A new AI model creates detailed 3D maps of how different brain regions age, revealing that Alzheimer's disease accelerates aging in specific memory-related areas—even before symptoms appear.
The Research
Researchers at the University of Southern California (USC) led by Associate Professor Andrei Irimia trained a deep learning neural network on MRI scans from nearly 15,000 cognitively healthy individuals aged 19 to 100. Unlike traditional methods that give a single 'brain age' number, this model produces high-resolution maps showing how old each part of the brain appears relative to the person's chronological age.
When applied to over 1,900 people with mild cognitive impairment or Alzheimer's, the AI found accelerated aging concentrated in the hippocampus, amygdala, and frontal-temporal regions—areas critical for memory and executive function. These localized changes were tightly linked to performance on cognitive tests, with the strongest correlation in advanced Alzheimer's cases.
The study, published in Proceedings of the National Academy of Sciences, also revealed that in healthy brains, frontal and temporal lobes tend to look older than occipital and parietal regions, and the right hemisphere ages slightly faster than the left.
Why It Matters
This technology could lead to earlier detection of dementia risk, before global brain changes are visible. It also offers a tool for tracking how new treatments affect specific brain regions in clinical trials, potentially accelerating drug development.
What You Can Do
While this AI isn't available for home use, you can support your brain health with regular physical exercise, a Mediterranean-style diet, mental stimulation, and social engagement. Staying cognitively active and monitoring your memory with tools like the iqgenio test can help you spot changes early.
Source: Neuroscience News
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