. This type of surrogate does not assume Gaussianity and preserves the whole statistical structure of the original time series . We use a nonparametric kernel distribution representation of the probability density function of the surrogate values of C , and compare the fraction of area of that distribution above the value of the NDTE flow of the original data , C original I , with the total area , and compute the corresponding P value . Supplementary Fig . 2 shows all the P values for all the pairs of time series across all the participants in each of the eight conditions coming from the surrogates .