Using neuroimaging to predict brain age: insights into typical and atypical development and risk for psychopathology

Childhood and adolescence are characterized by complex patterns of changes in brain structure and function. Recently, Truelove-Hill et al. (Truelove-Hill M, Erus G, Bashyam V, Varol E, Sako C, Gur RC, Gur RE, Koutsouleris N, Zhuo C, Fan Y, Wolf DH, Satterthwaite TD, Davatzikos C. J Neurosci 40: 1265-1275, 2020) used a novel machine learning algorithm to capture the subtle nuances of brain maturation during adolescence in two indices based on predicted brain age. In this article, we present an overview of the brain age prediction model used, provide further insight into the utility of this multimodal index to explore typical and atypical development, and discuss avenues for future research.