The observational ubiquity of inverse power law spectra (IPL) in complex phenomena entails theory for dynamic fractal phenomena capturing their fractal dimension, dynamics, and statistics. These and other properties are consequences of the complexity resulting from nonlinear dynamic networks collectively summarized for biomedical phenomena as the Network Effect (NE) or focused more narrowly as Network Physiology. Herein we address the measurable consequences of the NE on time series generated by different parts of the brain, heart, and lung organ networks, which are directly related to their inter-network and intra-network interactions. Moreover, these same physiologic organ networks have been shown to generate crucial event (CE) time series, and herein are shown, using modified diffusion entropy analysis (MDEA), to have scaling indices with quasiperiodic changes in complexity, as measured by scaling indices, over time. Such time series are generated by different parts of the brain, heart, and lung organ networks, and the results do not depend on the underlying coherence properties of the associated time series but demonstrate a generalized synchronization of complexity. This high order synchrony among the scaling indices of EEG (brain), ECG (heart), and respiratory time series is governed by the quantitative interdependence of the multifractal behavior of the various physiological organs' network dynamics. This consequence of the NE opens the door for an entirely general characterization of the dynamics of complex networks in terms of complexity synchronization (CS) independently of the scientific, engineering, or technological context.
翻译:在复杂现象中,反动力法光谱(IPL)的观测无处不在,这就要求对动态分形现象进行理论理论,以捕捉其分形的维度、动态和统计。这些和其他特性是生物医学现象的非线性动态网络(网络效应(NE))综合归纳为生物医学现象的非线性动态网络(网络效应(MDEA)综合归纳为网络效应(NE)或网络生理生理学比较集中为网络。这里我们讨论NE对由大脑、心脏和肺器官网络不同部分产生的时间序列的可测量后果,这些后果与其相关时间序列和网络内部互动直接相关。此外,这些物理器官网络已证明了产生关键事件(CE)时间序列的结果。这里还展示了使用经修改的传播酶分析(MDEA)将指数缩放为复杂性的准周期性指数,按指数的缩放为时间序列。这种时间序列是由大脑、心脏和肺器官器官网络的不同部分生成的,其结果并不取决于相关时间序列的基本一致性特性,但显示其复杂性的普遍同步性。在EG(CEG)的整个时间性结构结构结构结构结构结构结构结构结构变化变化中,其整个结构结构变化的分系的分级变化的分导结果。