The figures show more (7 vs. 2) significant clusters using the repaired data. The difference is more than usual, but the presence of artifacts and large motions can strongly reduce estimated effects. Since there are 1081 degrees of freedom in the not-repaired option, and 708 dof in the repaired option, there were likely about 373 scans marked for deweighting in the GLM. Generally, I suggest limiting repairs to fewer than 15-20% of the scans by raising the threshold, even for difficult head motions. It may help to try an example without using clipping, and to raise the threshold by one increment to get rid of any excess deweighted scans. If the activations remain after this process, I would be fairly confident in them.
Generally, I don't recommend using the "Clipping" option, which was built to support the rule of thumb of 3 mm maximum motion, and kept in the GUI as a legacy capability. Using art_motionregress is more effective. If art_motionregress is used, it is not necessary to add the six motion regressors to the GLM.
As mentioned in the previous post, it will help to see the realignment and art_global plots.
Best regards,
Paul
----- Original Message -----
From: "Christopher Watson" <[log in to unmask]>
To: [log in to unmask]
Sent: Tuesday, December 7, 2010 9:00:23 AM
Subject: Re: [SPM] Use of ArtRepair-large differences
The difference could be "normal". It depends on how much motion there was. Can you post the realignment plot and/or the art_global plot?
________________________________________
From: SPM (Statistical Parametric Mapping) [[log in to unmask]] On Behalf Of Nicole Van Hoeck [[log in to unmask]]
Sent: Tuesday, December 07, 2010 11:33 AM
To: [log in to unmask]
Subject: [SPM] Use of ArtRepair-large differences
Dear SPM users,
I’m using the toolbox ArtRepair for the first time. I’m surprised how much my results change. Therefore, I start to doubt myself in correctly applying this program.
This is the procedure I followed:
1) art_slice before preprocessing (Number of slices repaired: 515 = 1.5%)
2) art_global: ‘repair’ volumes (+ use of ‘clip’)
3) 1st model with the v-files (repaired files) and motion parameters as regressors
4) art_summary to compare repaired model to non-repaired model
Attached you can find the results (repaired and not repaired) of one of my subjects for one contrast.
Is the difference in results ‘normal’?
Thank you,
Nicole
--
Nicole Van Hoeck
Department of Clinical & Lifespan Psychology | Department of Experimental & Applied Psychology
Faculty of Psychology & Educational Science
Vrije Universiteit Brussel
Pleinlaan 2 | 1050 Brussels | Belgium
office: 3C235
phone: +32-(0)-2 / 629 25 26
email: [log in to unmask]<mailto:[log in to unmask]>
--
Paul K. Mazaika, PhD.
Center for Interdisciplinary Brain Sciences Research
Stanford University School of Medicine
Office: (650)724-6646 Cell: (650)799-8319
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