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静止状态EEG网络的图形理论分析区分了阿尔茨海默病和前性痴呆症

Li Zhu¹, Yue Pan², Zi-Liang Wang³

¹Department of Public Courses, Zhenjiang College, Jiangsu, China.

The International journal of neuroscience

|January 22, 2026

概括

脑电图 (EEG) 图形理论分析揭示了阿尔茨海默病 (AD) 和前性痴呆症 (FTD) 之间的明显大脑网络差异. 这些发现可能有助于使用EEG生物标志物区分痴呆症亚型.

科学领域:

神经科学是一个神经科学.
医疗成像医学成像
网络科学网络科学

背景情况:

阿尔茨海默病 (AD) 和前性痴呆症 (FTD) 是神经退行性疾病,症状重叠,使得诊断具有挑战性.
来自脑电图 (EEG) 的大脑连接指标提供了对大脑网络组织的见解,但需要进一步对AD和FTD进行比较分析.

研究的目的:

用EEG衍生图形理论指标研究和区分AD和FTD中的大脑网络变化.
探索EEG图表指标作为区分痴呆症亚型的生物标志物的潜力.

主要方法:

对公开的EEG数据集的分析,包括36名AD患者,23名FTD患者和29名健康对照 (HC) 患者.
休息状态眼睛关闭和眼睛打开的脑电图在三角形,三角形,α和β频段进行了分析.
使用相锁值 (PLV) 估计了功能连接,并通过大脑连接工具箱计算了图形理论指标.

主要成果:

阿尔茨海默病患者的全球效率和小世界性降低,特别是在α和β频段 (闭眼),表明全球整合受损.
前性痴呆症患者在前部/中部区域表现出局部网络干扰,在特定电极 (F3/F4,Pz) 上节点程度和局部效率降低,这表明区域特异性功能障碍.
这些网络差异在两个组的闭眼条件下更加明显.

结论:

通过EEG图形理论分析,成功地发现了AD和FTD特有的独特网络变化.
阿尔茨海默病与全球网络整合受损和小世界架构的丧失有关.
FTD的特点是特定区域的网络中断,这表明EEG图表指标是潜在的成本效益高的痴呆症亚型差异化生物标志物.

关键词:

阿尔茨海默氏症是阿尔茨海默氏症的一种疾病.这是一个EEGEEGEEGEEGEEG.前性痴呆症前性痴呆症图形理论中的图形理论.网络效率网络效率网络效率小小的世界性.

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