Estimating EEG Source Dipole Orientation Based on Singular-value Decomposition for Connectivity Analysis.

Détails

ID Serval
serval:BIB_9C12D5E939DB
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Estimating EEG Source Dipole Orientation Based on Singular-value Decomposition for Connectivity Analysis.
Périodique
Brain topography
Auteur(s)
Rubega M., Carboni M., Seeber M., Pascucci D., Tourbier S., Toscano G., Van Mierlo P., Hagmann P., Plomp G., Vulliemoz S., Michel C.M.
ISSN
1573-6792 (Electronic)
ISSN-L
0896-0267
Statut éditorial
Publié
Date de publication
07/2019
Peer-reviewed
Oui
Volume
32
Numéro
4
Pages
704-719
Langue
anglais
Résumé
In the last decade, the use of high-density electrode arrays for EEG recordings combined with the improvements of source reconstruction algorithms has allowed the investigation of brain networks dynamics at a sub-second scale. One powerful tool for investigating large-scale functional brain networks with EEG is time-varying effective connectivity applied to source signals obtained from electric source imaging. Due to computational and interpretation limitations, the brain is usually parcelled into a limited number of regions of interests (ROIs) before computing EEG connectivity. One specific need and still open problem is how to represent the time- and frequency-content carried by hundreds of dipoles with diverging orientation in each ROI with one unique representative time-series. The main aim of this paper is to provide a method to compute a signal that explains most of the variability of the data contained in each ROI before computing, for instance, time-varying connectivity. As the representative time-series for a ROI, we propose to use the first singular vector computed by a singular-value decomposition of all dipoles belonging to the same ROI. We applied this method to two real datasets (visual evoked potentials and epileptic spikes) and evaluated the time-course and the frequency content of the obtained signals. For each ROI, both the time-course and the frequency content of the proposed method reflected the expected time-course and the scalp-EEG frequency content, representing most of the variability of the sources (~ 80%) and improving connectivity results in comparison to other procedures used so far. We also confirm these results in a simulated dataset with a known ground truth.
Mots-clé
Dipole orientation, EEG, Epilepsy, Source space activity, Visual evoked potentials
Pubmed
Web of science
Création de la notice
13/12/2018 17:11
Dernière modification de la notice
21/08/2019 6:36
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