心因性疾病
脑电图
线性判别分析
癫痫
神经科学
脑功能
心理学
静息状态功能磁共振成像
判别函数分析
医学
人工智能
计算机科学
精神科
机器学习
作者
Zhenyu Wang,Qi‐Kun Xue,Xiuchun Xiong,Peiyang Li,Chunyang Tian,Cehong Fu,Yuping Wang,Dezhong Yao,Peng Xu
出处
期刊:PubMed
日期:2015-02-01
卷期号:32 (1): 8-12
摘要
Studies have shown that the clinical manifestation of patients with neuropsychiatric disorders might be related to the abnormal connectivity of brain functions. Psychogenic non-epileptic seizures (PNES) are different from the conventional epileptic seizures due to the lack of the expected electroencephalographically epileptic changes in central nervous system, but are related to the presence of significant psychological factors. Diagnosis of PNES remains challenging. We found in the present work that the connectivity between the frontal and parieto-occipital in PNES was weaker than that of the controls by using network analysis based on electroencephalogram (EEG) signals. In addition, PNES were recognized by using the network properties as linear discriminant nalysis (LDA) input and classification accuracy was 85%. This study may provide a feasible tool for clinical diagnosis of PNES.
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