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Music Ensemble: comparing musical skills, cognition and personality of musicians and nonmusicians
- Massimo Grassi
- Francesca Talamini
- Laura Ferreri
- Swathi Swaminathan
- Barbara Tillmann
- Anne Caclin
- Gianmarco Altoè
- Filippo Gambarota
- Jonathan Wilbiks
- Marco Roccato
- Lucrezia Guiotto Nai Fovino
- Véronique Drai-Zerbib
- Elvira Brattico
- Barbara Carretti
- Jessica Grahn
- Antoni Rodriguez-Fornells
- Peter Vuust
- Marcel Zentner
- Christ Billy Aryanto
- Aíssa Mariama Nascimento Baldé
- Deniz Başkent
- Laura Bishop
- Graziela Bortz
- Fleur L. Bouwer
- Axelle Calcus
- Giulio Carraturo
- Antonio Criscuolo
- Simone Dalla Bella
- Anne Danielsen
- Tor Endestad
- Anna Fiveash
- Reyna L. Gordon
- Assal Habibi
- Eleanor E. Harding
- Steffen Alexander Herff
- Kelly Jakubowski
- Sonja A. Kotz
- Bruno Laeng
- André Lee
- Miriam Lense
- Cesar Lima
- Daniel Mirman
- Daniel Müllensiefen
- Andrew Oxenham
- Edoardo Passarotto
- Hervé Platel
- Italo Ramon Rodrigues Menezes
- Rafael Román-Caballero
- Daniela Sammler
- L. Robert Slevc
- Hannah Strauss
- Mari Tervaniemi
- Renee Timmers
- Petri Toiviainen
- Laurel Trainor
- Jed Villanueva
- Claudia C. von Bastian
- Kelly L. Whiteford
- Florian Worschech
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Category: Project
Description: The Music Ensemble is a multilab, multisite empirical study that investigated individual differences between musicians and nonmusicians. Participating laboratories collected data in person, in lab using a common research protocol. The project provides the digital materials used for collecting the data and the data collected. The database stores data on musical, cognitive, personality, and demographic variables from 1,438 participants aged 18–30, collected across 16 countries (35 research sites). The standardized test battery includes tests of verbal, visuospatial, and musical short-term memory, executive functions, reasoning, verbal comprehension, and music perception, along with self-reports on music sophistication, music reward, personality, SES, and demographics. The dataset also includes a subsample of 678 musician–nonmusician pairs matched for age, gender, and education. The dataset enables robust analyses on the relationship between musical expertise and individual differences.