Hello,afni experts.When I use 3dICC to computes whole-brain voxel-wise ICC.There is a problem as shown below:
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***** Summary information of data structure *****
4 subjects : chen duan he yi
100 response values
5 levels for factor taste : bitter salty sour sweet umami
5 levels for factor session : five four one three two
100 levels for factor Tstat : chen_11_21_final_REML_MNI.nii[1] chen_11_21_final_REML_MNI.nii[10] chen_11_21_final_REML_MNI.nii[13] chen_11_21_final_REML_MNI.nii[4] chen_11_21_final_REML_MNI.nii[7] chen_11_26_final_REML_MNI.nii[1] chen_11_26_final_REML_MNI.nii[10] chen_11_26_final_REML_MNI.nii[13] chen_11_26_final_REML_MNI.nii[4] chen_11_26_final_REML_MNI.nii[7] chen_11_27_final_REML_MNI.nii[1] chen_11_27_final_REML_MNI.nii[10] chen_11_27_final_REML_MNI.nii[13] chen_11_27_final_REML_MNI.nii[4] chen_11_27_final_REML_MNI.nii[7] chen_12_1_final_REML_MNI.nii[1] chen_12_1_final_REML_MNI.nii[10] chen_12_1_final_REML_MNI.nii[13] chen_12_1_final_REML_MNI.nii[4] chen_12_1_final_REML_MNI.nii[7] chen_12_6_final_REML_MNI.nii[1] chen_12_6_final_REML_MNI.nii[10] chen_12_6_final_REML_MNI.nii[13] chen_12_6_final_REML_MNI.nii[4] chen_12_6_final_REML_MNI.nii[7] duan_01_01_final_REML_MNI.nii[1] duan_01_01_final_REML_MNI.nii[10] duan_01_01_final_REML_MNI.nii[13] duan_01_01_final_REML_MNI.nii[4] duan_01_01_final_REML_MNI.nii[7] duan_01_02_final_REML_MNI.nii[1] duan_01_02_final_REML_MNI.nii[10] duan_01_02_final_REML_MNI.nii[13] duan_01_02_final_REML_MNI.nii[4] duan_01_02_final_REML_MNI.nii[7] duan_01_03_final_REML_MNI.nii[1] duan_01_03_final_REML_MNI.nii[10] duan_01_03_final_REML_MNI.nii[13] duan_01_03_final_REML_MNI.nii[4] duan_01_03_final_REML_MNI.nii[7] duan_01_07_final_REML_MNI.nii[1] duan_01_07_final_REML_MNI.nii[10] duan_01_07_final_REML_MNI.nii[13] duan_01_07_final_REML_MNI.nii[4] duan_01_07_final_REML_MNI.nii[7] duan_01_10_final_REML_MNI.nii[1] duan_01_10_final_REML_MNI.nii[10] duan_01_10_final_REML_MNI.nii[13] duan_01_10_final_REML_MNI.nii[4] duan_01_10_final_REML_MNI.nii[7] he_00_17_final_REML_MNI.nii[1] he_00_17_final_REML_MNI.nii[10] he_00_17_final_REML_MNI.nii[13] he_00_17_final_REML_MNI.nii[4] he_00_17_final_REML_MNI.nii[7] he_00_22_final_REML_MNI.nii[1] he_00_22_final_REML_MNI.nii[10] he_00_22_final_REML_MNI.nii[13] he_00_22_final_REML_MNI.nii[4] he_00_22_final_REML_MNI.nii[7] he_01_03_final_REML_MNI.nii[1] he_01_03_final_REML_MNI.nii[10] he_01_03_final_REML_MNI.nii[13] he_01_03_final_REML_MNI.nii[4] he_01_03_final_REML_MNI.nii[7] he_01_08_final_REML_MNI.nii[1] he_01_08_final_REML_MNI.nii[10] he_01_08_final_REML_MNI.nii[13] he_01_08_final_REML_MNI.nii[4] he_01_08_final_REML_MNI.nii[7] he_01_17_final_REML_MNI.nii[1] he_01_17_final_REML_MNI.nii[10] he_01_17_final