We propose a new biological framework based on the Lynch et al. theory of Hybrid I/O Automata (HIOAs) for modeling and simulating excitable tissue. Within this framework, we view an excitable tissue as a composition of two main kinds of component: a diffusion medium and a collection of cells, both modeled as an HIOA. This approach yields a notion of decomposition that allows us to describe a tissue as the parallel composition of several interacting tissues, a property that could be exploited to parallelize, and hence improve, the efficiency of the simulation process. Wealso demonstrate the feasibility of our HIOA-based framework to capture and mimic different kinds of wave-propagation behavior in 2D isotropic cardiac tissue, including normal wave propagation along the tissue; the creation of spiral waves; the break-up of spiral waves into more complex patterns such as fibrillation; and the recovery of the tissue to the rest via electrical defibrillation.
Theoretical Computer Science (TCS), volume 410(33-34), pp. 3149-3165, August, 2009.
*This work was supported by the NSF Faculty Early Career
Development Award CCR01-33583 and the NSF CCF05-23863 Award.