Dear all,
I am currently working on the fMRI analysis of a motor task. This task
was performed by a group of patients who, due to their condition, were
unable to remain completely motionless inside the scanner. Since
motion can prevent adequate modelling with the GLM, I'm looking for
workarounds.
One such workaround is of course inserting the motion parameters into
the GLM, but in my case it probably would not work, since my patients
are doing a motor paradigm themselves, and I don't want to remove all
of my BOLD signal.
I've found several other workarounds, like inspecting data beforehand
and removing volumes/fixing slices, doing an 'unwarp' on your EPI
scans in the preprocessing, or using ICA analysis to identify&remove
components that are likely generated by motion.
Since there are so many diffferent ways of dealing with motion, I am
uncertain on how to proceed. For my group analysis, I'm rather
reluctant to just throw away a number of "failed" scans.
I was wondering if anyone have experience working with 'difficult' EPI
scans in fMRI (especially during motor paradigms), and could point me
in a good direction?
Regards,
Johan van der Meer
dept. Clinical Neurophysiology
Academic Medical Centre
Amsterdam
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