Over the past decade, converging theoretical and experimental results have indicated that brain functional networks typically have small-world topology, with short average path length (high global efficiency) and high clustering (high local efficiency). Brain functional networks tend to be robust to random lesions, but highly vulnerable to targeted lesions, due to the existence of hubs, i.e. highly connected nodes which account for a large fraction of the graph’s overall connectivity (Achard et al., 2006; He et al., 2007c, 2007a; Xia et al., 2010). Brain functional networks are sparse, that is, only a relatively small fraction of the total number of pairs is directly connected. Finally, brain functional networks often operate in a critical dynamical state, supporting rapid reconfiguration of graph topology, a feature thought to be related to the need to rapidly switch cognitive states.
