社交焦虑者在情绪加工和社会意图理解方面均可能存在异常, 以负向认知偏差为代表, 但目前尚缺乏针对社交焦虑的情绪与社会意图理解共性机制的研究和临床预测模型。本项目计划综合运用行为实验、功能磁共振成像和计算建模, 基于情绪识别与社会意图推理的生物运动范式, 并结合面部表情识别任务, 系统考察社交焦虑者在情绪加工和社会意图加工中的负向认知偏差机制, 并构建社交焦虑症状的预测模型, 检验精神疾病背后的多维数据关联, 以及多维数据对社交焦虑临床症状的客观分类和预测的作用。
Abstract (English):
Social anxiety disorder (SAD) is characterized by abnormal emotion processing and social intention inference, often accompanied by negative cognitive biases. However, there is still a lack of unified research examining the shared mechanisms and predictive models linking these processes. This study integrates behavioral experiments, fMRI, and computational modeling under a biological motion paradigm to explore emotion recognition and social intention inference in SAD, complemented by facial expression tasks. The aim is to reveal the cognitive and neural mechanisms underlying SAD, investigate multimodal data associations, and establish predictive models for clinical symptom classification and prognosis.