Analysis of Brain Functional Network Based on EEG Signals for Early-Stage Parkinson’s Disease Detection

Abstract

The early diagnosis of Parkinson’s disease (PD) has always been a difficult problem to be solved clinically. At present, there is no clinical auxiliary diagnostic index for reference. We attempted to extract potential biomarkers for early PD from the currently used scalp EEG detection methods in clinical practice. We calculated the phase synchronization index to quantify the synchrony of EEG channels in various frequency bands (delta, theta, alpha and beta bands) of early PD. The results showed that the synchronization of early PD in the delta band was significantly lower than the healthy level, and the brain region reflecting the lower synchronization was located in the temporal lobe, the posterior temporal lobe, the parietal lobe (the posterior center) and the occipital lobe. Moreover, this lower synchronicity is consistent with weaker brain functional connections. Besides, by constructing functional brain network, the graph theoretic topological features of each frequency band of early PD are presented. We have found that early PD has characteristics of small world network in the delta and beta bands, and functional integration and separation characteristics of brain network in early PD are significantly abnormal in the delta, theta, alpha and beta bands. These results indicate that early PD has significant pathological changes from the perspective of brain function network analysis, and its characteristics can be described by multiple features, which may provide auxiliary guidance for the clinical diagnosis of early PD, and also provide theoretical support for the brain function changes of early PD.

Keywords

• Parkinson’s disease
• brain functional network
• frequency variability