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Reduced conductivity dependence method for increase of dipole localization accuracy in the EEG inverse problem

Bertrand Russel Yitembe, Guillaume Crevecoeur UGent, Roger Van Keer and Luc Dupré UGent (2011) IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING. 58(5). p.1430-1440
abstract
The EEG is a neurological diagnostic tool with high temporal resolution. However, when solving the EEG inverse problem, its localization accuracy is limited because of noise in measurements and available uncertainties of the conductivity value in the forward model evaluations. This paper proposes the reduced conductivity dependence (RCD) method for decreasing the localization error in EEG source analysis by limiting the propagation of the uncertain conductivity values to the solutions of the inverse problem. We redefine the traditional EEG cost function, and in contrast to previous approaches, we introduce a selection procedure of the EEG potentials. The selected potentials are, as low as possible, affected by the uncertainties of the conductivity when solving the inverse problem. We validate the methodology on the widely used three-shell spherical head model with a single electrical dipole and multiple dipoles as source model. The proposed RCD method enhances the source localization accuracy with a factor ranging between 2 and 4, dependent on the dipole location and the noise in measurements. The selected potentials are as low as possible affected by the uncertainties of the conductivity when solving the inverse problem. We validate the methodology on the widely-used three shell spherical head model with a single electrical dipole and multiple dipoles as source model. The proposed RCD method enhances the source localization accuracy with a factor ranging between 2 to 4, dependent on the dipole location and the noise in measurements.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
source localization, uncertainty, inverse problems, EEG source analysis, Conductivity, MODELS, MEG
journal title
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
IEEE Trans. Biomed. Eng.
volume
58
issue
5
pages
1430 - 1440
Web of Science type
Article
Web of Science id
000289807300034
JCR category
ENGINEERING, BIOMEDICAL
JCR impact factor
2.278 (2011)
JCR rank
22/72 (2011)
JCR quartile
2 (2011)
ISSN
0018-9294
DOI
10.1109/TBME.2011.2107740
project
IUAP project B/0784
language
English
UGent publication?
yes
classification
A1
copyright statement
I have retained and own the full copyright for this publication
id
1922342
handle
http://hdl.handle.net/1854/LU-1922342
date created
2011-10-07 10:29:04
date last changed
2016-12-19 15:46:25
@article{1922342,
  abstract     = {The EEG is a neurological diagnostic tool with high temporal resolution. However, when solving the EEG inverse problem, its localization accuracy is limited because of noise in measurements and available uncertainties of the conductivity value in the forward model evaluations. This paper proposes the reduced conductivity dependence (RCD) method for decreasing the localization error in EEG source analysis by limiting the propagation of the uncertain conductivity values to the solutions of the inverse problem. We redefine the traditional EEG cost function, and in contrast to previous approaches, we introduce a selection procedure of the EEG potentials. The selected potentials are, as low as possible, affected by the uncertainties of the conductivity when solving the inverse problem. We validate the methodology on the widely used three-shell spherical head model with a single electrical dipole and multiple dipoles as source model. The proposed RCD method enhances the source localization accuracy with a factor ranging between 2 and 4, dependent on the dipole location and the noise in measurements. 

The selected potentials are as low as possible affected
by the uncertainties of the conductivity when solving the inverse problem. 

We validate the methodology on the widely-used three shell
spherical head model with a single electrical dipole and
multiple dipoles as source model. The proposed RCD method
enhances the source localization accuracy with a factor ranging
between 2 to 4, dependent on the dipole location and the noise
in measurements.},
  author       = {Yitembe, Bertrand Russel and Crevecoeur, Guillaume and Van Keer, Roger and Dupr{\'e}, Luc},
  issn         = {0018-9294},
  journal      = {IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING},
  keyword      = {source localization,uncertainty,inverse problems,EEG source analysis,Conductivity,MODELS,MEG},
  language     = {eng},
  number       = {5},
  pages        = {1430--1440},
  title        = {Reduced conductivity dependence method for increase of dipole localization accuracy in the EEG inverse problem},
  url          = {http://dx.doi.org/10.1109/TBME.2011.2107740},
  volume       = {58},
  year         = {2011},
}

Chicago
Yitembe, Bertrand Russel, Guillaume Crevecoeur, Roger Van Keer, and Luc Dupré. 2011. “Reduced Conductivity Dependence Method for Increase of Dipole Localization Accuracy in the EEG Inverse Problem.” Ieee Transactions on Biomedical Engineering 58 (5): 1430–1440.
APA
Yitembe, B. R., Crevecoeur, G., Van Keer, R., & Dupré, L. (2011). Reduced conductivity dependence method for increase of dipole localization accuracy in the EEG inverse problem. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 58(5), 1430–1440.
Vancouver
1.
Yitembe BR, Crevecoeur G, Van Keer R, Dupré L. Reduced conductivity dependence method for increase of dipole localization accuracy in the EEG inverse problem. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING. 2011;58(5):1430–40.
MLA
Yitembe, Bertrand Russel, Guillaume Crevecoeur, Roger Van Keer, et al. “Reduced Conductivity Dependence Method for Increase of Dipole Localization Accuracy in the EEG Inverse Problem.” IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 58.5 (2011): 1430–1440. Print.