Hello everyone,
I am currently working on an fMRI study with a 2 by 2 design, involving a single group of 36 participants. I have successfully processed the data using the fMRI pipeline and am now encountering issues during the 2nd level analysis. Also, I am using Matlab R2023a and SPM12 and I am running the SPM12 toolbox on Matlab by connecting to my university’s VPN.
Here is the script for my batch:
matlabbatch{1}.spm.stats.factorial_design.dir = {'D:\2ndlevel'};
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(1).name = 'Self-Other';
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(1).levels = 2;
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(1).dept = 0;
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(1).variance = 1;
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(1).gmsca = 0;
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(1).ancova = 0;
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(2).name = 'Present-Future';
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(2).levels = 2;
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(2).dept = 0;
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(2).variance = 1;
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(2).gmsca = 0;
matlabbatch{1}.spm.stats.factorial_design.des.fd.fact(2).ancova = 0;
matlabbatch{1}.spm.stats.factorial_design.des.fd.icell(1).levels = [1
1];
%%
matlabbatch{1}.spm.stats.factorial_design.des.fd.icell(1).scans = {
'D:\1stlevel_Copy\subj_27\con_0001.nii'
'D:\1stlevel_Copy\subj_28\con_0001.nii'
'D:\1stlevel_Copy\subj_30\con_0001.nii'
'D:\1stlevel_Copy\subj_31\con_0001.nii'
'D:\1stlevel_Copy\subj_32\con_0001.nii'
'D:\1stlevel_Copy\subj_33\con_0001.nii'
'D:\1stlevel_Copy\subj_34\con_0001.nii'
'D:\1stlevel_Copy\subj_36\con_0001.nii'
'D:\1stlevel_Copy\subj_37\con_0001.nii'
'D:\1stlevel_Copy\subj_38\con_0001.nii'
'D:\1stlevel_Copy\subj_39\con_0001.nii'
'D:\1stlevel_Copy\subj_40\con_0001.nii'
'D:\1stlevel_Copy\subj_41\con_0001.nii'
'D:\1stlevel_Copy\subj_42\con_0001.nii'
'D:\1stlevel_Copy\subj_45\con_0001.nii'
'D:\1stlevel_Copy\subj_48\con_0001.nii'
'D:\1stlevel_Copy\subj_52\con_0001.nii'
'D:\1stlevel_Copy\subj_57\con_0001.nii'
'D:\1stlevel_Copy\subj_54\con_0001.nii'
'D:\1stlevel_Copy\subj_58\con_0001.nii'
'D:\1stlevel_Copy\subj_62\con_0001.nii'
'D:\1stlevel_Copy\subj_63\con_0001.nii'
'D:\1stlevel_Copy\subj_64\con_0001.nii'
'D:\1stlevel_Copy\subj_66\con_0001.nii'
'D:\1stlevel_Copy\subj_68\con_0001.nii'
'D:\1stlevel_Copy\subj_70\con_0001.nii'
'D:\1stlevel_Copy\subj_71\con_0001.nii'
'D:\1stlevel_Copy\subj_72\con_0001.nii'
'D:\1stlevel_Copy\subj_73\con_0001.nii'
'D:\1stlevel_Copy\subj_74\con_0001.nii'
'D:\1stlevel_Copy\subj_76\con_0001.nii'
'D:\1stlevel_Copy\subj_78\con_0001.nii'
'D:\1stlevel_Copy\subj_80\con_0001.nii'
'D:\1stlevel_Copy\subj_81\con_0001.nii'
'D:\1stlevel_Copy\subj_83\con_0001.nii'
'D:\1stlevel_Copy\subj_90\con_0001.nii'
};
%%
matlabbatch{1}.spm.stats.factorial_design.des.fd.icell(2).levels = [1
2];
%%
matlabbatch{1}.spm.stats.factorial_design.des.fd.icell(2).scans = {
'D:\1stlevel_Copy\subj_27\con_0002.nii'
'D:\1stlevel_Copy\subj_28\con_0002.nii'
'D:\1stlevel_Copy\subj_30\con_0002.nii'
