项目名称: 首发精神分裂症面孔表情识别障碍的脑网络机制研究
项目编号: No.81471359
项目类型: 面上项目
立项/批准年度: 2015
项目学科: 医药、卫生
项目作者: 陆峥
作者单位: 同济大学
项目金额: 70万元
中文摘要: 面孔表情识别障碍是精神分裂症的病理认知特征之一。既往研究发现精神分裂症有关面孔表情识别的脑结构和脑功能异常,但目前确切机制不明。同样,精神分裂症具有家族遗传性,其一级亲属也发现部分脑结构或脑功能的异常,属于发病高危人群。因此我们提出以下假设:精神分裂症的面孔表情识别障碍可能存在某一情感通路,涉及多个起源点,并随病程进展而变化;这一通路在高危人群的异常程度可能较弱或关联脑区较少,同样随其转化过程而发生变化。为此,本研究拟采用临床对照研究设计,在我们前期工作的基础上,运用面孔表情识别任务,对首发精神分裂症、高危人群及健康对照进行fMRI检测,在基线、半年和一年随访观察。目的是比较三组人群的脑网络特征,观察早期可能出现的高危信号,探索与情绪识别障碍相关的特异性脑网络表征,为精神分裂症的机制研究提供理论基础,为精神分裂症的早期诊断、预后判断及疗效评价提供影像学线索。
中文关键词: 精神分裂症;首次发作;脑网络;面孔表情识别;功能磁共振
英文摘要: Facial recognition disorder is one of pathological cognitive characteristics in patients with schizophrenia. Previous studies have found that patients with schizophrenia had abnormal brain structure and function related with facial expression recognition,but the exact mechanism remains unclear. Similarly, as the high risk population of the schizophrenia, the first-degree relatives of patients with schizophrenia were found having abnormal brain structure and brain function. We hypothesis that there may be a emotion pathway in facial expression recognition disorder in schizophrenia patients, revolving many origin sites, varying with disease progression; This pathway is less abnormal, or revolves less related brain regions in high risk population, but may change with the transformation process. We design a controlled clinical observational study including three groups that are the first episode schizophrenia group, high-risk group and healthy control group. Brain fMRI data are collected at baseline, half-year and one-year using facial expression recognition tasks. Through comparing the brain network status in three groups, we observe the high risk signal in early stage of schizophrenia and explore the special characteristic of brain network related with emotion recognition disorder, in order to provide theory basis for mechanism study of schizophrenia and the imaging index for early diagnosis, prognosis and effectiveness evaluation of schizophrenia.
英文关键词: schizophrenia;first episode;brain network;facial expression recognition;functional magnetic resonance imaging