Department of Mathematics, University of Oslo, P.O.Box 1053 Blindern, 0316, Oslo, Norway.
Department of Computational Physiology, Simula Research Laboratory, 1325, Lysaker, Norway.
J Comput Neurosci. 2020 May;48(2):229-251. doi: 10.1007/s10827-020-00746-5. Epub 2020 May 12.
In this paper, we investigate the dynamics of a neuron-glia cell system and the underlying mechanism for the occurrence of seizures. For our mathematical and numerical investigation of the cell model we will use bifurcation analysis and some computational methods. It turns out that an increase of the potassium concentration in the reservoir is one trigger for seizures and is related to a torus bifurcation. In addition, we will study potassium dynamics of the model by considering a reduced version and we will show how both mechanisms are linked to each other. Moreover, the reduction of the potassium leak current will also induce seizures. Our study will show that an enhancement of the extracellular potassium concentration, which influences the Nernst potential of the potassium current, may lead to seizures. Furthermore, we will show that an external forcing term (e.g. electroshocks as unidirectional rectangular pulses also known as electroconvulsive therapy) will establish seizures similar to the unforced system with the increased extracellular potassium concentration. To this end, we describe the unidirectional rectangular pulses as an autonomous system of ordinary differential equations. These approaches will explain the appearance of seizures in the cellular model. Moreover, seizures, as they are measured by electroencephalography (EEG), spread on the macro-scale (cm). Therefore, we extend the cell model with a suitable homogenised monodomain model, propose a set of (numerical) experiment to complement the bifurcation analysis performed on the single-cell model. Based on these experiments, we introduce a bidomain model for a more realistic modelling of white and grey matter of the brain. Performing similar (numerical) experiment as for the monodomain model leads to a suitable comparison of both models. The individual cell model, with its seizures explained in terms of a torus bifurcation, extends directly to corresponding results in both the monodomain and bidomain models where the neural firing spreads almost synchronous through the domain as fast traveling waves, for physiologically relevant paramenters.
在本文中,我们研究了神经元-神经胶质细胞系统的动力学及其引发癫痫发作的潜在机制。对于我们对细胞模型的数学和数值研究,我们将使用分岔分析和一些计算方法。结果表明,储层中钾浓度的增加是引发癫痫发作的一个触发因素,与环面分岔有关。此外,我们将通过考虑简化版本来研究模型的钾动力学,并展示这两种机制是如何相互关联的。此外,钾泄漏电流的减少也会引发癫痫发作。我们的研究表明,增强外液钾浓度(影响钾电流的能斯特电位)可能导致癫痫发作。此外,我们将表明,外部强制项(例如作为单向矩形脉冲的电休克,也称为电惊厥疗法)将建立类似于增加外液钾浓度的无强制系统的癫痫发作。为此,我们将单向矩形脉冲描述为一个自治的常微分方程系统。这些方法将解释细胞模型中癫痫发作的出现。此外,癫痫发作,如脑电图(EEG)所测量的那样,在宏观尺度(cm)上传播。因此,我们通过合适的均匀化单域模型扩展细胞模型,提出了一组(数值)实验来补充对单细胞模型进行的分岔分析。基于这些实验,我们引入了一个双域模型,以更真实地模拟大脑的白质和灰质。执行与单域模型类似的(数值)实验会导致两种模型的合适比较。个体细胞模型及其以环面分岔解释的癫痫发作,可以直接扩展到单域和双域模型中的相应结果,在这些模型中,神经放电以快速传播波的形式几乎同步传播穿过域,对于生理相关的参数。