Figure 5. . Nodal changes measured by the Rank-Shift Index. (A) The rank-shift index quantifies the change in the rank of nodes from the empirical connectome to the perturbed network when they are ordered by a particular graph-theoretic measure. More specifically, it calculates the sum of the difference between graph-theoretic values for each node in the empirical and perturbed matrices, divided by the maximum potential difference that could exist between these two networks (where a value of 0 indicates no change, and a value of 1 indicates the maximum change). See Methods for further explanation. (B) Rank-shift index of hub nodes across all perturbed networks, for each graph-theoretic measure. (C) Difference in the rank-shift index between the false negative and false positive networks for all nodes (left), and hub nodes (right). A positive value indicates that the false negative connections cause greater changes in the ranking of nodes, whereas a negative value indicates the same for false positive connections. (D) Rank-shift index for each graph-theoretic measure summed across all connectomes. (E) Rank-shift index values summed across all graph-theoretic measures for each density-preserving connectome. (B–E) Results correspond to the mean over 50 trials for which 5% of randomly selected unidirectional connections are modified in each perturbed network (error bars show the standard error of the mean). Graph-theoretic measures are as follows: K = degree, B = betweenness centrality, C = clustering coefficient, Y = participation index, and S = small-world index (). M47: the macaque connectome with 47 nodes, M71: macaque N = 71, M242: macaque N = 242, C52: cat, M213: mouse, C279: C. elegans.
