According to experts at Max Planck Institute for Human Cognitive and Brain Sciences, an individual’s biological age may be accurately established through brain images via artificial neural networks.
The study was released online in NeuroImage.
Researchers focused on the magnetic resonance imaging (MRI) data of more than 2,600 people between the ages of 18 and 82.
“We combined ensembles of convolutional neural networks with Layer-wise Relevance Propagation (LRP) to detect which brain features contribute to brain age (BA),” the authors explained in their report.
“We find that BA estimates capture ageing at both small and large-scale changes, revealing gross enlargements of ventricles and subarachnoid spaces, as well as white matter lesions, and atrophies that appear throughout the brain.”
“Divergence from expected ageing reflected cardiovascular risk factors and accelerated ageing was more pronounced in the frontal lobe.”
“Applying LRP, our study demonstrates how superior deep learning models detect brain-ageing in healthy and at-risk individuals throughout adulthood,” the authors concluded.