Data‐driven beamforming technique to attenuate ballistocardiogram artefacts in electroencephalography–functional magnetic resonance imaging without detecting cardiac pulses in electrocardiography recordings

• Published in: Human brain mapping Vol. 42; no. 12; pp. 3993 - 4021
• Main Authors: Uji, Makoto, Cross, Nathan, Pomares, Florence B., Perrault, Aurore A., Jegou, Aude, Nguyen, Alex, Aydin, Umit, Lina, Jean‐Marc, Dang‐Vu, Thien Thanh, Grova, Christophe
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 15-08-2021; Wiley
• Subjects: Adult; Anabolic steroids; Attenuation; ballistocardiogram (BCG) artefacts; Ballistocardiograms; Ballistocardiography - methods; Ballistocardiography - standards; BCG; BCG vaccines; Beamforming; beamforming technique; Brain; Brain mapping; Cardiology; Cognitive science; Data acquisition; Data processing; EEG; EEG–fMRI; EKG; Electrocardiogram; Electrocardiography; Electroencephalography; Electroencephalography - methods; Electroencephalography - standards; Eye movements; Female; Functional magnetic resonance imaging; Functional Neuroimaging - methods; Functional Neuroimaging - standards; Heart; Humans; Investigations; Magnetic fields; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Magnetic Resonance Imaging - standards; Male; Medical imaging; Methods; motor beta ERD; Neuroimaging; Neurophysiology; Neuroscience; Recording; Resonance; Scanners; Sleep; Spatial filtering; Subtraction; time–frequency analysis; visual alpha event‐related desynchronization (ERD); Visual stimuli; Young Adult; motor beta ERD; ballistocardiogram (BCG) artefacts; EEG-fMRI; beamforming technique; visual alpha event-related desynchronization (ERD); time-frequency analysis
• ISSN: 1065-9471; 1097-0193
• DOI: 10.1002/hbm.25535

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.
Our proposed data‐driven beamforming spatial filtering approach outperformed the standard denoising technique in terms of both attenuating the ballistocardiogram (BCG) artefacts and recovering the meaningful task‐based‐induced neural activities in electroencephalography–functional magnetic resonance imaging (EEG–fMRI). This beamforming BCG artefact correction approach neither requires identifying noise and signal components nor relying on simultaneous ECG recording, which makes it promising. Our findings support and extend the previous findings of the beamforming spatial filtering application, and bring new insight into an active area of research in EEG‐fMRI‐related to the extraction of meaningful brain signals and suppression of MRI‐related artefacts.