Common and unique brain aging patterns between females and males quantified by large-scale deep learning.

ABSTRACT: There has been extensive evidence that aging affects human brain function. However, there is no complete picture of what brain functional changes are mostly related to normal aging and how aging affects brain function similarly and differently between males and females. Based on resting-state brain functional connectivity (FC) of 25,582 healthy participants (13,373 females) aged 49-76 years from the UK Biobank project, we employ deep learning with explainable AI to discover primary FCs related to progressive aging and reveal similarity and difference between females and males in brain aging. Using a nested cross-validation scheme, we conduct 4200 deep learning models to classify all paired age groups on the main data for females and males separately and then extract gender-common and gende

SUBMITTER: Du Y 

PROVIDER: S-EPMC11369911 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature