Abnormal dynamic features of cortical microstates for detecting early-stage Parkinson's disease by resting-state electroencephalography: Systematic analysis of the influence of eye condition

Resting state electroencephalography (EEG) has proved useful in studying electrophysiological changes in neurodegenerative diseases. In many neuropathologies, microstate analysis of the eyes-closed (EC) scalp EEG is a robust and highly reproducible technique for assessing topological changes with high temporal resolution. However, scalp EEG microstate maps tend to underestimate the non-occipital or non-alpha-band networks, which can also be used to detect neuropathological changes. Recent evidence has shown that the source-space microstates can characterize distinct functional connectivity patterns but its clinical ability to detect neuropathological changes has not been demonstrated so far. It should also be remembered that the eye condition may play an important role in neural activity dynamics. The aim of this study was to systematically characterize the dynamic neuropathological features of sensor-space and source-space EEG microstates in PD patients with no cognitive impairment in both EC and EO conditions with the aim of identifying potential biomarkers that could be used as a complementary clinical screening method for early PD detection. We found that the dynamic features of the source-space microstates were more sensitive in detecting PD than the sensor-space microstates, while EO was able to detect neuropathological changes in PD patients better than EC. In EO, PD disease exhibited significantly higher occurrence and coverage in visual-network related source-space microstates and abnormally high duration in sensorimotor network-related microstates. Our results suggest that the source-space microstate analysis of resting-state EEG could provide robust biomarkers to detect early-stage PD, which would allow the development of patient-oriented strategies to prevent the disease and improve the patients' quality of life.