On Mon, 6 Oct 2008 21:51:26 +0100, Thomas Nichols <[log in to unmask]>
wrote:
Do you mean at the individual level or 2nd level? How can I see values for this?
>Are the problems related to smoothness estimation?
On the within group data I receive the following output:
>I.e. is the smoothness FWHM or Resels NaN as well? Or, are their strange
values for the
>"Expected voxels per cluster" or "Expected number of clusters"? Is the
number of the
>voxels in the analysis what you expect? (Mask not way too large or too
>small?)
For Stroop task, using default values on results:
1. Using no correction: some clusters, Expected voxels per cluster (EVC) =
.003, Expected # of clusters (E#C) = 64075.98, Expected FDR = .66
2. Using FDR: No suprathreshold clusters, EVC = NaN, E#C = NaN, EFDR = .66
3. Using FWE: 2 clusters, 1 large one with 199336 voxels, EVC = 221, E#C =
.05, FDR = .90
For OSPAN task:
1. No correction: Showed scattered, random looking activation and gave the
following warning many times
Warning: Returning NaN for out of range arguments
> In spm_Pcdf at 88
In spm_P_RF at 106
In spm_P at 48
In spm_list at 487
I pressed Ctrl+C to stop the repition of these warnings and the volume table
had a 25 page list of clusters all with NaNs for Pcorrected.
2.Using FDR: same as in Stroop, except EFDR = .10
3. Using FWE: no clusters, EVC=0.000, E#C = 393619779.31, EFDR=.10
The # of voxels for the analyses were around 205,000 voxels.
The RPV images for the group data have some NaN values outside of the brain,
>If there are NaN's in the smoothness estimate, look at the FWHM image
>(compute from the RPV image with ImCalc as FWHM = RPV.^(1/3)). Viewing this
>image with CheckReg with other images (e.g. the mask, or T image, ResMS (or
>its square root), etc). If the is *really* irregularly shaped (i.e. no
>contiguous voxels) it is possible to have almost all NaN's in the RPV image.
which as you suggested may be normal. However, the images are of a very low
intensity, from about .002 - 3.0, expect for a few high intensity points.
The FWHM from this doesn't show much of course.
I hope this helps to describe the problem. Also, some of the activation on
the single subject data looks really bad, just big huge blobs.
Thanks,
Carlos
>
>-Tom
>
>
>On Mon, Oct 6, 2008 at 9:08 PM, Carlos Faraco <[log in to unmask]> wrote:
>
>> Dear SPMers,
>>
>> Today I read through many of the posts regarding NaNs, however I am still
>> confused as to what would be the best remedy for my situation.
>>
>> The problem is I keep on receiving NaNs for the p-vals on the second level
>> analysis. I tried changing the NaNs to 0s in the con images (which seem to
>> appear only or mostly outside the brain; and becasue I read not to do this
>> for the beta images) using ImCalc but that still doesn't work. I therefore
>> checked some files from some other studies we had previously done, and it
>> appears that setting voxels outside the brain to NaN is normal SPM
>> behavior.
>>
>> Is the fix for this then something that has to be modified within the SPM
>> code?
>>
>> Thanks,
>>
>> Carlos Faraco
>>
>>
>
>
>--
>____________________________________________
>Thomas Nichols, PhD
>Director, Modelling & Genetics
>GlaxoSmithKline Clinical Imaging Centre
>
>Senior Research Fellow
>Oxford University FMRIB Centre
>