Global topological properties of Pearson's-correlation and partial-correlation-based networks with and without global signal regression.

<p>Plots show the changes in small-world parameters (Cp, Lp, γ, λ and σ), network efficiency (Local efficiency and Global efficiency), assortativity coefficient (α) and hierarchy coefficient (β) in functional brain networks dependent on both correlation metrics (Pearson's correlation or partial correlation) and global signal (regressed or not) as a function of sparsity thresholds. Local and global efficiency of random and regular networks with the same number of nodes and edges as the real networks were shown in gray lines in the network efficiency plots.