FreeSurfer offers several ways to correct for multiple comparisons on the surface. One way is similar to Gaussian Random Fields (GRF) but uses a simulation rather than analitic equations to estimate the corrected voxel-wise and clusterwise p-values. See Hagler,et al. Using a simulation has seveal advantages, namely that the assumptions of needed to make the GRF equations work do not apply (eg, cluster-forming threshold and minimum smoothness). The disadvantage is that it is slow to run the simulation. However, it is possible to run simulations under many different conditions and store the results for later use. This has alread been performed for fsaverage and fsaverage_sym and are used automatically by mri_glmfit-sim (which performs the correction).
If you are using one of these two subjects with a whole cortex analysis, then you can use the precomputed results. If you want to use a different subject or to limit your analysis to a smaller spatial region, then you will need to run you own simulations. mri_mcsim is a program which efficiently performs this simulation
mri_mcsim --o $FREESURFER_HOME/average/mult-comp-cor \
- --base mc-z --surface yoursubject lh --nreps 10000
And one for the right hemi too.
This will create a directory structure similar to $FREESURFER_HOME/average/mult-comp-cor/fsaverage
It may take a couple of days to run but once it is done, you don't need to run it again. After that you can just run mri_glmfit-sim
Note, you can put it into a different directory and then spec that folder when you run mri_glmfit-sim with the --cache-dir flag.