Your birth certificate gives one age for your whole body, but your brain may tell a much more complicated story.
New research from the University of Southern California suggests that one part of the brain can look relatively young while another appears to have aged much faster.
To reveal these differences, USC researchers created an artificial intelligence model that turns MRI scans into detailed maps of brain aging. The study, led by Associate Professor Andrei Irimia of the USC Leonard Davis School of Gerontology, was published in the Proceedings of the National Academy of Sciences.
Scientists have long known that aging affects the brain. Some people maintain strong memory and thinking skills into very old age, while others develop mild cognitive impairment or diseases such as Alzheimer’s.
One way researchers study these differences is by estimating “brain age.” Computers learn what brains usually look like at different ages and then compare a new scan with those normal patterns.
Most previous systems have simplified this information into one number. That can be useful, but it is a little like describing the weather across an entire country with one temperature because it hides important local differences.
The USC model takes a different approach. It estimates age across tiny three-dimensional areas within an MRI scan, allowing researchers to build a map of places that appear to be aging normally, slowly or faster than expected.
To teach the system, the researchers used MRI scans from 14,748 adults who were considered cognitively healthy. Participants ranged from 19 to 100 years old, giving the AI examples of brain structure across almost the entire adult lifespan.
The scans came from six large research collections. These included major projects such as the UK Biobank, the Human Connectome Project and the Alzheimer’s Disease Neuroimaging Initiative.
Once trained, the system was tested on more than 1,900 other people. Some had normal thinking abilities, some had mild cognitive impairment, and others had Alzheimer’s disease.
The maps showed that normal aging itself is uneven. In healthy people, the frontal and temporal parts of the brain generally looked older than the parietal and occipital areas farther toward the back.
That difference is interesting because these regions do different jobs. Frontal and temporal areas are important for memory, language, judgment and planning, while other regions help with functions such as vision and understanding where objects are in space.
The study also found that the right half of the brain tended to look slightly older than the left half. The pattern remained even when the researchers considered whether people were right-handed or left-handed.
The most important results appeared when the researchers examined people with cognitive problems. In mild cognitive impairment and Alzheimer’s disease, certain regions looked much older than would normally be expected.
Among them was the hippocampus, a small structure that plays a central role in making and storing memories. The amygdala and other deeper brain areas involved in memory and thinking also showed faster-looking aging.
These findings fit with existing knowledge about Alzheimer’s disease. The hippocampus and nearby regions are often damaged early as the disease develops, which helps explain why memory loss can be one of its first noticeable symptoms.
The researchers also found that brain regions that looked older were linked with poorer results on cognitive tests. This relationship was especially strong in people with Alzheimer’s disease, suggesting that the maps may reflect changes that matter for everyday brain function.
In the future, this type of technology could help scientists understand why two people of the same age can have very different patterns of decline. It might also help researchers follow disease progression or measure whether a new treatment is protecting vulnerable areas of the brain.
Still, there are important reasons for caution. The model remains a research tool, and MRI scans collected during carefully controlled studies may differ from scans produced in ordinary hospitals and clinics.
The study also relied heavily on comparisons between different people at different ages rather than repeatedly scanning the same people over many years. Long-term studies will be needed to learn whether these maps can actually predict who will later develop mild cognitive impairment or Alzheimer’s disease.
The study’s main strength is its scale and level of detail. Training on nearly 15,000 healthy people allowed the researchers to build a broad picture of normal aging, while local measurements revealed information that a single brain-age score could easily miss.
At the same time, an AI estimate of an “older” brain region is not the same as a medical diagnosis. Age, genetics, health conditions and many other factors can influence brain structure, so doctors would need much more evidence before using such maps to make decisions about an individual patient.
Even with those limits, the research changes the way brain age can be viewed. Rather than imagining the brain as one organ growing old at one speed, the findings suggest a patchwork of regions with different levels of resilience and vulnerability—and Alzheimer’s disease may make that patchwork much more pronounced.
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