Resting-State Temporal Synchronization Networks Emerge from Connectivity Topology and Heterogeneity
Fig 7
Emergence of transient synchronization patterns.
a) Temporal evolution of activation strengths of the communities of the anatomically connected heterogeneous Kuramoto model (G = 0.2 and K = 10). b) Temporal evolution of the total community activation strength S (top) and the order parameter R (bottom) of the model anatomically connected heterogeneous Kuramoto model (G = 0.2 and K = 10). The correlation coefficient between S(t) and R(t) is 0.82 (p<10–3). c) Top: The largest correlation coefficient rmax (and 95% confidence interval) between the model communities and the empirical communities was calculated for various number of components (K = 2, …, 16) as a function of the global coupling. Middle: rmax was compared to the expected upper 95% confidence bound of the largest correlation coefficient (rmax, perm) between the model communities and 103 random permutations of the n elements of each empirical communities, for each K and each G. Bottom: Probability that rmax> rmax, perm.