Circuits synchronized “at rest” are constrained to known, direct or polysynaptic anatomically interconnected regions (Greicius et al., 2009; Honey et al., 2009; Damoiseaux and Greicius, 2009), thus constituting plausible functional networks. Critically, the strength of these networks “at rest” predicts both behavioral accuracy and subsequent activation of the same brain areas during task performance (e.g., Hampson et al., 2006; Seeley et al., 2007; Kelly et al., 2008; Kim et al., 2009; Tambini et al., 2010). Further, there is growing evidence that alterations in rsFC strength can potentially be used to assess various neuropsychiatric disease trajectories, and where available treatment outcomes, including: Alzheimer’s disease (Lustig et al., 2003; Greicius et al., 2004; Rombouts et al., 2005; Wang et al., 2006), autism (Kennedy et al., 2006), depression (Anand et al., 2005), multiple sclerosis (Lowe et al., 2002), and attention deficit/hyperactive disorder (ADHD; Tian et al., 2006). Emerging evidence further suggests a genetic linkage between rsFC networks and various behavioral phenotypes (Meyer-Lindenberg, 2009; Glahn et al., 2010), raising promise that functional connectivity may serve as a systems-level biomarker to identify individual differences in
