Graph-theoretic analysis of scalp EEG brain networks in epilepsy — The influence of montage and volume conduction

Abstract

It is well established that both the choice of recording reference (montage) and volume conduction affect the connectivity measures obtained from scalp EEG. Our purpose in this work is to establish the extent to which they influence the graph theoretic measures of brain networks in epilepsy obtained from scalp EEG. We evaluate and compare two commonly used linear connectivity measures - cross-correlation and coherence - with measures that account for volume conduction, namely corrected cross-correlation, imaginary coherence, phase lag index and weighted phase lag index. We show that the graphs constructed with cross-correlation and coherence are the most affected by volume conduction and montage; however, they demonstrate the same trend - decreasing connectivity at seizure onset, which continues decreasing in the ictal and early post-ictal period, increasing again several minutes after the seizure has ended-with all other measures except imaginary coherence. In particular, networks constructed using cross-correlation yield better discrimination between the pre-ictal and ictal periods than the measures less sensitive to volume conduction. Thus, somewhat paradoxically, although removing effects of volume conduction allows for a more accurate reconstruction of the true underlying networks this may come at the cost of discrimination ability with respect to brain state.