Hi AFNI experts,

I am running into some issue with using AlphaSim correction.

I have been analyzing a structural dataset and these data were preprocessed by VBM SPM. I then fed these data into AFNI and ran 3dLME to look at group differences adding with covariates. The LME ran fine and I double checked the model was set up correctly and my main findings made a lot of sense. Since I was looking at the findings at whole-brain uncorrected p<0.005, I then tried to perform 3dClustim for correction. The mask I used was generated from my own sample. And somehow I kept getting weirdly large size of cluster (see below). I'd greatly appreciated if I could receive some help on this.

The steps I performed:

3dFWHMx -input LME_3Grp_covar_resid.nii.gz -mask mask_1.5mm.nii.gz -acf

++ Authored by: The Bob
++ Number of voxels in mask = 559909
*+ WARNING: removed 12734 voxels from mask because they are constant in time
++ start ACF calculations out to radius = 27.65 mm
+ ACF done (0.00 CPU s thus far)
0 0 0 0
0.783367 8.58099 31.2275 21.8855

3dClustSim -mask mask_1.5mm.nii.gz -acf 0.783343 8.58107 31.2219 -prefix corrected

++ 3dClustSim: AFNI version=AFNI_18.0.09 (Jul 7 2015) [64-bit]
++ Authored by: RW Cox and BD Ward
++ 559909 voxels in mask (26.37% of total)
++ Kernel function radius = 74.39 mm
++ ACF(0.78,8.58,31.22) => FWHM=21.89 => 121x145x121 pads to 240x256x240
+ Kernel image dimensions 33 x 35 x 33
++ Startup clock time = 1.9 s
++ Using 15 OpenMP threads
Simulating:0123456789.0123456789.0123456789.0123456789.01234567!
++ Clock time now = 1244.7 s
bi-sided thresholding
# Grid: 121x145x121 1.50x1.50x1.50 mm^3 (559909 voxels in mask)
#
# CLUSTER SIZE THRESHOLD(pthr,alpha) in Voxels
# -NN 2 | alpha = Prob(Cluster >= given size)
# pthr | .10000 .05000 .02000 .01000
# ------ | ------ ------ ------ ------
0.050000 7942.0 9761.0 12269 14301
0.020000 3348.5 4037.0 5013.0 5841.0
0.010000 2013.5 2462.0 3052.0 3483.0
0.005000 1290.0 1588.0 2032.0 2298.0
0.002000 769.5 961.7 1215.0 1417.5
0.001000 525.8 662.5 864.0 1039.0
0.000500 361.0 465.7 622.0 770.0
0.000200 210.4 290.0 405.0 508.0
0.000100 132.7 199.1 289.0 364.7