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Exploring Frequency-Dependent Brain Networks from Ongoing EEG Using Spatial ICA During Music Listening
Yongjie Zhu1,2, Chi Zhang1, Hanna Poikonen3
1School of Biomedical Engineering, Faculty of Electronic and Electrical Engineering, Dalian University of Technology, Dalian, 116024, China.
This study reveals how brain networks process musical features using electroencephalography (EEG). Specific neural rhythms, like alpha and beta oscillations, are linked to processing music elements in distinct brain regions.
Area of Science:
- Neuroscience
- Cognitive Science
- Music Psychology
Background:
- Exploring brain activity during naturalistic stimuli like music is challenging due to low signal-to-noise ratios in brain data.
- While fMRI and EEG/MEG have studied the listening brain, the role of neural rhythms in brain network activity during naturalistic stimuli remains unclear.
Purpose of the Study:
- To investigate the involvement of neural rhythms in brain network activity during music listening.
- To explore the interplay between spatial and spectral patterns of brain networks engaged by music.
- To identify frequency-dependent oscillatory patterns associated with musical feature processing.
Main Methods:
- Utilized ongoing electroencephalography (EEG) and musical feature analysis during free music listening.
- Employed a data-driven approach combining music information retrieval with spatial Fourier Independent Components Analysis (spatial Fourier-ICA).
- Correlated EEG-derived brain network time courses with music feature time series to identify musical feature-related oscillatory patterns.
Main Results:
- Brain networks involved in musical feature processing demonstrated frequency-dependent characteristics.
- Musical features, such as fluctuation centroid and key, correlated with increased beta activation in the bilateral superior temporal gyrus.
- Increased alpha oscillations in the bilateral occipital cortex were observed, aligning with the alpha functional suppression hypothesis.
- Enhanced delta-beta oscillatory activity in the prefrontal cortex was associated with musical feature processing.
Conclusions:
- Neural rhythms play a frequency-dependent role in processing musical features within specific brain networks.
- The study identified distinct oscillatory patterns (alpha, beta, delta-beta) linked to different aspects of music perception.
- The proposed method is valuable for characterizing large-scale, frequency-dependent brain activity during music listening.
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