4.5 Article

STATE-DEPENDENT VARIABILITY OF DYNAMIC FUNCTIONAL CONNECTIVITY BETWEEN FRONTOPARIETAL AND DEFAULT NETWORKS RELATES TO COGNITIVE FLEXIBILITY

Journal

NEUROSCIENCE
Volume 339, Issue -, Pages 12-21

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neuroscience.2016.09.034

Keywords

brain dynamics; cognition; resting-state fMRI

Categories

Funding

  1. National Center for Research Resources [S10RR014978]
  2. National Institutes of Health [R01-NS069696, 5R01-NS060918, U01MH093765, S10RR023043, S10RR023401]
  3. National Science Foundation [1042134]
  4. Dutch Organization for Scientific Research (Rubicon) [825.11.002, 016.146.086]
  5. Society in Science
  6. National Center for Research Resources [S10RR014978]
  7. National Institutes of Health [R01-NS069696, 5R01-NS060918, U01MH093765, S10RR023043, S10RR023401]
  8. National Science Foundation [1042134]
  9. Dutch Organization for Scientific Research (Rubicon) [825.11.002, 016.146.086]
  10. Society in Science
  11. Division Of Mathematical Sciences
  12. Direct For Mathematical & Physical Scien [1042134] Funding Source: National Science Foundation

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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. (C) 2016 The Authors. Published by Elsevier Ltd on behalf of IBRO. This is an open access article under the CC BY-NC-ND license.

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