This provides a measure for the integration capacity of a network. It is computed by first evaluating the matrix of connection lengths, L = {Lij}, which are inversely related to the link weights, Wij. The higher the weight in the connection among two neurons, the shorter is their connection length. This matrix was then analyzed to compute the shortest path length dij between neurons i and j and, lastly, the global efficiency, GEFF, as the average inverse of the shortest path length (25, 26)Embedded Image(5)Embedded Image(6)where Luv is the length between nodes u and v, gij is the shortest geodesic path between nodes i and j calculated using the Dijkstra algorithm, and N is the total number of neurons. We note that dij = ∞ for disconnected pairs (i, j). To compare the global efficiency among different experiments, we considered its normalized form G*EFF = GEFF/GRGEFF, where GRGEFF is the global efficiency for the random graph equivalent (null model) of the studied network, computed from wS = {〈wSij}, as introduced before. We verified that the differences in global efficiency among the three configurations (merged, single bond, and triple bond) were robust to thresholds in the significance level of the procured effective networks (fig. S10).

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