首发精神分裂症患者脑网络特征提取与分析

Feature Extraction and Analysis of Brain Network in First-Episode Schizophrenics

精神分裂症是一种慢性迁延性疾病,在我国患病率平均每年在6‰~10‰之间,即1%左右,这个数字是比较大的。为了探索精神分裂症的病灶,基于首发精神分裂症患者和健康被试的静息态脑电数据提出了一种精神分裂症分类方法。同时分析了患者在治疗前后的脑区变化以及认知功能与脑功能活动的相关性,显著特征与量表得分和用药量的相关性。实验结果证明,β、δ和θ频段的病灶集中在额叶和颞叶。与治疗前相比,治疗后患者的额叶连通性有所改善。显著特征与panss分显著相关,与用药量无显著相关性。

Schizophrenia is a chronic persistent disease. The average annual prevalence rate in China is between 6‰ and 10‰, or about 1%, which is relatively large. In order to explore the focus of schizophrenia, a classification method of schizophrenia is proposed based on resting EEG data of first-episode schizophrenics and healthy subjects. At the same time, this paper analyzes the changes of brain regions, the correlation between the cognitive function and functional brain activity, and the significant characteristics and the scale score and drug dosage before and after treatment. The experimental results prove that the lesions in β, δ and θ frequency band are concentrated in frontal lobe and temporal lobe. Compared with before treatment, the frontal lobe connectivity of patients after treatment is improved. The significant characteristics are significantly correlated with panss scores, but not with drug dosage.