Dear Freesurfer users,

I am using mri_glmfit-sim to do clusterwise correction for multiple comparisons. I ran the Z Monte Carlo simulation for 5000 iterations for my 43 subjects (vertex wise threshold of 2.0 or p < 0.01), but I received different results than when I ran the correction using the "new" pre-cached simulation (using threshold of 2.0). In general, I get fewer clusters when running the simulation from scratch when compared with the pre-cached simulation. I used the fsaverage subject brain in the original analysis. Here are the commands I ran:

   initial glmfit (uncorrected):

mri_glmfit --y lh.HCvsCD.thickness.10.mgh --fsgd HCvsCD.fsgd dods --C group.diff.mtx --surf fsaverage lh --cortex --glmdir lh.HCvsCD.glmdir

Then corrections for multiple comparisons ....

   from scratch:

mri_glmfit-sim --glmdir lh.HCvsCD.glmdir --sim mc-z 5000 2.0 mc-z.pos --sim-sign pos  --bg 5

   using pre-cached:

mri_glmfit-sim --glmdir lh.HCvsCD.glmdir --cache 2.0 pos

Which method is most accurate?

Also, how does one turn off the polling writes to the console when running MC-Z from scratch?

Thanks,
Christopher Hyatt
Olin Neuropsychiatric Research Center / IOL
Hartford, CT