ReviewTrends in neurosciences2026
Brain rhythms of depression: A predictive processing perspective.
Review in Trends in neurosciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
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.
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