CONN module help

conn_module

provides access to independent CONN modules conn_module(module_name, ...) runs individual CONN's module "module_name" on user-defined data
Current module names: PREPROCESSING, GLM

PREPROCESSING : runs CONN preprocessing pipeline on user-defined data

         Basic syntax
            conn_module preprocessing;          Advanced syntax:
            conn_module('preprocessing', fieldname1, fieldvalue1 , fieldname2, fieldvalue2, ...)
                Input data is specified with field name/value pairs as defined in Setup conn_batch documentation                Preprocessing options are specified with field name/value pairs as defined in Setup.preprocessing conn_batch documentation (all Setup.preprocessing fields are available to conn_module)
                   functionals : list of functional data files for each subject and session { { Sub1Ses1, Sub1Ses2, ...}, {Sub2Ses1, Sub2Ses2, ...}, ...}
                   structurals : list of structural data files { Sub1, Sub2, ...}
                   steps : list of preprocessing steps (tpye "conn_module preprocessing steps" for a list of valid preprocessing step names)
                See "doc conn_batch" for a complete list of all preprocessing options        See Nieto-Castanon, 2020 for details about these preprocessing steps and pipelines (www.conn-toolbox.org/fmri-methods)

        Alternative syntax:
            conn_module('preprocessing',optionsfile)
              Input data and preprocessing options defined in .cfg (see conn_loadcfgfile/conn_savecfgfile) or .json (see spm_jsonread/spm_jsonwrite) structure text file          Alternative syntax:
            conn_module preprocessing steps
              Returns full list of valid preprocessing steps

Example #1: to run user-selected preprocessing pipeline or steps on the specified functional/structural data
          conn_module( 'preprocessing' , ...              'functionals', {{ '/data/func.nii' }} , ...              'structurals', { '/data/anat.nii' } , ...              'steps', '' );
Example #2: to run CONN's default minimal preprocessing pipeline on the specified functional/structural data (modify/add parameters below according to your data)
          conn_module( 'preprocessing',...              'functionals', {{ '/data/func.nii' }},...              'structurals', { '/data/anat.nii' },...              'steps', 'default_mni',...              'RT', 2,...              'sliceorder',' interleaved (Siemens)');
Example #3: to run CONN's default minimal preprocessing pipeline + default denoising pipeline on the specified functional/structural data (modify/add parameters below according to your data)
         conn_module( 'preprocessing', ...             'functionals', {{ '/data/func.nii' }}, ...             'structurals', { '/data/anat.nii' }, ...             'steps', {'default_mni', 'functional_regression', 'functional_bandpass'}, ...             'reg_names', {'realignment', 'scrubbing', 'White Matter', 'CSF'}, ...             'reg_dimensions', [inf, inf, 5, 5], ...             'reg_deriv', [1, 0, 0, 0], ...             'bp_filter', [0.008 inf] )

see also: CONN_BATCH

GLM : runs CONN second-level analyses on user-defined data

        Basic syntax:
           conn_module glm;
        Advanced syntax:
           conn_module('glm', fieldname1, fieldvalue1, fieldname2, fieldvalue2, ...)
                with the following field name/value pairs:
                   data : list of NIFTI files entered into second-level analysis (Nsubjects x Nmeasures) defining one or multiple outcome / dependent measures                                         note: when entering multiple files per subject (e.g. repeated measures) enter first all files (one per subject) for measure#1, followed by all files for measure#2, etc.                                        note: nifti files may contani 3d volume-level data, fsaverage surface-level data, or ROI-to-ROI data (see conn_surf_write and conn_mtx_write to create surface/matrix nifti files)                                     alternatively list of SPM.mat files containing first-level analyses (Nsubjects x 1, or Nsubjects x Nmeasures)                                     alternatively list of folder names containing SPM.mat first-level analyses (Nsubjects x 1, or Nsubjects x Nmeasures)
                   design_matrix : design matrix (Nsubjects x Neffects) defining different explanatory / independent measures or subject-effects                                         enter one row for each subject                                        each row should contain one value/number per modeled effect/covariate
                   contrast_between: between-subjects contrast vector/matrix (Nc1 x Neffects)
                   contrast_within : within-subjects contrast vector/matrix (Nc2 x Nmeasures)
                   contrast_names : (optional, only when entering SPM.mat files in #data field) list of contrast names to select from first-level analysis files (Nmeasures x 1)
                   data_labels : (optional) labels of columns of data matrix
                   design_labels : (optional) labels of columns of design matrix
                   mask : (optional) analysis mask file
                   analysistype : (optional) analysis type 1: include both parametric and non-parametric stats; 2: include only parametric stats; 3: include only non-parametric stats
                   design : (optional, for back-compatibility) transpose of design_matrix (Neffects x Nsubjects); enter one row for each modeled effect (across subjects); each row should contain one value/number per subject
                   folder : (optional) folder where analysis are stored; default current folder
        Alternative syntax:
           conn_module('glm',optionsfile)
               input data and GLM options defined in .cfg (see conn_loadcfgfile/conn_savecfgfile) or .json (see spm_jsonread/spm_jsonwrite) structure text file          Alternative syntax:
           spmfolder=conn_module('glm',...)
              skips results display step (only computes second-level analysis, and returns folder where results are stored)              use conn_display(spmfolder) syntax to then launch the results explorer window on previously computed analyses
          See also "doc conn_display" for displaying GLM results          See Nieto-Castanon, 2020 for details about General Linear Model analyses (www.conn-toolbox.org/fmri-methods)

Example #1: performs user-defined second-level analysis
          conn_module glm;

Example #2: performs a one-sample t-test and stores the analysis results in the current folder
          conn_module('glm', ...             'design_matrix',[1; 1; 1; 1] ,...             'data',{'subject1.img'; 'subject2.img'; 'subject3.img'; 'subject4.img'} );
        Example #3: performs a two-sample t-test and stores the analysis results in the current folder
           conn_module('glm', ...             'design_matrix',[1 0; 1 0; 0 1; 0 1; 0 1],...             'data', {'subject1_group1.img'; 'subject2_group1.img'; 'subject1_group2.img'; 'subject2_group2.img'; 'subject3_group2.img'},...             'contrast_between',[1 -1]);
              Example #4: performs a paired t-test and stores the analysis results in the current folder
           conn_module('glm', ...             'design_matrix', [1; 1; 1; 1],...             'data', {'subject1_time1.img', subject1_time2.img'; 'subject2_time1.img', subject2_time2.img'; 'subject3_time1.img', subject3_time2.img'; 'subject4_time1.img', subject4_time2.img'},...             'contrast_beetween',1,...             'contrast_within',[1 -1]);

Additional functionality: conn_module('get', 'structurals'); outputs current structural files (e.g. output of structural preprocessing steps) conn_module('get', 'functionals'); outputs current functional files (e.g. output of functional preprocessing steps) conn_module('get', 'l1covariates'); outputs first-level covariate files (e.g. other potential outputs of functional preprocessing) conn_module('get', 'l1covariates',covname); outputs covname first-level covariate files (e.g. other potential outputs of functional preprocessing) conn_module('get', 'l2covariates'); outputs second-level covariate files (e.g. other potential outputs of functional preprocessing) conn_module('get', 'l2covariates',covname); outputs covname second-level covariate files (e.g. other potential outputs of functional preprocessing) conn_module('get', 'masks'); outputs Grey Matter/White Matter/CSF files (e.g. other potential outputs of functional preprocessing) conn_module('get', 'masks',roiname); outputs roiname files (e.g. other potential outputs of functional preprocessing)