Resting-state networks (RSNs) have been identified on continuous source-reconstructed EEG data (electrical source imaging; EEG-ESI data), but their validation with simultaneous fMRI data is missing. Here, we found a comparable overlap with previous literature between EEG-ESI-derived RSNs and simultaneous fMRI-derived RSNs from 10 subjects. We showed the ability of EEG-ESI to map the task-specific facial expression processing network, and extracted dynamic functional connectivity (dFC) states from EEG-ESI and fMRI, founding a significant match between them. Our results push the limits of EEG towards being used as an imaging tool and support the existence of EEG correlates of fMRI-derived (d)FC.
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