The heritability of multi-modal connectivity in human brain activity

  1. Giles L Colclough  Is a corresponding author
  2. Stephen M Smith
  3. Tom E Nichols
  4. Anderson M Winkler
  5. Stamatios N Sotiropoulos
  6. Matthew F Glasser
  7. David C Van Essen
  8. Mark W Woolrich
  1. University of Oxford, United Kingdom
  2. University of Warwick, United Kingdom
  3. Washington University, United States
  4. Washington University in St Louis, United States

Abstract

Patterns of intrinsic human brain activity exhibit a profile of functional connectivity that is associated with behaviour and cognitive performance, and deteriorates with disease. This paper investigates the relative importance of genetic factors and the common environment between twins in determining this functional connectivity profile. Using functional magnetic resonance imaging (fMRI) on 820 subjects from the Human Connectome Project, and magnetoencephalographic (MEG) recordings from a subset, the heritability of connectivity between 39 cortical regions was estimated. On average over all connections, genes account for about 15% of the observed variance in fMRI connectivity (and about 10% in alpha-band and 20% in beta-band oscillatory power synchronisation), which substantially exceeds the contribution from the environment shared between twins. Therefore, insofar as twins share a common upbringing, it appears that genes, rather than the developmental environment, play a dominant role in determining the coupling of neuronal activity.

Data availability

The following previously published data sets were used
    1. Van Essen DC et al.
    (2013) The Human Connectome Project HCP500 data release
    Open access dataset available from ConnectomeDB (https://db.humanconnectome.org/app/template/Login.vm). Account registration is required and access to certain data elements such as family structure is subject to restricted use terms (please see http://www.humanconnectome.org/study/hcp-young-adult/data-use-terms).
    1. Larson-Prior LJ
    (2013) The Human Connectome Project MEG2 data release
    Open access dataset available from ConnectomeDB (https://db.humanconnectome.org/app/template/Login.vm). Account registration is required and access to certain data elements such as family structure is subject to restricted use terms (please see http://www.humanconnectome.org/study/hcp-young-adult/data-use-terms).

Article and author information

Author details

  1. Giles L Colclough

    Oxford Centre for Human Brain Activity, University of Oxford, Oxford, United Kingdom
    For correspondence
    giles.colclough@ohba.ox.ac.uk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1074-7186
  2. Stephen M Smith

    Oxford Centre for Human Brain Activity, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  3. Tom E Nichols

    Department of Statistics and WMG, University of Warwick, Coventry, United Kingdom
    Competing interests
    No competing interests declared.
  4. Anderson M Winkler

    Oxford Centre for Human Brain Activity, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  5. Stamatios N Sotiropoulos

    Oxford Centre for Human Brain Activity, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.
  6. Matthew F Glasser

    School of Medicine, Washington University, St. Louis, United States
    Competing interests
    No competing interests declared.
  7. David C Van Essen

    School of Medicine, Washington University in St Louis, St. Louis, United States
    Competing interests
    David C Van Essen, Senior editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7044-4721
  8. Mark W Woolrich

    Oxford Centre for Human Brain Activity, University of Oxford, Oxford, United Kingdom
    Competing interests
    No competing interests declared.

Funding

Research Councils UK (Digital Economy Programme (EP/G036861/1,Centre for Doctoral Training in Healthcare Innovation))

  • Giles L Colclough

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq,211534/2013-7)

  • Anderson M Winkler

Engineering and Physical Sciences Research Council (EP/L023067)

  • Stamatios N Sotiropoulos

National Institutes of Health (R01EB015611-01; NRSA fellowship (F30-MH097312); 1U54MH091657)

  • Tom E Nichols
  • Matthew F Glasser
  • David C Van Essen

National Institute for Health Research (NIHR Oxford Biomedical Research Centre)

  • Mark W Woolrich

Medical Research Council (MRC UK MEG Partnership Grant (MR/K005464/1))

  • Giles L Colclough
  • Mark W Woolrich

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: HCP data were acquired using protocols approved by the Washington University institutional review board. Informedconsent was obtained from subjects. Anonymised data are publicly available from ConnectomeDB (db.humanconnectome.org; Hodge et al. (2016)). Certain parts of the dataset used in this study, such as the family structures of the subjects, are available subject to restricted data usage terms, requiring researchers to ensure that the anonymity of subjects is protected (Van Essen et al., 2013).

Copyright

© 2017, Colclough et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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