Fibrillatory activity in cardiac reaction-diffusion models with time-varying parameters

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Atrial fibrillation (AF) is the most frequent arrhythmia and a major cause of stroke. My research program involves simulating these rhythm disorders in computer models of the atria to get insights into their mechanisms and investigate the factors promoting their occurrence. Cardiac electrical activity can be mathematically described by reaction-diffusion systems that integrate biological data from ion channel to organ anatomy. Some model parameters (e.g. ion channel conductances) may be regulated by external factors, e.g. by the autonomic nervous system through acetylcholine (ACh) release. We are going to study in a computational environment how time-dependent variation of parameters affects the vulnerability to atrial arrhythmias and the ensuing fibrillatory dynamics, using time-varying ACh action as a paradigm.