'D:\1stlevel_Copy\subj_31\con_0002.nii'
'D:\1stlevel_Copy\subj_32\con_0002.nii'
'D:\1stlevel_Copy\subj_33\con_0002.nii'
'D:\1stlevel_Copy\subj_34\con_0002.nii'
'D:\1stlevel_Copy\subj_36\con_0002.nii'
'D:\1stlevel_Copy\subj_37\con_0002.nii'
'D:\1stlevel_Copy\subj_38\con_0002.nii'
'D:\1stlevel_Copy\subj_39\con_0002.nii'
'D:\1stlevel_Copy\subj_40\con_0002.nii'
'D:\1stlevel_Copy\subj_41\con_0002.nii'
'D:\1stlevel_Copy\subj_42\con_0002.nii'
'D:\1stlevel_Copy\subj_45\con_0002.nii'
'D:\1stlevel_Copy\subj_48\con_0002.nii'
'D:\1stlevel_Copy\subj_52\con_0002.nii'
'D:\1stlevel_Copy\subj_57\con_0002.nii'
'D:\1stlevel_Copy\subj_54\con_0002.nii'
'D:\1stlevel_Copy\subj_58\con_0002.nii'
'D:\1stlevel_Copy\subj_62\con_0002.nii'
'D:\1stlevel_Copy\subj_63\con_0002.nii'
'D:\1stlevel_Copy\subj_64\con_0002.nii'
'D:\1stlevel_Copy\subj_66\con_0002.nii'
'D:\1stlevel_Copy\subj_68\con_0002.nii'
'D:\1stlevel_Copy\subj_70\con_0002.nii'
'D:\1stlevel_Copy\subj_71\con_0002.nii'
'D:\1stlevel_Copy\subj_72\con_0002.nii'
'D:\1stlevel_Copy\subj_73\con_0002.nii'
'D:\1stlevel_Copy\subj_74\con_0002.nii'
'D:\1stlevel_Copy\subj_76\con_0002.nii'
'D:\1stlevel_Copy\subj_78\con_0002.nii'
'D:\1stlevel_Copy\subj_80\con_0002.nii'
'D:\1stlevel_Copy\subj_81\con_0002.nii'
'D:\1stlevel_Copy\subj_83\con_0002.nii'
'D:\1stlevel_Copy\subj_90\con_0002.nii'
};
%%
matlabbatch{1}.spm.stats.factorial_design.des.fd.icell(3).levels = [2
1];
%%
matlabbatch{1}.spm.stats.factorial_design.des.fd.icell(3).scans = {
'D:\1stlevel_Copy\subj_27\con_0003.nii'
'D:\1stlevel_Copy\subj_28\con_0003.nii'
'D:\1stlevel_Copy\subj_30\con_0003.nii'
'D:\1stlevel_Copy\subj_31\con_0003.nii'
'D:\1stlevel_Copy\subj_32\con_0003.nii'
'D:\1stlevel_Copy\subj_33\con_0003.nii'
'D:\1stlevel_Copy\subj_34\con_0003.nii'
'D:\1stlevel_Copy\subj_36\con_0003.nii'
'D:\1stlevel_Copy\subj_37\con_0003.nii'
'D:\1stlevel_Copy\subj_38\con_0003.nii'
'D:\1stlevel_Copy\subj_39\con_0003.nii'
'D:\1stlevel_Copy\subj_40\con_0003.nii'
'D:\1stlevel_Copy\subj_41\con_0003.nii'
'D:\1stlevel_Copy\subj_42\con_0003.nii'
'D:\1stlevel_Copy\subj_45\con_0003.nii'
'D:\1stlevel_Copy\subj_48\con_0003.nii'
'D:\1stlevel_Copy\subj_52\con_0003.nii'
'D:\1stlevel_Copy\subj_57\con_0003.nii'
'D:\1stlevel_Copy\subj_54\con_0003.nii'
'D:\1stlevel_Copy\subj_58\con_0003.nii'
'D:\1stlevel_Copy\subj_62\con_0003.nii'
'D:\1stlevel_Copy\subj_63\con_0003.nii'
'D:\1stlevel_Copy\subj_64\con_0003.nii'
'D:\1stlevel_Copy\subj_66\con_0003.nii'
'D:\1stlevel_Copy\subj_68\con_0003.nii'
'D:\1stlevel_Copy\subj_70\con_0003.nii'
'D:\1stlevel_Copy\subj_71\con_0003.nii'
'D:\1stlevel_Copy\subj_72\con_0003.nii'
'D:\1stlevel_Copy\subj_73\con_0003.nii'
'D:\1stlevel_Copy\subj_74\con_0003.nii'
'D:\1stlevel_Copy\subj_76\con_0003.nii'
'D:\1stlevel_Copy\subj_78\con_0003.nii'
'D:\1stlevel_Copy\subj_80\con_0003.nii'
'D:\1stlevel_Copy\subj_81\con_0003.nii'
'D:\1stlevel_Copy\subj_83\con_0003.nii'
'D:\1stlevel_Copy\subj_90\con_0003.nii'
};
%%
matlabbatch{1}.spm.stats.factorial_design.des.fd.icell(4).levels = [2
2];
%%
matlabbatch{1}.spm.stats.factorial_design.des.fd.icell(4).scans = {
'D:\1stlevel_Copy\subj_27\con_0004.nii'
'D:\1stlevel_Copy\subj_28\con_0004.nii'
