Music Ensemble: a large dataset on musicianship, cognition, and personality in musicians and nonmusicians

The Music Ensemble dataset is a large-scale, cross-national database that provides detailed information about the musical, cognitive, personality, and demographic profiles of young adult musicians and nonmusicians. Data were collected from 1438 participants (aged 18-30) across thirty-five research sites in Europe, North America, South America, and Australia. Participants completed an in-person, in-lab battery of objective tests, including measures of verbal, visuospatial and musical short-term memory, executive functions (updating component), nonverbal reasoning, verbal comprehension, and music perception skills. The battery also included standardized and custom self-report questionnaires assessing music sophistication, music reward, personality traits, socioeconomic status, and demographic characteristics. Music Ensemble was preregistered, and the research protocol followed a standardized procedure across sites. The dataset also includes a large subsample of musicians and nonmusicians that are pair-matched for age, gender, and education (678 pairs). It enables well-powered investigations into the relationship between musical expertise and individual differences in cognition, personality, and demographic variables. It is also suitable for training in statistical and psychometric methods.

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Publication Details

Journal
Scientific Data
Published
2026-02-18
DOI
https://doi.org/10.1038/s41597-026-06654-0
Primary Topic
Neuroscience and Music Perception
Type
article
Field-Weighted Citation Impact
0.00

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article

Music Ensemble: a large dataset on musicianship, cognition, and personality in musicians and nonmusicians

Florian Worschech, J. Oxenham Andrew, Kelly Jakubowski, Jed Villanueva et al.
Scientific Data
Neuroscience and Music Perception
article

Music Ensemble: a large dataset on musicianship, cognition, and personality in musicians and nonmusicians

Florian Worschech, J. Oxenham Andrew, Kelly Jakubowski, Jed Villanueva, Deniz Başkent, Laurel J. Trainor, Axelle Calcus, Suvi Helinä Saarikallio, Mari H. Tervaniemi, Daniela Sammler, Edoardo Passarotto, Verónica Detlefsen, Fleur L. Bouwer, Noah R. Fram, Ana Zappa, Eleonora Fullone, André Lee, Graziela Bortz, Rafael Román-Caballero, Alice Poissonnier, Lucrezia Guiotto Nai Fovino, Pablo Ripollés, Marco Roccato, Swathi Swaminathan, Laura Bishop, Wanda Rubinstein, Christ Billy Aryanto, Neha Rajappa, Eleanor Harding, Antonio Criscuolo, Anna Fiveash, Francesca Talamini, Hervé Platel, Véronique Drai-Zerbib, Jonathan M. P. Wilbiks, Claudia C. von Bastian, Haakon Hansen, Delphine Dellacherie, Caitlin Fitzpatrick, Michaela Ritchie, Julieta Moltrasio, Miriam Lense, Reyna L. Gordon, Jessica P. Michael, Filippo Gambarota, Anne Danielsen, Tor Endestad, Séverine Samson, Emily A. Wood, Hannah Strauß, Giulio Carraturo, Mathilde Groussard, Victor Cepero-Escribano, Massimo Grassi, Vasiliki Provias, Bruno Laeng, César Lima, Simone Dalla Bella, Laura Ferreri, Changlin Liu, Aíssa M. Baldé, Elvira Brattico, Ragnya-Norasoa Souffiane, Florian J. Strauch, Nicholas Tantengco, Clara Tuske, Antonia Čerič, Léo Dairain, Anne-Isabelle de Parcevaux, Stefanie Gloggengießer, Veikka P. Holma, Maria G. Jol, Veronica Kandro, Rosaliina Kelo, Gangothri S. Ladegam, Simon P. Limmer, Langley McEntyre, Niloufar Najafi, Jaakko Nokkala, Ndassi Nzonlang, Marie-Elisabeth Plasse, Paula Roncaglia, Ms Kirsty Hawkins, Barbara Carretti, Daniel Mirman, Peter Vuust, Assal Habibi, Kelly L. Whiteford, Aarushi Kalsi, Katie Overy, Paulina d. C. Martín Sánchez, Anne Caclin, Marcel Zentner, Antoni Rodriguez-Fornells, Frederico C. Assis Leite, Juliana L. d. B. Fialho, Renee Timmers, Jessica Grahn, Farrah Y.-A. Sa’adullah, Steffen A. Herff, Italo R. Rodrigues Menezes, Oscar Daniel, E. Glenn Schellenberg, Maria Gabriela M. Oliveira, Karla Aguilar, Daniel Müllensiefen, Nora R. Serres, Rachel Thompson, Petri Toiviainen, L. Robert Slevc, Sonja A. Kotz, Barbara Tillmann, Lucia Gonzalez Sanchez, Juliette Fortier
article en

