Delaying “brain age” may sound like the latest quick-fix gimmick on a late-night infomercial, but the science underlying the concept is very real.
Rather than reflecting the average functional state of your chronological age, brain age looks at how well your brain is aging relative to how many birthdays you’ve celebrated. We all know people that seem sharper and act much younger than their age.
[A]n ambitious study in Nature Neuroscience married three disparate fields—neuroscience, longevity, and machine learning—into a single algorithm that can predict a person’s brain age based purely on MRI scans.
Using data from nearly 50,000 people with ages spanning 8 decades, the study is a first to tease out how common brain disorders, such as depression and autism, affect brain aging. What’s more, the team dug deep down into human genomic data from UK Biobank, pinpointing sets of genes related to neurological disorders that especially accelerate brain aging.
The immediate use of such a “brain age gap” is as a biomarker for brain aging, which can help doctors make informed decisions about their aging patients.
Read full, original post: How Old Is Your Brain? This AI Can Tell You