Comparative analysis of brainwave music translated from spontaneous EEG between major depression disorders and healthy people. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Xi Xi, Liang; Jiu Ju, Wang; Dan, Wu; Wen Xiang, Quan; Yan Ping, Song; Yu Xin, Tong; Wen Tian, Dong
• Is Part Of: Brain-Apparatus Communication: A Journal of Bacomics. Volume 1:Issue 1(2022)
• Page Start: 107
• Page End: 125
• Publication Date: 2022-12-31
• Subjects: Depression -- EEG -- brainwave music -- nonlinear dynamic -- brain network
• DOI: 10.1080/27706710.2022.2112535
• Languages: English
• ISSNs: 2770-6710

Abstract

Abstract: Purpose: This study aimed to calculate and analyze the differences in electroencephalogram (EEG) between major depression disorder (MDD) patients and healthy controls using the method of brainwave music to provide evidence of physiological parameters for clinical diagnosis of MDD. Methods: We translated the 5-minute resting EEG data of 20 MDD patients and 20 healthy controls, which were collected by Peking University Sixth Hospital, into brainwave music; and calculated the pitch, volume, duration and corresponding scaling exponents to analyze the differences between MDD patients and healthy people. Then combined the analysis methods of nonlinear dynamics and brain network structure to verify the validity of the proposed method. Results: The pitch, volume, and Lemple-Ziv complexity (LZC) in the frontal lobe of MDD patients were higher than those of healthy people. In the central, occipital, and temporal regions of the left hemisphere, the scaling exponents, degrees, and clustering coefficient of MDD patients were lower than those of healthy people ( P < 0.05). Conclusions: This study has shown that brainwave music analysis can reflect the differences between MDD patients and healthy controls from a new perspective, and these differences may provide a scientific basis for the clinical diagnosis and brainwave music therapy of MDD.