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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.


Mean effects in each emulator.Mean effect of each of the inputs on each output as each input is varied whilst the others are held at their mean value.
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pone.0130252.g007: Mean effects in each emulator.Mean effect of each of the inputs on each output as each input is varied whilst the others are held at their mean value.

Mentions: The mean effects obtained using the emulator for each output are shown in Fig 7. In the LR1991 model the action potential upstroke is controlled by INa, and the Max. dVm/dt and Max. Vm emulators have captured a strong dependence on GNa as shown in Fig 7(a) and 7(b). Dome voltage (Fig 7(c)) was mainly influenced by Gsi and Gb, with increasing Gsi acting to increase dome voltage, and Gb and to a lesser extent GKp acting in the opposite direction. In the LR1991 model these effects reflect the balance of inward and outward currents during the action potential plateau. Changes in resting voltage (Fig 7(d)) were small, and were controlled by Gb and GK1, while the mean effects for the APD50 emulator (Fig 7(e)) were very similar to those of the APD90 emulator (Fig 4), as well as the trends in the design data (Fig 2).


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

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

Mean effects in each emulator.Mean effect of each of the inputs on each output as each input is varied whilst the others are held at their mean value.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0130252.g007: Mean effects in each emulator.Mean effect of each of the inputs on each output as each input is varied whilst the others are held at their mean value.
Mentions: The mean effects obtained using the emulator for each output are shown in Fig 7. In the LR1991 model the action potential upstroke is controlled by INa, and the Max. dVm/dt and Max. Vm emulators have captured a strong dependence on GNa as shown in Fig 7(a) and 7(b). Dome voltage (Fig 7(c)) was mainly influenced by Gsi and Gb, with increasing Gsi acting to increase dome voltage, and Gb and to a lesser extent GKp acting in the opposite direction. In the LR1991 model these effects reflect the balance of inward and outward currents during the action potential plateau. Changes in resting voltage (Fig 7(d)) were small, and were controlled by Gb and GK1, while the mean effects for the APD50 emulator (Fig 7(e)) were very similar to those of the APD90 emulator (Fig 4), as well as the trends in the design data (Fig 2).

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.