Abstract
Abstract
Major depressive disorder (MDD) is biologically heterogeneous, but how this variability is expressed in the temporal organization of brain activity remains unclear. Using resting-state functional MRI from 2,225 participants, we applied hidden Markov modeling to identify recurrent brain states and quantify their temporal organization. Five states formed a shared repertoire across individuals with MDD and healthy controls, while MDD-related alterations were distributed across states, functional systems, and temporal properties. Within MDD, unsupervised clustering of state occupancy, persistence, and switching delineated two prototype neurodynamic architectures characterized by preferential deployment of ACS/VSS or MAS/DMS states within a preserved state repertoire and broadly similar transition backbone. The architectures showed different within-group brain–symptom associations and symptom-network patterns. Connectome transcriptome analyses organized architecture–state imaging patterns into three transcriptomic state families shared across architectures, and contrasting group-level deployment patterns were recovered in an independent MDD cohort. These findings suggest that MDD heterogeneity is expressed not only through spatially distributed neural alterations, but also through differences in how a common repertoire of recurrent brain states is organized over time.