_REML_MNI.nii[13] he_01_17_final_REML_MNI.nii[4] he_01_17_final_REML_MNI.nii[7] yi_11_12_final_REML_MNI.nii[1] yi_11_12_final_REML_MNI.nii[10] yi_11_12_final_REML_MNI.nii[13] yi_11_12_final_REML_MNI.nii[4] yi_11_12_final_REML_MNI.nii[7] yi_11_16_final_REML_MNI.nii[1] yi_11_16_final_REML_MNI.nii[10] yi_11_16_final_REML_MNI.nii[13] yi_11_16_final_REML_MNI.nii[4] yi_11_16_final_REML_MNI.nii[7] yi_11_23_final_REML_MNI.nii[1] yi_11_23_final_REML_MNI.nii[10] yi_11_23_final_REML_MNI.nii[13] yi_11_23_final_REML_MNI.nii[4] yi_11_23_final_REML_MNI.nii[7] yi_12_3_final_REML_MNI.nii[1] yi_12_3_final_REML_MNI.nii[10] yi_12_3_final_REML_MNI.nii[13] yi_12_3_final_REML_MNI.nii[4] yi_12_3_final_REML_MNI.nii[7] yi_12_8_final_REML_MNI.nii[1] yi_12_8_final_REML_MNI.nii[10] yi_12_8_final_REML_MNI.nii[13] yi_12_8_final_REML_MNI.nii[4] yi_12_8_final_REML_MNI.nii[7]
Contingency tables of subject distributions among the categorical variables:
***** End of data structure information *****
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Reading input files now…
Reading input files for effect estimates: Done!
Reading input files for tStat: Done!
Error in FUN(array(newX[, i], d.call, dn.call), …) :
object ‘Mask’ not found
Calls: array → apply → FUN
Execution halted
and I have confirmed the mask file is right,What surprised me is that when I delete the tFile in Data table ,the code run well,but I still want to add the t stats to analysis.the code I ran as shown below:
#!/bin/bash
test=(cat subject.txt)
3dICC -prefix test_run/ICC3_allrun111 -jobs 12
-mask all_rigid_mask.Pilot1+tlrc
-model ‘1+(1|taste)+(1|session)+(1|Subj)’
-Subj ‘subject’
-tStat ‘tFile’
-dataTable
subject taste session tFile InputFile
chen bitter one ${test[0]}[1] ${test[0]}[0]
chen salty one ${test[0]}[4] ${test[0]}[3]
chen sour one ${test[0]}[7] ${test[0]}[6]
chen sweet one ${test[0]}[10] ${test[0]}[9]
chen umami one ${test[0]}[13] ${test[0]}[12]
chen bitter two ${test[1]}[1] ${test[1]}[0]
chen salty two ${test[1]}[4] ${test[1]}[3]
chen sour two ${test[1]}[7] ${test[1]}[6]
chen sweet two ${test[1]}[10] ${test[1]}[9]
chen umami two ${test[1]}[13] ${test[1]}[12]
chen bitter three ${test[2]}[1] ${test[2]}[0]
chen salty three ${test[2]}[4] ${test[2]}[3]
chen sour three ${test[2]}[7] ${test[2]}[6]
chen sweet three ${test[2]}[10] ${test[2]}[9]
chen umami three ${test[2]}[13] ${test[2]}[12]
chen bitter four ${test[3]}[1] ${test[3]}[0]
chen salty four ${test[3]}[4] ${test[3]}[3]
chen sour four ${test[3]}[7] ${test[3]}[6]
chen sweet four ${test[3]}[10] ${test[3]}[9]
chen umami four ${test[3]}[13] ${test[3]}[12]
chen bitter five ${test[4]}[1] ${test[4]}[0]
chen salty five ${test[4]}[4] ${test[4]}[3]
chen sour five ${test[4]}[7] ${test[4]}[6]
chen sweet five ${test[4]}[10] ${test[4]}[9]