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Leadership in Orchestra Emerges from the Causal Relationships of Movement Kinematics

Overview of attention for article published in PLOS ONE, May 2012
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Title
Leadership in Orchestra Emerges from the Causal Relationships of Movement Kinematics
Published in
PLOS ONE, May 2012
DOI 10.1371/journal.pone.0035757
Pubmed ID
Authors

Alessandro D'Ausilio, Leonardo Badino, Yi Li, Sera Tokay, Laila Craighero, Rosario Canto, Yiannis Aloimonos, Luciano Fadiga

Abstract

Non-verbal communication enables efficient transfer of information among people. In this context, classic orchestras are a remarkable instance of interaction and communication aimed at a common aesthetic goal: musicians train for years in order to acquire and share a non-linguistic framework for sensorimotor communication. To this end, we recorded violinists' and conductors' movement kinematics during execution of Mozart pieces, searching for causal relationships among musicians by using the Granger Causality method (GC). We show that the increase of conductor-to-musicians influence, together with the reduction of musician-to-musician coordination (an index of successful leadership) goes in parallel with quality of execution, as assessed by musical experts' judgments. Rigorous quantification of sensorimotor communication efficacy has always been complicated and affected by rather vague qualitative methodologies. Here we propose that the analysis of motor behavior provides a potentially interesting tool to approach the rather intangible concept of aesthetic quality of music and visual communication efficacy.

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Geographical breakdown

Country Count As %
Italy 4 <1%
Germany 2 <1%
United States 2 <1%
Spain 2 <1%
Finland 1 <1%
United Kingdom 1 <1%
France 1 <1%
Canada 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 1097 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 162 15%
Other 43 4%
Researcher 38 3%
Student > Ph. D. Student 33 3%
Student > Postgraduate 29 3%
Other 84 8%
Unknown 724 65%
Readers by discipline Count As %
Business, Management and Accounting 77 7%
Computer Science 52 5%
Psychology 45 4%
Engineering 34 3%
Arts and Humanities 30 3%
Other 118 11%
Unknown 757 68%