Table 2.

Topological parameters of the brain functional networks.

Network properties	Characters	Descriptions
Global properties	Cp	Clustering coefficient of the network. It measures the extent of local cluster or cliquishness of the network and is the most commonly used measure of functional segregation.
	Lp	Characteristic path length of the network. It is the average shortest path length between all pairs of nodes in the network and is the most commonly used measure of functional integration.
	Eg	Global efficiency of the network. It measures the extent of information propagation through the whole network and is the most commonly used measure of functional integration.
	Eloc	Local efficiency of the network. It measures the mean local efficiency of the network and is the most commonly used measure of functional segregation.
	σ	Small-worldness of the network. Small-world networks, reflects an optimal balance of functional integration and segregation, often fulfill the σ > 1.
Nodal properties	NCp	Nodal clustering coefficient. It measures the extent of interconnectivity among the neighbors of the node and is the most commonly used measure of functional segregation.
	Ne	Nodal global efficiency. It measures the extent of information transmission of the node with all other nodes in the network and is the most commonly used measure of functional integration.
	NLe	Nodal local efficiency. It measures the extent of information transmission among the neighbors of the node and is the most commonly used measure of functional segregation.