Summary: Researchers have built one of the largest reference models ever created for the human brain. Using diffusion MRI scans from 54,583 individuals across 19 international datasets, the team produced definitive lifespan “growth and decline charts” for white matter microstructure that track how the brain’s communication pathways develop, mature, and deteriorate.
By measuring how water molecules move along neural pathways throughout life, this publicly available normative tool allows clinicians and researchers to detect person-specific structural deviations associated with aging, Alzheimer’s disease, schizophrenia risk, and other neurological or psychiatric conditions.
Key Facts
- White Matter Growth Metric: Similar to pediatric growth charts that benchmark height and weight, this framework offers a standardized reference for white matter microstructure. It maps how major neural pathways typically change over the lifespan, enabling early detection of subtle structural abnormalities.
- Diffusion MRI as a Microscope: The team relied on diffusion MRI, an imaging method that tracks microscopic water motion through brain tissue. Because water movement is constrained by nerve fibers and the insulating myelin sheath, diffusion MRI reveals microstructural changes invisible to standard clinical scans.
- Validation of “Last In, First Out”: Large-scale global data supported the long-standing theory that the brain’s last-developed pathways are the first to decline in old age. White matter tracts that mature later in childhood and adolescence showed faster structural decline in older adults.
- Individualized Diagnostic Insights: Applying the model to people with mild cognitive impairment, dementia, and 22q11.2 deletion syndrome (a genetic condition linked to high schizophrenia risk) highlighted clear deviations from age-expected norms. Importantly, deviations differed among individuals with the same diagnosis, supporting the need for personalized assessment of brain health.
- Clinical Trial and Treatment Evaluation: Developed by the USC Stevens Neuroimaging and Informatics Institute team led by senior author Paul M. Thompson and first author Julio E. Villalón-Reina, the models let researchers compare a person’s neural pathways against peers matched for age, sex, and demographics. This provides a standardized baseline to measure whether therapies restore white matter measures toward healthy ranges or slow degeneration.
- Unified Framework Across Disorders: Supported by the National Institutes of Health and international partners, the publicly available reference is being scaled to compare more than 30 neurological, psychiatric, and neurodevelopmental conditions within a single analytical framework.
Source: USC
Overview
Researchers at the USC Mark and Mary Stevens Neuroimaging and Informatics Institute (Stevens INI) at the Keck School of Medicine of USC assembled diffusion MRI scans from over 54,000 people to create one of the largest brain reference models to date. Published in Nature Communications, the study generates lifespan “growth charts” for white matter — the brain’s network of neural wiring that enables regions to exchange information efficiently.
The research team standardized data processing across 19 international diffusion MRI datasets and focused on four commonly used microstructure measures across 21 major white matter regions. By modeling how these measures vary by age and sex, they produced lifespan trajectories and percentile ranges that show typical patterns at different stages of life.
White matter development and aging follow distinct timelines: some pathways peak in early adulthood while others reach maturity in midlife and then decline at varying rates. These normative curves provide a quantitative baseline to identify when an individual’s brain wiring departs from expected ranges.
“Just as pediatric growth charts help clinicians track physical development, these brain charts give a reference for how neural pathways typically evolve,” said Julio E. Villalón-Reina, MD, PhD, a postdoctoral researcher and first author. “They give us a sensitive way to spot when an individual’s brain wiring falls outside the norm.”
Paul M. Thompson, PhD, associate director of the Stevens INI and senior author, noted that the study took seven years to complete. The enormous scale of the data and the fine-grained features measured now let clinicians and scientists evaluate an individual’s neural pathways relative to a demographically matched population, supporting personalized diagnostics and treatment monitoring.
Clinical Applications and Findings
When applied to clinical cohorts, the normative model detected atypical white matter patterns in regions tied to memory and interregional communication among people with mild cognitive impairment and dementia. In 22q11.2 deletion syndrome, the model identified distinct deviations across critical neural pathways, clarifying which systems develop differently in this high-risk group.
The charts can track whether a treatment brings a patient’s white matter metrics toward healthy ranges or slows their drift from normative patterns, offering a standardized outcome measure for therapeutic trials. The models are publicly available and designed to be extended as new imaging data emerge.
Impact and Open Science
This work demonstrates the power of international data sharing to create an accessible resource for the research community. By establishing a lifespan framework for white matter microstructure, researchers can now detect subtle disease-related changes, compare disorders more rigorously, and advance individualized models of brain health.
About the study
The study, “Lifespan normative modeling of brain microstructure,” was published in Nature Communications. Authors include Julio E. Villalón-Reina, 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, the Alzheimer’s Disease Neuroimaging Initiative, Paul M. Thompson, and colleagues.
Funding: This research was 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), 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-based reference ranges for key white matter measures across major brain regions, adjusted for age and sex. Clinicians can immediately see whether an individual’s white matter metrics fall within typical percentiles for their demographic group, flagging potential deviations from normal aging or disease-related changes.
A: It means that neural pathways that complete maturation later in development are more vulnerable to earlier decline in aging. The study found that late-maturing white matter tracts tend to show faster structural deterioration in older adults, linking developmental timelines to patterns of age-related vulnerability.
A: Neurological disorders affect individuals in heterogeneous ways. The normative model revealed that even within the same diagnostic category, persons can exhibit distinct patterns of white matter deviation from age-expected norms. This underscores the importance of individualized assessment for accurate diagnosis and personalized treatment planning.
Editorial Notes
- This article was edited by an editor at Neuroscience News.
- The journal paper was reviewed in full.
- Additional context was provided by editorial staff.
About this research and reporting
Author: Laura LeBlanc
Source: USC
Contact: Laura LeBlanc – USC
Image: Image 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
Normative population models of brain measures are valuable for detecting abnormalities across degenerative, psychiatric, and neurodevelopmental disorders, yet comprehensive models for white matter microstructure have been lacking. This study presents a large-scale normative model based on 19 international diffusion MRI datasets covering nearly the entire lifespan (N = 54,583 individuals, ages 4–91). Using standardized extraction of diffusion tensor imaging (DTI) metrics and hierarchical Bayesian regression, the team modeled the distribution of white matter measures as functions of age and sex, deriving average lifespan trajectories and centile curves for each region.
The researchers demonstrated 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 resource provides a common reference to detect disease effects on white matter microstructure in individuals or groups, compare disorders, and investigate factors influencing white matter abnormalities. The normative models are publicly available, adaptable, and extendable as additional imaging data become available.