Volpe Gualtiero, D'Ausilio Alessandro, Badino Leonardo, Camurri Antonio, Fadiga Luciano
Casa Paganini-InfoMus, DIBRIS, Università degli Studi di Genova, Viale Causa 13, Genova 16145, Italy
Istituto Italiano di Tecnologia, CTNSC IIT@UniFe, Via Fossato di Mortara 17/19, Ferrara 44121, Italy.
Philos Trans R Soc Lond B Biol Sci. 2016 May 5;371(1693). doi: 10.1098/rstb.2015.0377.
Music ensembles are an ideal test-bed for quantitative analysis of social interaction. Music is an inherently social activity, and music ensembles offer a broad variety of scenarios which are particularly suitable for investigation. Small ensembles, such as string quartets, are deemed a significant example of self-managed teams, where all musicians contribute equally to a task. In bigger ensembles, such as orchestras, the relationship between a leader (the conductor) and a group of followers (the musicians) clearly emerges. This paper presents an overview of recent research on social interaction in music ensembles with a particular focus on (i) studies from cognitive neuroscience; and (ii) studies adopting a computational approach for carrying out automatic quantitative analysis of ensemble music performances.
音乐合奏团体是对社会互动进行定量分析的理想试验平台。音乐本质上是一种社交活动，而音乐合奏团体提供了各种各样特别适合进行研究的场景。小型合奏团体，如弦乐四重奏，被视为自我管理团队的一个重要例子，其中所有音乐家对一项任务的贡献是平等的。在更大的合奏团体，如管弦乐队中，领导者（指挥）和一群追随者（音乐家）之间的关系清晰地显现出来。本文概述了近期关于音乐合奏团体中社会互动的研究，特别关注：（i）认知神经科学的研究；以及（ii）采用计算方法对合奏音乐表演进行自动定量分析的研究。
