ABSTRACT
The detailed mechanisms by which re-entry and ventricular fibrillation are initiated in the heart remain poorly understood because they are difficult to investigate experimentally. We have used a simplified excitable media computational model of action potential propagation to systematically study how re-entry can be produced by diffuse regions of inexcitable tissue. Patterns of excitable and inexcitable tissue were generated using a genetic algorithm. The inexcitable tissue was modeled in two ways: (i) diffusive, electrically connected but inexcitable tissue, or (ii) zero-flux, areas of tissue electrically disconnected in the same way as zero-flux boundary conditions. We were able to evolve patterns of diffuse inexcitable tissue that favored re-entry, but no single structure or pattern emerged. Diffusive inexcitable regions were inherently less arrhythmogenic than zero-flux inexcitable ones.
Subject(s)
Algorithms , Biophysics/methods , Heart/physiology , Myocardium/pathology , Animals , Computer Simulation , Heart Ventricles/pathology , Humans , Models, Biological , Models, Cardiovascular , Models, Genetic , Models, TheoreticalABSTRACT
We present an n-fold way kinetic Monte Carlo simulation of the hopping motion of Li+ ions in polyethylene on a grid of mesh 0.36 A superimposed on the voids of the rigid polymer. The structure of the polymer is derived from a higher-order simulation, and the energy of the ion at each site is derived by the self-consistent polarization field method. The ion motion evolves in time from free flight through anomalous diffusion to normal diffusion, with the average energy tending to decrease with increasing temperature through thermal annealing. We compare the results with those of hopping models with probabilistic energy distributions of increasing complexity by analyzing the mean-square displacement and the average energy of an ensemble of ions. The Gumbel distribution describes the ion energy statistics in this system better than the usual Gaussian distribution does; including energy correlation greatly affects the ion dynamics. The analysis uses the standard data compression program GZIP, which proves to be a powerful tool for data analysis by giving a measure of recurrences in the ion path.