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B_conn.m
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B_conn.m
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% Run denoising with the CONN
% see help conn_batch
% Notes: denoises ALL available functional scans. Some scans will be
% excluded in the next step
% directories
codeDir = fileparts(mfilename('fullpath')); % where this script is located
camcanDir = fileparts(codeDir);
fmriprepDir = fullfile(camcanDir, 'derivatives', 'fmriprep');
rawdataDir = fullfile(camcanDir, 'rawdata');
atlasDir = fullfile(codeDir, 'atlas');
ritcheyDir = fullfile(codeDir, 'Ritcheyetal2015_ROIs');
% software
spm = fullfile(codeDir, 'spm12');
conn = fullfile(codeDir, 'conn');
addpath(spm, conn);
%% Filename and parallel processing options
BATCH.filename = fullfile(camcanDir, 'derivatives', 'conn_gsr', 'conn_gsr.mat');
BATCH.parallel.N = 243;
BATCH.parallel.profile = 'Slurm computer cluster';
%% Setup
% We first need to setup a conn project
BATCH.Setup.isnew = 1;
BATCH.Setup.done = 1;
BATCH.Setup.overwrite = 1;
% how many subjects?
subjects = spm_select('List', fmriprepDir, 'dir', 'sub-CC[0-9]{6}');
subjects = cellstr(subjects);
BATCH.Setup.nsubjects = length(subjects);
BATCH.Setup.RT = NaN;
BATCH.Setup.acquisitiontype = 1;
% functionals
scans_vec = nan(1,length(subjects));
for nsub = 1:length(subjects)
csub_dir = fullfile(fmriprepDir, subjects{nsub}, 'func');
scans = spm_select('FPList', csub_dir, '^sub.*desc-preproc_bold\.nii$');
scans = cellstr(scans);
scans_vec(nsub) = length(scans);
for nses = 1:length(scans)
BATCH.Setup.functionals{nsub}{nses} = scans{nses};
end
end
% anatomicals
for nsub = 1:length(subjects)
csub_dir = fullfile(fmriprepDir, subjects{nsub}, 'anat');
scan = spm_select('FPList', csub_dir, '^sub.*space-MNI.*desc-preproc_T1w\.nii$');
BATCH.Setup.structurals{nsub} = scan;
end
BATCH.Setup.add = 0;
% masks
for nsub = 1:length(subjects)
csub_dir = fullfile(fmriprepDir, subjects{nsub}, 'anat');
grey = spm_select('FPList', csub_dir, '^sub.*space-MNI.*label-GM.*\.nii$');
BATCH.Setup.masks.Grey{nsub} = grey;
white = spm_select('FPList', csub_dir, '^sub.*space-MNI.*label-WM.*\.nii$');
BATCH.Setup.masks.White{nsub} = white;
csf = spm_select('FPList', csub_dir, '^sub.*space-MNI.*label-CSF.*\.nii$');
BATCH.Setup.masks.CSF{nsub} = csf;
end
% ROIs
roiNum = 1;
BATCH.Setup.rois.names{roiNum} = 'Schaefer Atlas';
schaferAtlasFile = fullfile(atlasDir, 'Parcellations', 'MNI', 'rSchaefer2018_400Parcels_17Networks_order_FSLMNI152_2mm.nii');
BATCH.Setup.rois.files{roiNum} = schaferAtlasFile;
BATCH.Setup.rois.dimensions{roiNum} = 1;
BATCH.Setup.rois.weighted(roiNum) = 0;
BATCH.Setup.rois.multiplelabels(roiNum) = 1;
BATCH.Setup.rois.mask(roiNum) = 0;
BATCH.Setup.rois.regresscovariates(roiNum) = 0;
BATCH.Setup.rois.dataset(roiNum) = 0;
roiNum = 2;
BATCH.Setup.rois.names{roiNum} = 'HIPP_BODY_L';
BATCH.Setup.rois.files{roiNum} = fullfile(ritcheyDir, 'rHIPP_BODY_L_mask.nii');
BATCH.Setup.rois.dimensions{roiNum} = 1;
BATCH.Setup.rois.weighted(roiNum) = 0;
BATCH.Setup.rois.multiplelabels(roiNum) = 0;
BATCH.Setup.rois.mask(roiNum) = 0;
BATCH.Setup.rois.regresscovariates(roiNum) = 0;
BATCH.Setup.rois.dataset(roiNum) = 0;
roiNum = 3;
BATCH.Setup.rois.names{roiNum} = 'HIPP_BODY_R';
BATCH.Setup.rois.files{roiNum} = fullfile(ritcheyDir, 'rHIPP_BODY_R_mask.nii');
BATCH.Setup.rois.dimensions{roiNum} = 1;
BATCH.Setup.rois.weighted(roiNum) = 0;
BATCH.Setup.rois.multiplelabels(roiNum) = 0;
BATCH.Setup.rois.mask(roiNum) = 0;
BATCH.Setup.rois.regresscovariates(roiNum) = 0;
BATCH.Setup.rois.dataset(roiNum) = 0;
roiNum = 4;
BATCH.Setup.rois.names{roiNum} = 'HIPP_HEAD_L';
