Dear Jerry
I think this may be due to a great variance in your residuals,
for some reason... could you check that the sessions are
scaled to the same values (I think this is the default) or that
there isn't something funny (or not funny) in your data ?
You could also check the residual mean square images (ResMS.img) of both
analyses and look at their values ... If the residual variance
is artefactually great, the smoothness estimate will be artefactually
great as well ... Normally a filter of 7-8 mm FWHM will not
produce such a great smoothness value.
best
jb
Jerry Allison wrote:
>
> I am getting unexpectected results from smoothing.
>
> I have 2 fMRI datasets (pre&post surgery) acquired 3 months apart.
>
> Both datasets were acquired using the same paradigm and the same pulse sequence and the same timing, etc. They were acquired identically.
>
> It's a block design. TR is 3.5 sec. The voxel size is 3.59mmx3.59mmx3.9mm. There are 120 scans consisting of 40 A, 40 B and 40 Control as follows:
> 10A 10 B 10Control 10A 10 B 10Control 10A 10 B 10Control 10A 10 B 10Control
>
> When I analyze the unsmoothed data, SPM99 reports similar estimated smoothness for both sets of data:
> 5.1mmx5.0mmx5.3mm and 4.5mmx4.5mmx4.7mm
>
> If I apply a filter kernel whose FWHM is 2 times the voxel size (7.2mmx7.2mmx7.8mm) and analyze the data, the estimated smootness reported by SPM99 is very different:
> 33.4mmx33.1mmx31.0mm versus 12.8mmx12.7mmx12.0mm
>
> How could such a modest amount of smoothing (2 times the voxel size) cause such a large estimed smoothess in the data (9 times the voxel size) in one set of data, but much less in the other?
>
> How does such a large disparity in smoothness affect my attempt to compare the pre&post surgery data?
>
> Jerry Allison, Ph.D.
> Medical College of Georgia
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