Researchers have pooled diffusion MRI data from more than 54,000 people across 19 international datasets to produce the most full normative model of the brain’s white matter ever created. Published in Nature Communications on 27 May 2026, the work establishes lifespan centile curves for key measures of brain microstructure – offering clinicians and trialists a sensitive new tool for detecting disease-related changes at the individual level.
From growth charts to brain wiring
A landmark study from the USC Mark and Mary Stevens Neuroimaging and Informatics Institute (Stevens INI) at the Keck School of Medicine of USC has now applied the same logic to the brain itself – specifically to the vast network of white matter fibres that wire its regions together. The result is a lifespan normative model of brain microstructure with direct implications for the diagnosis and monitoring of Alzheimer’s disease, schizophrenia, and a wide range of other neurological and psychiatric conditions.
When a paediatrician plots a child’s height on a growth chart, they are asking a deceptively simple question: is this person developing as expected for their age and sex? Statistical charts compiled from a large population allow brain abnormalities to be detected in new individuals.
“Just as paediatric growth charts help clinicians determine whether a child’s height or weight is developing as expected, these brain charts provide a reference for how the brain’s neural pathways typ”, said Julio E. Vil-lalón-Reina, MD, PhD, a postdoctoral researcher at the Stevens INI and the study’s first author. “That gives us a powerful new way to identify when an individual’s brain wiring falls outside the expected range.”
Trajectories across the lifespan
The resulting centile curves, running from the 2nd to the 98th percentile, paint a detailed picture of how white matter evolves from early childhood through to the ninth decade of life. FA, a marker of fibre organisation and myelination, follows an inverted U-shaped trajectory, rising during maturation and declining after a peak. The three diffusivity measures follow the reverse: a U-shaped pattern, falling as the brain matures and rising again in older age as microstructural integrity wanes.
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Critically, the timing differs substantially between metrics and between regions. On average, FA peaked earliest (around age 29 for the global white matter skeleton), followed by RD (minimum at 37 years), MD (minimum at 43 years), and AD (minimum at 53 years). Among individual tracts, FA peaked as early as 16 years in the genu of the corpus callosum and as late as 39 years in the fornix.
“Brain development and brain ageing are not uniform processes,” Villalón-Reina noted. “The brain’s neural pathways mature on distinct timelines, and some are more vulnerable to decline than others. Our model reveals this structure by merging data on a truly global scale.”
The ‘last in, first out’ principle
One of the more striking ancillary findings concerns an old theoretical question in neuroscience: does the brain age in the reverse order of how it developed? This retrogenesis hypothesis, sometimes called ‘last in, first out’, predicts that white matter tracts that mature late in development should be among the first to degenerate in old age, because they are less robustly myelinated and therefore more vulnerable.
Using the centile curves to measure percentage change in DTI metrics at different life stages, the researchers found significant support for the hypothesis for FA, MD, and AD, but not for RD. Tracts with a later age of peak maturation showed faster percentage change in the oldest age bands (75-91 years), consistent with a developmental origin for individual vulnerability to age-related white matter decline. The team did not find support for a related but distinct idea, the ‘gain-predicts-loss’ hypothesis, which predicts that the rate of maturation and the rate of degeneration should be directly correlated.
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