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MRI_processing/emo_1stlevel_parametric.m

+function emo_1stlevel_v01(subs_info,paths,mod,pupille,overwrite)
+
+for id = 1:length(subs_info)
+    
+    %this part of the code search for the preprocessed functional files (emo task) of the
+    %current subject being processed
+    
+    subject_info = char(subs_info(id));
+    subject_ID = subject_info(5:7);
+    
+    message = ['processing functional images of subject: ' char(subs_info(id))] ;
+    disp(message)
+    
+     
+%     if ~exist(fullfile(char([paths.data '/sub-' subject_ID '/' subject_info(9:end)])))
+%         message = ['(1) No data found for sub-', subject_ID '/' subject_info(9:end)] ;
+%         disp(message)
+%         continue
+%     end
+    
+    fprintf('Looking for preprocessed functional files (TASK : emo)')
+    emo_folder = char([paths.data '/' char(subs_info(id)) '/MRI' '/output_preprocessing' '/emo']) ;
+    
+    %We extracted the name of the .nii files but since the input in the
+    %batch need the entire path to the nifti files, we will change the
+    %content of the cell containing the names of the files to add the
+    %entire path before the name
+    list_folder = emo_folder ;
+    preprocessed_nifti = dir(fullfile(list_folder, 'sBET*')) ;
+    preprocessed_nifti = {preprocessed_nifti.name} ;
+    [r c] = size(preprocessed_nifti) ;
+    
+    %We save the entire path to the nifti files (fith the files names)
+    for i = 1:c
+        preprocessed_nifti{i} = char([list_folder '/' preprocessed_nifti{i}]) ;
+    end
+    
+    %Here, we reshape the cell into a format readable by spm. The input is
+    %put in a single 1x1 cell containing #volume x 1 cells.
+    preprocessed_nifti = preprocessed_nifti' ;
+    %preprocessed_nifti = {preprocessed_nifti} ;
+    fprintf('\n Preprocessed functional data found \n ')
+
+    %We will find for the "onsets_task_HILIGHT_ID" and the
+    %"REGRESSOR_emo_HILIGHT_ID_..." files created respectively with the
+    %"task_LM.m" codes and the "Merge_reg.m" code + creates output dir
+    
+    output = char([paths.data '/' char(subs_info(id)) '/MRI' '/output_1stlevel_MEL_Dark_Sept']) ;%we save that path to create an output folder
+    if mod == 0
+        onsets_emo = dir(fullfile(char([paths.data '/' char(subs_info(id)) '/LM/']), 'onsets_emo_nomod_Mel_Dark_*')) ;
+        output_emo = char([output '/emo_nomod']) ;
+    elseif mod == 1
+        onsets_emo = dir(fullfile(char([paths.data '/' char(subs_info(id)) '/LM/']), 'onsets_emo_lightmod_Mel_Dark_*')) ;
+        output_emo = char([output '/emo_lightmod']) ;
+    elseif mod == 2
+        onsets_emo = dir(fullfile(char([paths.data '/' char(subs_info(id)) '/LM/']), 'onsets_emo_timemod_Mel_HILIGHT_*')) ;
+        output_emo = char([output '/emo_timemod']) ;
+    elseif mod == 3
+        onsets_emo = dir(fullfile(char([paths.data '/' char(subs_info(id)) '/LM/']), 'onsets_emo_pupilmod_Mel_HILIGHT_*')) ;
+        output_emo = char([output '/emo_pupilmod']) ;
+    end
+    onset_emo = char([onsets_emo.folder '/' onsets_emo.name]) ;
+    
+    
+    
+    if pupille == 0
+        pupil_emo = dir(fullfile(char([paths.data '/' char(subs_info(id)) '/LM/']), 'REGRESSOR_Motion_Physio_noPUPIL_emo_HILIGHT_*')) ;
+        output_emo = char(strcat(output_emo,'_NoPUPIL')) ;
+    elseif pupille == 1
+        pupil_emo = dir(fullfile(char([paths.data '/' char(subs_info(id)) '/LM/']), 'REGRESSOR_Motion_Physio_PUPIL_emo_HILIGHT_*')) ;
+        output_emo = char(strcat(output_emo,'_PUPIL')) ;
+    end
+    pupil_emo = char([pupil_emo.folder '/' pupil_emo.name]) ;
+       
+    
+    
+    if ~exist(output)
+        mkdir(output)
+        mkdir(output_emo)
+    elseif ~exist(output_emo)
+        mkdir(output_emo)
+    end
+    
+    if ~isempty(dir(output_emo)) && overwrite == false
