Output of mri_glmfit-sim for a right hemisphere surface-based fMRI analysis (encode-v-base contrast):
{{{
# ClusterNo  Max   VtxMax   Size(mm^2)  MNIX   MNIY   MNIZ    CWP    CWPLow    CWPHi   NVtxs    WghtVtx   Annot
   1       10.497  122811   6130.25     43.5  -80.1   -4.4  0.00300  0.00000  0.00599   9021    45015.08  lateraloccipital
   2        4.097  157401    235.33     26.6  -57.5   46.5  0.02085  0.01195  0.02970    554     1836.83  superiorparietal
   3        3.680  140528     52.90     48.0   -1.2   46.3  0.28788  0.25878  0.31853     88      275.83  precentral
   4        3.357  100049     39.58      9.0   18.7   43.1  0.38804  0.35726  0.41991     81      238.64  superiorfrontal
   5        3.610   98248     31.56      9.9    6.4   65.6  0.47444  0.44256  0.50509     56      172.30  superiorfrontal
   6        3.130  140918     30.18     21.2   41.2  -13.4  0.49183  0.46065  0.52179     53      154.06  lateralorbitofrontal
   7        3.707  118371     29.06     36.6  -30.3  -25.2  0.49943  0.46856  0.52909     65      205.65  fusiform
}}}
* Much of the header has been removed for clarity
 * Max = maximum voxel-wise signifiance in the cluster
 * VtxMax - vertex number of the maximum
 * Size(mm2) - size of cluster in millimeters square
 * MNIX, MNIY, MNIZ  - MNI305 Coordinates of maximum
 * CWP - p-value of the cluster (CWP=Cluster-Wise P-value)
 * CWPLow - lower 95% confidence interval of CWP
 * CWPHi - upper 95% confidence interval of CWP
 * NVtxs - number of vertices in cluster (each vertex will not have the exact same area, you can estimate mean vertex area by dividing total surface area by the number of vertices)
 * Annot - name of annotation that maximum falls into