Hello, I have some block-design functional runs (3mm isotropic voxels) with
varied peaks of motion. Most of them have a single-TR peak of 4-6mm, while a
few had peaks of 12-20mm. As I understand one have two options to try to
correct head motion in FSL: a) feeding the motion parameters from the
prestats in the GLM model of FEAT; and b) using melodic to find the
extraneous components that are not task-related.
I am using as a rule-of-thumb that motions beyond the voxel dimension (3mm)
or that are time-correlated with the stimulus are to be rejected from
further analysis. As I am trying to salvage some of those runs that do not
follow this rule, some questions came to mind:
1) How can one tell if feeding the motion parameters into GLM succeeded in
removing the motion-related blobs? Are looking the blobs in the FEAT output
or in fslview the only options - which are fairly subjective?
2) Should I use both methods in conjunction (motion parameters in
GLM+melodic) to obtain a more robust motion correction?
3) What are the limits of using these methods; would they be able to
compensate a 12 or even a 20mm motion peak?
4) Motions that are time-locked with stimulus presentation can be safely
removed using the above methods?
5) If only one epoch (stimulus+rest) is affected by the peak motion,
removing the TRs composing the affected epoch using flsmaths would be an
acceptable approach?
If anybody has other methods to correct head motion or ways to tell if the
correction was successful, I would love to hear about it.
Thanks.
Estephan Moana, DDS
Graduate Student
Oral Biology PhD Program - Neurobiology track
School of Dentistry, UNC- Chapel Hill
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