+        message =  ['Output already exists and "overwrite" set to false. No 1st-level Analysis conducted for sub-', subject_ID] ;
+        disp(message)
+        continue
+    end
+
+%%%
+
+ %set up batch
+    if mod==0 %nomod
+        
+    clear matlabbatch
+    spm_jobman('initcfg') ;
+    
+    matlabbatch{1}.spm.stats.fmri_spec.dir = {output_emo};
+    matlabbatch{1}.spm.stats.fmri_spec.timing.units = 'scans';
+    matlabbatch{1}.spm.stats.fmri_spec.timing.RT = 2.34;
+    matlabbatch{1}.spm.stats.fmri_spec.timing.fmri_t = 16;
+    matlabbatch{1}.spm.stats.fmri_spec.timing.fmri_t0 = 8;
+    %%
+    matlabbatch{1}.spm.stats.fmri_spec.sess.scans = preprocessed_nifti ;
+    %%
+    matlabbatch{1}.spm.stats.fmri_spec.sess.cond = struct('name', {}, 'onset', {}, 'duration', {}, 'tmod', {}, 'pmod', {}, 'orth', {});
+    matlabbatch{1}.spm.stats.fmri_spec.sess.multi = {onset_emo} ;
+    matlabbatch{1}.spm.stats.fmri_spec.sess.regress = struct('name', {}, 'val', {});
+    matlabbatch{1}.spm.stats.fmri_spec.sess.multi_reg = {pupil_emo};
+    matlabbatch{1}.spm.stats.fmri_spec.sess.hpf = 256;
+    matlabbatch{1}.spm.stats.fmri_spec.fact = struct('name', {}, 'levels', {});
+    matlabbatch{1}.spm.stats.fmri_spec.bases.hrf.derivs = [0 0];
+    matlabbatch{1}.spm.stats.fmri_spec.volt = 1;
+    matlabbatch{1}.spm.stats.fmri_spec.global = 'None';
+    matlabbatch{1}.spm.stats.fmri_spec.mthresh = -inf;
+    matlabbatch{1}.spm.stats.fmri_spec.mask = {''};
+    matlabbatch{1}.spm.stats.fmri_spec.cvi = 'AR(1)';
+    matlabbatch{2}.spm.stats.fmri_est.spmmat(1) = cfg_dep('fMRI model 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;
+    
+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+    %creation of contrasts
+    matlabbatch{3}.spm.stats.con.spmmat(1) = cfg_dep('Model estimation: SPM.mat File', substruct('.','val', '{}',{2}, '.','val', '{}',{1}, '.','val', '{}',{1}), substruct('.','spmmat'));
+    matlabbatch{3}.spm.stats.con.consess{1}.tcon.name = 'Emo';
+    matlabbatch{3}.spm.stats.con.consess{1}.tcon.weights = [1];
+    matlabbatch{3}.spm.stats.con.consess{1}.tcon.sessrep = 'none';
+    matlabbatch{3}.spm.stats.con.delete = 1;
+        
+    matlabbatch{3}.spm.stats.con.consess{2}.tcon.name = 'Neut';
+    matlabbatch{3}.spm.stats.con.consess{2}.tcon.weights = [0 1];
+    matlabbatch{3}.spm.stats.con.consess{2}.tcon.sessrep = 'none';
+    matlabbatch{3}.spm.stats.con.delete = 1;
+%       
+    matlabbatch{3}.spm.stats.con.consess{3}.tcon.name = 'Emo-Neut';
+    matlabbatch{3}.spm.stats.con.consess{3}.tcon.weights = [1 -1];
+    matlabbatch{3}.spm.stats.con.consess{3}.tcon.sessrep = 'none';
+    matlabbatch{3}.spm.stats.con.delete = 1;
+       
+      if pupille==1
+            matlabbatch{3}.spm.stats.con.consess{4}.tcon.name = 'pupil_reg' ;
+            matlabbatch{3}.spm.stats.con.consess{4}.tcon.weights = [zeros(1,14) 1];
+            matlabbatch{3}.spm.stats.con.consess{4}.tcon.sessrep = 'none';
+            matlabbatch{3}.spm.stats.con.delete
+        end    
+        %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+        spm_jobman('run', matlabbatch) % run batch
+        
+        
+    elseif mod==1 % Lightmod
+    clear matlabbatch
+    spm_jobman('initcfg') ;
+    
+    matlabbatch{1}.spm.stats.fmri_spec.dir = {output_emo};
+    matlabbatch{1}.spm.stats.fmri_spec.timing.units = 'scans';
+    matlabbatch{1}.spm.stats.fmri_spec.timing.RT = 2.34;
+    matlabbatch{1}.spm.stats.fmri_spec.timing.fmri_t = 16;
+    matlabbatch{1}.spm.stats.fmri_spec.timing.fmri_t0 = 8;
+    matlabbatch{1}.spm.stats.fmri_spec.sess.scans = preprocessed_nifti ;
+    matlabbatch{1}.spm.stats.fmri_spec.sess.cond = struct('name', {}, 'onset', {}, 'duration', {}, 'tmod', {}, 'pmod', {}, 'orth', {});
+    matlabbatch{1}.spm.stats.fmri_spec.sess.multi = {onset_emo} ;
+    matlabbatch{1}.spm.stats.fmri_spec.sess.regress = struct('name', {}, 'val', {});
