Effective network analysis in music listening based on electroencephalogram

Music is present in every culture and affects humans in numerous ways. Music-related technologies, such as music generation, can extend the application scenarios of human–computer interaction systems. Despite its important role in cognitive and social domains, the brain networks involved in music listening remain unclear. To further explore the relationship between music and brain networks, in this study, we analyzed the brain networks of 29 participants under different musical conditions based on electroencephalogram (EEG) signals. Specifically, we utilized a public dataset that provided EEG signals of participants listening to music under different rhythmic and processing conditions. After EEG source localization, we selected 22 regions of interest (ROIs) that were relevant to music. The effective networks were subsequently established, where the ROIs are regarded as nodes, and the Granger causality relationships between nodes are considered as edges. We explored the differences among these effective networks and analyzed them further based on graph theory. The results demonstrate that different processing methods of music generate changes in the brain network. The results indicate the crucial role of the inferior parietal lobe in information transmission. The findings of this study provide new insights into the relationship between music and brain activity.