高特质焦虑个体情绪注意偏向的脑网络研

The topological structure and attributes of brain network are analyzed by the complex network analysis method to explore the brain function mechanism of emotional attention bias in individuals with high trait anxiety. Fifteen volunteers with high trait anxiety (HTA) and 15 volunteers with low trait anxiety (LTA) are selected to perform the task of searching for three emotional faces (happy, neutral and angry), and 64-channel electroencephalogram (EEG) is recorded simultaneously. Synchronous likelihood analysis is performed on EEG, the overall attribute parameters (global efficiency, clustering coefficient and characteristic path length) and node attribute parameters (node degree) of the network are calculated. The intra-group statistical analysis shows that in both the HTA and LTA groups, the node degrees of frontal and temporal lobe, clustering coefficient and global efficiency under angry face search task are significantly larger than the values of happy and neutral faces, while the characteristic path length is smaller than those of happy and neutral faces. The statistical analysis between groups shows that the node degrees of frontal and temporal lobe in HTA group are significantly larger than those in LTA group under the three face search tasks. In particular, the difference between the HTA and LTA groups is more obvious (P<0.001) under the angry face search task. Both the node attribute parameters and the overall attribute parameters of the HTA group are significantly different from those of the LTA group under the anger face search task, while there is significant difference only in node attribute parameters (not in the overall attribute parameters) between the HTA and LTA groups under happy and neutral face search tasks. As a result, HTA individuals are sensitive to emotional (especially negative emotional) information, the neural mechanism may be related to enhanced activity of frontal and temporal lobes and enhanced activity of brain network information transmission. This study explores the brain function characteristics of emotional cognition in HTA individuals from the level of brain network, which can provide a new perspective for revealing the cognitive neural mechanism of mental disorders such as anxiety disorder and depression.