Effective removal of the residual head motion artifact after motion correction in fMRI data.

We investigate the source of residual motion artifact after volumetric motion correction using a custom MR sequence acquisition with prospectively injected motion (SIMPACE). We injected various patterns of motion during scanning ex-vivo brain phantoms at 3T to synthesize head motion in an fMRI dataset. We propose voxelwise retrospective motion regressors in addition to 6 rigid body motion parameters, then compare it with the “standard” 6 motion parameters and their derivatives regressor models. The proposed model improves tSNR by 40% and 11% in linear drift of motion and the realistic motion case, respectively, compared to 6 motion parameter model.