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音乐家和非音乐家在聆听调性与无调性音乐会音乐时脑电图功能连接网络拓扑结构的变化

Modifications in the Topological Structure of EEG Functional Connectivity Networks during Listening Tonal and Atonal Concert Music in Musicians and Non-Musicians.

作者信息

González Almudena, Santapau Manuel, Gamundí Antoni, Pereda Ernesto, González Julián J

机构信息

Departamento de Historia del Arte (Música), Universidad de La Laguna, 38200 Tenerife, Spain.

Conservatorio de Música de Requena, 46340 Valencia, Spain.

出版信息

Brain Sci. 2021 Jan 26;11(2):159. doi: 10.3390/brainsci11020159.

Abstract

The present work aims to demonstrate the hypothesis that atonal music modifies the topological structure of electroencephalographic (EEG) connectivity networks in relation to tonal music. To this, EEG monopolar records were taken in musicians and non-musicians while listening to tonal, atonal, and pink noise sound excerpts. EEG functional connectivities (FC) among channels assessed by a phase synchronization index previously thresholded using surrogate data test were computed. Sound effects, on the topological structure of graph-based networks assembled with the EEG-FCs at different frequency-bands, were analyzed throughout graph metric and network-based statistic (NBS). Local and global efficiency normalized (vs. random-network) measurements (NLE|NGE) assessing network information exchanges were able to discriminate both music styles irrespective of groups and frequency-bands. During tonal audition, NLE and NGE values in the beta-band network get close to that of a small-world network, while during atonal and even more during noise its structure moved away from small-world. These effects were attributed to the different timbre characteristics (sounds spectral centroid and entropy) and different musical structure. Results from networks topographic maps for strength and NLE of the nodes, and for FC subnets obtained from the NBS, allowed discriminating the musical styles and verifying the different strength, NLE, and FC of musicians compared to non-musicians.

摘要

本研究旨在验证以下假设

与调性音乐相比,无调性音乐能改变脑电图(EEG)连接网络的拓扑结构。为此,在音乐家和非音乐家聆听调性、无调性和粉红噪声声音片段时,记录了他们的EEG单极记录。通过使用替代数据测试预先设定阈值的相位同步指数评估通道间的EEG功能连接性(FC)。通过图形度量和基于网络的统计(NBS)分析了声音效果对不同频段基于EEG-FC组装的基于图形的网络拓扑结构的影响。评估网络信息交换的局部和全局效率归一化(相对于随机网络)测量值(NLE|NGE)能够区分两种音乐风格,而与组别和频段无关。在聆听调性音乐时,β频段网络中的NLE和NGE值接近小世界网络的值,而在聆听无调性音乐时,尤其是在聆听噪声时,其结构偏离了小世界网络。这些影响归因于不同的音色特征(声音频谱质心和熵)和不同的音乐结构。节点强度和NLE以及从NBS获得的FC子网的网络地形图结果,能够区分音乐风格,并验证音乐家与非音乐家在强度、NLE和FC方面的差异。

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