Summary: Researchers have built one of the largest reference models for the human brain by compiling diffusion MRI scans from 54,583 people across 19 international datasets. The resulting, publicly available resource establishes lifespan “growth and decline charts” for white matter microstructure, enabling clinicians and researchers to detect person-specific structural deviations tied to aging, Alzheimer’s disease, and psychiatric risk.
By measuring how water molecules travel along neural pathways throughout life, this tool maps typical white matter development and decline and provides a normative baseline for comparing individual brain scans to age- and sex-matched expectations.
Key Facts
- White Matter Growth Metric: Similar to pediatric growth charts for height and weight, the model offers normative percentiles for white matter microstructure. It documents how the brain’s communication pathways mature and deteriorate, helping to detect subtle structural differences that standard scans miss.
- Diffusion MRI as a Lens: The team used diffusion MRI to follow microscopic water movement through brain tissue. Because water flow is shaped by nerve fiber orientation and myelin integrity, diffusion MRI reveals microstructure changes invisible to conventional imaging.
- Validating “Last In, First Out”: Large-scale data confirmed that pathways maturing last in childhood and adolescence are the first to show accelerated decline in older age, linking developmental timelines with vulnerability in aging.
- Person-Specific Diagnostic Deviations: Applying the normative curves to datasets from people with mild cognitive impairment, dementia, and 22q11.2 deletion syndrome revealed clear deviations from age-expected norms. Importantly, deviations varied among individuals with the same diagnosis, supporting the need for individualized assessment.
- Clinical Trial Dashboard: The framework enables researchers and clinicians to evaluate a person’s white matter measures relative to peers of the same age, sex, and demographics. This provides a common baseline to measure treatment effects—whether a therapy restores white matter toward healthy ranges or slows decline.
- Unified Framework for 30+ Conditions: Funded by the National Institutes of Health and international partners, the resource is already being scaled to compare more than 30 neurological, psychiatric, and neurodevelopmental conditions under a single analytical framework.
Source: USC
Overview
Researchers at the USC Mark and Mary Stevens Neuroimaging and Informatics Institute (Stevens INI), Keck School of Medicine of USC, created a large-scale normative model of the brain’s white matter by harmonizing diffusion MRI scans from 54,583 people aged 4 to 91. Published in Nature Communications, the study provides lifespan trajectories and centile charts for white matter microstructure across 21 major brain regions using four widely used diffusion measures.
The model was built using standardized processing and hierarchical Bayesian regression to estimate how white matter metrics vary with age and sex. The resulting curves capture typical development—including peaks in early adulthood and midlife for different measures—and describe how decline progresses in later life.
“Just as pediatric growth charts let clinicians track physical development, these brain charts give a reference for how neural pathways usually change over the lifespan,” said Julio E. Villalón-Reina, MD, PhD, the study’s first author. “They let us identify when an individual’s brain wiring falls outside the expected range.”
White matter—the brain’s network of wiring—supports communication between regions. Diffusion MRI detects microstructural features such as fiber coherence and myelin integrity by measuring water diffusion, providing sensitivity to subtle tissue changes that standard imaging does not capture.
The investigators applied the normative model to clinical groups and found distinct patterns of deviation in people with mild cognitive impairment, dementia, and 22q11.2 deletion syndrome. In dementia-related cases, atypical white matter patterns appeared in regions tied to memory and interregional communication. In the 22q11.2 cohort, multiple key tracts showed altered development pathways. Crucially, deviations differed between individuals, underscoring the importance of person-specific interpretation.
“This multi-year effort produces a tool that lets us compare an individual’s neural pathways to a representative population matched for age, sex, and other demographics,” said Paul M. Thompson, PhD, senior author. “It can serve clinical trials by showing whether treatments move white matter measures back toward normal ranges or slow their decline.”
The authors have made the normative models publicly available so the resource can grow as new datasets emerge. Researchers can apply the framework to study neurological, psychiatric, and neurodevelopmental disorders with a common reference standard for white matter microstructure.
About the study
The study, “Lifespan normative modeling of brain microstructure,” appears in Nature Communications. In addition to Villalón-Reina and Thompson, the author list includes Alyssa H. Zhu, Leila Nabulsi, Sophia I. Thomopoulos, Clara A. Moreau, Yixue Feng, Tamoghna Chattopadhyay, Sebastian Benavidez, Leila Kushan, John P. John, Himanshu Joshi, Iyad Ba Gari, Katherine E. Lawrence, Talia M. Nir, Neda Jahanshad, Carrie E. Bearden, Seyed Mostafa Kia, Andre F. Marquand, and collaborators from the Alzheimer’s Disease Neuroimaging Initiative.
Funding: Supported by grants from the National Institutes of Health (including the National Institute on Aging, the Fogarty International Center, and the National Institute of Mental Health), and by the Alzheimer’s Association, the European Research Council, the Wellcome Trust, and the Popovich Chair in Neurodegenerative Diseases.
Key Questions Answered:
A: The model provides percentile ranges for four diffusion-based measures across 21 brain regions, giving clinicians a reference to judge whether a person’s white matter structure matches expectations for their age and sex. Like pediatric charts, it reveals where an individual falls within a normative distribution and highlights deviations from the typical trajectory.
A: It means that neural pathways that finish maturing later in development are often the first to show accelerated decline in older age. The study’s large sample confirmed this pattern, linking late maturation in youth with greater vulnerability in later life.
A: Neurological disorders do not produce identical structural outcomes in every individual. When applying the normative model, researchers observed unique patterns of deviation across patients with the same diagnosis, which supports personalized assessment and tailored interventions.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- The full journal paper was reviewed.
- Additional context was provided by staff for clarity.
About this neuroscience and brain mapping research news
Author: Laura LeBlanc
Source: USC
Contact: Laura LeBlanc – USC
Image: The image is credited to Neuroscience News
Original Research: Open access. “Lifespan normative modeling of brain microstructure” by Julio E. Villalón-Reina et al., Nature Communications. DOI: 10.1038/s41467-026-72875-x
Abstract
Lifespan normative modeling of brain microstructure
Large normative models of brain measurements can help detect abnormalities across a range of disorders, but comprehensive models for white matter microstructure have been lacking. This study presents a large-scale normative model built from 19 international diffusion MRI datasets, totaling N = 54,583 individuals aged 4–91 years. Using a standardized pipeline to extract regional diffusion tensor imaging metrics and hierarchical Bayesian regression, the team estimated lifespan trajectories and centile curves for white matter regions.
The paper demonstrates the model’s utility by identifying and visualizing white matter deviations in mild cognitive impairment, Alzheimer’s disease, and 22q11.2 deletion syndrome. The resulting public resource provides a common reference to quantify disease effects on white matter at the individual and group level and can be extended as new data become available.