Atypical Dynamic Functional Network Connectivity State Engagement during Social-Emotional Processing in Schizophrenia and Autism.

Autism spectrum disorder (ASD) and schizophrenia (SZ) are separate clinical entities but share deficits in social-emotional processing and static neural functional connectivity patterns. We compared patients' dynamic functional network connectivity (dFNC) state engagement with typically developed (TD) individuals during social-emotional processing after initially characterizing such dynamics in TD. Young adults diagnosed with ASD (n = 42), SZ (n = 41), or TD (n = 55) completed three functional MRI runs, viewing social-emotional videos with happy, sad, or neutral content. We examined dFNC of 53 spatially independent networks extracted using independent component analysis and applied k-means clustering to windowed dFNC matrices, identifying four unique whole-brain dFNC states. TD showed differential engagement (fractional time, mean dwell time) in three states as a function of emotion. During Happy videos, patients spent less time than TD in a happy-associated state and instead spent more time in the most weakly connected state. During Sad videos, only ASD spent more time than TD in a sad-associated state. Additionally, only ASD showed a significant relationship between dFNC measures and alexithymia and social-emotional recognition task scores, potentially indicating different neural processing of emotions in ASD and SZ. Our results highlight the importance of examining temporal whole-brain reconfiguration of FNC, indicating engagement in unique emotion-specific dFNC states.