Frontiers in Human Neuroscience (Nov 2010)
Localizing and estimating causal relations of interacting brain rhythms
Abstract
Estimating brain connectivity and especially causality betweendifferent brain regions from EEG or MEG is limited by the fact thatthe data are a largely unknown superposition of the actual brainactivities. Any method, which is not robust to mixing artifacts, isprone to yield false positive results. We here review a number ofmethods that allow to address this problem. They are all based on theinsight that the imaginary part of the cross-spectra cannot beexplained as a mixing artifact. First, a joined decomposition of theseimaginary parts into pairwise activities allows to separate subsystemscontaining different rhythmic activities. Second, assuming that therespective source estimates are least overlapping allows a separation of therhythmic interacting subsystem into the source topographiesthemselves. Finally, a causal relation between these sources can beestimated using the newly proposed measure Phase Slope Index (PSI).This work, for the first time, presents the above methods in combination;all applied to a single data set.
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