Human-to-monkey transfer learning identifies the frontal white matter as a key determinant for predicting monkey brain age.

ABSTRACT: The application of artificial intelligence (AI) to summarize a whole-brain magnetic resonance image (MRI) into an effective "brain age" metric can provide a holistic, individualized, and objective view of how the brain interacts with various factors (e.g., genetics and lifestyle) during aging. Brain age predictions using deep learning (DL) have been widely used to quantify the developmental status of human brains, but their wider application to serve biomedical purposes is under criticism for requiring large samples and complicated interpretability. Animal models, i.e., rhesus monkeys, have offered a unique lens to understand the human brain - being a species in which aging patterns are similar, for which environmental and lifestyle factors are more readily controlled. However, applying DL

SUBMITTER: He S 

PROVIDER: S-EPMC10646581 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature