Investigation of EEG abnormalities in the early stage of Parkinson’s disease

• Published in: Cognitive neurodynamics 2013-08, Vol.7 (4), p.351-359
• Main Authors: Han, Chun-Xiao, Wang, Jiang, Yi, Guo-Sheng, Che, Yan-Qiu
• Format: Article
• Language: English
• Subjects: Abnormalities; Artificial Intelligence; Biochemistry; Biomarkers; Biomedical and Life Sciences; Biomedicine; Cognitive Psychology; Computer Science; EEG; Electroencephalography; Entropy; Experiments; Fourier transforms; Frequencies; Methods; Movement disorders; Neurodegenerative diseases; Neurosciences; Older people; Parkinson's disease; Power; Research Article; Signal processing
• ISSN: 1871-4080; 1871-4099
• DOI: 10.1007/s11571-013-9247-z

The objective of the present study was to investigate brain activity abnormalities in the early stage of Parkinson’s disease (PD). To achieve this goal, eyes-closed resting state electroencephalography (EEG) signals were recorded from 15 early-stage PD patients and 15 age-matched healthy controls. The AR Burg method and the wavelet packet entropy (WPE) method were used to characterize EEG signals in different frequency bands between the groups, respectively. In the case of the AR Burg method, an increase of relative powers in the δ - and θ -band, and a decrease of relative powers in the α - and β -band were observed for patients compared with controls. For the WPE method, EEG signals from patients showed significant higher entropy over the global frequency domain. Furthermore, WPE in the γ -band of patients was higher than that of controls, while WPE in the δ -,  θ -,  α - and β -band were all lower. All of these changes in EEG dynamics may represent early signs of cortical dysfunction, which have potential use as biomarkers of PD in the early stage. Our findings may be further used for early intervention and early diagnosis of PD.