'D:\1stlevel_Copy\subj_30\con_0004.nii'
'D:\1stlevel_Copy\subj_31\con_0004.nii'
'D:\1stlevel_Copy\subj_32\con_0004.nii'
'D:\1stlevel_Copy\subj_33\con_0004.nii'
'D:\1stlevel_Copy\subj_34\con_0004.nii'
'D:\1stlevel_Copy\subj_36\con_0004.nii'
'D:\1stlevel_Copy\subj_37\con_0004.nii'
'D:\1stlevel_Copy\subj_38\con_0004.nii'
'D:\1stlevel_Copy\subj_39\con_0004.nii'
'D:\1stlevel_Copy\subj_40\con_0004.nii'
'D:\1stlevel_Copy\subj_41\con_0004.nii'
'D:\1stlevel_Copy\subj_42\con_0004.nii'
'D:\1stlevel_Copy\subj_45\con_0004.nii'
'D:\1stlevel_Copy\subj_48\con_0004.nii'
'D:\1stlevel_Copy\subj_52\con_0004.nii'
'D:\1stlevel_Copy\subj_57\con_0004.nii'
'D:\1stlevel_Copy\subj_54\con_0004.nii'
'D:\1stlevel_Copy\subj_58\con_0004.nii'
'D:\1stlevel_Copy\subj_62\con_0004.nii'
'D:\1stlevel_Copy\subj_63\con_0004.nii'
'D:\1stlevel_Copy\subj_64\con_0004.nii'
'D:\1stlevel_Copy\subj_66\con_0004.nii'
'D:\1stlevel_Copy\subj_68\con_0004.nii'
'D:\1stlevel_Copy\subj_70\con_0004.nii'
'D:\1stlevel_Copy\subj_71\con_0004.nii'
'D:\1stlevel_Copy\subj_72\con_0004.nii'
'D:\1stlevel_Copy\subj_73\con_0004.nii'
'D:\1stlevel_Copy\subj_74\con_0004.nii'
'D:\1stlevel_Copy\subj_76\con_0004.nii'
'D:\1stlevel_Copy\subj_78\con_0004.nii'
'D:\1stlevel_Copy\subj_80\con_0004.nii'
'D:\1stlevel_Copy\subj_81\con_0004.nii'
'D:\1stlevel_Copy\subj_83\con_0004.nii'
'D:\1stlevel_Copy\subj_90\con_0004.nii'
};
%%
matlabbatch{1}.spm.stats.factorial_design.des.fd.contrasts = 1;
%%
matlabbatch{1}.spm.stats.factorial_design.cov(1).c = [14.28
16.14
17
17.56
14.18
17.1
16.52
15.77
14.2
16.5
15
16.2
16.8
16.78
17.69
16.6
17.34
17.2
12.23
16.78
17.69
16.78
17.69
15.89
17.51
15.99
15
12.57
16.42
15.47
17.33
17.86
15.76
16.98
17.78
16];
%%
matlabbatch{1}.spm.stats.factorial_design.cov(1).cname = 'Age';
matlabbatch{1}.spm.stats.factorial_design.cov(1).iCFI = 1;
matlabbatch{1}.spm.stats.factorial_design.cov(1).iCC = 5;
%%
matlabbatch{1}.spm.stats.factorial_design.cov(2).c = [1
1
1
1
1
2
1
2
2
1
1
2
1
1
1
2
2
2
1
2
2
2
2
1
1
2
1
1
1
1
2
2
1
1
1
1];
%%
matlabbatch{1}.spm.stats.factorial_design.cov(2).cname = 'Sex';
matlabbatch{1}.spm.stats.factorial_design.cov(2).iCFI = 1;
matlabbatch{1}.spm.stats.factorial_design.cov(2).iCC = 5;
matlabbatch{1}.spm.stats.factorial_design.multi_cov = struct('files', {}, 'iCFI', {}, 'iCC', {});
matlabbatch{1}.spm.stats.factorial_design.masking.tm.tm_none = 1;
matlabbatch{1}.spm.stats.factorial_design.masking.im = 1;
matlabbatch{1}.spm.stats.factorial_design.masking.em = {''};
matlabbatch{1}.spm.stats.factorial_design.globalc.g_omit = 1;
matlabbatch{1}.spm.stats.factorial_design.globalm.gmsca.gmsca_no = 1;
matlabbatch{1}.spm.stats.factorial_design.globalm.glonorm = 1;
matlabbatch{2}.spm.stats.fmri_est.spmmat(1) = cfg_dep('Factorial design specification: SPM.mat File', substruct('.','val', '{}',{1}, '.','val', '{}',{1}, '.','val', '{}',{1}), substruct('.','spmmat'));
matlabbatch{2}.spm.stats.fmri_est.write_residuals = 0;
matlabbatch{2}.spm.stats.fmri_est.method.Classical = 1;
When I try to run my batch, I get this error:
Error using horzcat
Dimensions of arrays being concatenated are not consistent.
Could anyone please give me advice as to what is going wrong?
Thank you in advance!