**Data description**
EEG and fMRI connectomes are derived from two independent datasets acquired from two different sites. The main dataset consisted
of 26 healthy subjects with 3 runs of 10 minutes of concurrent EEG-fMRI during task-free restingstate (Sadaghiani et al., 2010). The generalization dataset consisted of 14 subjects, 20 minutes
resting-state runs of concurrent EEG-fMRI (Wirsich et al., 2017). The data was used to extract the
main joint independent components co-occurring during EEG-fMRI resting-state. For details see [(Wirsich et al. 2020)][1].
**Usage**
Use
vec = connICA.connICA_matrixfMRI(subjno, :);
matrix=vec(triu(true(148,148),1));
to unpack connectivity vector of subject 'subjno' to a connectivity matrix.
The here saved vectors can be directly used with the connICA toolbox (https://engineering.purdue.edu/ConnplexityLab/publications/connICA_toolbox_v1.1.tar.gz)
**Bibliography**
Associated publication:
Wirsich, J., Amico, E., Giraud A.L. Goñi, J, Sadaghiani S.,2020 Multi-timescale hybrid components of the functional brain connectome: A bimodal EEG-fMRI decomposition, Netw Neurosci (just accepted), https://doi.org/10.1162/netn_a_00135
See also:
Amico, E., Goñi, J., 2018. Mapping hybrid functional-structural connectivity traits in the human connectome. Netw Neurosci 2, 306–322. https://doi.org/10.1162/netn_a_00049
Amico, E., Goñi, J., 2018. The quest for identifiability in human functional connectomes. Sci Rep 8, 1–14. https://doi.org/10.1038/s41598-018-25089-1
Sadaghiani, S., Scheeringa, R., Lehongre, K., Morillon, B., Giraud, A.-L., Kleinschmidt, A., 2010. Intrinsic connectivity networks, alpha oscillations, and tonic alertness: a simultaneous electroencephalography/functional magnetic resonance imaging study. J. Neurosci. 30, 10243–10250. https://doi.org/10.1523/JNEUROSCI.1004-10.2010
Wirsich, J., Ridley, B., Besson, P., Jirsa, V., Bénar, C., Ranjeva, J.-P., Guye, M., 2017 Complementary contributions of concurrent EEG and fMRI connectivity for predicting structural connectivity. NeuroImage 161, 251–260. https://doi.org/10.1016/j.neuroimage.2017.08.055
[1]: https://www.mitpressjournals.org/doi/abs/10.1162/netn_a_00135 "(Wirsich et al. 2020)"
