Output of mri_glmfit-sim for a left 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       11.659   97629   6136.15    -42.0  -48.0  -13.5  0.00030  0.00000  0.00060   9152    53229.39  fusiform
   2        6.315  157496   1801.73    -24.1  -71.6   25.5  0.00030  0.00000  0.00060   3905    15096.38  superiorparietal
   3        5.190   30291    768.79    -39.7    1.6   25.9  0.00030  0.00000  0.00060   1656     5859.67  precentral
   4        5.954   73097    548.29     -9.0   20.9   42.4  0.00030  0.00000  0.00060   1031     4011.96  superiorfrontal
   5        4.727  154486    324.21    -48.9   12.5   14.6  0.00060  0.00000  0.00120    574     1845.59  parsopercularis
   6        4.252   68077    259.77    -40.4   28.4    3.7  0.00210  0.00120  0.00300    488     1589.40  parstriangularis
   7        6.139   52930    147.16    -28.4  -14.2  -31.6  0.03966  0.03528  0.04404    303     1160.92  entorhinal
}}}

 * 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