Optimal slice timing correction and its interaction with fMRI parameters and artifacts.

Due to the nature of fMRI acquisition protocols, slices in the plane of acquisition are not acquired simultaneously or sequentially, and therefore are temporally misaligned with each other. Slice timing correction (STC) is a critical preprocessing step that corrects for this temporal misalignment. Interpolation-based STC is implemented in all major fMRI processing software packages. To date, little effort has gone towards assessing the optimal method of STC. Delineating the benefits of STC can be challenging because of its slice-dependent gain as well as its interaction with other fMRI artifacts. In this study, we propose a new optimal method (Filter-Shift) based on the fundamental properties of sampling theory in digital signal processing. We then evaluate our method by comparing it to two other methods of STC from the most popular statistical software packages, SPM and FSL. STC methods were evaluated using 338 simulated and 30 real fMRI data and demonstrate the effectiveness of STC in general as well as the superiority of the proposed method in comparison to existing ones. All methods were evaluated under various scan conditions such as motion level, interleave sequence, scanner sampling rate, and the duration of the scan itself.