Feasibility of Reconstructing Source Functional Connectivity with Low-Density EEG

Objectives Functional connectivity (FC) is increasingly used as target for neuromodulation and enhancement of performance. A reliable assessment of FC with electroencephalography (EEG) currently requires a laboratory environment with high-density montages and a long preparation time. This study investigated the feasibility of reconstructing source FC with a low-density EEG montage towards a usage in real life applications. Methods Source FC was reconstructed with inverse solutions and quantified as node degree of absolute imaginary coherence in alpha frequencies. We used simulated coherent point sources as well as two real datasets to investigate the impact of electrode density (19 vs. 128 electrodes) and usage of template vs. individual MRI-based head models on localization accuracy. In addition, we checked whether low-density EEG is able to capture inter-individual variations in coherence strength. Results In numerical simulations as well as real data, a reduction of the number of electrodes led to less reliable reconstructions of coherent sources and of coupling strength. Yet, when comparing different approaches to reconstructing FC from 19 electrodes, source FC obtained with beamformers outperformed sensor FC, FC computed after independent component analysis, and source FC obtained with sLORETA. In particular, only source FC based on beamformers was able to capture neural correlates of motor behavior. Conclusion Reconstructions of FC from low-density EEG is challenging, but may be feasible when using source reconstructions with beamformers.

Automated summary

Functional connectivity (FC) assessment with EEG currently requires high-density montages and long preparation time. This study investigated reconstructing source FC with a low-density EEG montage, finding that beamformers outperformed other methods in capturing neural correlates of motor behavior.