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Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator.

Chang ET, Strong M, Clayton RH - PLoS ONE (2015)

Bottom Line: In this study we show that a surrogate statistical model of a cardiac cell model (the Luo-Rudy 1991 model) can be built using Gaussian process (GP) emulators.We found that the GP emulators could be fitted to a small number of model runs, and behaved as would be expected based on the underlying physiology that the model represents.We have shown that an emulator approach is a powerful tool for uncertainty and sensitivity analysis in cardiac cell models.

View Article: PubMed Central - PubMed

Affiliation: Insigneo Institute for in-silico Medicine, University of Sheffield, Sheffield, United Kingdom; Department of Computer Science University of Sheffield, Sheffield, United Kingdom.

ABSTRACT
Models of electrical activity in cardiac cells have become important research tools as they can provide a quantitative description of detailed and integrative physiology. However, cardiac cell models have many parameters, and how uncertainties in these parameters affect the model output is difficult to assess without undertaking large numbers of model runs. In this study we show that a surrogate statistical model of a cardiac cell model (the Luo-Rudy 1991 model) can be built using Gaussian process (GP) emulators. Using this approach we examined how eight outputs describing the action potential shape and action potential duration restitution depend on six inputs, which we selected to be the maximum conductances in the Luo-Rudy 1991 model. We found that the GP emulators could be fitted to a small number of model runs, and behaved as would be expected based on the underlying physiology that the model represents. We have shown that an emulator approach is a powerful tool for uncertainty and sensitivity analysis in cardiac cell models.

No MeSH data available.


Outputs produced by the LR91 model.(a) Action potential biomarkers used as model outputs to characterise the model. (b) Action potential time series from 200 runs of the LR1991 model used as design data for the GP emulator.
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pone.0130252.g001: Outputs produced by the LR91 model.(a) Action potential biomarkers used as model outputs to characterise the model. (b) Action potential time series from 200 runs of the LR1991 model used as design data for the GP emulator.

Mentions: Each time the simulator was run (for generating both design and test data) nine S1 stimuli of strength -25.5 μA cm-2 and duration 2 ms were delivered to the simulator at a 1000 ms cycle length. The final action potential in this S1 sequence was used to obtain the outputs. Fig 1(a) shows the 200 action potentials that were used to generate the outputs. Fig 1(b) shows the six outputs that were measured directly from the action potential.


Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator.

Chang ET, Strong M, Clayton RH - PLoS ONE (2015)

Outputs produced by the LR91 model.(a) Action potential biomarkers used as model outputs to characterise the model. (b) Action potential time series from 200 runs of the LR1991 model used as design data for the GP emulator.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4482712&req=5

pone.0130252.g001: Outputs produced by the LR91 model.(a) Action potential biomarkers used as model outputs to characterise the model. (b) Action potential time series from 200 runs of the LR1991 model used as design data for the GP emulator.
Mentions: Each time the simulator was run (for generating both design and test data) nine S1 stimuli of strength -25.5 μA cm-2 and duration 2 ms were delivered to the simulator at a 1000 ms cycle length. The final action potential in this S1 sequence was used to obtain the outputs. Fig 1(a) shows the 200 action potentials that were used to generate the outputs. Fig 1(b) shows the six outputs that were measured directly from the action potential.

Bottom Line: In this study we show that a surrogate statistical model of a cardiac cell model (the Luo-Rudy 1991 model) can be built using Gaussian process (GP) emulators.We found that the GP emulators could be fitted to a small number of model runs, and behaved as would be expected based on the underlying physiology that the model represents.We have shown that an emulator approach is a powerful tool for uncertainty and sensitivity analysis in cardiac cell models.

View Article: PubMed Central - PubMed

Affiliation: Insigneo Institute for in-silico Medicine, University of Sheffield, Sheffield, United Kingdom; Department of Computer Science University of Sheffield, Sheffield, United Kingdom.

ABSTRACT
Models of electrical activity in cardiac cells have become important research tools as they can provide a quantitative description of detailed and integrative physiology. However, cardiac cell models have many parameters, and how uncertainties in these parameters affect the model output is difficult to assess without undertaking large numbers of model runs. In this study we show that a surrogate statistical model of a cardiac cell model (the Luo-Rudy 1991 model) can be built using Gaussian process (GP) emulators. Using this approach we examined how eight outputs describing the action potential shape and action potential duration restitution depend on six inputs, which we selected to be the maximum conductances in the Luo-Rudy 1991 model. We found that the GP emulators could be fitted to a small number of model runs, and behaved as would be expected based on the underlying physiology that the model represents. We have shown that an emulator approach is a powerful tool for uncertainty and sensitivity analysis in cardiac cell models.

No MeSH data available.