在阿尔茨海默病中,默认模式网络功能障碍和认知衰退的神经生理学特征
Recep A Ozdemir1,2, Brice Passera1,2, Peter J Fried1,2
1Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Science advances
|November 28, 2025
概括
阿尔茨海默氏症 (AD) 显示神经过度兴奋. 一种新的TMS-EEG方法揭示了AD中特定网络的大脑功能障碍,预测认知能力下降,并提供潜在的早期检测标记.
科学领域:
- 神经科学是一个神经科学.
- 神经学 神经学
- 生物医学工程 生物医学工程
背景情况:
- 阿尔茨海默病 (AD) 的特点是神经过度刺激和动物模型中的网络功能障碍.
- 这些神经生理学变化的存在和临床意义在人类中尚不清楚.
- 调查默认模式网络 (DMN) 对于了解早期AD至关重要.
研究的目的:
- 通过基于扰乱的方法,研究早期AD中DMN功能障碍的神经生理基础.
- 为了比较静止状态EEG (rsEEG) 和与EEG (TMS-EEG) 结合的跨磁刺激的见解.
- 确定AD中网络特异的神经生理学障碍的临床相关性.
主要方法:
- 使用基于扰动的方法,结合了跨磁刺激和脑电图 (TMS-EEG).
- 使用休息状态EEG (rsEEG) 来评估整体大脑活动.
- 分析了DMN活动,连接性以及它们与认知功能和大脑结构的关系.
主要成果:
- rsEEG显示全球神经减速和失调的同步,表明广泛的变化.
- TMS-EEG检测出神经壁膜网的局部网络特异性过敏性,以及与前部膜网区域的连接中断.
- 这些TMS-EEG发现独特地预测了认知障碍,并调解了大脑结构和认知之间的联系.
结论:
- 网络特异的神经生理学障碍,特别是DMN内的过度兴奋和改变的连接性,显著导致AD相关的认知功能障碍.
- 基于乱的评估,如TMS-EEG显示,作为早期阿尔茨海默病检测,疾病进展监测和治疗干预措施评估的潜在生物标志物具有前途.
- 恢复异常的神经生理学是AD的潜在治疗策略.
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