spisakt
commented
2 years ago Dear @siproes,
Sorry for the late answer. I am afraid the images you put into pTFCE may not fully comply with the assumptions of Gaussian Random Field Theory. Namely, the smoothness of the images look pretty inhomogenous, which can be problematic with pTFCE.
The need to truncate is related to computational issues, depending on the implementation, large Z-scores easily end up in p-values being to small for computers... Are you using the R-package?
In general, your use-case is not typical for pTFCE, so I would be cautious when using it.
The increase in Z-scores may be expected, actually Z-score enhancement is the primary aim of pTFCE.
Hope it helps, Tamas
Hi,
I have been trying to use the pTFCE tool but I'm very new to this kind of analysis. I'm having some issues so I might be doing something wrong.
I generated z-maps of FDG-PET images of lesioned rat brains by calculating (x-µ)/SD, where x is a voxel value in an image post-lesion and µ and SD are the voxel mean and standard deviation derived from a baseline average template of control animals. My images contain some very high z-scores but the pTFCE tool runs smoothly after truncating those values and setting them to 30. However, after pTFCE, the actual voxel z-scores are changed. E.g. after the analysis, there will be z-scores of over 30 again. If I input an image with only positive z-scores, after pTFCE some voxels will have a negative value. I don't think this should be happening since this might probably generate incorrect results when performing fwer thresholding?
Maybe I'm not using this tool correctly. I'm also not sure if truncating the high values might have a significant influence on my results...
Here are some example images.
Zmaps.zip
Thanks a lot in advance!