The functional correlation between neurons i and j was quantified using the Pearson CC, rijEmbedded Image(2)where xi(t) is either fi or the inferred spike trains Si, and Embedded Image is the corresponding time-averaged values. Si(t) are binary signals, representing 1 for the presence of a spike at time t and 0 otherwise. For each network, the mean correlation was evaluated as Embedded Image, where N is the number of neurons, and was used as an index of the degree of global correlation. Mean neural correlation within a single module and between two separated modules was evaluated as the intramodular and intermodular correlations, respectively, by selecting corresponding i-j pairs.

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