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       10.148   18876   6019.28     43.4  -79.0   -5.5  0.00300  0.00000  0.00599   8837    43917.52  lateraloccipital
   2        4.977    9524    442.81     25.9  -57.1   47.0  0.00300  0.00000  0.00599   1053     3785.22  superiorparietal
   3        3.753   72285    121.53      9.4   11.2   55.5  0.07883  0.06169  0.09857    248      743.41  superiorfrontal
   4        3.692   72818     57.61     48.5   -2.2   47.3  0.28068  0.25139  0.30919     96      290.20  precentral
   5        3.480   27113     40.44     20.9   40.0  -15.0  0.40305  0.37058  0.43439     68      205.19  lateralorbitofrontal
   6        4.168   29057     40.36      9.2    5.2   66.1  0.40305  0.37058  0.43439     73      241.49  superiorfrontal
   7        3.397   44263     38.15     31.2  -48.9   38.4  0.42821  0.39665  0.45866    106      308.32  superiorparietal
}}}
* 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