BATCH.Setup.rois.files{roiNum} = fullfile(ritcheyDir, 'rHIPP_HEAD_L_mask.nii');
BATCH.Setup.rois.dimensions{roiNum} = 1;
BATCH.Setup.rois.weighted(roiNum) = 0;
BATCH.Setup.rois.multiplelabels(roiNum) = 0;
BATCH.Setup.rois.mask(roiNum) = 0;
BATCH.Setup.rois.regresscovariates(roiNum) = 0;
BATCH.Setup.rois.dataset(roiNum) = 0;
roiNum = 5;
BATCH.Setup.rois.names{roiNum} = 'HIPP_HEAD_R';
BATCH.Setup.rois.files{roiNum} = fullfile(ritcheyDir, 'rHIPP_HEAD_R_mask.nii');
BATCH.Setup.rois.dimensions{roiNum} = 1;
BATCH.Setup.rois.weighted(roiNum) = 0;
BATCH.Setup.rois.multiplelabels(roiNum) = 0;
BATCH.Setup.rois.mask(roiNum) = 0;
BATCH.Setup.rois.regresscovariates(roiNum) = 0;
BATCH.Setup.rois.dataset(roiNum) = 0;
roiNum = 6;
BATCH.Setup.rois.names{roiNum} = 'HIPP_TAIL_L';
BATCH.Setup.rois.files{roiNum} = fullfile(ritcheyDir, 'rHIPP_TAIL_L_mask.nii');
BATCH.Setup.rois.dimensions{roiNum} = 1;
BATCH.Setup.rois.weighted(roiNum) = 0;
BATCH.Setup.rois.multiplelabels(roiNum) = 0;
BATCH.Setup.rois.mask(roiNum) = 0;
BATCH.Setup.rois.regresscovariates(roiNum) = 0;
BATCH.Setup.rois.dataset(roiNum) = 0;
roiNum = 7;
BATCH.Setup.rois.names{roiNum} = 'HIPP_TAIL_R';
BATCH.Setup.rois.files{roiNum} = fullfile(ritcheyDir, 'rHIPP_TAIL_R_mask.nii');
BATCH.Setup.rois.dimensions{roiNum} = 1;
BATCH.Setup.rois.weighted(roiNum) = 0;
BATCH.Setup.rois.multiplelabels(roiNum) = 0;
BATCH.Setup.rois.mask(roiNum) = 0;
BATCH.Setup.rois.regresscovariates(roiNum) = 0;
BATCH.Setup.rois.dataset(roiNum) = 0;
BATCH.Setup.rois.add = 0;
% conditions
BATCH.Setup.conditions.missingdata = 1;
%BATCH.Setup.conditions.model{} = ; % optional
BATCH.Setup.conditions.importfile = fullfile(camcanDir, 'derivatives', 'conditions', 'conditions.csv');
%BATCH.Setup.conditions.importfile_options = ; % optional
BATCH.Setup.conditions.add = 0;
% covariates
BATCH.Setup.covariates.names{1} = 'standard';
for nsub = 1:length(subjects)
csub_dir = fullfile(camcanDir, 'derivatives', 'covariates_gsr');
regExp = sprintf('%s.*_standard_motion.txt', subjects{nsub});
covFiles = spm_select('FPList', csub_dir, regExp);
covFiles = cellstr(covFiles);
for nses = 1:length(covFiles)
BATCH.Setup.covariates.files{1}{nsub}{nses} = covFiles{nses};
end
end
BATCH.Setup.covariates.add = 0;
BATCH.Setup.analyses = 1;
BATCH.Setup.voxelmask = 2;
%BATCH.Setup.voxelmaskfile = ;
BATCH.Setup.voxelresolution = 3;
BATCH.Setup.analysisunits = 2;
BATCH.Setup.outputfiles = [0 0 0 0 0 0];
%BATCH.Setup.spmfiles = ;
%BATCH.Setup.spmfiles_options = ;
%BATCH.Setup.vdm_functionals = ;
%BATCH.Setup.fmap_functionals = ;
%BATCH.Setup.coregsource_functionals = ;
BATCH.Setup.localcopy = 0;
%BATCH.Setup.binary_threshold = ; % default, unneeded
%BATCH.Setup.binary_threshold_type = ;
%BATCH.Setup.exclude_grey_matter = ;
%BATCH.Setup.erosion_steps = ;
%BATCH.Setup.erosion_neighb = ;
%% Denoising
BATCH.Denoising.done = 1;
BATCH.Denoising.overwrite = 1;
BATCH.Denoising.filter = [0.008, 0.1];
BATCH.Denoising.detrending = 1;
BATCH.Denoising.despiking = 0;
BATCH.Denoising.regbp = 1;
BATCH.Denoising.confounds.names = {'standard', 'Effect of AudOnly', 'Effect of AudVid1200', 'Effect of AudVid300', 'Effect of AudVid600', 'Effect of VidOnly'};
BATCH.Denoising.confounds.dimensions = repmat({Inf}, 1, 6);
BATCH.Denoising.confounds.deriv = repmat({0}, 1, 6);
BATCH.Denoising.confounds.power = repmat({1}, 1, 6);
BATCH.Denoising.confounds.filter = repmat({0}, 1, 6);
%% First Level Analysis
BATCH.Analysis.done = 1;
BATCH.Analysis.overwrite = 1;
BATCH.Analysis.name = 'Analysis';
BATCH.Analysis.measure = 1;
BATCH.Analysis.weight = 1;
BATCH.Analysis.modulation = 0;
%BATCH.Analysis.conditions = ;
BATCH.Analysis.type = 1;
%BATCH.sources = ;
conn_batch(BATCH);