Localizing and Estimating Causal Relations of Interacting Brain Rhythms - Nolte, Guido; Mueller, Klaus R. (Frontiers in Human Neuroscience, 2010)
Estimating brain connectivity and especially causality between different brain regions from EEG or MEG is limited by the fact that the data are a largely unknown superposition of the actual brain activities. Any method, which is not robust to mixing artifacts, is prone to yield false positive results. We here review a number of methods that allow to address this problem. They are all based on the insight that the imaginary part of the cross-spectra cannot be explained as a mixing artifact. First, a joined decomposition of these imaginary parts into pairwise activities allows to separate subsystems containing different rhythmic activities. Second, assuming that the respective source estimates are least overlapping allows a separation of the rhythmic interacting subsystem into the source topographies themselves. Finally, a causal relation between these sources can be estimated 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.