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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月18日

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

摘要

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.