Paper No: 60
Multi-Modal ICA Exemplified on Simultaneously Measured MEG and EEG Data
Author(s): Heriberto Zavala-Fernandez, Tilmann H. Sander, Martin Burghoff, Reinhold Orglmeister, Lutz Trahms
Abstract
A multi-modal linear mixing model is suggested for simultaneously
measured MEG and EEG data. On the basis of this model an
ICA decomposition is calculated for a combined MEG and EEG signal
vector using the TDSEP algorithm. A single modality demixing procedure
is developed to classify ICA components to be multi-modality
sources detected by EEG and MEG simultaneously or to be single mode
sources.With this procedure, data from 10 subjects are analysed and four
exemplary types of sources are selected. We found that these sources
represent physically meaningful multi- and single-mode signals: Alpha
oscillations, heart activity, eye blinks, and slow signal drifts. |
