Key result
Average artifact subtraction slightly outperforms optimal basis sets for ballistocardiogram artifact reduction during EEG-fMRI.
Why the study?
Electroencephalography data recorded during fMRI acquisition are subject to large cardiac-related artifacts that must be corrected during postprocessing, but a comparison of widely used ballistocardiogram correction algorithms was lacking.
May support preferring average artifact subtraction for BCG correction; leaves open optimal method selection pending larger validation.
Electroencephalography data recorded during functional magnetic resonance imaging acquisition are subject to large cardiac-related artifacts that must be corrected during postprocessing. This study compared two widely used ballistocardiogram (BCG) correction algorithms as implemented in two software programs. Reduction of BCG amplitude, correlation of corrected data with electrocardiogram traces, correlation of independent components with electrocardiogram traces, and event-related potential signal-to-noise ratio from each algorithm were compared. Both algorithms effectively reduced the BCG artifact, with a slight advantage of average artifact subtraction over the optimal basis set method (0.1-2.2%) when the quality of the correction was examined at the individual subject level. This study provides users of these software tools with an important, practical, and previously unavailable comparison of the performance of these two methods.
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Harrison et al. (2014) studied Healthy volunteers (n=40). Average artifact subtraction (AAS) method vs. Optimal basis set (OBS) method was evaluated on Reduction of ballistocardiogram (BCG) amplitude and correlation of corrected data with ECG traces (0.1-2.2% advantage). Average artifact subtraction demonstrated a slight advantage of 0.1-2.2% over the optimal basis set method in effectively reducing ballistocardiogram artifacts during simultaneous EEG-fMRI recordings.
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