Abstract

The Music Ensemble dataset is a large-scale, cross-national database that provides detailed information about the musical, cognitive, personality, and demographic profiles of young adult musicians and nonmusicians. Data were collected from 1438 participants (aged 18-30) across thirty-five research sites in Europe, North America, South America, and Australia. Participants completed an in-person, in-lab battery of objective tests, including measures of verbal, visuospatial and musical short-term memory, executive functions (updating component), nonverbal reasoning, verbal comprehension, and music perception skills. The battery also included standardized and custom self-report questionnaires assessing music sophistication, music reward, personality traits, socioeconomic status, and demographic characteristics. Music Ensemble was preregistered, and the research protocol followed a standardized procedure across sites. The dataset also includes a large subsample of musicians and nonmusicians that are pair-matched for age, gender, and education (678 pairs). It enables well-powered investigations into the relationship between musical expertise and individual differences in cognition, personality, and demographic variables. It is also suitable for training in statistical and psychometric methods.

Scientific DataVol. 13(1)
Université Claude Bernard Lyon 1 (FR), University of New Brunswick (CA), University of Southern California (US), Institució Catalana de Recerca i Estudis Avançats (ES), Leiden University (NL), Western University (CA), Centre National de la Recherche Scientifique (FR), The University of Sydney (AU), University of Minnesota (US), Allen Institute for Brain Science (US), Université Libre de Bruxelles (BE), University Medical Center Groningen (NL), University of Helsinki (FI), University of Padua (IT), Inserm (FR), Institut Pasteur (FR), École Pratique des Hautes Études (FR), Atma Jaya Catholic University of Indonesia (ID), University of Groningen (NL), Universidad de Granada (ES), Université de Bourgogne (FR), University of Oslo (NO), University of Toronto (CA), Durham University (GB), Universität Innsbruck (AT), Tilburg University (NL), Vanderbilt University (US), Aarhus University (DK), Université Paris Cité (FR), Université de Lille (FR), National University of General San Martín (AR), Universidad de Buenos Aires (AR), University of Pavia (IT), Université Paris Sciences et Lettres (FR), Saint John Regional Hospital (CA), TUM Klinikum (DE), Maastricht University (NL), Max Planck Institute for Empirical Aesthetics (DE), Institut d'Investigació Biomédica de Bellvitge (ES), VIZJA University (PL), Centre de Recherche en Neurosciences de Lyon (FR), Assistance Publique – Hôpitaux de Paris (FR), Centre for Research on Brain Language and Music (CA), Hanover University of Music Drama and Media (DE), Iscte – Instituto Universitário de Lisboa (PT), Royal Academy of Music (DK), Centre Hospitalier Universitaire de Caen Normandie (FR), Helgeland Museum (NO), Instituto de Neurología Cognitiva (AR), Max Planck Institute for Human Cognitive and Brain Sciences (DE), University of Palermo (AR), Cyceron (FR), Universidade Cruzeiro do Sul (BR), Sydney University Musical Society (AU), International Laboratory for Brain, Music and Sound Research (CA), Université Bourgogne Europe (FR), Goldsmiths University of London (GB), University of Bari Aldo Moro (IT), New York University (US), Western Sydney University (AU), University of Maryland, College Park (US), Université de Montréal (CA), Universidade Estadual Paulista (Unesp) (BR), Universidade Federal de São Paulo (BR), Vanderbilt University Medical Center (US), University of Sheffield (GB), University of Jyväskylä (FI), McMaster University (CA), University of Edinburgh (GB), Université de Caen Normandie (FR)
National Research Foundation, Danmarks Grundforskningsfond, Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Quality Education
Openalex Percentile: Top 53%
Neuroscience and Music Perception
DOIOpen Access PDFOpenAlex
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