Learning and Detecting Emergent Behavior in Networks of Cardiac Myocytes

  • R. Grosu
  • E. Bartocci
  • F. Corradini
  • E. Entcheva
  • S. A. Smolka
  • A. Wasilewska
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4981)


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.


Spiral Wave Probability Mass Function Excitable Cell Atomic Proposition Kripke Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • R. Grosu
    • 1
  • E. Bartocci
    • 1
    • 2
  • F. Corradini
    • 2
  • E. Entcheva
    • 3
  • S. A. Smolka
    • 1
  • A. Wasilewska
    • 1
  1. 1.Department of Computer ScienceStony Brook UniversityStony BrookUSA
  2. 2.Department of Mathematics and Computer ScienceUniversity of CamerinoCamerino (MC)Italy
  3. 3.Department of Biomedical EngineeringStony Brook UniversityStony BrookUSA

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