DOI: 10.1162/netn_a_00330 ISSN: 2472-1751

The human brain connectome weighted by the myelin content and total intra-axonal cross-sectional area of white matter tracts

Mark C. Nelson, Jessica Royer, Wen Da Lu, Ilana R. Leppert, Jennifer S. W. Campbell, Simona Schiavi, Hyerang Jin, Shahin Tavakol, Reinder Vos de Wael, Raul Rodriguez-Cruces, G. Bruce Pike, Boris C. Bernhardt, Alessandro Daducci, Bratislav Misic, Christine L. Tardif
  • Applied Mathematics
  • Artificial Intelligence
  • Computer Science Applications
  • General Neuroscience


A central goal in neuroscience is the development of a comprehensive mapping between structural and functional brain features, which facilitates mechanistic interpretation of brain function. However, the interpretability of structure-function brain models remains limited by a lack of biological detail. Here, we characterize human structural brain networks weighted by multiple white matter microstructural features including total intra-axonal cross-sectional area and myelin content. We report edge-weight-dependent spatial distributions, variance, small-worldness, rich club, hubs, as well as relationships with function, edge length, and myelin. Contrasting networks weighted by the total intra-axonal cross-sectional area and myelin content of white matter tracts, we find opposite relationships with functional connectivity, an edge-length-independent inverse relationship with each other, and the lack of a canonical rich club in myelin-weighted networks. When controlling for edge length, networks weighted by either fractional anisotropy, radial diffusivity, or neurite density show no relationship with whole-brain functional connectivity. We conclude that the co-utilization of structural networks weighted by total intra-axonal cross-sectional area and myelin content could improve our understanding of the mechanisms mediating the structure-function brain relationship.

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