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Endogenous Human Brain Dynamics Recover Slowly Following Cognitive Effort

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  • Anna Barnes
  • Edward T Bullmore
  • John Suckling

Abstract

Background: In functional magnetic resonance imaging, the brain's response to experimental manipulation is almost always assumed to be independent of endogenous oscillations. To test this, we addressed the possible interaction between cognitive task performance and endogenous fMRI oscillations in an experiment designed to answer two questions: 1) Does performance of a cognitively effortful task significantly change fractal scaling properties of fMRI time series compared to their values before task performance? 2) If so, can we relate the extent of task-related perturbation to the difficulty of the task? Methodology/Principal Findings: Using a novel continuous acquisition “rest-task-rest” design, we found that endogenous dynamics tended to recover their pre-task parameter values relatively slowly, over the course of several minutes, following completion of one of two versions of the n-back working memory task and that the rate of recovery was slower following completion of the more demanding (n = 2) version of the task. Conclusion/Significance: This result supports the model that endogenous low frequency oscillatory dynamics are relevant to the brain's response to exogenous stimulation. Moreover, it suggests that large-scale neurocognitive systems measured using fMRI, like the heart and other physiological systems subjected to external demands for enhanced performance, can take a considerable period of time to return to a stable baseline state.

Suggested Citation

  • Anna Barnes & Edward T Bullmore & John Suckling, 2009. "Endogenous Human Brain Dynamics Recover Slowly Following Cognitive Effort," PLOS ONE, Public Library of Science, vol. 4(8), pages 1-6, August.
    • Handle: RePEc:plo:pone00:0006626
    DOI: 10.1371/journal.pone.0006626
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    References listed on IDEAS

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    1. Manfred G Kitzbichler & Marie L Smith & Søren R Christensen & Ed Bullmore, 2009. "Broadband Criticality of Human Brain Network Synchronization," PLOS Computational Biology, Public Library of Science, vol. 5(3), pages 1-13, March.
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    1. Fabrizio Esposito & Tobias Otto & Fred R H Zijlstra & Rainer Goebel, 2014. "Spatially Distributed Effects of Mental Exhaustion on Resting-State FMRI Networks," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-13, April.
    2. Vivien Marmelat & Kjerstin Torre & Peter J Beek & Andreas Daffertshofer, 2014. "Persistent Fluctuations in Stride Intervals under Fractal Auditory Stimulation," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-9, March.
    3. Danielle S Bassett & Nicholas F Wymbs & M Puck Rombach & Mason A Porter & Peter J Mucha & Scott T Grafton, 2013. "Task-Based Core-Periphery Organization of Human Brain Dynamics," PLOS Computational Biology, Public Library of Science, vol. 9(9), pages 1-16, September.

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