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Peer-reviewedCC BYNature

White matter micro- and macrostructure brain charts for the human lifespan

  • Michael E. Kim1
  • Chenyu Gao2
  • Karthik Ramadass3,2
  • Nancy R. Newlin3
  • Praitayini Kanakaraj3
  • Sam Bogdanov4
  • Gaurav Rudravaram2
  • Derek B. Archer5,6,7
  • Timothy J. Hohman6,7
  • Angela Lee Jefferson8,9,10,11,7
  • Victoria L. Morgan12,13,14
  • Alexandra Roche14
24 more authors
  • Dario J. Englot12,3,2,15,13
  • Susan M. Resnick16
  • Lori L. Beason‐Held16
  • Laurie E. Cutting17,5
  • Laura A. Barquero17
  • Micah A. D’Archangel17
  • Tin Q. Nguyen17,5,14
  • Kathryn Leigh Humphreys11
  • Yanbin Niu11
  • Sophia Vinci‐Booher11
  • Carissa J. Cascio18
  • The HABS-HD Study Team
  • Sid E. O’Bryant19
  • Alzheimer’s Disease Neuroimaging Initiative
  • Arthur W. Toga20
  • The BIOCARD Study Team
  • Marilyn Albert21
  • L Taylor Davis13
  • Zhiyuan Li22
  • Simon Vandekar23
  • Panpan Zhang23,7
  • John C. Gore12,13,14
  • Bennett A. Landman24,25,26,27,28,29,30,31,32,33
  • Kurt G. Schilling34,35,36
36 affiliations
  1. 1Department of Computer Science, Vanderbilt University, Nashville, TN, USA. [email protected]
  2. 2Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
  3. 3Department of Computer Science, Vanderbilt University, Nashville, TN, USA
  4. 4Medical Scientist Training Program, Vanderbilt University, Nashville, TN, USA
  5. 5Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
  6. 6Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
  7. 7Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
  8. 8Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
  9. 9Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
  10. 10Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
  11. 11Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, USA
  12. 12Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
  13. 13Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
  14. 14Vanderbilt University Institute of Imaging Science, Nashville, TN, USA
  15. 15Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
  16. 16Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
  17. 17Department of Special Education, Peabody College of Education and Human Development, Nashville, TN, USA
  18. 18Life Span Institute and Department of Psychology, University of Kansas, Lawrence, KS, USA
  19. 19Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
  20. 20Laboratory of Neuro Imaging, Department of Neurology, University of California School of Medicine, Los Angeles, CA, USA
  21. 21Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
  22. 22Department of Computer Science, Park University, Parkville, MO, USA
  23. 23Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
  24. 24Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA. [email protected]
  25. 25Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA. [email protected]
  26. 26Department of Computer Science, Vanderbilt University, Nashville, TN, USA. [email protected]
  27. 27Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA. [email protected]
  28. 28Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA. [email protected]
  29. 29Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA. [email protected]
  30. 30Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, USA. [email protected]
  31. 31Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA. [email protected]
  32. 32Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA. [email protected]
  33. 33Vanderbilt University Institute of Imaging Science, Nashville, TN, USA. [email protected]
  34. 34Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA. [email protected]
  35. 35Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA. [email protected]
  36. 36Vanderbilt University Institute of Imaging Science, Nashville, TN, USA. [email protected]
Open at sourceDOICite

Abstract

Normative reference charts are widely used in healthcare, especially for assessing the development of individuals by benchmarking anatomic and physiological features against population trajectories across the lifespan. Recent work has extended this concept to gray matter morphology in the brain, but no such reference framework currently exists for white matter (WM) even though WM constitutes the essential substrate for neuronal communication and large-scale network integration. Here, we present the first comprehensive WM brain charts, which describe how microstructural and macrostructural features of WM evolve across the lifespan, by leveraging over 26,199 diffusion MRI scans from 42 harmonized studies. Using generalized additive models for location, scale, and shape (GAMLSS), we estimate age- and sex-stratified trajectories for 72 individual white matter pathways, quantifying both tract-specific microstructural and morphometric features. We demonstrate that these WM brain charts enable four important applications: (1) defining normative trajectories of WM maturation and decline across distinct pathways, (2) identifying previously uncharacterized developmental milestones and spatial gradients of tract maturation, (3) detecting individualized deviations from normative patterns with clinical relevance across multiple neurological disorders, and (4) facilitating standardized, cross-study centile scoring of new datasets. By establishing a unified, interpretable reference framework for WM structure, these brain charts provide a foundational metric for research and clinical neuroscience. The accompanying open-access trajectories, centile scoring tools, and harmonization methods facilitate precise mapping of WM development, aging, and pathology across diverse populations. We release the brain charts and provide an out-of-sample alignment process as a Docker image: https://zenodo.org/records/15367426.

