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Hi Mark, After more reading (particularly http://www.nitrc.org/forum/forum.php?thread_id=3785&forum_id=1456) I think I have a few questions regarding the optimal pipeline to incorporate FUGUE/epi_reg along with slice timing, physio and volume motion correction for resting state data. A) Having a siemens interleaved EPI sequence with physio collected I want to create a pipeline to incorporate physio correction, slice time , motion as well as Fugue for resting state data. FUGUE is used to correct for B0 inhomogeneity. The question I have is since the head moves a bit from volume 1 to volume 280 do I still run fugue first or do I need to run some sort of motion correction prior to that fugue applies the distortion correction to the appropriate voxels (ie in case of shift)? On one hand the map is collected prior to the first volume so should I motion correct all EPI volumes to the first timepoint or can I use the last (my ref frame for motion correction) in order to ensure the map matches the brain position. On the other hand the brains were in reality shifted when the EPI was taken so would the field map correction be incorrect since we adjust the position through volume correction, which does not represent the voxels true position in the magnetic field when the scan was acquired (ie run FUGUE PRIOR to motion correction). My guess is that we should motion correct first and then run FUGUE and I can align to the last time point, but please confirm. B) Aside from just motion correction I am trying to have the optimal pipeline to incorporate fugue with standard slice timing, motion correction etc. The following passage is from the link I attached above: "slice timing correction will make physiologic noise in your data unrecoverable by any means. The slice time correction resamples the data acquired at X msec after the start of the volume and assumes that everything is Nyquist-sampled (ie. no freq higher than 1/(2*TR) Hz). Any frequency lower than the Nyquist is correctly resampled as if it occurred at the start of the volume. However, any frequency in the data that is higher than the Nyquist gets smeared all over the Fourier spectrum randomly depending on where it happened to bin. Most (possibly anything slower than 200-400msec TR, due to higher harmonics of cardiac) acquisitions do not have a volumetric sample rate fast enough to capture physiologic noise." For some earlier datasets we do not have physio so I was going to use seed-based regression of CSF/Saggital sinus which captures physio signal and use as a regressor. Based on the above does this mean that I would not be able to use this method due to the fact that slice-timing was performed? Or would this still be a valid approach? C) For data that I do have physio collected for, does the order below make sense to incorporate fugue, or any modifications you suggest? : 1) Run some sort of physio correction using physio data 2) Run slice time correction 3) Discard initial timepoints since steady state was not reached yet. 4) Run motion correction to the last time point (since first few time points will be discarded we align to last timepoint) 5) Align the magnitude/fieldmap image to the last time point and apply then apply FUGUE Sorry for the long email!!!! Thanks, Ajay