Modelling the effect of gap junctions on tissue-level cardiac electrophysiology

Doug Bruce
(Computational Biology Group, Department of Computer Science, University of Oxford)
Pras Pathmanathan
(Computational Biology Group, Department of Computer Science, University of Oxford)
Jonathan P. Whiteley
(Computational Biology Group, Department of Computer Science, University of Oxford)

When modelling tissue-level cardiac electrophysiology, continuum approximations to the discrete cell-level equations are used to maintain computational tractability. One of the most commonly used models is represented by the bidomain equations, the derivation of which relies on a homogenisation technique to construct a suitable approximation to the discrete model. This derivation does not explicitly account for the presence of gap junctions connecting one cell to another. It has been seen experimentally [Rohr, Cardiovasc. Res. 2004] that these gap junctions have a marked effect on the propagation of the action potential, specifically as the upstroke of the wave passes through the gap junction.

In this paper we explicitly include gap junctions in a both a 2D discrete model of cardiac electrophysiology, and the corresponding continuum model, on a simplified cell geometry. Using these models we compare the results of simulations using both continuum and discrete systems. We see that the form of the action potential as it passes through gap junctions cannot be replicated using a continuum model, and that the underlying propagation speed of the action potential ceases to match up between models when gap junctions are introduced. In addition, the results of the discrete simulations match the characteristics of those shown in Rohr 2004. From this, we suggest that a hybrid model — a discrete system following the upstroke of the action potential, and a continuum system elsewhere — may give a more accurate description of cardiac electrophysiology.

In Ezio Bartocci and Luca Bortolussi: Proceedings First International Workshop on Hybrid Systems and Biology (HSB 2012), Newcastle Upon Tyne, 3rd September 2012, Electronic Proceedings in Theoretical Computer Science 92, pp. 1–15.
Published: 15th August 2012.

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