在默认模式网络中异常增强的马同步与慢性疼痛相关
Zhaoshun Jiang1,2, Fei Tao1, Feidong Lv1
1Department of Anesthesiology, Huadong Hospital, Fudan University, Shanghai, China.
European journal of neurology
|October 10, 2025
概括
慢性疼痛涉及到大脑活动的改变,特别是在默认模式网络 (DMN) 中增加了马同步. 这种DMN马同步显示出作为慢性疼痛诊断的神经标记物的潜力.
科学领域:
- 神经科学是一个神经科学.
- 神经生理学 神经生理学
- 医疗成像医学成像
背景情况:
- 慢性疼痛的机制尚未完全理解.
- 持续的疼痛影响全球数百万人.
- 慢性疼痛的神经特征需要识别.
研究的目的:
- 研究慢性疼痛中的大脑振荡和连接.
- 识别用于慢性疼痛诊断的神经特征.
- 探索默认模式网络 (DMN) 在慢性疼痛中的作用.
主要方法:
- 分析了42名慢性疼痛患者和42名对照组的脑电图 (EEG) 数据.
- 利用基于网络的统计数据进行连接分析.
- 使用机器学习来评估神经特征作为生物标志物.
主要成果:
- 慢性疼痛患者显示高频功率下降,但增强了马同步.
- 观察到DMN内部加大了马同步,特别是在具有更强的内连接的状态.
- 一个机器学习模型在使用DMN连接功能来区分患者和对照者方面实现了75.5%的准确性.
结论:
- 增强的DMN马同步在慢性疼痛病理生理学中至关重要.
- DMN马同步可能作为一种有价值的慢性疼痛神经标志物.
- 这项研究为慢性疼痛的神经支提供了新的见解.
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