| Literature DB >> 27069054 |
Gualtiero Volpe1, Alessandro D'Ausilio2, Leonardo Badino2, Antonio Camurri3, Luciano Fadiga4.
Abstract
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.Entities:
Keywords: computational approaches; leadership; mirror neurons; music ensembles; social interaction; synchronization
Mesh:
Year: 2016 PMID: 27069054 PMCID: PMC4843615 DOI: 10.1098/rstb.2015.0377
Source DB: PubMed Journal: Philos Trans R Soc Lond B Biol Sci ISSN: 0962-8436 Impact factor: 6.237