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

Kharche, S; Lüdtke, N; Panzeri, S; Zhang, H

doi:10.1007/978-3-642-01932-6_40

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Conference Paper

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

MPS-Authors

/persons/resource/persons84064

Lüdtke, N
Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource

https://link.springer.com/content/pdf/10.1007%2F978-3-642-01932-6_40.pdf
(Publisher version)

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

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.

Cite as: http://hdl.handle.net/21.11116/0000-0002-EAEB-E

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.