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Scaling Principles of White Matter Connectivity in the Human and Nonhuman Primate Brain

  • Dirk Jan Ardesch*
  • , Lianne H. Scholtens
  • , Siemon C. De Lange
  • , Lea Roumazeilles
  • , Alexandre A. Khrapitchev
  • , Todd M. Preuss
  • , James K. Rilling
  • , Rogier B. Mars
  • , Martijn P. Van Den Heuvel
  • *Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Brains come in many shapes and sizes. Nature has endowed big-brained primate species like humans with a proportionally large cerebral cortex. Comparative studies have suggested, however, that the total volume allocated to white matter connectivity - the brain's infrastructure for long-range interregional communication - does not keep pace with the cortex. We investigated the consequences of this allometric scaling on brain connectivity and network organization. We collated structural and diffusion magnetic resonance imaging data across 14 primate species, describing a comprehensive 350-fold range in brain size across species. We show volumetric scaling relationships that indeed point toward a restriction of macroscale connectivity in bigger brains. We report cortical surface area to outpace white matter volume, with larger brains showing lower levels of overall connectedness particularly through sparser long-range connectivity. We show that these constraints on white matter connectivity are associated with longer communication paths, higher local network clustering, and higher levels of asymmetry in connectivity patterns between homologous areas across the left and right hemispheres. Our findings reveal conserved scaling relationships of major brain components and show consequences for macroscale brain circuitry, providing insights into the connectome architecture that could be expected in larger brains such as the human brain.

Original languageEnglish
Article numberbhab384
Pages (from-to)2831-2842
Number of pages12
JournalCerebral cortex (New York, N.Y. : 1991)
Volume32
Issue number13
Early online date24 Nov 2021
DOIs
Publication statusPublished - 1 Jul 2022

Bibliographical note

Publisher Copyright:
© 2021 The Author(s) 2021. Published by Oxford University Press.

Funding

FundersFunder number
National Institute of Neurological Disorders and StrokeR24NS092988
NIH Office of the DirectorP51OD011132
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UK Research and InnovationBB/M011224/1
National Institute on AgingP01AG026423
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Wellcome Trust203139

    Keywords

    • allometry
    • connectome
    • evolution
    • neuroimaging
    • specialization

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