A merged dataset was constructed by considering data from the six cortical regions of the two subjects, thus yielding a set of 12 cortical signals. In order to clean out existing differences in the average activity and variance of the signals of two distinct subjects' brains, a z-transformation of the original cortical waveforms has been taken into account (see Methods S4 for more details). The transformed cortical waveforms, one for each ROI of the merged data set, were then processed to estimate functional connectivity by means of the Partial Directed Coherence (PDC) method [27]. The PDC is a multivariate spectral measure used to determine the directed influences between any given pair of signals in a multivariate data set (see also Methods S5). In order to consider only the functional links that are not due to chance, we used a statistical significance threshold referred to as the spectral causality criterion (SCC) [3]. According to this approach, only connections whose intensities are higher than the predetermined threshold are taken into account, while the remaining connections are excluded. Concerning the spectral properties of
