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Two common and distinct forms of variation in human functional brain networks

Nature Neuroscience (2024)Cite this article

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Abstract

The cortex has a characteristic layout with specialized functional areas forming distributed large-scale networks. However, substantial work shows striking variation in this organization across people, which relates to differences in behavior. While most previous work treats individual differences as linked to boundary shifts between the borders of regions, here we show that cortical ‘variants’ also occur at a distance from their typical position, forming ectopic intrusions. Both ‘border’ and ‘ectopic’ variants are common across individuals, but differ in their location, network associations, properties of subgroups of individuals, activations during tasks, and prediction of behavioral phenotypes. Border variants also track significantly more with shared genetics than ectopic variants, suggesting a closer link between ectopic variants and environmental influences. This work argues that these two dissociable forms of variation—border shifts and ectopic intrusions—must be separately accounted for in the analysis of individual differences in cortical systems across people.

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Fig. 1: Variant definition, splitting and classification as border or ectopic.
Fig. 2: Prevalence of border and ectopic variants across individuals.
Fig. 3: Spatial distributions of ectopic and border variants.
Fig. 4: Network linkages of border and ectopic variants.
Fig. 5: Task-evoked activation of variant locations in the MSC and HCP.
Fig. 6: Estimating the genetic influence of border and ectopic variants across individuals in the HCP dataset.
Fig. 7: Similarity of border and ectopic variants across subgroups of individuals.

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Data availability

Data from the MSC are publicly available at https://openneuro.org/datasets/ds000224/. Imaging data from the HCP (1200 Subjects Release) can be accessed at https://db.humanconnectome.org/; some data elements utilized in this work (for example, family structure and behavioral measures) require second-tier permissions from the HCP for access. Data associated with the WashU 120 are available at https://openneuro.org/datasets/ds000243/versions/00001/.

Code availability

Code for original network variant definition and primary analyses is available at https://github.com/MidnightScanClub/SeitzmanGratton-2019-PNAS/. Code used to analyze border and ectopic variants is available at https://github.com/GrattonLab/Dworetsky_BorderEctopicVariants/.

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Acknowledgements

Funding was provided by National Institutes of Health (NIH) grant R01MH118370 (to C.G.), the James S. McDonnell Foundation (to S.E.P.), NIH grant R01MH111640 (to M.N.), NIH grant T32MH100019 (to A.N.N.), the Therapeutic Cognitive Neuroscience Fund (to D.M.S.) and NIH grant K01AA030083 (to A.S.H.).

Author information

Authors and Affiliations

  1. Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA

    Ally Dworetsky & Steven E. Petersen

  2. Department of Psychology, Florida State University, Tallahassee, FL, USA

    Ally Dworetsky & Caterina Gratton

  3. Department of Psychology, Northwestern University, Evanston, IL, USA

    Ally Dworetsky, Derek M. Smith & Caterina Gratton

  4. Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA

    Benjamin A. Seitzman

  5. Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA

    Babatunde Adeyemo, Ashley N. Nielsen & Steven E. Petersen

  6. Department of Psychological and Brain Sciences, Washington University School of Medicine, St. Louis, MO, USA

    Alexander S. Hatoum & Steven E. Petersen

  7. Department of Neurology, Division of Cognitive Neurology/Neuropsychology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Derek M. Smith

  8. Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom

    Thomas E. Nichols

  9. Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

    Thomas E. Nichols

  10. Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA

    Maital Neta

  11. Center for Brain, Biology, and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA

    Maital Neta

  12. Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA

    Steven E. Petersen

  13. Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA

    Steven E. Petersen

  14. Neuroscience Program, Florida State University, Tallahassee, FL, USA

    Caterina Gratton

  15. Department of Neurology, Northwestern University, Evanston, IL, USA

    Caterina Gratton

  16. Interdepartmental Neuroscience Program, Northwestern University, Evanston, IL, USA

    Caterina Gratton

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  1. Ally Dworetsky
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Contributions

Conceptualization: C.G., S.E.P., B.A.S. and A.D.; methodology, formal analysis and visualization: A.D., C.G., A.N.N., B.A.S., D.M.S., A.S.H. and T.E.N.; writing: A.D. and C.G.; review and editing: B.A.S., M.N., S.E.P., B.A., A.N.N., A.S.H., T.E.N., D.M.S., A.D. and C.G.; supervision and funding: C.G., S.E.P., M.N., A.N.N., D.M.S. and A.S.H.

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Correspondence to Caterina Gratton.

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Supplementary Results, Figs. 1–22 and Tables 1–3.

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Dworetsky, A., Seitzman, B.A., Adeyemo, B. et al. Two common and distinct forms of variation in human functional brain networks. Nat Neurosci (2024). https://doi.org/10.1038/s41593-024-01618-2

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