The individuality of shape asymmetries of the human cerebral cortex

  1. Yu-Chi Chen  Is a corresponding author
  2. Aurina Arnatkevičiūtė
  3. Eugene McTavish
  4. James C Pang
  5. Sidhant Chopra
  6. Chao Suo
  7. Alex Fornito
  8. Kevin M Aquino
  9. for the Alzheimer's Disease Neuroimaging Initiative
  1. Monash University, Australia
  2. Yale University, United States
  3. University of Sydney, Australia

Abstract

Asymmetries of the cerebral cortex are found across diverse phyla and are particularly pronounced in humans, with important implications for brain function and disease. However, many prior studies have confounded asymmetries due to size with those due to shape. Here, we introduce a novel approach to characterize asymmetries of the whole cortical shape, independent of size, across different spatial frequencies using magnetic resonance imaging data in three independent datasets. We find that cortical shape asymmetry is highly individualized and robust, akin to a cortical fingerprint, and identifies individuals more accurately than size-based descriptors, such as cortical thickness and surface area, or measures of inter-regional functional coupling of brain activity. Individual identifiability is optimal at coarse spatial scales (~37 mm wavelength), and shape asymmetries show scale-specific associations with sex and cognition, but not handedness. While unihemispheric cortical shape shows significant heritability at coarse scales (~65 mm wavelength), shape asymmetries are determined primarily by subject-specific environmental effects. Thus, coarse-scale shape asymmetries are highly personalized, sexually dimorphic, linked to individual differences in cognition, and are primarily driven by stochastic environmental influences.

Data availability

All data generated or analysed during this study are included in the manuscript. All code and dependent toolboxes used in this study can be found at: https://github.com/cyctbdbw/Shape-Asymmetry-Signature. The code of shape-DNA can be found at: http://reuter.mit.edu/software/shapedna/. The OASIS-3 dataset is available under https://www.oasis-brains.org/. The ADNI dataset is available under https://adni.loni.usc.edu. The HCP dataset is available under https://db.humanconnectome.org/.

The following previously published data sets were used

Article and author information

Author details

  1. Yu-Chi Chen

    Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
    For correspondence
    yu-chi.chen@monash.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9167-6417
  2. Aurina Arnatkevičiūtė

    Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
    Competing interests
    No competing interests declared.
  3. Eugene McTavish

    Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
    Competing interests
    No competing interests declared.
  4. James C Pang

    Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2461-2760
  5. Sidhant Chopra

    Department of Psychology, Yale University, New Haven, United States
    Competing interests
    No competing interests declared.
  6. Chao Suo

    Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
    Competing interests
    No competing interests declared.
  7. Alex Fornito

    Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia
    Competing interests
    Alex Fornito, Reviewing editor, eLife.
  8. Kevin M Aquino

    Center of Excellence for Integrative Brain Function, University of Sydney, Sydney, Australia
    Competing interests
    Kevin M Aquino, is a scientific advisor and shareholder in BrainKey Inc., a medical image analysis software company..

Funding

Sylvia and Charles Viertel Charitable Foundation (Senior Medical Research Fellowship)

  • Alex Fornito

National Health and Medical Research Council (1197431)

  • Alex Fornito

National Health and Medical Research Council (1146292)

  • Alex Fornito

Australian Research Council (DP200103509)

  • Alex Fornito

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

Reviewing Editor

  1. Ingrid S Johnsrude, University of Western Ontario, Canada

Ethics

Human subjects: This study only involved subjects from the open-sourced datasets, and all subjects were de-identified by the datasets. Each dataset was approved by its relevant ethics committee and obtained written informed consent from each participant.

Version history

  1. Preprint posted: September 15, 2021 (view preprint)
  2. Received: October 28, 2021
  3. Accepted: October 4, 2022
  4. Accepted Manuscript published: October 5, 2022 (version 1)
  5. Accepted Manuscript updated: October 6, 2022 (version 2)
  6. Version of Record published: November 16, 2022 (version 3)

Copyright

© 2022, Chen 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. Yu-Chi Chen
  2. Aurina Arnatkevičiūtė
  3. Eugene McTavish
  4. James C Pang
  5. Sidhant Chopra
  6. Chao Suo
  7. Alex Fornito
  8. Kevin M Aquino
  9. for the Alzheimer's Disease Neuroimaging Initiative
(2022)
The individuality of shape asymmetries of the human cerebral cortex
eLife 11:e75056.
https://doi.org/10.7554/eLife.75056

Share this article

https://doi.org/10.7554/eLife.75056

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