On Tue, 15 Sep 2009 06:55:11 -0500, Johan <[log in to unmask]>
wrote:
>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.
Remember, though, that changes in signal directly due to motion and changes
in signal due to BOLD response from motor activation won't be very correlated
because of the delay in the hemodynamic response. So in principle you could
remove all the variation directly due to motion, and yet not remove much of
the BOLD response.
>
>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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