We first examined graph-theoretic metrics obtained for the functional brain networks constructed by thresholding (threshold values ranged from 0.01 to 0.99, with an increment of 0.01) the wavelet correlation matrix at three different frequency scales. Scale 1 encompassed 0.13–0.25 Hz, scale 2 encompassed 0.06–0.12 Hz, and scale 3 encompassed 0.01–0.05 Hz. As shown in Figure 1, for both the children and young-adult groups, the mean degree—the average number of edges incident on a node belonging to the network—was highest at scale 3 for a wide range of correlation thresholds (0.01<R<0.8). The mean characteristic path length (λ) for both groups, when controlled for the degree of the network (1<λ<1.57), showed similar trends at all three scales. The clustering coefficient (γ) for both groups, when controlled for the degree of the network, was highest at scale 3. Due to higher mean γ values, the small-world measure σ (γ/λ), when controlled for degree of the network, was highest at scale 3 for both groups. The small-world property (σ>1) showed a monotonic increase in small-worldness as the threshold increased and the degree decreased. σ
