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Investigating directed phase couplings from multivariate EEG/MEG time series

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If you have a question about this talk, please contact Johan Carlin .

Recent works suggest that the use of bivariate methods to analyse EEG /MEG time series is suboptimal when functional connectivity is the target. Indeed, the application of dimensionality reduction approaches to multivariate time series, such as parcel signals, unavoidably leads to discard a large part of the information. In my talk I will present a computational method called Multivariate Phase Slope Index. This method allows to directly investigate the directionality of functional interactions between brain regions from multivariate EEG /MEG time series.

This talk is part of the Imagers Interest Group series.

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