First off, DARTEL is a fantastic tool, and I'd definitely recommend
trying it out as John suggests.
But in any case, I would strongly suggest that you display your
activations on an average of your normalized T1 images instead of the
MNI template. If normalization fails for any reason, it will be
immediately obvious. Also, normalization is never quite perfect, and
your average normalized T1 will differ from the MNI template. Using the
avg T1, you can be much more certain that your activations are exactly
where you think they are.
You might also try, as John suggests, double checking that your fMRI and
T1 data are in register.
Regards,
Neil
Chris Watson wrote:
> I've attached a screenshot of Check Reg with the group's mask.img and
> avg152T1.img. There is some weird artifact bilaterally (possibly due
> to bad headphones), but this spot is around 20mm posterior to the SPM
> screenshot I posted previously. However, is it possible this artifact
> is what's screwing up the process? The T1's look fine (example T1
> attached). Is there anything like lesion masking that can be done to
> improve this, or do I have to live with these results?
>
> Thanks,
> Chris
>
> John Ashburner wrote:
>> To me, it looks like an issue with the generation of the mask used for
>> determining which regions to include when fitting the GLM. I suggest
>> you use the Check Reg button to see how well your spatially normalised
>> images are aligned with the images that are supplied with SPM.
>>
>> Also make sure that the fMRI and anatomical data are well aligned
>> together (Check Reg) before you do any spatially normalising based on
>> the anatomical.
>>
>> The best procedure varies from scanner to scanner. If you can achieve
>> good alignment between fMRI and anatomical, then the segmentation
>> approach should do a reasonable job. If accurate coregistration is not
>> possible because of distortions (which could maybe be corrected via the
>> FieldMap toolbox), then a different approach may be preferable.
>> Sometimes it is possible to segment the fMRI directly and use the
>> resulting deformation to spatially normalise the data.
>>
>> Personally though, I would use the DARTEL toolbox of SPM8 to do my
>> spatial normalisation. Instructions are in the spm8/man/manual.pdf
>> file.
>>
>> Best regards,
>> -John
>>
>>
>> On Wed, 2009-08-12 at 14:19 -0400, Chris Watson wrote:
>>
>>> Hello,
>>> I was wondering if anyone has seen something similar to what I'm
>>> going to describe. I'm attaching a screenshot of results from a
>>> finger-tapping experiment.
>>> As can be seen, the edge of the blobs are several millimeters away
>>> from the edge of the template image. Looking at the mask image and
>>> the template together also show this. I have seen this with almost
>>> all of the subjects. Could it be the subjects' age (mean age 11-12
>>> years)? I ran a couple of subjects using the regular Normalization
>>> step and the mean functional image as the source, and it looks
>>> better, but I haven't done all the subjects yet. I considered making
>>> a study-specific template, but unfortunately n=8 for both groups
>>> (I'm assuming there are too few subjects). I don't expect perfect
>>> registration but there are several millimeters difference in some
>>> areas, as if the warped images are "shrunken" compared to the template.
>>>
>>> So, even though Unified Segmentation is the suggested method, would
>>> it be invalid to use the Normalization step?
>>>
>>> Thanks,
>>> Chris
>>>
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