通过内在概率密度函数量化意识
Norden E Huang1, Wei-Shuai Yuan2, Albert C Yang3
1Institute of Brain Science, National Yang-Ming Chiao Tung University, Taipei 11221, Taiwan; Cognitive Intelligence and Precision Healthcare Center, National Central University, Taoyuan 320317, Taiwan; First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China.
Biological psychology
|August 8, 2025
概括
我们引入了内在概率密度函数 (iPDF) 来量化意识动态. 这种新的方法可以区分大脑状态,在清醒时显示超高斯模式,在减少意识时显示近高斯模式,有助于临床查.
科学领域:
- 神经科学是一个神经科学.
- 定量生物学 定量生物学
- 信号处理 信号处理
背景情况:
- 意识是复杂的,很难用传统方法量化.
- 了解不同意识状态背后的神经动态至关重要.
- 现有的方法可能无法完全捕捉神经活动中的微妙变化.
研究的目的:
- 提出和验证内在概率密度函数 (iPDF) 作为评估意识状态中的皮层间相互作用的定量度量.
- 评估iPDF在区分各种生理和病理大脑疾病中的实用性.
- 建立一个强大的框架来评估意识.
主要方法:
- 经验模式分解 (EMD) 来从电脑电图 (EEG) 信号中提取内在模式函数 (IMF).
- 为IMF的连续部分和生成规模依赖的概率密度函数.
- 在全身麻醉,睡眠阶段,感官状况和痴呆症患者与健康对照对 iPDF 分析进行测试.
主要成果:
- 超高斯 iPDF 模式在清醒和REM 睡眠期间具有活跃神经相互作用的特征.
- 接近高斯的iPDF配置文件与麻醉和深度睡眠中的神经相互作用减少有关.
- 使用iPDF特征的分类模型在区分痴呆症患者和健康受试者方面实现了~87%的准确性.
结论:
- 意识是从复杂的,规模依赖的神经过程中产生的.
- 该iPDF提供了一个强大的定量框架来评估意识.
- iPDF分析显示,它有可能作为临床查的生物标志物,特别是神经退行性疾病.
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