Removal of pulse artefact from EEG data recorded in MR environment at 3T. setting of ICA parameters for marking artefactual components: Application to resting-state data

Eleonora Maggioni, Jorge Arrubla, Tracy Warbrick, Jürgen Dammers, Anna M. Bianchi, Gianluigi Reni, Michela Tosetti, Irene Neuner, N. Jon Shah

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow for a non-invasive investigation of cerebral functions with high temporal and spatial resolution. The main challenge of such integration is the removal of the pulse artefact (PA) that affects EEG signals recorded in the magnetic resonance (MR) scanner. Often applied techniques for this purpose are Optimal Basis Set (OBS) and Independent Component Analysis (ICA). The combination of OBS and ICA is increasingly used, since it can potentially improve the correction performed by each technique separately. The present study is focused on the OBS-ICA combination and is aimed at providing the optimal ICA parameters for PA correction in resting-state EEG data, where the information of interest is not specified in latency and amplitude as in, for example, evoked potential. A comparison between two intervals for ICA calculation and four methods for marking artefactual components was performed. The performance of the methods was discussed in terms of their capability to 1) remove the artefact and 2) preserve the information of interest. The analysis included 12 subjects and two resting-state datasets for each of them. The results showed that none of the signal lengths for the ICA calculation was highly preferable to the other. Among the methods for the identification of PA-related components, the one based on the wavelets transform of each component emerged as the best compromise between the effectiveness in removing PA and the conservation of the physiological neuronal content.

Original languageEnglish
Article numbere112147
JournalPLoS One
Volume9
Issue number11
DOIs
Publication statusPublished - Nov 10 2014

Fingerprint

electroencephalography
Independent component analysis
Magnetic resonance
Electroencephalography
Artifacts
Magnetic Resonance Spectroscopy
Wavelet Analysis
methodology
evoked potentials
scanners
Evoked Potentials
magnetic resonance imaging
Bioelectric potentials
preserves
Wavelet transforms
Magnetic Resonance Imaging
Conservation

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Removal of pulse artefact from EEG data recorded in MR environment at 3T. setting of ICA parameters for marking artefactual components : Application to resting-state data. / Maggioni, Eleonora; Arrubla, Jorge; Warbrick, Tracy; Dammers, Jürgen; Bianchi, Anna M.; Reni, Gianluigi; Tosetti, Michela; Neuner, Irene; Shah, N. Jon.

In: PLoS One, Vol. 9, No. 11, e112147, 10.11.2014.

Research output: Contribution to journalArticle

Maggioni, Eleonora ; Arrubla, Jorge ; Warbrick, Tracy ; Dammers, Jürgen ; Bianchi, Anna M. ; Reni, Gianluigi ; Tosetti, Michela ; Neuner, Irene ; Shah, N. Jon. / Removal of pulse artefact from EEG data recorded in MR environment at 3T. setting of ICA parameters for marking artefactual components : Application to resting-state data. In: PLoS One. 2014 ; Vol. 9, No. 11.
@article{6a94d410bef54ffbb452a096f83c2e6e,
title = "Removal of pulse artefact from EEG data recorded in MR environment at 3T. setting of ICA parameters for marking artefactual components: Application to resting-state data",
abstract = "Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow for a non-invasive investigation of cerebral functions with high temporal and spatial resolution. The main challenge of such integration is the removal of the pulse artefact (PA) that affects EEG signals recorded in the magnetic resonance (MR) scanner. Often applied techniques for this purpose are Optimal Basis Set (OBS) and Independent Component Analysis (ICA). The combination of OBS and ICA is increasingly used, since it can potentially improve the correction performed by each technique separately. The present study is focused on the OBS-ICA combination and is aimed at providing the optimal ICA parameters for PA correction in resting-state EEG data, where the information of interest is not specified in latency and amplitude as in, for example, evoked potential. A comparison between two intervals for ICA calculation and four methods for marking artefactual components was performed. The performance of the methods was discussed in terms of their capability to 1) remove the artefact and 2) preserve the information of interest. The analysis included 12 subjects and two resting-state datasets for each of them. The results showed that none of the signal lengths for the ICA calculation was highly preferable to the other. Among the methods for the identification of PA-related components, the one based on the wavelets transform of each component emerged as the best compromise between the effectiveness in removing PA and the conservation of the physiological neuronal content.",
author = "Eleonora Maggioni and Jorge Arrubla and Tracy Warbrick and J{\"u}rgen Dammers and Bianchi, {Anna M.} and Gianluigi Reni and Michela Tosetti and Irene Neuner and Shah, {N. Jon}",
year = "2014",
month = "11",
day = "10",
doi = "10.1371/journal.pone.0112147",
language = "English",
volume = "9",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "11",