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Cite

BibTeXRIS
BibTeX
@article{kim2026white,
  title = {{White matter micro- and macrostructure brain charts for the human lifespan}},
  author = {Michael E. Kim and Chenyu Gao and Karthik Ramadass and Nancy R. Newlin and Praitayini Kanakaraj and Sam Bogdanov and Gaurav Rudravaram and Derek B. Archer and Timothy J. Hohman and Angela Lee Jefferson and Victoria L. Morgan and Alexandra Roche and Dario J. Englot and Susan M. Resnick and Lori L. Beason‐Held and Laurie E. Cutting and Laura A. Barquero and Micah A. D’Archangel and Tin Q. Nguyen and Kathryn Leigh Humphreys and Yanbin Niu and Sophia Vinci‐Booher and Carissa J. Cascio and The HABS-HD Study Team and Sid E. O’Bryant and Alzheimer’s Disease Neuroimaging Initiative and Arthur W. Toga and The BIOCARD Study Team and Marilyn Albert and L Taylor Davis and Zhiyuan Li and Simon Vandekar and Panpan Zhang and John C. Gore and Bennett A. Landman and Kurt G. Schilling},
  journal = {Nature},
  year = {2026},
  month = may,
  doi = {10.1038/s41586-026-10454-2},
  url = {https://doi.org/10.1038/s41586-026-10454-2},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - White matter micro- and macrostructure brain charts for the human lifespan
AU  - Michael E. Kim
AU  - Chenyu Gao
AU  - Karthik Ramadass
AU  - Nancy R. Newlin
AU  - Praitayini Kanakaraj
AU  - Sam Bogdanov
AU  - Gaurav Rudravaram
AU  - Derek B. Archer
AU  - Timothy J. Hohman
AU  - Angela Lee Jefferson
AU  - Victoria L. Morgan
AU  - Alexandra Roche
AU  - Dario J. Englot
AU  - Susan M. Resnick
AU  - Lori L. Beason‐Held
AU  - Laurie E. Cutting
AU  - Laura A. Barquero
AU  - Micah A. D’Archangel
AU  - Tin Q. Nguyen
AU  - Kathryn Leigh Humphreys
AU  - Yanbin Niu
AU  - Sophia Vinci‐Booher
AU  - Carissa J. Cascio
AU  - The HABS-HD Study Team
AU  - Sid E. O’Bryant
AU  - Alzheimer’s Disease Neuroimaging Initiative
AU  - Arthur W. Toga
AU  - The BIOCARD Study Team
AU  - Marilyn Albert
AU  - L Taylor Davis
AU  - Zhiyuan Li
AU  - Simon Vandekar
AU  - Panpan Zhang
AU  - John C. Gore
AU  - Bennett A. Landman
AU  - Kurt G. Schilling
PY  - 2026
DA  - 2026/05/13
JO  - Nature
DO  - 10.1038/s41586-026-10454-2
UR  - https://doi.org/10.1038/s41586-026-10454-2
AB  - Normative reference charts are widely used in healthcare, especially for assessing the development of individuals by benchmarking anatomic and physiological features against population trajectories across the lifespan. Recent work has extended this concept to gray matter morphology in the brain, but no such reference framework currently exists for white matter (WM) even though WM constitutes the essential substrate for neuronal communication and large-scale network integration. Here, we present the first comprehensive WM brain charts, which describe how microstructural and macrostructural features of WM evolve across the lifespan, by leveraging over 26,199 diffusion MRI scans from 42 harmonized studies. Using generalized additive models for location, scale, and shape (GAMLSS), we estimate age- and sex-stratified trajectories for 72 individual white matter pathways, quantifying both tract-specific microstructural and morphometric features. We demonstrate that these WM brain charts enable four important applications: (1) defining normative trajectories of WM maturation and decline across distinct pathways, (2) identifying previously uncharacterized developmental milestones and spatial gradients of tract maturation, (3) detecting individualized deviations from normative patterns with clinical relevance across multiple neurological disorders, and (4) facilitating standardized, cross-study centile scoring of new datasets. By establishing a unified, interpretable reference framework for WM structure, these brain charts provide a foundational metric for research and clinical neuroscience. The accompanying open-access trajectories, centile scoring tools, and harmonization methods facilitate precise mapping of WM development, aging, and pathology across diverse populations. We release the brain charts and provide an out-of-sample alignment process as a Docker image: https://zenodo.org/records/15367426.
SN  - 0028-0836
SN  - 1476-4687
ER  -