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

Carusi, Annamaria; Burrage, Kevin; Rodríguez, Blanca

doi:10.1152/ajpheart.01151.2011

Cited by 90 publications

(86 citation statements)

References 109 publications

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“…The heart rhythm cannot be modelled bottom-up from ionic current models because solving the equations requires boundary conditions (e.g., cell voltage) provided by action potential models. 20 Similarly, if the attempt is to develop simulations of the whole heart, molecular and cell-scale models need boundary conditions from propagation models (partial differential equations) that incorporate data from optimal mapping of tissue structures (Carusi et al, 2012).…”

Section: Boundary Conditions and Top-down Effectsmentioning

confidence: 99%

Biology meets physics: Reductionism and multi-scale modeling of morphogenesis

Green

Batterman

2017

Studies in History and Philosophy of Science Part C: Studies in

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A common reductionist assumption is that macro-scale behaviors can be described "bottom-up" if only sufficient details about lower-scale processes are available. The view that an "ideal" or "fundamental" physics would be sufficient to explain all macro-scale phenomena has been met with criticism from philosophers of biology. Specifically, scholars have pointed to the impossibility of deducing biological explanations from physical ones, and to the irreducible nature of distinctively biological processes such as gene regulation and evolution. This paper takes a step back in asking whether bottom-up modeling is feasible even when modeling simple physical systems across scales. By comparing examples of multi-scale modeling in physics and biology, we argue that the "tyranny of scales" problem presents a challenge to reductive explanations in both physics and biology. The problem refers to the scale-dependency of physical and biological behaviors that forces researchers to combine different models relying on different scale-specific mathematical strategies and boundary conditions. Analyzing the ways in which different models are combined in multi-scale modeling also has implications for the relation between physics and biology. Contrary to the assumption that physical science approaches provide reductive explanations in biology, we exemplify how inputs from physics often reveal the importance of macro-scale models and explanations. We illustrate this through an examination of the role of biomechanics modeling in developmental biology. In such contexts, the relation between models at different scales and from different disciplines is neither reductive nor completely autonomous, but interdependent.

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Section: Boundary Conditions and Top-down Effectsmentioning

confidence: 99%

Biology meets physics: Reductionism and multi-scale modeling of morphogenesis

Green

Batterman

2017

Studies in History and Philosophy of Science Part C: Studies in

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“…Ionic current models (molecular level) provide inputs to action potential models (cell-level), and these in turn provide inputs to propagation models (tissues or whole organ) (Carusi et al 2012;Southern et al 2008). Figure 2 illustrates the direction of such inputs in a simplified representation of the relations between selected models at different scales.…”

Section: Modeling the Human Heartmentioning

confidence: 99%

The Sum of the Parts: Large-Scale Modeling in Systems Biology

Groß¹,

Green²

2017

Philosophy, Theory, and Practice in Biology

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Systems biologists often distance themselves from reductionist approaches and formulate their aim as understanding living systems "as a whole." Yet, it is often unclear what kind of reductionism they have in mind, and in what sense their methodologies would offer a superior approach. To address these questions, we distinguish between two types of reductionism which we call "modular reductionism" and "bottom-up reductionism." Much knowledge in molecular biology has been gained by decomposing living systems into functional modules or through detailed studies of molecular processes. We ask whether systems biology provides novel ways to recompose these findings in the context of the system as a whole via computational simulations. As an example of computational integration of modules, we analyze the first whole-cell model of the bacterium M. genitalium. Secondly, we examine the attempt to recompose processes across different spatial scales via multi-scale cardiac models. Although these models rely on a number of idealizations and simplifying assumptions as well, we argue that they provide insight into the limitations of reductionist approaches. Whole-cell models can be used to discover properties arising at the interfaces of dynamically coupled processes within a biological system, thereby making more apparent what is lost through decomposition. Similarly, multi-scale modeling highlights the relevance of macroscale parameters and models and challenges the view that living systems can be understood "bottom-up." Specifically, we point out that system-level properties constrain lower-scale processes. Thus, large-scale modeling reveals how living systems at the same time are more and less than the sum of the parts. Editorial introduction: This contribution from Fridolin Gross and Sara Green focuses on the promises and possible pitfalls of large-scale modelling in systems biology, from both a practical and a theoretical point of view. As readers will be aware, molecular biology has often been accused of being "reductionist." Systems biology has been presented as a potential response to this reductionism. Gross and Green distinguish two types of reductionisms: "modular reductionism" (the claim that living systems consist of individual functional subunits) and "bottom-up reductionism" (the claim that biological phenomena can and should be studied at the molecular level, understood as the "fundamental" biological level). They show how systems biology questions both forms of reductionism. To this end, they use two examples: whole-cell modelling of a very "simple" bacterium (from a piece published in 2012), and multi-scale computer modelling of the human heart. Without masking the limitations of these models, Gross and Green show the insights they can yield for anyone interested in ontologies of the living world. KeywordsAs with some of the other contributions in this special issue (e.g. Fagan's, and Kendig and Eckdahl's), a virtue of this paper is to illustrate how research strategies-particularly modelling strategies-can in...

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“…Many cardiac models, from cellular level models based on ion channels to tissue level models for ventricles, atria and the whole heart, have been proposed to study the electrophysiological and mechanical activities of the heart (Cherry and Fenton, 2011;Clayton et al, 2011;Trayanova, 2011;Trayanova et al, 2011;Carusi et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Fibroblast proliferation alters cardiac excitation conduction and contraction: a computational study

Zhan

Xia

Shou

et al. 2014

J. Zhejiang Univ. Sci. B

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Abstract:In this study, the effects of cardiac fibroblast proliferation on cardiac electric excitation conduction and mechanical contraction were investigated using a proposed integrated myocardial-fibroblastic electromechanical model. At the cellular level, models of the human ventricular myocyte and fibroblast were modified to incorporate a model of cardiac mechanical contraction and cooperativity mechanisms. Cellular electromechanical coupling was realized with a calcium buffer. At the tissue level, electrical excitation conduction was coupled to an elastic mechanics model in which the finite difference method (FDM) was used to solve electrical excitation equations, and the finite element method (FEM) was used to solve mechanics equations. The electromechanical properties of the proposed integrated model were investigated in one or two dimensions under normal and ischemic pathological conditions. Fibroblast proliferation slowed wave propagation, induced a conduction block, decreased strains in the fibroblast proliferous tissue, and increased dispersions in depolarization, repolarization, and action potential duration (APD). It also distorted the wave-front, leading to the initiation and maintenance of re-entry, and resulted in a sustained contraction in the proliferous areas. This study demonstrated the important role that fibroblast proliferation plays in modulating cardiac electromechanical behaviour and which should be considered in planning future heart-modeling studies.

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

Cited by 90 publications

References 109 publications

Biology meets physics: Reductionism and multi-scale modeling of morphogenesis

Biology meets physics: Reductionism and multi-scale modeling of morphogenesis

The Sum of the Parts: Large-Scale Modeling in Systems Biology

Fibroblast proliferation alters cardiac excitation conduction and contraction: a computational study

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