Accurate numerical simulation of electrodiffusion and water movement in brain tissue

TL;DR

This paper develops and evaluates finite element-based numerical schemes for simulating ionic electrodiffusion and water movement in brain tissue, emphasizing accuracy and efficiency in physiologically relevant scenarios like cortical spreading depression.

Contribution

It introduces and assesses novel splitting schemes for complex electrodiffusion models, highlighting their accuracy, convergence, and computational performance in brain tissue simulations.

Findings

Optimal convergence rates for smooth solutions.

High resolution needed for accurate CSD wave characteristics.

Challenges in simulating physiologically relevant scenarios.

Abstract

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.