Distinct sources of resting-state EEG microstates in amyotrophic lateral sclerosis

Abstract

Abstract Brain microstates are a well-established method for the dynamic analysis of resting-state electroencephalogram (EEG). We observed four quasi-stable, transient and reoccurring resting-state topographies in the high density EEG data (128 electrodes, 3x2 min recording blocks). The four microstates were reliably observed across conditions: individuals with Amyotrophic lateral sclerosis (ALS) (n = 99) versus age-matched healthy controls (HC, n = 78). To improve the understanding of the neural mechanisms underlying microstates, we estimated the sources of microstates topographies. A general linear model was applied to predict the microstate sequence based on EEG-estimated source space time courses. High reproducibility across participants of influential brain sources led to the identification of four microstate specific networks. Some brain regions contributed to several microstate networks, which may indicate that these regions (including the precuneus, the superior frontal gyrus and the hippocampus) are functional neuronal ‘hubs’ of connection. Additionally, distinct source patterns were observed between ALS patients and healthy controls, highlighting potential functional changes in the brain networks in ALS.