Mathematical modelling of ionic electrodiffusion and water movement is emerging as a powerful avenue of investigation to provide new physiological insight into brain homeostasis. However, in order to provide solid answers and resolve controversies, the accuracy of the predictions is essential. Ionic electrodiffusion models typically comprise non-trivial systems of non-linear and highly coupled partial and ordinary differential equations that govern phenomena on disparate time scales. Here, we study numerical challenges related to approximating these systems. We consider a homogenized model for electrodiffusion and osmosis in brain tissue and present and evaluate different associated finite element-based splitting schemes in terms of their numerical properties, including accuracy, convergence, and computational efficiency for both idealized scenarios and for the physiologically relevant setting of cortical spreading depression (CSD). We find that the schemes display optimal convergence rates in space for problems with smooth manufactured solutions. However, the physiological CSD setting is challenging: we find that the accurate computation of CSD wave characteristics (wave speed and wave width) requires a very fine spatial and fine temporal resolution.
翻译:电离电流和水运动的数学建模正在形成一个强大的调查渠道,以提供对脑组织内电流和渗透的新生理洞察力。然而,为了提供可靠的答案和解决争议,预测的准确性至关重要。电离电流模型通常包括非线性和非线性和非线性和非线性以及高度交错的局部和普通等式的非三维系统,在不同的时间尺度上制约现象。在这里,我们研究与这些系统相近相关的数字挑战。我们认为大脑组织内电流和渗透的同质化模型,并且提出和评估与其数字特性相关的不同、以元素为基础的不同有限分裂计划,包括理想情景的准确性、趋同性和计算效率,以及与生理相关的波状扩散抑郁(CSD)的形成。我们发现,这些系统在空间中表现出最佳的趋同率,解决平滑的解决方案存在问题。但是,CSD的生理环境具有挑战性:我们发现,准确计算CD波特性(波速和波波宽度)需要非常精确的空间和精确的时间分辨率分辨率分辨率。