomedical Engineering / Q000379:methods*; D001931:Brain Mapping / Q000379:methods*; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D005260:Female; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted; D012984:Software; D013997:Time Factors