Brain rhythms of depression: A predictive processing perspective

Depression is marked by anhedonia, social withdrawal, and a diminished capacity to learn from positive experiences-features that can be framed within predictive processing. Here, we review findings from human electroencephalography (EEG) that, owing to its temporal resolution, can illuminate the moment-to-moment dynamics of inference in depression. Across evoked, oscillatory, and aperiodic measures, incoming information appears to be registered yet may carry insufficient precision to revise higher-level beliefs about the self and the world. This imbalance may favour model maintenance over flexibility, with rumination as one possible subjective correlate of relative state stability. Together, these findings motivate inference phenotypes as a complementary lens on depression and yield testable predictions for EEG-guided stratification and mechanistically targeted intervention.