Table 2.

Graph theoretical features of functional connectivity networks

Feature	Feature description	Feature calculation
ldg	Link density of the graph	(2 × ne)/(nn × (nn - 1))
acc	Average of closeness centrality	(1/nn) ∑nn(sum of reciprocal distances from a node to all other nodes)
gcc	Graph clustering coefficient	(3 × number of triangles)/(number of connected triples of nodes)
rcc	Rich club coefficient	(ne_k)/(nn_k × (nnk - 1))
smg	S-metric of graph	Sum of the nodal degree products for every edge.
acg	Algebraic connectivity of graph	Second smallest eigenvalue of the Laplacian of adjacency matrix.
eng	Energy of network graph	Sum of absolute values of the real components of eigenvalues of adjacency matrix.

ne: Number of graph edges; nn: number of graph nodes;

nn_k: Number of nodes with degree larger thank; ne_k: number of edges among nodes with degree larger than k.