Characterization and correction of interpolation effects in the realignment of fMRI time series

Subject motion in functional magnetic resonance imaging (fMRI) studies can be accurately estimated using realignment algorithms. However, residual cha nges in signal intensity arising from motion have been identified in the da ta even after realignment of the image time series. The nature of these art ifacts is characterized using simulated displacements of an fMRI image and is attributed to interpolation errors introduced by the resampling inherent within realignment. A correction scheme that uses a periodic function of t he estimated displacements to remove interpolation errors from the image ti me series on a voxel-by-voxel basis is proposed. The artifacts are investig ated using a brain phantom to avoid physiological confounds Small- and larg e-scale systematic displacements show that the artifacts have the same form as revealed by the simulated displacements. A randomly displaced phantom a nd a human subject are used to demonstrate that interpolation errors are mi nimized using the correction. (C) 2000 Academic Press.