Optimisation of a Generic Ionic Model of Cardiac Myocyte Electrical Activity

Abstract

A generic cardiomyocyte ionic model, whose complexity lies between a simple phenomenological formulation and a biophysically detailed ionic membrane current description, is presented. The model provides a user-defined number of ionic currents, employing two-gate Hodgkin-Huxley type kinetics. Its generic nature allows accurate reconstruction of action potential waveforms recorded experimentally from a range of cardiac myocytes. Using a multiobjective optimisation approach, the generic ionic model was optimised to accurately reproduce multiple action potential waveforms recorded from central and peripheral sinoatrial nodes and right atrial and left atrial myocytes from rabbit cardiac tissue preparations, under different electrical stimulus protocols and pharmacological conditions. When fitted simultaneously to multiple datasets, the time course of several physiologically realistic ionic currents could be reconstructed. Model behaviours tend to be well identified when extra experimental information is incorporated into the optimisation.

Improving cardiomyocyte model fidelity and utility via dynamic electrophysiology protocols and optimization algorithms

“…Gradient descent methods and genetic algorithms have been used in several studies to optimize parameters in cardiac cell models (e.g. Dokos & Lovell, 2004;Syed et al 2005;Bot et al 2012;Guo et al 2013;Kaur et al 2014;Groenendaal et al 2015), rather than adjusting post hoc and by hand. Other techniques used for these or similar types of optimization problems include simulated annealing (Vanier & Bower, 1999) and particle swarm optimization (Weber et al 2008;Chen et al 2012).…”

“…The difficulty and the computational cost of an optimization problem increases tremendously with the number of parameters, as the addition of each parameter adds another dimension to the parameter space, and because more data are required to constrain more parameters. Therefore, many parameter estimation problems have concentrated on optimizing simplified models with fewer parameters (Bueno-Orovio et al 2008;Weber et al 2008;Abed et al 2013;Guo et al 2013) or, for biophysically detailed models which can contain hundreds of parameters, have focused on either identifying kinetic and steady-state parameters for a single current only Zhou et al 2009) or determining maximal conductances only (Syed et al 2005). We have done the latter in previous work (Bot et al 2012;Groenendaal et al 2015), based on the assumption that ion channel kinetics are preserved among (healthy) subjects while conductances vary as a result of differences in expression levels.…”

“…; Guo et al . ) or, for biophysically detailed models which can contain hundreds of parameters, have focused on either identifying kinetic and steady‐state parameters for a single current only (Fink & Noble, ; Zhou et al . ) or determining maximal conductances only (Syed et al .…”

Optimisation of Ionic Models to Fit Tissue Action Potentials: Application to 3D Atrial Modelling

“…Fitting the generic model to more complex experimental waveforms that better capture the changes in AP morphology during fibrillation is required for more accurate 3D modelling of atrial arrhythmias. Towards this aim, the authors have recently developed [38] a single cell generic cardiac ionic model optimised to fit AP morphology alternans at a uniform pacing cycle length of 200 ms as well as the response to random pacing intervals. Using the tissue-based optimisation approach described in this paper, such ionic models can be incorporated into 3D atrial geometries to allow more realistic simulations of the dynamics of AF.…”

“…Using the tissue-based optimisation approach described in this paper, such ionic models can be incorporated into 3D atrial geometries to allow more realistic simulations of the dynamics of AF. Like most existing ionic models, our generic model has certain limitations [38], which are mainly due to assumptions made in order to simplify the model to produce computationally efficient simulations in 3D geometries as well as to optimise the disc models. We have not incorporated intracellular compartments for calcium cycling, ionic pumps and exchangers as we assume that all of our reconstructed membrane currents consist of two first-order voltage-dependent ( p and q ) gating processes, which is unlikely to capture the kinetics of these mechanisms.…”