自然主义的急性疼痛状态从神经和面部动态解码
Yuhao Huang1, Jay Gopal2, Bina Kakusa3
1Department of Neurosurgery, Stanford University School of Medicine, Palo Alto, CA, USA. yhhuang@stanford.edu.
Nature communications
|May 11, 2025
概括
研究人员用患者的大脑活动和面部表情解码了急性疼痛状态. 这揭示了可靠的神经行为疼痛标志物,用于现实世界的监测和个性化干预.
科学领域:
- 神经科学是一个神经科学.
- 疼痛研究 疼痛研究
- 计算神经科学是一种神经科学.
背景情况:
- 在自然,无任务的环境中理解疼痛是有限的.
- 现有的研究往往缺乏现实世界的适用性.
- 急性疼痛的神经行为基础需要进一步调查.
研究的目的:
- 在自然主义的背景下解码急性疼痛状态.
- 为了确定可靠的神经行为疼痛标志物.
- 探索现实世界疼痛监测的潜力.
主要方法:
- 多模式方法:内脑电图 (iEEG),疼痛自我报告,面部表情分析.
- 机器学习用于从神经活动和面部表情解码疼痛状态.
- 在12名患者中进行持续的神经和视听监测.
主要成果:
- 成功解码来自分布神经活动的高与低疼痛状态 (中临界区域,纹状体,时皮层).
- 神经疼痛表示数小时稳定,并根据疼痛开始/缓解进行调节.
- 客观面部表情也分类疼痛状态,与神经发现相关联.
- 使用神经和面部特征,从中性状态识别和区分暂时疼痛的短暂时期.
结论:
- 在自然环境中建立了可靠的神经行为标记,用于急性疼痛.
- 证明了现实世界疼痛监测的潜力.
- 突出了个性化疼痛干预的可能性.
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