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Global vs. module-specific properties in the human brain functional networks.

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Figshare2015-12-02 更新2026-05-11 收录
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The table illustrates the fraction r of modules (and standard deviation) whose topological parameters significantly (P, average degree; Cp, clustering coefficient; Lp, characteristic path length; Eglob, global efficiency; and Eloc, local efficiency. Notably, the first column (network threshold, S) denotes the network sparsity thresholds corresponding to the Bonferroni-corrected significance levels (P = 0.001, 0.005, 0.01, 0.05 and 0.10, respectively) that were used to construct brain functional networks at the temporal scale. Under each threshold, there were 5 modules that were identified in the temporal functional brain networks by using the modular identification algorithms (Table S2). For details, see Materials and Methods.

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2015-12-02
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