The relationship between EEG and fMRI connectomes is reproducible across simultaneous EEG-fMRI studies from 1.5T to 7T

Connectome dataset for the publication: 'The relationship between EEG and fMRI connectomes is reproducible across simultaneous EEG-fMRI studies from 1.5T to 7T'
Wirsich et al. 2021, NeuroImage, doi: 10.1016/j.neuroimage.2021.117864

Data description

eeg-fmri_connectomes_$atlas$_scrubbed_$dataset$.mat
datasets with filename truncTo4min58_5s hold static connectivities based on timeseries truncated
to 4min58.5s. All other datasets are based on static connectivities derived from the total session
timeseries.

subj: subject
subj.name: name of the subject
subj.sess: session
subj.sess.sess_name: name of the session
subj.sess.fMRI: vector of upper triangular of fMRI connectivity
subj.sess.EEG: EEG connectomes
subj.sess.EEG.name: name of connectivity measure used (imaginary part of the coherency: iCoh,
amplitude envelope correlation (orthongonaliyzed): hilb_Ortho, Amplitude envelope correlation
(not orthongonaliyzed): hilb_noOrtho)
subj.sess.EEG.bands: EEG frequency bands
subj.sess.EEG.bands.name: name of frequency band (delta, theta, alpha, beta, gamma)
subj.sess.EEG.bands.name.conn: vector of upper triangular of EEG connectivity
subj.atlas: Atlas
subj.atlas.name: name of atlas used (Desikan or Destrieux)
subj.atlas.regions: number of regions

Use the following code to convert connectivity vectors to a connectivity matrix for atlas(1):

regions = length(atlas(1).labels)
mrtx = zeros(regions);
count = 1;
for r1 = 1:regions-1
 for r2 = r1+1:regions
  mrtx(r1, r2) = subj.sess.fMRI(count);
  mrtx(r2, r1) = mrtx(r1, r2);
  count = count + 1;
 end
end

atlas_labels.mat

atlas.name: atlas Name

atlas.labels: labels of each atlas region