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  A Global Sensitivity Index for Biophysically Detailed Cardiac Cell Models: A Computational Approach

Kharche, S., Lüdtke, N., Panzeri, S., & Zhang, H. (2009). A Global Sensitivity Index for Biophysically Detailed Cardiac Cell Models: A Computational Approach. In N. Ayache, H. Delingette, & M. Sermesant (Eds.), Functional Imaging and Modeling of the Heart: 5th International Conference, FIMH 2009, Nice, France, June 3-5, 2009 (pp. 366-375). Berlin, Germany: Springer.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0002-EAEB-E Version Permalink: http://hdl.handle.net/21.11116/0000-0002-EAEC-D
Genre: Conference Paper

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https://link.springer.com/content/pdf/10.1007%2F978-3-642-01932-6_40.pdf (Publisher version)
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 Creators:
Kharche, S, Author
Lüdtke, N1, 2, Author              
Panzeri, S, Author              
Zhang, H, Author
Affiliations:
1Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Biophysically detailed cardiac cell models are based upon stiff ordinary differential equations describing ionic channels and intracellular dynamics aiming at reproducing experimental action potentials (APs) and intracellular calcium ([Ca2+]i) transients. Channel blocking and bifurcation analyses are local sensitivity analyses in model parameter space. However, all parameters influence model behaviour and require a global sensitivity index quantifying the influence of parameters on model responses. Identification of the influence of individual parameters increases our understanding of models. A global parameter sensitivity index for assessing the sensitivity of model responses to parameters in cardiac cell models is proposed. The robust index was applied to four widely used models. The analysis revealed that whilst models have common sets of parameters influencing AP and [Ca2+]i transients, there are subtle differences. This sensitivity analysis offers a systematic method for quantifying the influence of individual parameters on model behaviour to assist in model reduction, refinement or development.

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 Dates: 2009-06
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1007/978-3-642-01932-6_40
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Title: 5th International Conference on Functional Imaging and Modeling of the Heart (FIMH 2009)
Place of Event: Nice, France
Start-/End Date: 2009-06-03 - 2009-06-05

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Title: Functional Imaging and Modeling of the Heart: 5th International Conference, FIMH 2009, Nice, France, June 3-5, 2009
Source Genre: Proceedings
 Creator(s):
Ayache, N, Editor
Delingette, H, Editor
Sermesant, M, Editor
Affiliations:
-
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 366 - 375 Identifier: ISBN: 978-3-642-01931-9

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Pages: - Volume / Issue: 5528 Sequence Number: - Start / End Page: - Identifier: -