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Chunk #53 — Materials and Methods — Small-World Analysis of the Whole-Brain Functional Connectivity

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Development of large-scale functional brain networks in children.
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of all the nodes in the network. The clustering coefficient and path length of nodes completely disconnected with the network were set as 0 and Inf respectively, and these nodes were excluded while computing C and L. To evaluate the network for small-world properties, we compared the clustering coefficient and the characteristic path length of the network with corresponding values (C ran, L ran) obtained and averaged across 1,000 random networks with the same number of nodes and degree distribution [98]. The degree of every node (a measure of its connectivity) was calculated by counting the number of edges incident on that node. The mean degree of the network was the average of the degree of all the nodes in the network. Small-world networks are characterized by high normalized clustering coefficient γ (C/C ran)>1 and low normalized characteristic path length λ (L/L ran)≈1 compared to random networks [99]. A cumulative metric σ—the ratio of normalized clustering coefficient (γ) to the characteristic path length (λ), a measure of small-worldness—is thus greater than 1 for small world networks.