Emotion processing models in individuals with different levels of social anxiety based on the crowd emotion perception task

Previous studies on dyadic face perception have shown that individuals with high social anxiety (HSA) exhibit a strong attentional bias toward threat-related faces. However, it remains unclear whether this bias persists when multiple faces appear simultaneously. The present study combined an average emotion judgment task with event-related potentials (ERP) and functional brain network analysis to examine the temporal dynamics of crowd facial expression processing and the influence of social anxiety. Behaviorally, individuals with HSA identified crowd emotional expressions more accurately than individuals with low social anxiety (LSA). ERP results revealed enhanced late positive potential (LPP) amplitudes to angry versus happy crowd faces only in the HSA group, indicating sustained attention to social threat. In contrast, Dual Laplacian Granger Causality Analysis (DLap-GCA) showed stronger frontal-parietal and frontal-occipital connectivity in the LSA group, suggesting more efficient integration of regulatory, attentional, and visual processes during crowd emotion perception. A graph neural network trained on these connectivity features achieved an average accuracy of 87.14% in discriminating anxiety groups. These findings indicate that social anxiety modulates crowd emotion processing through distinct mechanisms: HSA is characterized by amplified threat sensitivity, whereas LSA relies on stronger regulatory network coordination that supports stable and efficient emotional integration in socially threatening contexts.