Cardiac Reentry Modeled by Spatiotemporal Chaos in a Coupled Map Lattice

TL;DR

This paper introduces a simplified, map-based model of cardiac tissue that captures complex arrhythmic behaviors, including reentry and spiral waves, providing insights into the dynamics of heart arrhythmias with fewer parameters than traditional models.

Contribution

It demonstrates the effectiveness of three-dimensional map-based models in simulating complex cardiac arrhythmias, offering a computationally efficient alternative to detailed conductance-based models.

Findings

Reentry phenomena modeled with spatiotemporal chaos.

Identification of torsade de pointes in simulations.

Discovery of wavefronts with synchronized plateaus and bursts.

Abstract

Arrhythmias are potentially fatal disruptions to the normal heart rhythm, but their underlying dynamics is still poorly understood. Theoretical modeling is an important tool to fill this gap. Typical studies often employ detailed multidimensional conductance-based models. We describe the cardiac muscle with a three-dimensional map-based membrane potential model in lattices. Although maps retain the biophysical behavior of cells and generate computationally efficient tissue models, few studies have used them to understand cardiac dynamics. Our study captures healthy and pathological behaviors with fewer parameters and simpler equations than conductance models. We successfully generalize results obtained previously with reaction-diffusion systems, showing how chaotic properties result in reentry, a pathological propagation of stimuli that evolves to arrhythmias with complex spatiotemporal features. The bifurcation diagram of the single cell is very similar to that obtained in a detailed conductance-based model. We find torsade de pointes, a clinical manifestation of some types of tachycardia in the electrocardiogram, using a generic sampling of the whole network during spiral waves. We also find a novel type of dynamical pattern, with wavefronts composed of synchronized cardiac plateaus and bursts. Our study provides the first in-depth look at the use of map-based models to simulate complex cardiac dynamics.