Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan.
Oxford Center for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom; and Wellcome Center for Integrative Neuroscience, University of Oxford, Oxford, United Kingdom.
Anesthesiology. 2022 Sep 1;137(3):290-302. doi: 10.1097/ALN.0000000000004293.
A complex system is often associated with emergence of new phenomena from the interactions between the system's components. General anesthesia reduces brain complexity and so inhibits the emergence of consciousness. An understanding of complexity is necessary for the interpretation of brain monitoring algorithms. Complexity indices capture the "difficulty" of understanding brain activity over time and/or space. Complexity-entropy plots reveal the types of complexity indices and their balance of randomness and structure. Lempel-Ziv complexity is a common index of temporal complexity for single-channel electroencephalogram containing both power spectral and nonlinear effects, revealed by phase-randomized surrogate data. Computing spatial complexities involves forming a connectivity matrix and calculating the complexity of connectivity patterns. Spatiotemporal complexity can be estimated in multiple ways including temporal or spatial concatenation, estimation of state switching, or integrated information. This article illustrates the concept and application of various complexities by providing working examples; a website with interactive demonstrations has also been created.
复杂系统通常与系统组件之间的相互作用产生新现象有关。全身麻醉会降低大脑的复杂性，从而抑制意识的出现。理解复杂性是解释脑监测算法所必需的。复杂性指数捕捉了随时间和/或空间理解大脑活动的“难度”。复杂度-熵图揭示了复杂性指数的类型及其随机性和结构的平衡。Lempel-Ziv 复杂度是一种常见的单通道脑电图时间复杂度指数，包含功率谱和非线性效应，通过相位随机化替代数据揭示。计算空间复杂度涉及形成连接矩阵并计算连接模式的复杂性。可以通过多种方式估计时空复杂性，包括时间或空间的串联、状态切换的估计或综合信息。本文通过提供实际示例说明了各种复杂性的概念和应用；还创建了一个带有交互式演示的网站。
