Global analysis of self-sustained reentry by cellular automata models

It is demonstrated in a simple first-order cellular automata model that a statistical dynamical approach provides a mechanism for the analysis of self-sustained reentrant arrhythmias by stationary probability distributions describing the global state of the heart, analogous to a thermodynamic equilibrium in statistical mechanics. The description of parameters of local conduction physiology is coupled to the structure of the global pattern of self-sustained reentrant activity which results from that conduction physiology. This formulation may therefore serve as a guide to optimizing the effect of antiarrhythmic pharmaceuticals, based on their effects on local conduction physiology, as well as a guide to developing novel diagnostic information about local conduction physiology from measures of global patterns of activity, such as the electrocardiogram