Figure 1. Schematic of the computation of LZc and SCE.

LZc: (a) x_i is the activity of the i^th channel and a_i is the (Hilbert) amplitude of x_i. (b) b_i is a_i binarised, using the mean activity of a_i as the binarisation threshold. (c) After binarisation of all n signals, (d) the multidimensional time series are concatenated observation-by-observation into one binary sequence k and then (e) repeated patterns are searched and listed into a dictionary of binary words via a Lempel-Ziv algorithm. Lempel-Ziv complexity LZc is proportional to the size of this dictionary. SCE: (a) Two time series. (b) The analytic signals of these two, which are complex signals with the real part being the original signal and the imaginary part being the Hilbert transform of the original signal. (c) A binary synchrony time series is created for this pair of signals; a 1 indicates that the phases of the complex values of the analytic signals are similar (difference of less than 0.8 modulo 2π). (d) Such time series are obtained to represent each channel’s synchrony with seed channel i. e) SCE⁽ⁱ⁾ is the entropy over observations in the resulting data matrix. The overall SCE is then the mean value of SCE⁽ⁱ⁾ across choices of seed channel i.