Reducing complexity and unidentifiability when modelling human atrial cells. (25th May 2020)
- Record Type:
- Journal Article
- Title:
- Reducing complexity and unidentifiability when modelling human atrial cells. (25th May 2020)
- Main Title:
- Reducing complexity and unidentifiability when modelling human atrial cells
- Authors:
- Houston, C.
Marchand, B.
Engelbert, L.
Cantwell, C. D. - Abstract:
- Abstract : Mathematical models of a cellular action potential (AP) in cardiac modelling have become increasingly complex, particularly in gating kinetics, which control the opening and closing of individual ion channel currents. As cardiac models advance towards use in personalized medicine to inform clinical decision-making, it is critical to understand the uncertainty hidden in parameter estimates from their calibration to experimental data. This study applies approximate Bayesian computation to re-calibrate the gating kinetics of four ion channels in two existing human atrial cell models to their original datasets, providing a measure of uncertainty and indication of potential issues with selecting a single unique value given the available experimental data. Two approaches are investigated to reduce the uncertainty present: re-calibrating the models to a more complete dataset and using a less complex formulation with fewer parameters to constrain. The re-calibrated models are inserted back into the full cell model to study the overall effect on the AP. The use of more complete datasets does not eliminate uncertainty present in parameter estimates. The less complex model, particularly for the fast sodium current, gave a better fit to experimental data alongside lower parameter uncertainty and improved computational speed. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.
- Is Part Of:
- Philosophical transactions. Volume 378:Number 2173(2020)
- Journal:
- Philosophical transactions
- Issue:
- Volume 378:Number 2173(2020)
- Issue Display:
- Volume 378, Issue 2173 (2020)
- Year:
- 2020
- Volume:
- 378
- Issue:
- 2173
- Issue Sort Value:
- 2020-0378-2173-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-05-25
- Subjects:
- cardiac modelling -- approximate Bayesian computation -- uncertainty -- unidentifiability -- action potential
Physical sciences -- Periodicals
Engineering -- Periodicals
Mathematics -- Periodicals
500 - Journal URLs:
- https://royalsocietypublishing.org/loi/rsta ↗
- DOI:
- 10.1098/rsta.2019.0339 ↗
- Languages:
- English
- ISSNs:
- 1364-503X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library STI - ELD Digital store
- Ingest File:
- 13894.xml