EEG-assisted retrospective motion correction for fMRI: E-REMCOR

Physics – Medical Physics

Scientific paper

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13 pages, 10 figures, submitted for publication

Scientific paper

We propose a method for retrospective motion correction of fMRI data in simultaneous EEG-fMRI that employs the EEG array as a sensitive motion detector. EEG motion artifacts are used to generate motion regressors describing rotational head movements with millisecond temporal resolution. These regressors are employed for slice-specific motion correction of unprocessed fMRI data. The method does not require any specialized equipment beyond the standard EEG-fMRI instrumentation. Its performance is demonstrated by correction of fMRI data from four patients with major depressive disorder, who exhibited random head movements by 1-3 mm during a resting EEG-fMRI run. The fMRI datasets, corrected using eight EEG-based motion regressors, show significant improvements in temporal SNR (tSNR) of fMRI time series, particularly in the frontal brain regions and near the surface of the brain. The tSNR improvements are as high as 50% for large brain areas in single-subject analysis and as high as 25% when the results are averaged across the subjects. Simultaneous application of the EEG-based motion correction and physiological noise correction by means of RETROICOR leads to average tSNR enhancements as high as 35% for large brain regions. The proposed EEG-assisted method of retrospective fMRI motion correction (referred to as E-REMCOR) can be applied to improve quality of fMRI data with severe motion artifacts and reduce spurious correlations between the EEG and fMRI datasets caused by head movements.

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