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Functional alignment with anatomical networks is associated with cognitive flexibility

Nature Human Behaviourvolume 2pages156164 (2018) | Download Citation

Abstract

Cognitive flexibility describes the human ability to switch between modes of mental function to achieve goals. Mental switching is accompanied by transient changes in brain activity, which must occur atop an anatomical architecture that bridges disparate cortical and subcortical regions via underlying white matter tracts. However, an integrated understanding of how white matter networks might constrain brain dynamics during cognitive processes requiring flexibility has remained elusive. Here, to address this challenge, we applied emerging tools from graph signal processing to examine whether blood oxygen level-dependent signals measured at each point in time correspond to complex underlying anatomical networks in 28 individuals performing a perceptual task that probed cognitive flexibility. We found that the alignment between functional signals and the architecture of the underlying white matter network was associated with greater cognitive flexibility across subjects. By computing a concise measure using multi-modal neuroimaging data, we uncovered an integrated structure–function relation of human behaviour.

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Acknowledgements

J.D.M. acknowledges support from the Office of the Director at the National Institutes of Health through grant number 1-DP5-OD-021352-01 and the Perelman School of Medicine. D.S.B. acknowledges support from the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, the Army Research Laboratory and the Army Research Office through contract numbers W911NF-10-2-0022 and W911NF-14-1-0679, the National Institute of Health (R01-DC-009209-11, R01-HD-086888-01, R01-MH-107235, R01-MH107703, R01-MH-109520, R01-NS-099348 and R21-MH-106799), the Office of Naval Research and the National Science Foundation (BCS-1441502, CAREER PHY-1554488, BCS-1631550, and CNS-1626008). The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding agencies. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Affiliations

  1. Department of Psychology, Drexel University, Philadelphia, PA, USA

    • John D. Medaglia
    •  & Apoorva Kelkar
  2. Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    • John D. Medaglia
  3. Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA

    • Weiyu Huang
    • , Alejandro Ribeiro
    •  & Danielle S. Bassett
  4. Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA

    • Elisabeth A. Karuza
    •  & Sharon L. Thompson-Schill
  5. Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA

    • Danielle S. Bassett

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Contributions

J.D.M. conceptualized the overall project, created the behavioural tasks, collected the data, wrote the manuscript and conducted behavioural and network data processing and analyses. W.H. performed primary analyses using GFT to integrate BOLD fMRI data with anatomical networks and to correlate them with cognitive measures. E.A.K. preprocessed BOLD fMRI data. A.K. adapted processing procedures to analyse the Human Connectome Project data. S.L.T.-S. assisted with the behavioural task design. A.R. supervised applications of the GFT analysis to the imaging data. D.S.B. funded the data acquisition, assisted with the interpretation of the primary findings and edited the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Danielle S. Bassett.

Supplementary information

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    Supplementary Results, Supplementary Tables 1–39, Supplementary Figures 1–8, Supplementary References.

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DOI

https://doi.org/10.1038/s41562-017-0260-9

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