Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells

The EMI model represents excitable cells in a more accurate manner than traditional homogenized models at the price of increased computational complexity. The increased complexity of solving the EMI model stems from a significant increase in the number of computational nodes and from the form of the...

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Main Authors: Karoline Horgmo Jæger, Kristian Gregorius Hustad, Xing Cai, Aslak Tveito
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-01-01
Series:Frontiers in Physics
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2020.579461/full
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spelling doaj-19377b282d984e0d97de2bbefe3899ae2021-01-13T05:42:41ZengFrontiers Media S.A.Frontiers in Physics2296-424X2021-01-01810.3389/fphy.2020.579461579461Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac CellsKaroline Horgmo Jæger0Kristian Gregorius Hustad1Xing Cai2Xing Cai3Aslak Tveito4Aslak Tveito5Simula Research Laboratory, Lysaker, NorwaySimula Research Laboratory, Lysaker, NorwaySimula Research Laboratory, Lysaker, NorwayDepartment of Informatics, University of Oslo, Oslo, NorwaySimula Research Laboratory, Lysaker, NorwayDepartment of Informatics, University of Oslo, Oslo, NorwayThe EMI model represents excitable cells in a more accurate manner than traditional homogenized models at the price of increased computational complexity. The increased complexity of solving the EMI model stems from a significant increase in the number of computational nodes and from the form of the linear systems that need to be solved. Here, we will show that the latter problem can be solved by careful use of operator splitting of the spatially coupled equations. By using this method, the linear systems can be broken into sub-problems that are of the classical type of linear, elliptic boundary value problems. Therefore, the vast collection of methods for solving linear, elliptic partial differential equations can be used. We demonstrate that this enables us to solve the systems using shared-memory parallel computers. The computing time scales perfectly with the number of physical cells. For a collection of 512 × 256 cells, we solved linear systems with about 2.5×108 unknows. Since the computational effort scales linearly with the number of physical cells, we believe that larger computers can be used to simulate millions of excitable cells and thus allow careful analysis of physiological systems of great importance.https://www.frontiersin.org/articles/10.3389/fphy.2020.579461/fullelectrophysiological modelcardiac conductioncell modelingfinite difference methodoperator splitting algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Karoline Horgmo Jæger
Kristian Gregorius Hustad
Xing Cai
Xing Cai
Aslak Tveito
Aslak Tveito
spellingShingle Karoline Horgmo Jæger
Kristian Gregorius Hustad
Xing Cai
Xing Cai
Aslak Tveito
Aslak Tveito
Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells
Frontiers in Physics
electrophysiological model
cardiac conduction
cell modeling
finite difference method
operator splitting algorithm
author_facet Karoline Horgmo Jæger
Kristian Gregorius Hustad
Xing Cai
Xing Cai
Aslak Tveito
Aslak Tveito
author_sort Karoline Horgmo Jæger
title Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells
title_short Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells
title_full Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells
title_fullStr Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells
title_full_unstemmed Efficient Numerical Solution of the EMI Model Representing the Extracellular Space (E), Cell Membrane (M) and Intracellular Space (I) of a Collection of Cardiac Cells
title_sort efficient numerical solution of the emi model representing the extracellular space (e), cell membrane (m) and intracellular space (i) of a collection of cardiac cells
publisher Frontiers Media S.A.
series Frontiers in Physics
issn 2296-424X
publishDate 2021-01-01
description The EMI model represents excitable cells in a more accurate manner than traditional homogenized models at the price of increased computational complexity. The increased complexity of solving the EMI model stems from a significant increase in the number of computational nodes and from the form of the linear systems that need to be solved. Here, we will show that the latter problem can be solved by careful use of operator splitting of the spatially coupled equations. By using this method, the linear systems can be broken into sub-problems that are of the classical type of linear, elliptic boundary value problems. Therefore, the vast collection of methods for solving linear, elliptic partial differential equations can be used. We demonstrate that this enables us to solve the systems using shared-memory parallel computers. The computing time scales perfectly with the number of physical cells. For a collection of 512 × 256 cells, we solved linear systems with about 2.5×108 unknows. Since the computational effort scales linearly with the number of physical cells, we believe that larger computers can be used to simulate millions of excitable cells and thus allow careful analysis of physiological systems of great importance.
topic electrophysiological model
cardiac conduction
cell modeling
finite difference method
operator splitting algorithm
url https://www.frontiersin.org/articles/10.3389/fphy.2020.579461/full
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