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

Abstract

Abstract 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.