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