抑郁障碍社会认知异常的多模态磁共振研究

Depression is a severe mental disorder with high incidence and high morbidity. Previous studies used clinical scales to detect the social impairment in depression and found that impaired social function has a critical impact on the occurrence, development and prognosis of the depressive disorder. However, the cognitive and neural mechanisms underlying these abnormalities are still unclear. This project attempts to apply cognitive experiment design, multimodal MRI and pattern recognition technologies to systematically explore the neuropathological mechanism of social cognition abnormality in depression, and build the neural markers for predicting the abnormal social behaviors and those for individual diagnosis of depression. Our research mainly includes: (1) revealing the abnormal activations and functional connectivities underlying the negative self schema, hypersensitivity to social rejection and social competition avoidance in depression; (2) exploring the multimodal neural indexes associated with social cognition abnormality in depression; and (3) proposing a prediction model of abnormal social behaviors in depression upon the neual indexes found above, and furthermore, selecting the neural diagnostic indexes which could help to diagnose depression with higher accurateness. This project would provide important empirical data for constructing the social cognitive model of depression and scientific evidence for screening the susceptibility, diagnosing and evaluating prognosis of depression.

抑郁障碍是一种高发病率、高社会负担的精神疾病。其社会功能损伤对疾病的发生、发展和预后都具有关键性的影响。然而，针对抑郁障碍社会功能损伤的现有研究还主要停留在行为水平，这些损伤的认知神经机制还很不明确。本项目拟结合认知实验设计、多模态影像和模式识别技术，从自我图式、社会知觉、人际交互三个维度，较为系统的探测抑郁障碍社会认知异常的神经病理机制，并建立针对行为预测和疾病个体识别的影像学指标。主要内容包括：（1）揭示抑郁障碍的负性自我图式、社会排斥敏感和社会竞争回避的异常激活脑区和脑网络连接模式；（2）从局部脑区和脑网络层面，挖掘社会认知异常的多模态影像指标；（3）建立社会认知异常内在影像表征对外在行为表征的预测模型，并筛选针对患者个体识别的影像诊断指标。本项目将为构建抑郁障碍的社会认知模型提供数据支持，也为抑郁障碍的风险人群筛查、诊断和预后评估提供科学依据，具有重要的理论和实践意义。

项目主要针对抑郁障碍社会认知异常的多模态脑影像神经机制问题，通过设计抑郁障碍社会认知实验，探测患者在自我、正负性社会线索加工中的认知异常模式；发展多模态脑网络分析方法，从局部-网络、结构-功能、静态-动态多个角度揭示抑郁障碍社会认知异常的多模态脑影像神经基础；并建立基于多模态脑影像表征的抑郁障碍认知-临床预测和模式识别分类计算模型；本项目目前已积累150余例患者和正常对照的认知行为、临床数据和多模态磁共振数据。研究结果发现，自我和心理理论相关网络，包括默认网络、顶联合区和脑岛等社会认知的核心脑区，在抑郁患者中出现功能活动与灰质体积的异常改变；这些异常在静息状态和社会认知任务状态下均可查见；且基于静态和动态脑功能连异常模式可有效预测患者的社会认知异常行为指标（如自尊水平、快感缺失），并可有效识别患者、区分单双相抑郁亚型。项目研究成果为抑郁障碍社会功能损伤的早期诊断、干预和预后评估提供了客观影像学依据，也为揭示抑郁障碍社会认知模型提供了理论依据。按照项目计划完成了研究工作，并适当拓展了研究领域。.项目成果在Neuropsychopharmacology, Human Brain Mapping, Psychological Medicine, IEEE Transactions on Medical Imaging和Schizophrenia Bulletin等脑影像和精神疾病权威SCI期刊论文36篇；项目负责人入选2018年四川省学术和技术带头人后备人选。