Kurth Jutta G, Rings Thorsten, Lehnertz Klaus
Department of Epileptology, University Hospital Bonn, Venusberg Campus 1, 53127 Bonn, Germany.
Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn, Germany.
Entropy (Basel). 2021 Mar 5;23(3):309. doi: 10.3390/e23030309.
Stochastic approaches to complex dynamical systems have recently provided broader insights into spatial-temporal aspects of epileptic brain dynamics. Stochastic qualifiers based on higher-order Kramers-Moyal coefficients derived directly from time series data indicate improved differentiability between physiological and pathophysiological brain dynamics. It remains unclear, however, to what extent stochastic qualifiers of brain dynamics are affected by other endogenous and/or exogenous influencing factors. Addressing this issue, we investigate multi-day, multi-channel electroencephalographic recordings from a subject with epilepsy. We apply a recently proposed criterion to differentiate between Langevin-type and jump-diffusion processes and observe the type of process most qualified to describe brain dynamics to change with time. Stochastic qualifiers of brain dynamics are strongly affected by endogenous and exogenous rhythms acting on various time scales-ranging from hours to days. Such influences would need to be taken into account when constructing evolution equations for the epileptic brain or other complex dynamical systems subject to external forcings.
随机方法应用于复杂动力系统，最近为癫痫性脑动力学的时空方面提供了更广泛的见解。基于直接从时间序列数据导出的高阶克莱默斯-莫亚尔系数的随机限定符表明，生理和病理生理脑动力学之间的可区分性得到了改善。然而，目前尚不清楚脑动力学的随机限定符在多大程度上受到其他内源性和/或外源性影响因素的影响。为了解决这个问题，我们研究了一名癫痫患者的多天、多通道脑电图记录。我们应用最近提出的一个标准来区分朗之万型过程和跳跃扩散过程，并观察最适合描述脑动力学的过程类型如何随时间变化。脑动力学的随机限定符受到作用于从数小时到数天等各种时间尺度的内源性和外源性节律的强烈影响。在构建癫痫脑或其他受外部强迫作用的复杂动力系统的演化方程时，需要考虑到这种影响。
