Early detection of Parkinson’s disease based on beta dynamic features and beta-gamma coupling from non-invasive resting state EEG: Influence of the eyes

作者：G. Gimenez-Aparisi, Enrique Guijarro-Estellés, A. Chornet-Lurbe, M. Diaz-Roman, Dongmei Hao, Guangfei Li, Yiyao Ye-Lin · 发表于：Biomedical Signal Processing and Control · 年份：2025 · DOI：10.1016/j.bspc.2025.107868 · 被引用次数：5 · 研究领域：Neural dynamics and brain function、EEG and Brain-Computer Interfaces、Neuroscience and Neural Engineering

• Reactivity-to-eyes opening was more sensitive at detecting Parkinson’s Disease. • Beta bursts dynamics in resting brain activity can detect Parkinson’s disease. • Parkinson’s Disease exhibits impaired beta-gamma phase amplitude coupling. • Parkinson’s disease showed impaired motor, working memory and visuospatial skills. Resting state electroencephalography (EEG) has been shown to provide relevant information for detecting neuropathological changes of the brain’s electrical activity in neurodegenerative patients. Studies conducted on local field potential recordings have shown that exaggerated beta oscillations and abnormally high beta-gamma phase amplitude coupling (PAC) are hallmark Parkinson’s disease (PD) signatures. Extracting beta bursts from non-invasive magnetoencephalography has also been found to be feasible, as it provides a better signal-to-noise ratio than electroencephalography and is less affected by volume conduction. It is still unclear whether beta burst dynamic features and beta-gamma PAC from resting state EEG can be used to assess the progress of PD. In the present study, it has been proposed to assess the potential utility of beta burst dynamic and the beta-gamma PAC to discriminate PD patients from healthy subjects, as well as their relationship with clinical symptoms. Resting state EEG data have been analysed in both eyes closed (EC) and open (EO) and reactivity-to-eyes opening (REO) of a public database consisting of 20 healthy and 13 Parkinson pati...