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