Limited generalizability of dynamic fMRI correlates of adolescent rumination

Abstract

Rumination, or perseverative negative self-referential thinking, is a hallmark of depression. In adults, a dynamic resting-state functional magnetic resonance imaging model of trait rumination was recently identified through predictive modeling. In adolescents, a development period during which rumination and depression increase, the neurobiological correlates of ruminative thinking are less clear. Here, in the current preregistered study, we examine dynamic connectivity correlates of self-reported rumination in a large sample of adolescents (n = 443, containing clinical and nonclinical individuals). Notably, the adult model failed to generalize to our sample. In addition, linear models trained on default-mode network (DMN) connectivity, as well as whole-brain connectome models, failed to generalize to held-out data. In an exploratory random forest analysis, we found significant prediction performance of a model in which increased variability between DMN–cerebellum, DMN–dorsal attention network and DMN–DMN connections was nominally associated with higher rumination. However, the model did not generalize to an external sample with lower rumination scores and a distinct scanner protocol. Our findings illustrate the difficulty of characterizing the neurodevelopment of risk factors for depression.