大学生焦虑人群情绪冲突反应的脑功能网络研究

doi:10.3969/j.issn.0258-8021.2020.02.03

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Abstract The aim of this work is to analyze the topological structure and properties of brain network with complex network analysis method based on graph theory exploring the characteristics of brain functional network in emotional conflict response on anxious population of college students. Sixteen volunteers in the anxiety group and the normal control group were selected for the emotional word-face stroop conflict task, and 64 EEG were recorded simultaneously. The EEG data with beta(14 ～ 30 Hz) and high gamma(50 ～ 80 Hz) were analyzed by synchronous likelihood analysis, and the appropriate threshold value was selected to construct the brain network topology, and the node degree and clustering coefficient of the network were calculated. Results showed that in beta and high-gamma rhythms, there were abnormal connections in the brain areas including frontal lobe, temporal lobe, and parietal lobe in anxiety group, and the node degree of frontal lobe and parietal lobe was lower than that of normal group (P<0.05), while the node degree of temporal lobe was higher than that of the normal group (P<0.05)(in beta rhythm,the node degrees of the frontal FP1, parietal CP1 and temporal T7 electrodes were 5.21±0.62, 6.25±0.53, 7.91±0.71 respectively in anxiety group and 10.42±1.53, 7.94±0.55, 3.55±0.36 in the normal group, indicating that the function of frontal lobe and parietal lobe were decreased in the anxiety group, while the function of temporal lobe was increased. The clustering coefficient of the brain network in the anxiety group was lower than that in the normal group (P<0.05) (the clustering coefficients of beta and high gamma rhythm in anxiety group were 0.523 8±0.039 2 and 0.586 4±0.055 8, respectively, while those in normal group were0.603 2±0.071 1 and 0.664 7±0.060 1), which indicated that the degree of internal clustering of the brain network in the anxious group and the information transmission ability of the network were decreased. This study can provide a new perspective for the neural mechanism research of psychological and mental diseases such as anxiety and depression.

Key words： anxiety the brain network synchronous likelihood analysis Stroop conflict

Received: 30 August 2019

PACS:

R318

Corresponding Authors: ^*E-mail: shumeiji110@126.com

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	Ji Shumei
	Su Xinle
	Xun Xingmiao
	Bu Xinxin
	Xu Quansheng

Cite this article:

Ji Shumei,Su Xinle,Xun Xingmiao, et al. Study on Brain Function Network of Emotional Conflict Response inCollege Students with Anxiety[J]. Chinese Journal of Biomedical Engineering, 2020, 39(2): 145-151.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2020.02.03 OR http://cjbme.csbme.org/EN/Y2020/V39/I2/145

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