Characterizing functional integrity: intraindividual brain signal variability predicts memory performance in patients...

Computational modeling suggests that variability in brain signals provides important information regarding the system's capacity to adopt different network configurations that may promote optimal responding to stimuli. Although there is limited empirical work on this construct, a recent study indicates that age-related decreases in variability across the adult lifespan correlate with less efficient and less accurate performance. Here, we extend this construct to the assessment of cerebral integrity by comparing fMRI BOLD variability and fMRI BOLD amplitude in their ability to account for differences in functional capacity in patients with focal unilateral medial temporal dysfunction. We were specifically interested in whether either of these BOLD measures could identify a link between the affected medial temporal region and memory performance (as measured by a clinical test of verbal memory retention). Using partial least-squares analyses, we found that variability in a set of regions including the left hippocampus predicted verbal retention and, furthermore, this relationship was similar across a range of cognitive tasks measured during scanning (i.e., the same pattern was seen in fixation, autobiographical recall, and word generation). In contrast, signal amplitude in the hippocampus did not predict memory performance, even for a task that reliably activates the medial temporal lobes (i.e., autobiographical recall). These findings provide a powerful validation of the concept that variability in brain signals reflects functional integrity. Furthermore, this measure can be characterized as a robust biomarker in this clinical setting because it reveals the same pattern regardless of cognitive challenge or task engagement during scanning.