Brain Age: A State-Of-Mind? On the Stability of Functional Connectivity across Behavioral States.

Editor's Note: These short, critical reviews of recent papers in the Journal, written exclusively by graduate students or postdoctoral fellows, are intended to summarize the important findings of the paper and provide additional insight and commentary. For more information on the format and purpose of the Journal Club, please see Review of Geerligs et al. The study of functional connectivity (FC) has become a major branch of functional MRI (fMRI) research. Biswal et al. (1995)'s seminal discovery, that voxels in the sensorimotor cortex exhibited highly correlated activity at rest, seeded the field; however, it took at least 10 more years for it to gain widespread interest (Cordes et al. There is currently much research into using FC as a biomarker for clinical diagnosis (Greicius, 2008; Linden, 2012) and, more generally, to gain insight into individual differences in brain function (Smith et al., 2013). Most studies investigate FC in the so-called " resting state " : subjects in the scanner are instructed to " lie still and think of nothing in particular, " with eyes closed, or open and fixating (Patriat et al., 2013); however, FC can also be computed from task fMRI data, usually after regressing out stimulus-evoked activity (Fair et al., 2007). Cole et al. (2014) showed that, on average across subjects, a reliable intrinsic network structure is preserved through all tasks and rest. Additionally, ϳ40% of the connections show mild but significant changes that are task-(equivalently, state-) dependent. The variability of FC in individual subjects is now well recognized ; functional network structure actually moves through several states within the span of a single resting-state run (Hutchison et al., 2013; Allen et al., 2014). While some authors have used the dynamic nature of individual network structure to their advantage, e.g., Damaraju et al. (2014), there is growing concern that this variability could impede our ability to use FC as a stable, trait-like measure of individual subjects. A recent study in The Journal of Neuroscience (Geerligs et al., 2015) reinforces this concern. Geerligs et al. (2015)'s study is among the first published outputs of the Cam-bridge Centre for Ageing and Neur-oscience (Cam-CAN) cohort study, a large-scale (N ϭ ϳ700), multimodal (MRI, MEG, and behavioral), cross-sectional, population-based adult lifespan (18 – 87 years old) investigation of the neural underpinnings of successful cogni-tive aging (Shafto et al., 2014; Taylor et al., 2015). Geerligs et al. (2015) used state-of-the-art imaging and preprocessing …