时空大脑复杂性量化了干扰范式之外的意识
Martin Breyton1, Jan Fousek2, Giovanni Rabuffo3
1Aix-Marseille Université, APHM, Inserm, INS Institut de Neurosciences des Systèmes, Hôpital Sainte-Marguerite, Service de Pharmacologie Clinique et Pharmacosurveillance, Marseille, France.
eLife
|October 23, 2025
概括
研究人员确定了一个"流动"的大脑状态,其特点是高网络重组,这预测了意识水平. 与复杂的扰动方法相比,这提供了一种更简单的方法来测量意识.
科学领域:
- 神经科学是一个神经科学.
- 动态系统理论 动态系统理论
- 计算精神病学是一种计算精神病学.
背景情况:
- 意识与神经元活动模式有关.
- 时空复杂性是意识的一个有希望的指标,但需要困难的扰乱方法.
- 需要替代的,可访问的指标用于常规的临床使用.
研究的目的:
- 探索测量意识的替代方法.
- 来识别休息状态大脑活动的新指标.
- 将这些指标与既有措施和药物效应进行验证.
主要方法:
- 在全脑模型中系统地探索大脑刺激和静止状态活动.
- 动态模式和网络重组的分析.
- 动态系统理论指标的应用.
- 在各种意识状态和药物影响下 (Xenon,Propofol,Ketamine) 的15个人类受试者的队列中验证.
主要成果:
- 确定了一种特定的动态模式,称为"高脑流动性".
- 这种模式的特点是自发活动期间显著的功能网络重组.
- 这种方案的指标成功地预测了改变意识的药物的影响.
- 这些发现与人类受试者的已建立的扰乱复杂度指标进行了验证.
结论:
- 高度的脑流动性,可以通过可访问的指标来衡量,作为意识的强有力的指标.
- 这一发现为在临床环境中评估意识提供了更实用的范式.
- 这项研究强调了大脑动态的复杂性在意识的出现中的重要性.
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