biostudies-literatureNelson MCNSERC-DiscoveryBrain Canada Azrieli Future LeadersFonds de Recherche du Québec – Santé, Research Scholar Junior 1Tier-2 Canada Research Chairs ProgramAzrieli Center for Autism Research, Montreal Neurological InstituteSickkids New InvestigatorCIHRHealthy Brains for Healthy Lives1363-1388https://www.ebi.ac.uk/biostudies/studies/S-EPMC10697181biostudies-literatureUnknown7(4)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 relationshipNetwork neuroscience (Cambridge, Mass.)The human brain connectome weighted by the myelin content and total intra-axonal cross-sectional area of white matter tracts.PMC106971811304413, DGECR-2018-002161c-ll-13NI17-039280246 and 266479FDN-154298, PJT-1749951304413, RGPIN-2018-05176Lu WDTavakol SMisic BCampbell JSWNelson MCTardif CLDaducci ABernhardt BCSchiavi SRoyer JJin HVos de Wael RPike GBLeppert IRRodriguez-Cruces RfalseThe human brain connectome weighted by the myelin content and total intra-axonal cross-sectional area of white matter tracts.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 relationship2023-01-01T00:00:00Z20232026-06-03T11:46:38.747Z2025-04-19T14:32:50.722ZS-EPMC106971813814469110.1162/netn_a_00330