Thank you for the hint.
I followed the advice but got an error message:
mri_label2vol --annot $SUBJECTS_DIR/$SUBJECT/label/lh.aparc.annot --temp $SUBJECTS_DIR/$SUBJECT/mri/T1.mgz --o $SUBJECTS_DIR/$SUBJECT/label/aseg-in-func.mgh --subject $SUBJECT --hemi lh
mri_segstats --seg $SUBJECTS_DIR/$SUBJECT/label/aseg-in-func.mgh --ctab $FREESURFER_HOME/tkmeditColorsCMA --nonempty --excludeid 0 --in /home/sandy/data/meg/ptp/sub05/cond8-lh.mgh --frame 205 --sum $SUBJECTS_DIR/$SUBJECT/label/sub05_cond8.aseg-in-func.sum
Does this look about right? The functional --in volume is a time series with results.
And then the following ERROR MESSAGE comes up:
Voxel Volume is 1 mm^3
Generating list of segmentation ids
Found 165 segmentations
Computing statistics for each segmentation
1 1 Left-Cerebral-Exterior 919 919
Segmentation fault
I tried this both on a 32bit and a 64bit
machine.
Does anyone have a suggestion what the problem may be?
Thanks a lot.
Sandy
Doug Greve <greve@nmr.mgh.harvard.edu> wrote:
You can map the segmentations (aseg or aparc+aseg) to the functional space with mri_label2vol, then run mri_segstats passing it the func space aseg and your input mgh file.
doug
oxro03@yahoo.com wrote:Hi Freesurfers,
I have functional activation files (.mgh) which I can overlay onto a subject's surface. Now I am trying to do a functional ROI analysis based on the annotation files, e.g. to get information about the mean activation in a specific area based on FS segmentations.
Does anybody have any suggestion on how to do this in a straightforward manner?
Thanks a lot.
Sandy
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