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Stochastic uncertainty quantification of the conductivity in EEG source analysis by using polynomial chaos decomposition

Roman Gaignaire, Guillaume Crevecoeur UGent, Luc Dupré UGent, Ruth V Sabariego, Patrick Dular and Christophe Geuzaine (2010) IEEE TRANSACTIONS ON MAGNETICS. 46(8). p.3457-3460
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.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (proceedingsPaper)
publication status
published
subject
keyword
DIPOLES, BOUNDS, BRAIN, HEAD MODELS, Inverse problems, non-intrusive methods, polynomial chaos decomposition, stochastic methods
journal title
IEEE TRANSACTIONS ON MAGNETICS
IEEE Trans. Magn.
volume
46
issue
8
pages
3457 - 3460
conference name
17th International Conference on the Computation of Electromagnetic Fields (COMPUMAG 09)
conference location
Santa Catarina, Brazil
conference start
2009-11-22
conference end
2009-11-26
Web of Science type
Proceedings Paper
Web of Science id
000283428700181
JCR category
ENGINEERING, ELECTRICAL & ELECTRONIC
JCR impact factor
1.052 (2010)
JCR rank
115/247 (2010)
JCR quartile
2 (2010)
ISSN
0018-9464
DOI
10.1109/TMAG.2010.2044233
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
2116180
handle
http://hdl.handle.net/1854/LU-2116180
date created
2012-05-25 20:25:18
date last changed
2016-12-19 15:42:57
@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 Dupr{\'e}, Luc and Sabariego, Ruth V and Dular, Patrick and Geuzaine, Christophe},
  issn         = {0018-9464},
  journal      = {IEEE TRANSACTIONS ON MAGNETICS},
  keyword      = {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://dx.doi.org/10.1109/TMAG.2010.2044233},
  volume       = {46},
  year         = {2010},
}

Chicago
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.
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. Presented at the 17th International Conference on the Computation of Electromagnetic Fields (COMPUMAG 09).
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.
MLA
Gaignaire, Roman, Guillaume Crevecoeur, Luc Dupré, et al. “Stochastic Uncertainty Quantification of the Conductivity in EEG Source Analysis by Using Polynomial Chaos Decomposition.” IEEE TRANSACTIONS ON MAGNETICS 46.8 (2010): 3457–3460. Print.