+    matlabbatch{1}.spm.stats.fmri_spec.sess.multi_reg = {pupil_emo};
+    matlabbatch{1}.spm.stats.fmri_spec.sess.hpf = 256;
+    matlabbatch{1}.spm.stats.fmri_spec.fact = struct('name', {}, 'levels', {});
+    matlabbatch{1}.spm.stats.fmri_spec.bases.hrf.derivs = [0 0];
+    matlabbatch{1}.spm.stats.fmri_spec.volt = 1;
+    matlabbatch{1}.spm.stats.fmri_spec.global = 'None';
+    matlabbatch{1}.spm.stats.fmri_spec.mthresh = -inf;
+    matlabbatch{1}.spm.stats.fmri_spec.mask = {''};
+    matlabbatch{1}.spm.stats.fmri_spec.cvi = 'AR(1)';
+    matlabbatch{2}.spm.stats.fmri_est.spmmat(1) = cfg_dep('fMRI model 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;
+    
+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+    %creation of contrasts
+     matlabbatch{3}.spm.stats.con.spmmat(1) = cfg_dep('Model estimation: SPM.mat File', substruct('.','val', '{}',{2}, '.','val', '{}',{1}, '.','val', '{}',{1}), substruct('.','spmmat'));
+     matlabbatch{3}.spm.stats.con.consess{1}.tcon.name = 'Emo';
+     matlabbatch{3}.spm.stats.con.consess{1}.tcon.weights = [1];
+     matlabbatch{3}.spm.stats.con.consess{1}.tcon.sessrep = 'none';
+     matlabbatch{3}.spm.stats.con.delete = 1;
+        
+     matlabbatch{3}.spm.stats.con.consess{2}.tcon.name = 'Neut';
+     matlabbatch{3}.spm.stats.con.consess{2}.tcon.weights = [0 0 1];
+     matlabbatch{3}.spm.stats.con.consess{2}.tcon.sessrep = 'none';
+     matlabbatch{3}.spm.stats.con.delete = 1;
+%     
+     matlabbatch{3}.spm.stats.con.consess{3}.tcon.name = 'Emo_M';
+     matlabbatch{3}.spm.stats.con.consess{3}.tcon.weights = [0 1];
+     matlabbatch{3}.spm.stats.con.consess{3}.tcon.sessrep = 'none';
+     matlabbatch{3}.spm.stats.con.delete = 1;
+    
+     matlabbatch{3}.spm.stats.con.consess{4}.tcon.name = 'Neut_M';
+     matlabbatch{3}.spm.stats.con.consess{4}.tcon.weights = [0 0 0 1];
+     matlabbatch{3}.spm.stats.con.consess{4}.tcon.sessrep = 'none';
+     matlabbatch{3}.spm.stats.con.delete = 1;
+%     
+     matlabbatch{3}.spm.stats.con.consess{5}.tcon.name = 'Emo-Neut';
+     matlabbatch{3}.spm.stats.con.consess{5}.tcon.weights = [1 0 -1];
+     matlabbatch{3}.spm.stats.con.consess{5}.tcon.sessrep = 'none';
+     matlabbatch{3}.spm.stats.con.delete = 1;
+        
+     matlabbatch{3}.spm.stats.con.consess{6}.tcon.name = 'Emo_M-Neut_M';
+     matlabbatch{3}.spm.stats.con.consess{6}.tcon.weights = [0 1 0 -1];
+     matlabbatch{3}.spm.stats.con.consess{6}.tcon.sessrep = 'none';
+     matlabbatch{3}.spm.stats.con.delete = 1;   
+     
+     matlabbatch{3}.spm.stats.con.consess{7}.tcon.name = 'Emo_M_plus_Neut_M';
+     matlabbatch{3}.spm.stats.con.consess{7}.tcon.weights = [0 1 0 1];
+     matlabbatch{3}.spm.stats.con.consess{7}.tcon.sessrep = 'none';
+     matlabbatch{3}.spm.stats.con.delete = 1;  
+     
+        if pupille==1
+            matlabbatch{3}.spm.stats.con.consess{8}.tcon.name = 'pupil_reg' ;
+            matlabbatch{3}.spm.stats.con.consess{8}.tcon.weights = [zeros(1,14) 1];
+            matlabbatch{3}.spm.stats.con.consess{8}.tcon.sessrep = 'none';
+            matlabbatch{3}.spm.stats.con.delete
+        end    
+        %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+        spm_jobman('run', matlabbatch) % run batch
+     
+    
+    end
+
+    %%
+% Coregistration of statistical maps to the template ans MNI spaces.
+
+    input1= paths.ANTs ;
+    input2= char([paths.data '/' char(subs_info(id)) '/MRI' '/output_preprocessing' '/emo']) ; 
+     input3= char([paths.data '/sub-' subject_ID '/ses-struct/MRI/output_preprocessing/mp2rage_UNI']);
+    input4= paths.template;
+    input5= output_emo ;
+    
+    PathToScript= [paths.bash '/Coreg_Stat.sh'];
+    cmdStr=[PathToScript ' ' input1 ' ' input2 ' ' input3 ' ' input4 ' ' input5];
+    system(cmdStr)
+    
+end
+end
+    
+    
\ No newline at end of file