Suppr超能文献

合唱演唱过程中的超高频网络拓扑变化。

Hyper-Frequency Network Topology Changes During Choral Singing.

作者信息

Müller Viktor, Delius Julia A M, Lindenberger Ulman

机构信息

Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.

Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, United Kingdom.

出版信息

Front Physiol. 2019 Mar 6;10:207. doi: 10.3389/fphys.2019.00207. eCollection 2019.

Abstract

Choral singing requires the coordination of physiological subsystems within and across individuals. Previously, we suggested that the choir functions as a superordinate system that imposes boundary conditions on the dynamic features of the individual singers and found reliable differences in the network topography by analyzing within- and cross-frequency couplings (WFC and CFC, respectively). Here, we further refine our analyses to investigate hyper-frequency network (HFN) topology structures (i.e., the layout or arrangement of connections) using a graph-theoretical approach. In a sample of eleven singers and one conductor engaged in choral singing (aged between 23 and 56 years, and including five men and seven women), we calculated phase coupling (WFC and CFC) between respiratory, cardiac, and vocalizing subsystems across ten frequencies of interest. All these couplings were used for construction of HFN with nodes being a combination of frequency components and subsystems across choir participants. With regard to the network topology measures, we found that clustering coefficients (s) as well as local and global efficiency were highest and characteristic path lengths, correspondingly, were shortest when the choir sang a canon in parts as compared to singing it in unison. Furthermore, these metrics revealed a significant relationship to individual heart rate, as an indicator of arousal, and to an index of heart rate variability indicated by the ratio (low and high frequency, respectively), and reflecting the balance between sympathetic and parasympathetic activity. In addition, we found that the and local efficiency for groups singing the same canon part were higher than for groups of singers constructed randomly , indicating stronger neighbor-neighbor connections in the former. We conclude that network topology dynamics are a crucial determinant of group behavior and may represent a potent biomarker for social interaction.

摘要

合唱需要个体内部以及个体之间生理子系统的协调配合。此前,我们提出合唱团起着一个上级系统的作用,它会对个体歌手的动态特征施加边界条件,并且通过分别分析频率内耦合和跨频率耦合(WFC和CFC),发现了网络拓扑结构存在可靠差异。在此,我们进一步完善分析方法,采用图论方法研究超高频网络(HFN)拓扑结构(即连接的布局或排列)。在一个由11名歌手和1名指挥组成的合唱样本中(年龄在23至56岁之间,包括5名男性和7名女性),我们计算了呼吸、心脏和发声子系统在十个感兴趣频率之间的相位耦合(WFC和CFC)。所有这些耦合都用于构建HFN,其节点是合唱团参与者中频率成分和子系统的组合。关于网络拓扑测量,我们发现与齐唱相比,合唱团分声部演唱卡农曲时,聚类系数(s)以及局部和全局效率最高,相应地,特征路径长度最短。此外,这些指标显示出与作为唤醒指标的个体心率以及由 比值(分别为低频和高频)表示的心率变异性指数存在显著关系,该指数反映了交感神经和副交感神经活动之间的平衡。此外,我们发现演唱同一卡农声部的组的 和局部效率高于随机组建的歌手组,这表明前者中相邻成员之间的连接更强。我们得出结论,网络拓扑动态是群体行为的关键决定因素,可能代表社会互动的一个有力生物标志物。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验