Removing zero-lag functional connections can alter EEG source space networks at rest

Abstract

Electro-encephalography (EEG) source connectivity is an emerging approach to estimate brain networks with high time/space resolution. Here, we aim to evaluate the effect of different functional connectivity (FC) methods on the EEG-source space networks at rest. The two main families of FC methods tested are: i) the FC methods that do not remove the zero-lag connectivity including the Phase Locking Value (PLV) and the Amplitude Envelope Correlation (AEC) and ii) the FC methods that remove the zero-lag connections such as the Phase Lag Index (PLI) and orthogonalisation approach combined with PLV (PLVorth) and AEC (AECorth). Methods are evaluated on resting state dense-EEG signals recorded from 20 healthy participants. Networks obtained by each FC method are compared with fMRI networks at rest (from the Human Connectome Project -HCP-, N=487). Results show low correlations for all the FC methods, however PLV and AEC networks are significantly correlated with fMRI networks ({rho} = 0.12, p = 1.93x10-8 and {rho} = 0.06, p = 0.007, respectively), while other methods are not. These observations are consistent for each EEG frequency bands and for different FC matrices threshold. Furthermore, the effect of electrode density was also tested using four EEG montages (dense-EEG 256 electrodes, 128, 64 and 32 electrodes). Results show no significant differences between the four EEG montages in terms of correlations with the fMRI networks. Our main message here is to be careful when selecting the FC methods and mainly those that remove the zero-lag connections as they can affect the network characteristics. More comparative studies (based on simulation and real data) are still needed in order to make EEG source connectivity a mature technique to address questions in cognitive and clinical neuroscience.