Data-driven beamforming technique to attenuate ballistocardiogram artefacts in electroencephalography-functional magnetic resonance imaging without detecting cardiac pulses in electrocardiography recordings.
EEG-fMRI
ballistocardiogram (BCG) artefacts
beamforming technique
motor beta ERD
time-frequency analysis
visual alpha event-related desynchronization (ERD)
Journal
Human brain mapping
ISSN: 1097-0193
Titre abrégé: Hum Brain Mapp
Pays: United States
ID NLM: 9419065
Informations de publication
Date de publication:
15 08 2021
15 08 2021
Historique:
revised:
03
05
2021
received:
19
01
2021
accepted:
06
05
2021
pubmed:
9
6
2021
medline:
17
3
2022
entrez:
8
6
2021
Statut:
ppublish
Résumé
Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a very promising non-invasive neuroimaging technique. However, EEG data obtained from the simultaneous EEG-fMRI are strongly influenced by MRI-related artefacts, namely gradient artefacts (GA) and ballistocardiogram (BCG) artefacts. When compared to the GA correction, the BCG correction is more challenging to remove due to its inherent variabilities and dynamic changes over time. The standard BCG correction (i.e., average artefact subtraction [AAS]), require detecting cardiac pulses from simultaneous electrocardiography (ECG) recording. However, ECG signals are also distorted and will become problematic for detecting reliable cardiac peaks. In this study, we focused on a beamforming spatial filtering technique to attenuate all unwanted source activities outside of the brain. Specifically, we applied the beamforming technique to attenuate the BCG artefact in EEG-fMRI, and also to recover meaningful task-based neural signals during an attentional network task (ANT) which required participants to identify visual cues and respond accurately. We analysed EEG-fMRI data in 20 healthy participants during the ANT, and compared four different BCG corrections (non-BCG corrected, AAS BCG corrected, beamforming + AAS BCG corrected, beamforming BCG corrected). We demonstrated that the beamforming approach did not only significantly reduce the BCG artefacts, but also significantly recovered the expected task-based brain activity when compared to the standard AAS correction. This data-driven beamforming technique appears promising especially for longer data acquisition of sleep and resting EEG-fMRI. Our findings extend previous work regarding the recovery of meaningful EEG signals by an optimized suppression of MRI-related artefacts.
Identifiants
pubmed: 34101939
doi: 10.1002/hbm.25535
pmc: PMC8288107
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
3993-4021Subventions
Organisme : CIHR
ID : MOP 142191
Pays : Canada
Organisme : CIHR
ID : MOP-133619
Pays : Canada
Organisme : CIHR
ID : PJT 153115
Pays : Canada
Organisme : CIHR
ID : PJT 156125
Pays : Canada
Organisme : CIHR
ID : PJT 166167
Pays : Canada
Organisme : CIHR
ID : PJT-159948
Pays : Canada
Informations de copyright
© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
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