Dear SPMers!
Some authors think the methods for correction of multiple comparisons implemented in spm99 are too conservative for VBM studies in contrast with functional imaging.
I wonder where is the problem.
I can imagine there might be two reasons: in functional imaging you get higher contrast/difference/effect than in VBM or in VBM studies you have more ressels (more voxels with more or less the same smoothing kernel). Since I have a limited experience with functional studies I donīt know anything about the magnitude of the difference and the number of ressels, that is I only guess.
Could someone correct me?
Are there any changes in correction using random field theory between spm99 and spm2?
Did someone make computations of this problem to quote it?
The second question I want to ask is about small volume correction. Mathew Brett wrote the formula for computing ECs in small volumes have to be adjusted for shape differences. So, you get different results when you do a ROI analysis (for example hippocampus mask using WFU PickAtlas) and when you do small volume correction with the same mask as in ROI.
What is more appropriate aproach?
Is there something that favours one of the two aproaches?
Again, are there any differences between spm99 and spm2?
Thank you in advance,
Tomas Kasparek
Dep. of Psychiatry
Brno, the Czech Republic
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