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Ballistocardiogram suppression in concurrent EEG‐MRI by dynamic modeling of heartbeats

The ballistocardiogram (BCG), the induced electric potentials by the head motion originating from heartbeats, is a prominent source of noise in electroencephalography (EEG) data during magnetic resonance imaging (MRI). Although methods have been proposed to suppress the BCG artifact, more work consi...

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Autores principales: Lee, Hsin‐Ju, Graham, Simon J., Kuo, Wen‐Jui, Lin, Fa‐Hsuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9435020/
https://www.ncbi.nlm.nih.gov/pubmed/35695703
http://dx.doi.org/10.1002/hbm.25965
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author Lee, Hsin‐Ju
Graham, Simon J.
Kuo, Wen‐Jui
Lin, Fa‐Hsuan
author_facet Lee, Hsin‐Ju
Graham, Simon J.
Kuo, Wen‐Jui
Lin, Fa‐Hsuan
author_sort Lee, Hsin‐Ju
collection PubMed
description The ballistocardiogram (BCG), the induced electric potentials by the head motion originating from heartbeats, is a prominent source of noise in electroencephalography (EEG) data during magnetic resonance imaging (MRI). Although methods have been proposed to suppress the BCG artifact, more work considering the variability of cardiac cycles and head motion across time and subjects is needed to provide highly robust correction. Here, a method called “dynamic modeling of heartbeats” (DMH) is proposed to reduce BCG artifacts in EEG data recorded inside an MRI system. The DMH method models BCG artifacts by combining EEG points at time instants with similar dynamics. The modeled BCG artifact is then subtracted from the EEG recording to suppress the BCG artifact. Performance of DMH was tested and specifically compared with the Optimal Basis Set (OBS) method on EEG data recorded inside a 3T MRI system with either no MRI acquisition (Inside‐MRI), echo‐planar imaging (EPI‐EEG), or fast MRI acquisition using simultaneous multi‐slice and inverse imaging methods (SMS‐InI‐EEG). In a steady‐state visual evoked response (SSVEP) paradigm, the 15‐Hz oscillatory neuronal activity at the visual cortex after DMH processing was about 130% of that achieved by OBS processing for Inside‐MRI, SMS‐InI‐EEG, and EPI‐EEG conditions. The DMH method is computationally efficient for suppressing BCG artifacts and in the future may help to improve the quality of EEG data recorded in high‐field MRI systems for neuroscientific and clinical applications.
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spelling pubmed-94350202022-09-08 Ballistocardiogram suppression in concurrent EEG‐MRI by dynamic modeling of heartbeats Lee, Hsin‐Ju Graham, Simon J. Kuo, Wen‐Jui Lin, Fa‐Hsuan Hum Brain Mapp Research Articles The ballistocardiogram (BCG), the induced electric potentials by the head motion originating from heartbeats, is a prominent source of noise in electroencephalography (EEG) data during magnetic resonance imaging (MRI). Although methods have been proposed to suppress the BCG artifact, more work considering the variability of cardiac cycles and head motion across time and subjects is needed to provide highly robust correction. Here, a method called “dynamic modeling of heartbeats” (DMH) is proposed to reduce BCG artifacts in EEG data recorded inside an MRI system. The DMH method models BCG artifacts by combining EEG points at time instants with similar dynamics. The modeled BCG artifact is then subtracted from the EEG recording to suppress the BCG artifact. Performance of DMH was tested and specifically compared with the Optimal Basis Set (OBS) method on EEG data recorded inside a 3T MRI system with either no MRI acquisition (Inside‐MRI), echo‐planar imaging (EPI‐EEG), or fast MRI acquisition using simultaneous multi‐slice and inverse imaging methods (SMS‐InI‐EEG). In a steady‐state visual evoked response (SSVEP) paradigm, the 15‐Hz oscillatory neuronal activity at the visual cortex after DMH processing was about 130% of that achieved by OBS processing for Inside‐MRI, SMS‐InI‐EEG, and EPI‐EEG conditions. The DMH method is computationally efficient for suppressing BCG artifacts and in the future may help to improve the quality of EEG data recorded in high‐field MRI systems for neuroscientific and clinical applications. John Wiley & Sons, Inc. 2022-06-13 /pmc/articles/PMC9435020/ /pubmed/35695703 http://dx.doi.org/10.1002/hbm.25965 Text en © 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Lee, Hsin‐Ju
Graham, Simon J.
Kuo, Wen‐Jui
Lin, Fa‐Hsuan
Ballistocardiogram suppression in concurrent EEG‐MRI by dynamic modeling of heartbeats
title Ballistocardiogram suppression in concurrent EEG‐MRI by dynamic modeling of heartbeats
title_full Ballistocardiogram suppression in concurrent EEG‐MRI by dynamic modeling of heartbeats
title_fullStr Ballistocardiogram suppression in concurrent EEG‐MRI by dynamic modeling of heartbeats
title_full_unstemmed Ballistocardiogram suppression in concurrent EEG‐MRI by dynamic modeling of heartbeats
title_short Ballistocardiogram suppression in concurrent EEG‐MRI by dynamic modeling of heartbeats
title_sort ballistocardiogram suppression in concurrent eeg‐mri by dynamic modeling of heartbeats
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9435020/
https://www.ncbi.nlm.nih.gov/pubmed/35695703
http://dx.doi.org/10.1002/hbm.25965
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