Melancholic major depressive disorder (MDD-M), characterized by anhedonia, is a clinically distinct subtype with poor treatment response and impaired social function. This study aimed to investigate abnormal patterns of inter-regional neural communication in MDD-M. This study included 1541 participants who underwent resting-state fMRI scans across three independent datasets: an exploration dataset (n = 1175), a validation dataset (n = 216), and a longitudinal clinical cohort ( n = 150) with at least two scans per participant. Granger causality analysis was used to evaluate directed information flow between brain regions. In the exploration cohort, we applied directed Network-Based Statistics to identify melancholic-specific network features and correlate these features with clinical characteristics. These features were then used to construct a classification model in the validation dataset. Finally, we assessed the stability of these features in the longitudinal cohort via repeated-measures ANOVA. MDD-M exhibited a hypo-connectivity network pattern compared to the control group. Specifically, MDD-M reported weakened bidirectional connectivity between the thalamic ventrolateral nucleus (ThalVL) and the nucleus accumbens, as well as diminished causal outflow from the cerebellar vermis to both the globus pallidus and the ThalVL. This hypo-connectivity network pattern achieved an AUC of 0.81 in the validation set. Longitudinal analysis further confirmed the stability of the hypo-connectivity pattern in MDD-M. We identified a connectivity pattern of diminished directed information flow within the cerebello-basal ganglia-thalamic circuit that may represent a potential circuit-level feature of MDD-M. This stable and directional brain network feature may help identify the subtype and develop targeted treatments.
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