Brain age prediction in children and adolescents: current challenges and future directions

Recent advancements in computational techniques have enhanced our understanding of human brain development, particularly through the analysis of high-dimensional data from magnetic resonance imaging (MRI). One notable approach is the “brain age prediction” framework, which predicts biological age based on neuroimaging data and calculates the brain age gap (BAG); a marker indicating deviation from expected (chronological) age. This method has most commonly been used in adult samples, but has in recent years increasingly been applied to youth populations to assess brain maturation. However, there are a number of unique considerations that must be taken into account when applying brain age prediction in youth. In this Perspective, we briefly review the existing brain age literature in children and adolescents. We next identify important challenges and considerations, and provide recommendations for researchers, as well as future directions for the field.