Spatial (Mis)match Between EEG and fMRI Signal Patterns Revealed by Spatio-Spectral Source-Space EEG Decomposition
In this work, we aimed to directly compare and integrate EEG whole-brain patterns of neural dynamics with concurrently measured fMRI BOLD data. For that purpose, we set out to derive EEG patterns based on a spatio-spectral decomposition of band-limited EEG power in the source-reconstructed space. On a large data set of 72 subjects resting-state hdEEG-fMRI we showed that the proposed approach is reliable both in terms of the extracted patterns as well as their spatial BOLD signatures. The five most robust EEG spatio-spectral patterns include, but go beyond, the well-known occipital alpha power dynamics. The EEG spatial-spectral patterns show relatively weak, yet statistically significant spatial similarity to their fMRI BOLD signatures, particularly the patterns that show stronger temporal synchronization with BOLD. However, we observed an insignificant relation between the temporal synchronization and spatial overlap of the EEG spatio-spectral patterns and the classical fMRI BOLD resting state networks (as obtained by independent component analysis). This provides evidence that both EEG (frequency-specific) power and BOLD signal capture reproducible spatiotemporal patterns of neural dynamics. Rather than being mutually redundant, these are only partially overlapping, carrying to a large extent complementary information concerning the underlying low-frequency dynamics. Finally, we report and interpret the most stable source space EEG-fMRI patterns, along with the corresponding EEG electrode space patterns better known from the literature.