Investigation of global and local network properties of music perception with culturally different styles of music
Investigation of global and local network properties of music perception with culturally different styles of music
复制标题
研究不同文化音乐风格的音乐感知的全球和本地网络特性
DOI：
10.1016/j.compbiomed.2014.08.017
复制
发表时间：
2014-11
影响因子：
7.7
通讯作者：
Pu Fang
中科院分区：
文献类型：
--
作者：
Li Yan;Rui Xue;Li Shuyu;Pu Fang
背景图理论分析近年来已成为神经科学研究的一个热门工具，然而，关于音乐知觉的脑反应的研究却很少，特别是当音乐知觉涉及到不同文化风格时，研究的结果更少。对于事件相关电位，相位相干性在α带中计算，然后构造成相关矩阵。聚类系数和特征路径长度进行了评估的全球属性，而聚类系数和效率进行了评估，为本地网络properties.ResultsPerception轻音乐和西方古典音乐表现出小世界网络属性，特别是与一个相对较低的比例的权重的相关矩阵。对于局部分析，效率比聚类系数更易识别。然而，中国传统和西方古典音乐perception.ConclusionsPerception不同风格的音乐介绍了不同的网络属性，全球和本地之间没有显着的歧视。全球和本地网络属性的研究已经在其他领域进行，但是，这是一个初步的调查，旨在提出一种可能的新方法，大脑网络的音乐感知性能。
BackgroundGraph theoretical analysis has recently become a popular research tool in neuroscience, however, there have been very few studies on brain responses to music perception, especially when culturally different styles of music are involved.MethodsElectroencephalograms were recorded from ten subjects listening to Chinese traditional music, light music and western classical music. For event-related potentials, phase coherence was calculated in the alpha band and then constructed into correlation matrices. Clustering coefficients and characteristic path lengths were evaluated for global properties, while clustering coefficients and efficiency were assessed for local network properties.ResultsPerception of light music and western classical music manifested small-world network properties, especially with a relatively low proportion of weights of correlation matrices. For local analysis, efficiency was more discernible than clustering coefficient. Nevertheless, there was no significant discrimination between Chinese traditional and western classical music perception.ConclusionsPerception of different styles of music introduces different network properties, both globally and locally. Research into both global and local network properties has been carried out in other areas; however, this is a preliminary investigation aimed at suggesting a possible new approach to brain network properties in music perception.
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影响因子：
4.3
作者：
Achard S;Bullmore E
通讯作者：
Bullmore E
DOI：
10.1109/embc.2012.6345868
发表时间：
2012-11
期刊：
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
影响因子：
--
作者：
Lei Wang;Xiaoli Guo;Junfeng Sun;Zheng Jin;S. Tong
通讯作者：
Lei Wang;Xiaoli Guo;Junfeng Sun;Zheng Jin;S. Tong
影响因子：
1.6
作者：
Joan Newman;John H. Rosenbach;Kathryn L. Burns;Brian C. Latimer;Helen R. Matocha;E. R. Vogt
通讯作者：
Joan Newman;John H. Rosenbach;Kathryn L. Burns;Brian C. Latimer;Helen R. Matocha;E. R. Vogt
通过静息态脑电图网络预测基于 SSVEP 的 BCI 性能
影响因子：
4
作者：
Y Zhang;P Xu;D Guo;D Yao
通讯作者：
D Yao
影响因子：
2.4
作者：
Onnela, JP;Saramäki, J;Kaski, K
通讯作者：
Kaski, K