An expanding manifold in transmodal regions characterizes adolescent reconfiguration of structural connectome organization

Abstract

Adolescence is a critical time for the continued maturation of brain networks. Here, we assessed structural connectome development in a large longitudinal sample ranging from childhood to young adulthood. By projecting high-dimensional connectomes into compact manifold spaces, we identified a marked expansion of structural connectomes with the strongest effects in transmodal regions during adolescence. Findings reflected increased within-module connectivity together with increased segregation, indicating increasing differentiation of higher-order association networks from the rest of the brain. Projection of subcortico-cortical connectivity patterns into these manifolds showed parallel alterations in pathways centered on the caudate and thalamus. Connectome findings were contextualized via spatial transcriptome association analysis, highlighting genes enriched in cortex, thalamus, and striatum. Statistical learning of cortical and subcortical manifold features at baseline and their maturational change predicted measures of intelligence at follow-up. Our findings demonstrate that connectome manifold learning can bridge the conceptual and empirical gaps between macroscale network reconfigurations, microscale processes, and cognitive outcomes in adolescent development.

Data availability

The imaging and phenotypic data were provided by the Neuroscience in Psychiatry Network (NSPN) 2400 cohort. As stated in https://doi.org/10.1093/ije/dyx117, the NSPN project is committed to make the anonymised dataset fully available to the research community, and participants have consented to their de-identified data being made available to other researchers. A data request can be made to openNSPN@medschl.cam.ac.uk. Codes for connectome manifold generation are available at https://github.com/MICA-MNI/BrainSpace and those for calculating manifold eccentricity and subcortical-weighted manifold, as well as performing linear mixed effect modeling to assess age-effects on these features at https://github.com/MICA-MNI/micaopen/tree/master/manifold_features.

Article and author information

Author details

  1. Bo-yong Park

    Department of Data Science, Inha University, Incheon, Republic of Korea
    For correspondence
    by9433@gmail.com
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7096-337X
  2. Richard AI Bethlehem

    Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0714-0685
  3. Casey Paquola

    Neurology and Neurosurgery, McGill University, Montreal, Canada
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0190-4103
  4. Sara Larivière

    Neurology and Neurosurgery, McGill University, Montreal, Canada
    Competing interests
    No competing interests declared.
  5. Raul Rodríguez-Cruces

    Neurology and Neurosurgery, McGill University, Montreal, Canada
    Competing interests
    No competing interests declared.
  6. Reinder Vos de Wael

    McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
    Competing interests
    No competing interests declared.
  7. Neuroscience in Psychiatry Network (NSPN) Consortium

  8. Edward T Bullmore

    Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    Edward T Bullmore, E.T.B. serves on the scientific advisory board of Sosei Heptares and as a consultant for GlaxoSmithKline..
  9. Boris C Bernhardt

    Neurology and Neurosurgery, McGill University, Montreal, Canada
    For correspondence
    boris.bernhardt@mcgill.ca
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9536-7862

Funding

Canada Research Chairs

  • Boris C Bernhardt

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.The Neuroscience and Psychiatry Network (NSPN) study was funded by a Wellcome Trust award to the University of Cambridge and University College London. The data were curated and analyzed using a computational facility funded by an MRC research infra-structure award (MR/M009041/1) and supported by the NIHR Cambridge Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.

Reviewing Editor

  1. Lucina Q Uddin, University of Miami, United States

Ethics

Human subjects: Participants provided informed written consent for each aspect of the study, and parental consent was obtained for those aged 14-15 y old. Ethical approval was granted for this study by the NHS NRES Committee East of England-Cambridge Central (project ID 97546). The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

Version history

  1. Received: November 7, 2020
  2. Accepted: March 30, 2021
  3. Accepted Manuscript published: March 31, 2021 (version 1)
  4. Version of Record published: April 30, 2021 (version 2)

Copyright

© 2021, Park 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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  1. Bo-yong Park
  2. Richard AI Bethlehem
  3. Casey Paquola
  4. Sara Larivière
  5. Raul Rodríguez-Cruces
  6. Reinder Vos de Wael
  7. Neuroscience in Psychiatry Network (NSPN) Consortium
  8. Edward T Bullmore
  9. Boris C Bernhardt
(2021)
An expanding manifold in transmodal regions characterizes adolescent reconfiguration of structural connectome organization
eLife 10:e64694.
https://doi.org/10.7554/eLife.64694

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https://doi.org/10.7554/eLife.64694

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