ORBi: Leclercq Yves - Rejection of pulse related artefact (PRA) from continuous electroencephalographic (EEG) time series recorded during functional magnetic resonance imaging (fMRI) using constraint independent component analysis (cICA).

Reference : Rejection of pulse related artefact (PRA) from continuous electroencephalographic (EEG) ...


	Document type :	Scientific journals : Article
	Discipline(s) :	Human health sciences : Neurology
	To cite this reference:	http://hdl.handle.net/2268/104707

Title :	Rejection of pulse related artefact (PRA) from continuous electroencephalographic (EEG) time series recorded during functional magnetic resonance imaging (fMRI) using constraint independent component analysis (cICA).
Language :	English
Author, co-author :	Leclercq, Yves [Université de Liège - ULg > > Centre de recherches du cyclotron >]
	Balteau, Evelyne [Université de Liège - ULg > > Centre de recherches du cyclotron >]
	Dang Vu, Thien Thanh [Université de Liège - ULg > Département des sciences cliniques > Neurologie >]
	Schabus, M. [> > > >]
	Luxen, André [Université de Liège - ULg > Département de chimie (sciences) > Chimie organique de synthèse - Centre de recherches du cyclotron >]
	Maquet, Pierre [Centre Hospitalier Universitaire de Liège - CHU > > Neurologie Sart Tilman >]
	Phillips, Christophe [Université de Liège - ULg > > Centre de recherches du cyclotron - Dép. d'électric., électron. et informat. (Inst.Montefiore) >]
Publication date :	2009
Journal title :	NeuroImage
Publisher :	Academic Press
Volume :	44
Issue/season :	3
Pages :	679-91
Audience :	International
ISSN :	1053-8119
e-ISSN :	1095-9572
City :	Orlando
Country :	FL
Abstract :	[en] Rejection of the pulse related artefact (PRA) from electroencephalographic (EEG) time series recorded simultaneously with fMRI data is difficult, particularly during NREM sleep because of the similarities between sleep slow waves and PRA, in both temporal and frequency domains and the need to work with non-averaged data. Here we introduce an algorithm based on constrained independent component analysis (cICA) for PRA removal. This method has several advantages: (1) automatic detection of the components corresponding to the PRA; (2) stability of the solution and (3) computational treatability. Using multichannel EEG recordings obtained in a 3 T MR scanner, with and without concomitant fMRI acquisition, we provide evidence for the sensitivity and specificity of the method in rejecting PRA in various sleep and waking conditions.
Permalink :	http://hdl.handle.net/2268/104707
DOI :	10.1016/j.neuroimage.2008.10.017

File(s) associated to this reference

Fulltext file(s):

	File	Commentary	Version	Size	Access
Restricted access	leclercq_neuroimage_2008.pdf		Publisher postprint	1.56 MB	Request copy

All documents in ORBi are protected by a user license.

Dspace v1.5