Técnicas computacionais para a solução numérica de modelos cardíacos baseados em cadeias de Markov

Abstract

This work compares different numerical schemes for the solution of modern electrophysiology models for cardiac myocytes. We present the Uniformization Method - frequently applied to stochastic problems in computer science - which significantly increase the numerical stability when used for the solution of cardiac models based on Continuous Time Markov Chains, with respect to traditional explicit schemes such as Rush-Larsen Method and Foward Euler Method. The Markov Chains formulation for subcellular structures, e.g. ionic channels, enables an accurate description of the electrical behaviour of cardiac cells for important experimental applications, for instance the simulation of the effects of drugs or toxins on the electrical activity of the cell's membrane. However, the differential equations associated with the Markov Chains for ionic channels frequently cause problems of numerical stability, which severely limits the time step used by explicit schemes. By using the Uniformization Method we could significantly increase the time steps size in simulations of three models of cardiac electrophysiology based on Markov Chains. In this work we show how the Uniformization Method can be used along with other foward numerical schemes for the solution of these models, and how these techniques significantly improve the computational performance with respect to traditional numerical methods. In adition, we propose extensions of the Rush-Larsen method and the Uniformization method with second-order accuracy for developing foward time-adaptive techniques, aiming to reduce the computational cost of simulations with strict numerical tolerances.