title: Separation and reconstruction of BCG and EEG signals during continuous EEG and fMRI recordings.
abstract: Despite considerable effort to remove it, the ballistocardiogram (BCG) remains a major artifact in electroencephalographic data (EEG) acquired inside magnetic resonance imaging (MRI) scanners, particularly in continuous (as opposed to event-related) recordings. In this study, we have developed a new Direct Recording Prior Encoding (DRPE) method to extract and separate the BCG and EEG components from contaminated signals, and have demonstrated its performance by comparing it quantitatively to the popular Optimal Basis Set (OBS) method. Our modified recording configuration allows us to obtain representative bases of the BCG- and EEG-only signals. Further, we have developed an optimization-based reconstruction approach to maximally incorporate prior knowledge of the BCG/EEG subspaces, and of the signal characteristics within them. Both OBS and DRPE methods were tested with experimental data, and compared quantitatively using cross-validation. In the challenging continuous EEG studies, DRPE outperforms the OBS method by nearly sevenfold in separating the continuous BCG and EEG signals.
authors.affiliation: Department of Bioengineering, University of California, Los Angeles Los Angeles, CA, USA.
authors.forename: Hongjing
authors.initials: H
authors.lastname: Xia
authors.affiliation: Department of Bioengineering, University of California, Los Angeles Los Angeles, CA, USA ; Department of Radiation Oncology, University of California, Los Angeles Los Angeles, CA, USA.
authors.forename: Dan
authors.initials: D
authors.lastname: Ruan
authors.affiliation: Department of Bioengineering, University of California, Los Angeles Los Angeles, CA, USA ; Department of Psychiatry, Neurology, Radiology, Psychology, Biomedical Physics, California NanoSystems Institute, University of California, Los Angeles Los Angeles, CA, USA.
authors.forename: Mark S
authors.initials: MS
authors.lastname: Cohen
keywords: artifacts; ballistocardiogram; group sparsity; segmentation; signal separation; simultaneous EEG-fMRI; split Bregman