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Neuroscience. 2013 Oct 10;250:49-59. doi: 10.1016/j.neuroscience.2013.06.021. Epub 2013 Jun 24.

The effects of music on brain functional networks: a network analysis.

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1
Cognitive Science Department, Xiamen University, Xiamen, China; Fujian Key Laboratory of the Brain-like Intelligent Systems, Xiamen University, Xiamen, China.

Abstract

The human brain can dynamically adapt to the changing surroundings. To explore this issue, we adopted graph theoretical tools to examine changes in electroencephalography (EEG) functional networks while listening to music. Three different excerpts of Chinese Guqin music were played to 16 non-musician subjects. For the main frequency intervals, synchronizations between all pair-wise combinations of EEG electrodes were evaluated with phase lag index (PLI). Then, weighted connectivity networks were created and their organizations were characterized in terms of an average clustering coefficient and characteristic path length. We found an enhanced synchronization level in the alpha2 band during music listening. Music perception showed a decrease of both normalized clustering coefficient and path length in the alpha2 band. Moreover, differences in network measures were not observed between musical excerpts. These experimental results demonstrate an increase of functional connectivity as well as a more random network structure in the alpha2 band during music perception. The present study offers support for the effects of music on human brain functional networks with a trend toward a more efficient but less economical architecture.

KEYWORDS:

DSI; DTI; EEG; EOG; FIR; GLS; GuangLingSan; MEG; MHSN; MeiHuaSanNong; OLWJ; OuLuWangJi; PLI; PSD; SD; diffusion spectrum imaging; diffusion tensor imaging; electroencephalography; electrooculogram; fMRI; finite impulse response; functional magnetic resonance imaging; graph theory; magnetoencephalography; music; phase lag index; power spectral density; small-world network; standard deviation; synchronization

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