PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Estimating true brain connectivity from EEG/MEG data invariant to linear and static transformations in sensor space
Arne Ewald, Laura Marzetti, Filippo Zappasodi, Frank Meinecke and Guido Nolte
NeuroImage Volume 60, Number 1, pp. 476-488, 2012. ISSN 1053-8119

Abstract

The imaginary part of coherency is a measure to investigate the synchronization of brain sources on the EEG/MEG sensor level, robust to artifacts of volume conduction meaning that independent sources cannot generate a significant result. It does not mean, however, that volume conduction is irrelevant when true interactions are present. Here, we analyze in detail the possibilities to construct measures of true brain interactions which are strictly invariant to linear spatial transformations of the sensor data. Specifically, such measures can be constructed from maximization of imaginary coherency in virtual channels, bivariate measures as a corrected variate of imaginary coherence, and global measures indicating the total interaction contained within a space or between two spaces. A complete theoretic framework on this question is provided for second order statistical moments. Relations to existing linear and nonlinear approaches are presented. We applied the methods to resting state EEG data, showing clear interactions at all bands, and to a combined measurement of EEG and MEG during rest condition and a finger tapping task. We found that MEG was capable of observing brain interactions which were not observable in the EEG data.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
Theory & Algorithms
ID Code:9474
Deposited By:Frank Meinecke
Deposited On:16 March 2012