Bridging experiments, models and simulations : an integrative approach to validation in computational cardiac electrophysiology

Carusi, Annamaria, Burrage, Kevin, & Rodriguez, Blanca (2012) Bridging experiments, models and simulations : an integrative approach to validation in computational cardiac electrophysiology. American Journal of Physiology - Heart and Circulatory Physiology, 303(2), H144-H155.

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Abstract

Computational models in physiology often integrate functional and structural information from a large range of spatio-temporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and scepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace and refine animal experiments. A fundamental requirement to fulfil these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations between experiments, models and simulations in cardiac electrophysiology. We describe the processes, data and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. Validation must therefore take into account the complex interplay between models, simulations and experiments. Key points for developing strategies for validation are:

1) understanding sources of bio-variability is crucial to the comparison between simulation and experimental results;

2) robustness of techniques and tools is a pre-requisite to conducting physiological investigations using the MSE system;

3) definition and adoption of standards facilitates interoperability of experiments, models and simulations;

4) physiological validation must be understood as an iterative process that defines the specific aspects of electrophysiology the MSE system targets, and is driven by advancements in experimental and computational methods and the combination of both.

Impact and interest:

43 citations in Scopus
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38 citations in Web of Science®

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ID Code: 75632
Item Type: Journal Article
Refereed: Yes
Additional Information: Articles free to read on journal website after 12 months
Keywords: Bridging Experiments, Models and Simulations in Electrophysiology
DOI: 10.1152/ajpheart.01151.2011
ISSN: 1522-1539
Divisions: Current > Schools > School of Earth, Environmental & Biological Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 American Physiological Society
Deposited On: 28 Aug 2014 03:20
Last Modified: 22 Jan 2015 04:15

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