Vanderbilt University and Vanderbilt Health Map Brain Lifespan Wiring with AI

Researchers at Vanderbilt University have published the first growth charts for white matter in the human brain, tracking how its structure changes from birth to age 100. The study, published in Nature in May 2026, was made possible by an AI-enabled computing platform that processed one of the largest neuroimaging datasets.

Michael Kim, the study's lead author said, "Defining these pathway-specific trajectories and milestones allows researchers to explore interesting neurobiological questions. They also help us investigate how white matter abnormalities present similarly or differently across diseases."

White matter consists of bundled nerve fibers that act as the brain's primary communication network. The researchers mapped 72 distinct pathways and tracked how they develop and decline across a full human lifespan.

The work draws on nearly two decades of Vanderbilt research and an AI platform developed at the university's lab for immersive AI translation, known as VALIANT. That infrastructure made it possible to standardize and process imaging data at a scale that was previously out of reach.

The VALIANT platform's allowed the harmonization and analysis of millions of images across dozens of independent studies, without which, the dataset would have remained too fragmented to draw population-level conclusions.

AI Maps Brain Lifespan

The study analyzed MRI data from nearly 42,000 brains across more than 4 million individual images, drawing from 50 global population studies. Datasets from different studies rarely use identical imaging protocols, so aligning them required years of development work before the AI analysis could begin.

Bennett Landman, who directs VALIANT and is a key contributor to the study, said: "What's exciting is that these data harmonization efforts, really a decade in the making that involved numerous collaborations between Vanderbilt University and Vanderbilt Health, are reaching the point of enabling transformative discovery."

The analysis found that white matter volume peaks in a person's early to mid 30s before beginning a gradual decline, while pathway integrity plateaus in the mid-20s. Pathways that mature later were found to resist aging longer.

The study did not address what happens to specific brain functions like cognition at various developmental points, so how these peaks and declines affect behaviour remains an open question. The charts establish anatomical reference points, not functional ones, for now.

Potential clinical applications span conditions including autism, ADHD, dyslexia, epilepsy, multiple sclerosis, Alzheimer's, and Parkinson's disease. The analogy the researchers use is straightforward, the same way pediatricians use height and weight charts to flag developmental concerns, neurologists could soon use white matter charts to detect abnormalities earlier.