Wed Sep 7, 11-12, 4750 Boelter Hall

Efficient Modeling of Excitable Cells Using Hybrid Automata

Scott Smolka
SUNY Stony Brook

We present an approach to modeling complex biological systems
based on Hybrid Automata (HA).  HA combine discrete transition
graphs with continuous dynamics.  Our goal is to efficiently
capture the behavior of excitable cells previously modeled by
systems of nonlinear differential equations.  Our much simpler
HA models are able to successfully capture the action-potential
morphology of the different cells, as well as reproduce typical
excitable cell characteristics, such as refractoriness (period
of non-responsiveness to external stimulation) and restitution
(adaptation to pacing rates).  To model electrical wave
propagation in a cell network, the single-cell HA models are
linked to a classical 2D spatial model.  The resulting
simulation framework exhibits significantly improved
computational efficiency in modeling complex wave patterns,
including the spiral waves underlying pathological conditions
in the heart.

Joint work with Emilia Entcheva, Radu Grosu, Pei Ye.

Scott Smolka is a Professor of Computer Science at SUNY Stony
Brook.  His research interests include model checking, process
algebra and the application of Hybrid automata to the modeling
of complex biological systems.  He is also president and
co-founder of Reactive Systems, Inc., which makes automated
testing and validation tools for models of embedded control
software.
        
Host: Jens Palsberg