Thank you Bruce, Douglas.
Yes, I think thicknesses were obtained with v 5.3.0. There might be errors as Bruce pointed out, I am going now through all maps to check them. This makes me think of a question. Volumetric template registrations sometimes go wrong. Does this happen also to surface registrations in FS sometimes ???
I am using other statistics, not glm, but thanks for suggesting it. Data are imported and exported in R using some R functions I built myself, nothing fancy, just using intermediate text files to get what I want and put it back for visualization.
Thank you
On Thu, Mar 9, 2017 at 11:23 AM, Douglas N Greve greve@nmr.mgh.harvard.edu wrote:
On 03/08/2017 09:27 PM, Dorian P. wrote:
Hi Freesurfers,
I am using R to perform thickness analyses. All subjects are transformed in fsaverage space and all values are placed in a matrix with 327684 columns (163842 for each hemisphere). I put the results back in a surface file (.asc format) and then convert it to a binary Freesurfer format. I then open the files in Freesurfer to view them.
Overall the results make sense and fall in the right places. But I am concerned that some results fall into the corpus callosum, which, if I remember correctly should not have any thickness value, and therefore no results.
Here is a screenshot: Inline image 1
Can someone help my understand what might be wrong? Or, if this is normal, why I am finding thickness results where there is no thickness?
Is this 5.3? The thickness may not be 0 in the medial wall, but non-zero values are meaningless and should be masked out or ignored.
Is there a way to find label numbers for each vertex in fsaverage space (i.e. list of parcel number for each vertex). This might be useful to exclude certain vertices or compute summery statistics of the results directly in R.
You can load the annotation into matlab with read_annotation.m
Third question, is it possible to threshold the above map based on minimal cluster area (i.e., in mri_surfcluster). If yes, do I need to prepare a binary file with p-values for thresholding (0-1), or can I use mri_surfcluster with t-score maps (0-Inf)?
You can use any map you want, you just have to specify the threshold correctly. Also, you will need to have a FWHM. To get this I would run an analysis in mri_glmfit using a design similar to what you used in R (small differences probably won't affect the FWHM measure).
Thank you for your help. Dorian
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