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fMRI_analysis.m
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fMRI_analysis.m
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cosmomvpaToolboxRoot = '~/lib/MATLAB/CoSMoMVPA/'; addpath(genpath(cosmomvpaToolboxRoot));
subjects = {'1606'};
conditions = {'BF_Happy' 'BF_Fear' 'BF_Neu' 'FR_Happy' 'FR_Fear' 'FR_Neu' 'STR_Happy' 'STR_Fear' 'STR_Neu'};
nr_subjects = length(subjects);
nr_conditions = length(conditions);
study_path = 'fMRI_zmaps';
% output_path =
for currSubject = 1 : nr_subjects
for currCondition = 1 : nr_conditions
currFilename = fullfile(study_path, strcat(subjects{currSubject}, '_', conditions{currCondition}, '.nii'));
if (currCondition == 1)
fMRI_dataset = cosmo_fmri_dataset(currFilename, 'mask', false);
else
fMRI_dataset = cosmo_stack({fMRI_dataset, cosmo_fmri_dataset(currFilename, 'mask', false)}, 1);
end
% fMRI_dataset(currCondition,currSubject) = fMRI_data;
end
fMRI_dataset.sa.targets = (1 : nr_conditions)';
fMRI_dataset.sa.chunks = ones(nr_conditions, 1);
% fMRI_dataset.sa.targets = repelem(1 : nr_conditions, 400000)';
% dsm1=cosmo_squareform(cosmo_pdist(fMRI_dataset.samples, 'correlation'))
dsm = cosmo_dissimilarity_matrix_measure(fMRI_dataset, 'metric', 'spearman');
fMRI_dsm(:,:,currSubject) = cosmo_squareform(dsm.samples);
end