}

TY - JOUR

T1 - Removal of pulse artefact from EEG data recorded in MR environment at 3T. setting of ICA parameters for marking artefactual components

T2 - Application to resting-state data

AU - Maggioni, Eleonora

AU - Arrubla, Jorge

AU - Warbrick, Tracy

AU - Dammers, Jürgen

AU - Bianchi, Anna M.

AU - Reni, Gianluigi

AU - Tosetti, Michela

AU - Neuner, Irene

AU - Shah, N. Jon

PY - 2014/11/10

Y1 - 2014/11/10

N2 - Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow for a non-invasive investigation of cerebral functions with high temporal and spatial resolution. The main challenge of such integration is the removal of the pulse artefact (PA) that affects EEG signals recorded in the magnetic resonance (MR) scanner. Often applied techniques for this purpose are Optimal Basis Set (OBS) and Independent Component Analysis (ICA). The combination of OBS and ICA is increasingly used, since it can potentially improve the correction performed by each technique separately. The present study is focused on the OBS-ICA combination and is aimed at providing the optimal ICA parameters for PA correction in resting-state EEG data, where the information of interest is not specified in latency and amplitude as in, for example, evoked potential. A comparison between two intervals for ICA calculation and four methods for marking artefactual components was performed. The performance of the methods was discussed in terms of their capability to 1) remove the artefact and 2) preserve the information of interest. The analysis included 12 subjects and two resting-state datasets for each of them. The results showed that none of the signal lengths for the ICA calculation was highly preferable to the other. Among the methods for the identification of PA-related components, the one based on the wavelets transform of each component emerged as the best compromise between the effectiveness in removing PA and the conservation of the physiological neuronal content.

AB - Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow for a non-invasive investigation of cerebral functions with high temporal and spatial resolution. The main challenge of such integration is the removal of the pulse artefact (PA) that affects EEG signals recorded in the magnetic resonance (MR) scanner. Often applied techniques for this purpose are Optimal Basis Set (OBS) and Independent Component Analysis (ICA). The combination of OBS and ICA is increasingly used, since it can potentially improve the correction performed by each technique separately. The present study is focused on the OBS-ICA combination and is aimed at providing the optimal ICA parameters for PA correction in resting-state EEG data, where the information of interest is not specified in latency and amplitude as in, for example, evoked potential. A comparison between two intervals for ICA calculation and four methods for marking artefactual components was performed. The performance of the methods was discussed in terms of their capability to 1) remove the artefact and 2) preserve the information of interest. The analysis included 12 subjects and two resting-state datasets for each of them. The results showed that none of the signal lengths for the ICA calculation was highly preferable to the other. Among the methods for the identification of PA-related components, the one based on the wavelets transform of each component emerged as the best compromise between the effectiveness in removing PA and the conservation of the physiological neuronal content.

UR - http://www.scopus.com/inward/record.url?scp=84911391093&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84911391093&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0112147

DO - 10.1371/journal.pone.0112147

M3 - Article

C2 - 25383625

AN - SCOPUS:84911391093

VL - 9

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 11

M1 - e112147

ER -