抑郁症情绪面孔加工的大脑功能网络研究

发布时间：2018-04-17 12:35

本文选题：抑郁症 + 脑电　；参考：《中国生物医学工程学报》2014年05期

【摘要】：研究抑郁症患者和正常人在不同的情绪认知任务下大脑功能网络是否存在差异。采用了相位同步的方法以衡量不同脑区间的连接强度,运用网络参数全局和局部效率来刻画大脑的小世界拓扑结构。选取16个抑郁症患者和14个正常被试进行正负情绪面孔搜索的认知任务,同时记录头皮脑电。选择低gamma(30~50 Hz)和高gamma(50~80 Hz)两个频段的数据建立相位同步矩阵。结果显示:抑郁症患者组的全局相位同步值高于正常组;低gamma频段网络成本区间在(0.25~0.50)内,高gamma频段网络成本区间为(0.25~0.55),情绪加工网络的全局和平均局部效率介于随机网络和规则网络之间,具有小世界特性;在高gamma频段,在最大效费差下(网络成本为0.3),全局效率值在组间有显著性差异,此时局部效率无显著性差异发现;在网络成本为0.5时,发现抑郁症组在左顶颞区和枕区的局部效率显著高于正常组,在情绪间未发现显著性差异。综上反映了抑郁症患者情绪加工网络的异常特性,为抑郁症患者神经网络机制的研究提供了一定的参考。
[Abstract]:Study on patients with depression and normal human brain in emotional cognitive tasks under the different functions of the network whether there are differences. By using the method of phase synchronization connection strength to measure the different brain regions of the small world topology using the network parameters of global and local efficiency to describe the brain. Selected 16 patients with depression and 14 normal subjects of cognition the task of positive and negative emotional faces search, simultaneous recording of scalp EEG. Low gamma (30~50 Hz) and gamma (50~80 Hz) two bands of data to establish a matrix phase synchronization. The results showed that: the global phase depression group synchronization value is higher than the normal group; the low cost of the network in the range of gamma band (0.25~0.50). High frequency of gamma network cost range (0.25~0.55), a global network between emotional processing and average local efficiency between random networks and regular network, small world properties in high gamma; In the band, the maximum effect of fee difference (the cost of the network is 0.3), the overall efficiency values were significantly different between groups, the local efficiency had no significant difference found in the network; the cost is 0.5, found that local depression group efficiency in the left parieto temporal area and occipital area was significantly higher than the normal group, no significant difference found in the mood. The characteristics of the network reflects abnormal emotion processing in patients with depression, provide a reference for study of the mechanism of neural network in patients with depression.

【作者单位】：上海大学通信与信息工程学院上海大学生物医学工程研究所;
【基金】：国家自然科学基金(61171032) 上海市教委自然科学创新重点项目(12ZZ099)
【分类号】：R749.4

【相似文献】