State-dependent variability of dynamic functional connectivity between frontoparietal and default networks relates to cognitive flexibility

• Published in: Neuroscience Vol. 339; pp. 12 - 21
• Main Authors: Douw, Linda, Wakeman, Daniel G., Tanaka, Naoaki, Liu, Hesheng, Stufflebeam, Steven M.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 17.12.2016
• Subjects: Adult; Brain - diagnostic imaging; Brain - physiology; brain dynamics; Brain Mapping; cognition; Cognition - physiology; Cohort Studies; Executive Function - physiology; Female; Humans; Magnetic Resonance Imaging; Male; Neural Pathways - diagnostic imaging; Neural Pathways - physiology; Neurology; Rest; resting-state fMRI; Stroop Test; PCC; DMN; cognition; FDR; FPN; vdFC; resting-state fMRI; brain dynamics; EPI; frontoparietal network; variability of dynamic functional connectivity; echo planar imaging; posterior cingulate cortex; default mode network; false discovery rate
• ISSN: 0306-4522; 1873-7544; 1873-7544
• DOI: 10.1016/j.neuroscience.2016.09.034

•Higher task-state FPN–DMN dynamics associate with greater cognitive flexibility.•Higher resting-state FPN–DMN dynamics relate to poorer performance.•Cognitive flexibility depends on state-dependent dynamic connectivity. The brain is a dynamic, flexible network that continuously reconfigures. However, the neural underpinnings of how state-dependent variability of dynamic functional connectivity (vdFC) relates to cognitive flexibility are unclear. We therefore investigated flexible functional connectivity during resting-state and task-state functional magnetic resonance imaging (rs-fMRI and t-fMRI, resp.) and performed separate, out-of-scanner neuropsychological testing. We hypothesize that state-dependent vdFC between the frontoparietal network (FPN) and the default mode network (DMN) relates to cognitive flexibility. Seventeen healthy subjects performed the Stroop color word test and underwent t-fMRI (Stroop computerized version) and rs-fMRI. Time series were extracted from a cortical atlas, and a sliding window approach was used to obtain a number of correlation matrices per subject. vdFC was defined as the standard deviation of connectivity strengths over these windows. Higher task-state FPN–DMN vdFC was associated with greater out-of-scanner cognitive flexibility, while the opposite relationship was present for resting-state FPN–DMN vdFC. Moreover, greater contrast between task-state and resting-state vdFC related to better cognitive performance. In conclusion, our results suggest that not only the dynamics of connectivity between these networks is seminal for optimal functioning, but also that the contrast between dynamics across states reflects cognitive performance.