brain NAVigation Lab


Brain Aging (BA)

How old is ones’ brain? This apparently simple question hides an extremely complex system where endogenous and exogenous variables of different type interplay in a still unknown manner. Marked changes occur in the brain during the lifespan and individual rates of aging have revealed pronounced individual differences giving rise to subject-specific brainprints, that are the signature of the brain. The predictions of the brain age (BA) can be derived from neuroimaging endophenotypes using machine or deep learning techniques. Predictive models leading to accurate estimates while revealing which features contribute most to the final predictions would be the key to unveil the mechanisms subserving the evolution of brain aging patterns and to develop accurate biomarkers for disentangling age-related from disease-specific changes at the single-subject level.


Boscolo Galazzo I., Cruciani F., Brusini L., Salih A., Radeva P., Storti S. F. and Menegaz G.
“Explainable Artificial Intelligence for Magnetic Resonance Imaging Aging Brainprints: Grounds and challenges”
IEEE Signal Processing Magazine ( Volume: 39, Issue: 2, March 2022)

Salih A., Boscolo Galazzo I., Petersen S. E., Lekadir K., Radeva P., Menegaz G. and Altmann A.
“Telomere length is causally connected to brain MRI image derived phenotypes: A mendelian randomization study”
PLOS ONE , 17 (11) , Article e0277344

Salih A., Boscolo Galazzo I., Raisi-Estabragh Z., Rauseo E., Gkontra P., Petersen S. E., Lekadir K., Altmann A., Radeva P. and Menegaz G.
“Brain age estimation at tract group level and its association with daily life measures, cardiac risk factors and genetic variants”
Scientific Reports volume 11, Article number: 20563 (2021)