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Multi-task connectivity reveals flexible hubs for adaptive task control

Nature Neuroscience volume 16, pages 1348–1355 (2013)Cite this article

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Abstract

Extensive evidence suggests that the human ability to adaptively implement a wide variety of tasks is preferentially a result of the operation of a fronto-parietal brain network (FPN). We hypothesized that this network's adaptability is made possible by flexible hubs: brain regions that rapidly update their pattern of global functional connectivity according to task demands. Using recent advances in characterizing brain network organization and dynamics, we identified mechanisms consistent with the flexible hub theory. We found that the FPN's brain-wide functional connectivity pattern shifted more than those of other networks across a variety of task states and that these connectivity patterns could be used to identify the current task. Furthermore, these patterns were consistent across practiced and novel tasks, suggesting that reuse of flexible hub connectivity patterns facilitates adaptive (novel) task performance. Together, these findings support a central role for fronto-parietal flexible hubs in cognitive control and adaptive implementation of task demands.

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Figure 1: Conceptual illustration of task-control flexible hubs in the FPN.
Figure 2: The permuted rule operations behavioral procedure, in combination with recent advances in task-state connectivity methods, allows detection of flexible connectivity across a wide variety of task states.
Figure 3: Graph theoretical brain network partition and context-dependent functional connectivity estimation.
Figure 4: GVC, a measure of global variable connectivity, is highest for the FPN.
Figure 5: FPN's variable connectivity is truly global.
Figure 6: The FPN's connectivity varies systematically, suggesting the previous results were not simply a result of network noise properties and that FPN connectivity likely represents task information.
Figure 7: Decoding of task identity from FPN's context-dependent connectivity patterns.

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  • 05 August 2013

    In the version of this article initially published, in the sentence following the equation in Online Methods, an â character was substituted for the β. The error has been corrected in the HTML and PDF versions of the article.

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Acknowledgements

We thank S. Petersen, D. Bassett and J. Etzel for helpful feedback and suggestions during preparation of this manuscript. We also thank W. Schneider for access to data from his laboratory. Our work was supported by the US National Institutes of Health under awards K99MH096801 (M.W.C.), DP5OD012109-01 (A.A.) and a Brain and Behavior Research Foundation (NARSAD) Young Investigator Award (A.A.).

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Authors and Affiliations

  1. Department of Psychology, Washington University in St. Louis, St. Louis, Missouri, USA

    Michael W Cole & Todd S Braver

  2. Department of Psychology, University of Denver, Denver, Colorado, USA

    Jeremy R Reynolds

  3. Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA

    Jonathan D Power

  4. Department of Psychology, University of Ljubljana, Slovenia

    Grega Repovs

  5. Department of Psychiatry and the Abraham Ribicoff Research Facilities, Yale University, New Haven, Connecticut, USA

    Alan Anticevic

  6. National Institute on Alcohol Abuse and Alcoholism Center for the Translational Neuroscience of Alcoholism, New Haven, Connecticut, USA

    Alan Anticevic

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  1. Michael W Cole
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Contributions

M.W.C., T.S.B., J.R.R. and J.D.P. planned and conducted data analyses. M.W.C., T.S.B., J.D.P., J.R.R., G.R. and A.A. wrote the manuscript. All of the authors discussed data analysis choices, the results and the manuscript.

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Correspondence to Michael W Cole.

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Cole, M., Reynolds, J., Power, J. et al. Multi-task connectivity reveals flexible hubs for adaptive task control. Nat Neurosci 16, 1348–1355 (2013). https://doi.org/10.1038/nn.3470

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