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Steps 1-3 will be performed by one command (mris_preproc), step 4 by mri_surf2surf, and step 5 by mri_glmfit. Two [[FsgdFormat|FSGD]] files will be required, one for Steps 1-3, and one for Step 5. = Create the First [[FsgdFormat|FSGD]] File = The first FSGD file just needs the subject names of the inputs. The matching pairs must be listed consecutively. You do not need to specify groups or variables at this point (that is needed below) -- you can, it is just not needed. Eg, if you created the file below and called it "pairs.fsgd" {{{ GroupDescriptorFile 1 Class Main Input subject1 Main Input subject1match Main Input subject2 Main Input subject2match Main Input subject3 Main Input subject3match Main Input subject3 Main Input subject3match Main }}} where subject1match is the match for subject1 (either another time point or a match based on some sort of demographic). = Run mris_preproc = The mris_preproc command will be: {{{ mris_preproc --target fsaverage --hemi lh \ --meas thickness --out lh.paired-diff.thickness.mgh \ --fsgd pairs.fsgd --paired-diff }}} This peforms Steps 1-3 above, saving the data to lh.paired-diff.thickness.mgh. The key difference between this invokation and a "norma" invocation is the addition of the --paired-diff argument. This tells mris_preproc to compute the difference between the first and second, the third and fourth, etc. This has two implications: * One implication of this is that the number of frames in the output file will be half the number of subjects listed in the FSGD file.<<BR>> * The difference is subject-subjectmatch,so positives mean subject > subjectmatch and negatives mean subject < subjectmatch.<<BR>> |
This document describes how to perform a paired analysis in FreeSurfer. This includes a two time-point longitudinal analysis in which the same subject was scanned twice with each scan being run through FreeSurfer separately (using the longitudinal stream). It also includes a cross-over analysis in which each subject of a cohort has a matching subject in another cohort. In either, case this describes how to perform statistical tests on the difference between the pairs.
Overall Strategy
- Sample each individual's surface onto the average surface.
- Compute the difference between each of the pairs in the average surface space.
- Concatenate the differences into one file.
- Smooth on the surface (optional)
- Perform analysis with mri_glmfit on this file
Steps 1-3 will be performed by one command (mris_preproc), step 4 by mri_surf2surf, and step 5 by mri_glmfit. Two FSGD files will be required, one for Steps 1-3, and one for Step 5.
Create the First [[FsgdFormat|FSGD]] File
The first FSGD file just needs the subject names of the inputs. The matching pairs must be listed consecutively. You do not need to specify groups or variables at this point (that is needed below) -- you can, it is just not needed. Eg, if you created the file below and called it "pairs.fsgd"
GroupDescriptorFile 1 Class Main Input subject1 Main Input subject1match Main Input subject2 Main Input subject2match Main Input subject3 Main Input subject3match Main Input subject3 Main Input subject3match Main
where subject1match is the match for subject1 (either another time point or a match based on some sort of demographic).
Run mris_preproc
The mris_preproc command will be:
mris_preproc --target fsaverage --hemi lh \ --meas thickness --out lh.paired-diff.thickness.mgh \ --fsgd pairs.fsgd --paired-diff
This peforms Steps 1-3 above, saving the data to lh.paired-diff.thickness.mgh. The key difference between this invokation and a "norma" invocation is the addition of the --paired-diff argument. This tells mris_preproc to compute the difference between the first and second, the third and fourth, etc. This has two implications:
- One implication of this is that the number of frames in the output
file will be half the number of subjects listed in the FSGD file.
The difference is subject-subjectmatch,so positives mean subject > subjectmatch and negatives mean subject < subjectmatch.