Abstract
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. We also 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.
| Original language | English |
|---|---|
| Pages (from-to) | 3149-3165 |
| Number of pages | 17 |
| Journal | Theoretical Computer Science |
| Volume | 410 |
| Issue number | 33-34 |
| DOIs | |
| State | Published - Aug 21 2009 |
Keywords
- Computational systems biology
- Excitable tissue
- Formal analysis
- Hybrid automata
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