Stochastic uncertainty quantification of the conductivity in EEG source analysis by using polynomial chaos decomposition
- Author
- Roman Gaignaire, Guillaume Crevecoeur (UGent) , Luc Dupré (UGent) , Ruth V Sabariego, Patrick Dular and Christophe Geuzaine
- Organization
- Abstract
- The electroencephalogram (EEG) is one of the techniques used for the non-invasive diagnosis of patients suffering from epilepsy. EEG source localization identifies the neural activity, starting from measured EEG. This numerical localization procedure has a resolution, which is difficult to determine due to uncertainties in the EEG forward models. More specifically, the conductivities of the brain and the skull in the head models are not precisely known. In this paper, we propose the use of a non-intrusive stochastic method based on a polynomial chaos decomposition for quantifying the possible errors introduced by the uncertain conductivities of the head tissues. The accuracy and computational advantages of this non-intrusive method for EEG source analysis is illustrated. Further, the method is validated by means of Monte Carlo simulations.
- Keywords
- DIPOLES, BOUNDS, BRAIN, HEAD MODELS, Inverse problems, non-intrusive methods, polynomial chaos decomposition, stochastic methods
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-2116180
- MLA
- Gaignaire, Roman, et al. “Stochastic Uncertainty Quantification of the Conductivity in EEG Source Analysis by Using Polynomial Chaos Decomposition.” IEEE TRANSACTIONS ON MAGNETICS, vol. 46, no. 8, 2010, pp. 3457–60, doi:10.1109/TMAG.2010.2044233.
- APA
- Gaignaire, R., Crevecoeur, G., Dupré, L., Sabariego, R. V., Dular, P., & Geuzaine, C. (2010). Stochastic uncertainty quantification of the conductivity in EEG source analysis by using polynomial chaos decomposition. IEEE TRANSACTIONS ON MAGNETICS, 46(8), 3457–3460. https://doi.org/10.1109/TMAG.2010.2044233
- Chicago author-date
- Gaignaire, Roman, Guillaume Crevecoeur, Luc Dupré, Ruth V Sabariego, Patrick Dular, and Christophe Geuzaine. 2010. “Stochastic Uncertainty Quantification of the Conductivity in EEG Source Analysis by Using Polynomial Chaos Decomposition.” IEEE TRANSACTIONS ON MAGNETICS 46 (8): 3457–60. https://doi.org/10.1109/TMAG.2010.2044233.
- Chicago author-date (all authors)
- Gaignaire, Roman, Guillaume Crevecoeur, Luc Dupré, Ruth V Sabariego, Patrick Dular, and Christophe Geuzaine. 2010. “Stochastic Uncertainty Quantification of the Conductivity in EEG Source Analysis by Using Polynomial Chaos Decomposition.” IEEE TRANSACTIONS ON MAGNETICS 46 (8): 3457–3460. doi:10.1109/TMAG.2010.2044233.
- Vancouver
- 1.Gaignaire R, Crevecoeur G, Dupré L, Sabariego RV, Dular P, Geuzaine C. Stochastic uncertainty quantification of the conductivity in EEG source analysis by using polynomial chaos decomposition. IEEE TRANSACTIONS ON MAGNETICS. 2010;46(8):3457–60.
- IEEE
- [1]R. Gaignaire, G. Crevecoeur, L. Dupré, R. V. Sabariego, P. Dular, and C. Geuzaine, “Stochastic uncertainty quantification of the conductivity in EEG source analysis by using polynomial chaos decomposition,” IEEE TRANSACTIONS ON MAGNETICS, vol. 46, no. 8, pp. 3457–3460, 2010.
@article{2116180,
abstract = {{The electroencephalogram (EEG) is one of the techniques used for the non-invasive diagnosis of patients suffering from epilepsy. EEG source localization identifies the neural activity, starting from measured EEG. This numerical localization procedure has a resolution, which is difficult to determine due to uncertainties in the EEG forward models. More specifically, the conductivities of the brain and the skull in the head models are not precisely known. In this paper, we propose the use of a non-intrusive stochastic method based on a polynomial chaos decomposition for quantifying the possible errors introduced by the uncertain conductivities of the head tissues. The accuracy and computational advantages of this non-intrusive method for EEG source analysis is illustrated. Further, the method is validated by means of Monte Carlo simulations.}},
author = {{Gaignaire, Roman and Crevecoeur, Guillaume and Dupré, Luc and Sabariego, Ruth V and Dular, Patrick and Geuzaine, Christophe}},
issn = {{0018-9464}},
journal = {{IEEE TRANSACTIONS ON MAGNETICS}},
keywords = {{DIPOLES,BOUNDS,BRAIN,HEAD MODELS,Inverse problems,non-intrusive methods,polynomial chaos decomposition,stochastic methods}},
language = {{eng}},
location = {{Santa Catarina, Brazil}},
number = {{8}},
pages = {{3457--3460}},
title = {{Stochastic uncertainty quantification of the conductivity in EEG source analysis by using polynomial chaos decomposition}},
url = {{http://doi.org/10.1109/TMAG.2010.2044233}},
volume = {{46}},
year = {{2010}},
}
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