Altered EEG Oscillatory Brain Networks During Music-Listening in Major Depression
Zhu Y, Wang X, Mathiak K, Toiviainen P, Ristaniemi T, Xu J, Chang Y, Cong F
International journal of neural systems · 11 citations
Review labels
Neutral facts our review recorded about how this study was done. They describe method, never whether we like the result.
How it was studied
- Design
- Case-control study (classified by our AI screen)
- Studied in
- People
- Main outcome
- Mechanisms only
Who paid for it
- Funding
- Funding not disclosed
Publication
- Published
- 2020-12-22 · Int J Neural Syst · vol. 31 · issue 03 · p. 2150001
- Publisher
- World Scientific
- Cited
- 18 citations · more than 74% of similar papers · 1.0× the field average
- References
- 67 works
- Access
- Open access (repository copy) · OTHER-OA
- Research areas
- Neural dynamics and brain function · Neuroscience and Music Perception · Functional Brain Connectivity Studies
- Keywords
- Electroencephalography, Psychology, Magnetoencephalography, Active listening, Independent component analysis, Audiology, Brain activity and meditation, Alpha (finance), Neuroscience, Cognitive psychology, Communication, Artificial intelligence, Medicine, Developmental psychology, Computer science
- MeSH
- brain, humans, electroencephalography, brain mapping, depression, auditory perception, music, major depressive disorder
8 authors
From FI, CN, DE
- Yongjie ZhuUniversity of Helsinki; Dalian University of Technology; University of Jyväskylä
- Xiaoyu WangDalian University of Technology
- Klaus MathiakRWTH Aachen University
- Petri ToiviainenUniversity of Jyväskylä
- Tapani RistaniemiUniversity of Jyväskylä
- Jing XuDalian Medical University; First Affiliated Hospital of Dalian Medical University
Abstract
To examine the electrophysiological underpinnings of the functional networks involved in music listening, previous approaches based on spatial independent component analysis (ICA) have recently been used to ongoing electroencephalography (EEG) and magnetoencephalography (MEG). However, those studies focused on healthy subjects, and failed to examine the group-level comparisons during music listening. Here, we combined group-level spatial Fourier ICA with acoustic feature extraction, to enable group comparisons in frequency-specific brain networks of musical feature processing. It was then applied to healthy subjects and subjects with major depressive disorder (MDD). The music-induced oscillatory brain patterns were determined by permutation correlation analysis between individual time courses of Fourier-ICA components and musical features. We found that (1) three components, including a beta sensorimotor network, a beta auditory network and an alpha medial visual network, were involved in music processing among most healthy subjects; and that (2) one alpha lateral component located in the left angular gyrus was engaged in music perception in most individuals with MDD. The proposed method allowed the statistical group comparison, and we found that: (1) the alpha lateral component was activated more strongly in healthy subjects than in the MDD individuals, and that (2) the derived frequency-dependent networks of musical feature processing seemed to be altered in MDD participants compared to healthy subjects. The proposed pipeline appears to be valuable for studying disrupted brain oscillations in psychiatric disorders during naturalistic paradigms.
Abstract via Europe PMC. Copyright remains with the authors or publisher.
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