Estimation of core-periphery structure and network flexibility.

(a) Thresholded correlation matrices are separately treated as: a) layers in a multi-layer network, their communities estimated, and network flexibility estimated as the frequency with which a node changes its community assignment across layers; b) the consistency matrix is submitted to a core-periphery detection algorithm and each node’s “coreness” is estimated. Here, consistency measures the fraction of layers (recording sessions) in which a connection was present. (b) Node’s flexibility scores plotted in anatomical space. (c) Nodes’ “coreness” plotted in anatomical space. The size of nodes in panels b and c is proportional to their average weight across all five recording sessions. (d) Because flexibility is a measure of variability while “coreness” is a measure of stability, we find that the two are inversely correlated with one another (red line represents the identity line). (e) Cross-subject consistency of optimal parameters for fitting the core-periphery model. For each mouse, we calculated the difference between observed core quality and that of a null model, and we retained the top 10% of those points. These points are depicted at the level of individual mice in panel f. In panel e, we aggregate those values across all mice.