Hello,

we obviously already miss the AFNI bootcamp!
What am I trying to do: run 3dttest++ with an anatomical mask on bilateral parietal lobes.
What error I get:

++ 3dttest++: AFNI version=AFNI_19.0.17 (Feb 22 2019) [64-bit]
++ Authored by: Zhark++
++ option -setA :: processing as LONG form (label label dset label dset ...)
++ have 20 volumes corresponding to option '-setA'
++ 189973 voxels in -mask dataset
** FATAL ERROR: -mask doesn't match datasets number of voxels
** Program compile date = Feb 22 2019

I checked my stat.subject.HEAD files with 3dinfo and this is my output

++ 3dinfo: AFNI version=AFNI_19.0.17 (Feb 22 2019) [64-bit]

Dataset File:    stats.sub-011_REML+tlrc
Identifier Code: AFN_xXX_dIM3W6rsmxmGT1m_kQ  Creation Date: Mon Mar  4 13:54:55 2019
Template Space:  HaskinsPeds
Dataset Type:    Func-Bucket (-fbuc)
Byte Order:      LSB_FIRST [this CPU native = LSB_FIRST]
Storage Mode:    BRIK
Storage Space:   283,948,280 (284 million) bytes
Geometry String: "MATRIX(-1.5,0,0,88.5,0,-1.5,0,125.5,0,0,1.5,-68.5):119,145,121"
Data Axes Tilt:  Plumb
Data Axes Orientation:
  first  (x) = Left-to-Right
  second (y) = Posterior-to-Anterior
  third  (z) = Inferior-to-Superior   [-orient LPI]
R-to-L extent:   -88.500 [R] -to-    88.500 [L] -step-     1.500 mm [119 voxels]
A-to-P extent:   -90.500 [A] -to-   125.500 [P] -step-     1.500 mm [145 voxels]
I-to-S extent:   -68.500  -to-   111.500 [S] -step-     1.500 mm [121 voxels]

All my subjects are preprocessed to the Haskins_NL_template (below the preprocessing steps)

I then checked my mask:

++ 3dinfo: AFNI version=AFNI_19.0.17 (Feb 22 2019) [64-bit]

Dataset File:    anat_bilateral_parietal_mask+tlrc
Identifier Code: AFN_H9_F7DvqxfWaxI-hhtAu8Q  Creation Date: Tue Apr  2 14:44:25 2019
Template Space:  HaskinsPeds
Dataset Type:    Echo Planar (-epan)
Byte Order:      LSB_FIRST [this CPU native = LSB_FIRST]
Storage Mode:    BRIK
Storage Space:   7,102,004 (7.1 million) bytes
Geometry String: "MATRIX(-1,0,0,89,0,-1,0,126,0,0,1,-69):179,218,182"
Data Axes Tilt:  Plumb
Data Axes Orientation:
  first  (x) = Left-to-Right
  second (y) = Posterior-to-Anterior
  third  (z) = Inferior-to-Superior   [-orient LPI]
R-to-L extent:   -89.000 [R] -to-    89.000 [L] -step-     1.000 mm [179 voxels]
A-to-P extent:   -91.000 [A] -to-   126.000 [P] -step-     1.000 mm [218 voxels]
I-to-S extent:   -69.000  -to-   112.000 [S] -step-     1.000 mm [182 voxels]

The mask has the same dimensions as the Haskins template I made it from but my subjects have different dimensions. I don't understand why my stats.subj files have 1.5 mm voxels and not 1mm like the template.
What am I missing here?

here it the preprocessing steps from the stats.subject file in case I made a mistake at some point.

HISTORY -----
[nens.lab@C07T20JBG1J2.local: Mon Mar  4 13:54:55 2019] Matrix source: ; 3dDeconvolve -input pb04.sub-011.r01.scale+tlrc.HEAD 
pb04.sub-011.r02.scale+tlrc.HEAD -censor censor_sub-011_combined_2.1D -ortvec mot_demean.r01.1D mot_demean_r01 
-ortvec mot_demean.r02.1D mot_demean_r02 -polort 2 -float -num_stimts 4 -stim_times 1 stimuli/Easy.tsv GAM 
-stim_label 1 LargeD -stim_times 2 stimuli/Medium.tsv GAM -stim_label 2 MediumD -stim_times 3 stimuli/Hard.tsv GAM 
-stim_label 3 SmallD -stim_times 4 stimuli/control_n.tsv GAM -stim_label 4 Ctrl_n -bout -jobs 4 -gltsym 'SYM: SmallD -LargeD' -glt_label 1 Small-Large 
-gltsym 'SYM: SmallD -MediumD' -glt_label 2 Small-Medium -gltsym 'SYM: MediumD -LargeD' -glt_label 3 Medium-Large 
-gltsym 'SYM: SmallD MediumD LargeD -3*Ctrl_n' -glt_label 4 All-control -gltsym 'SYM: LargeD -Ctrl_n' -glt_label 5 Large-Control 
-gltsym 'SYM: SmallD -Ctrl_n' -glt_label 6 Small-Control -gltsym 'SYM: MediumD -Ctrl_n' -glt_label 7 Medium-Control -fout -tout -x1D X.xmat.1D 
-xjpeg X.jpg -x1D_uncensored X.nocensor.xmat.1D -fitts fitts.sub-011 -errts errts.sub-011 -bucket stats.sub-011
[nens.lab@C07T20JBG1J2.local: Mon Mar  4 13:54:55 2019] {AFNI_19.0.17:macos_10.12_local} 3dREMLfit -matrix X.xmat.1D 
-input 'pb04.sub-011.r01.scale+tlrc.HEAD pb04.sub-011.r02.scale+tlrc.HEAD' -fout -tout -Rbuck stats.sub-011_REML -Rvar stats.sub-011_REMLvar 
-Rfitts fitts.sub-011_REML -Rerrts errts.sub-011_REML -verb
[nens.lab@C07T20JBG1J2.local: Mon Mar  4 15:12:30 2019] {AFNI_19.0.17:macos_10.12_local} 3drefit -atrstring AFNI_CLUSTSIM_NN1_1sided file:files_ClustSim/ClustSim.ACF.NN1_1sided.niml 
-atrstring AFNI_CLUSTSIM_MASK file:files_ClustSim/ClustSim.ACF.mask 
-atrstring AFNI_CLUSTSIM_NN2_1sided file:files_ClustSim/ClustSim.ACF.NN2_1sided.niml 
-atrstring AFNI_CLUSTSIM_NN3_1sided file:files_ClustSim/ClustSim.ACF.NN3_1sided.niml 
-atrstring AFNI_CLUSTSIM_NN1_2sided file:files_ClustSim/ClustSim.ACF.NN1_2sided.niml 
-atrstring AFNI_CLUSTSIM_NN2_2sided file:files_ClustSim/ClustSim.ACF.NN2_2sided.niml 
-atrstring AFNI_CLUSTSIM_NN3_2sided file:files_ClustSim/ClustSim.ACF.NN3_2sided.niml 
-atrstring AFNI_CLUSTSIM_NN1_bisided file:files_ClustSim/ClustSim.ACF.NN1_bisided.niml 
-atrstring AFNI_CLUSTSIM_NN2_bisided file:files_ClustSim/ClustSim.ACF.NN2_bisided.niml 
-atrstring AFNI_CLUSTSIM_NN3_bisided file:files_ClustSim/ClustSim.ACF.NN3_bisided.niml stats.sub-011+tlrc 
stats.sub-011_REML+tlrc

Finally, and not related, regarding the eBIDS, you should add a rating on quality, movement and whether participants were taken to the Rockbottom.