Abstract
The anterior cingulate cortex (ACC) is critically implicated in major depressive disorder (MDD), with distinct subregional dysfunctions related to specific aspects of emotional and cognitive dysregulation. However, its precise functional architecture, including the number, boundaries and intrinsic connectivity patterns of subdivisions, remains to be characterized in MDD. To address this, we employed data-driven connectivity-based parcellation (CBP) to delineate the optimal ACC functional partitions in 158 first-episode medication-naïve non-comorbid patients with MDD, and 152 healthy controls (HC). We generated subregion-specific ACC intrinsic connectivity maps, and analyzed group differences using diagnosis-by-subregion flexible factorial analyses of variance. We further explored the relationship between connectivity changes and clinical features. The ACC was optimally parcellated into bilateral ventral ACC (vACC) and dorsal ACC (dACC): The vACC showed preferential connections with default mode network (DMN) regions, whereas the dACC primarily connected to salience network and subcortical areas. Significant diagnosis-by-subregion interactions in ACC connectivity were mainly in the DMN regions: in HC, vACC showed stronger connectivity with DMN regions compared to the dACC, while this difference was attenuated in MDD, characterized by the vACC-DMN hypoconnectivity and a trend towards dACC-DMN hyperconnectivity. Clinically, lower vACC-DMN connectivity was related with core depressive symptoms, i.e., lower mood and longer illness duration, while higher dACC-DMN connectivity was linked to elevated maladaptive behaviors, e.g., suicide and insomnia. These findings confirm ventral-dorsal functional heterogeneity of ACC architecture and reveal symptom-specific patterns of subregional ACC-DMN dysconnectivity in MDD, which may provide insights for developing tailored interventions to address specific clinical manifestations.