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CoSy Bibliography Learning and Detecting Emergent Behavior in Networks of Cardiac Myocytes
Radu Grosu, Ezio Bartocci, Flavio Corradini, Emilia Entcheva, Scott A. Smolka, Anita Wasilewska

abstract:
We address the problem of specifying and detecting emergent behavior in networks of cardiac myocytes, spiral electric waves in particular, a precursor to atrial and ventricular fibrillation. To solve this
problem we: (1) Apply discrete mode-abstraction to the cycle-linear hybrid automata (CLHA) we have recently developed for modeling the
behavior of myocyte networks; (2) Introduce the new concept of spatial-superposition of CLHA modes; (3) Develop a new spatial logic, based on spatial-superposition, for specifying emergent behavior; (4) Devise a new method for learning the formulae of this logic from the spatial patterns under investigation; and (5) Apply bounded model checking to detect (within milliseconds) the onset of spiral waves. We have implemented our methodology as the Emerald tool-suite, a component of our EHA framework for specification, simulation, analysis and control of excitable hybrid automata. We illustrate the effectiveness of our approach by applying Emerald to the scalar electrical fields produced by our CellExcite simulator.

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