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

Francesca Talamini; Massimo Grassi; Gianmarco Altoe; Elvira Brattico; Anne Caclin; Barbara Carretti; Veronique 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; Aissa M. Balde; Deniz Baskent; Laura Bishop; Graziela Bortz; Fleur L. Bouwer; Axelle Calcus; Giulio Carraturo; Antonia Ceric; Antonio Criscuolo; Leo Dairain; Simone Dalla Bella; Oscar Daniel; Anne Danielsen; Anne-Isabelle De Parcevaux; Delphine Dellacherie; Veronica 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; Et al.; Sonja A. Kotz

doi:10.1038/s41597-026-06654-0

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

Francesca Talamini^*
, Massimo Grassi^*
, Gianmarco Altoe
, Elvira Brattico
, Anne Caclin
, Barbara Carretti
, Veronique 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, Aissa M. Balde, Deniz Baskent, Laura Bishop, Graziela Bortz, Fleur L. Bouwer, Axelle Calcus, Giulio Carraturo, Antonia Ceric, Antonio Criscuolo, Leo Dairain, Simone Dalla Bella, Oscar Daniel, Anne Danielsen, Anne-Isabelle De Parcevaux, Delphine Dellacherie, Veronica 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, Et al., Sonja A. Kotz

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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.

Original language	English
Article number	473
Number of pages	17
Journal	Scientific data
Volume	13
Issue number	1
DOIs	https://doi.org/10.1038/s41597-026-06654-0
Publication status	Published - 18 Feb 2026

Keywords

PLASTICITY
SOPHISTICATION
INTELLIGENCE
VALIDATION
INSTRUMENT
MODEL

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Talamini, F., Grassi, M., Altoe, G., Brattico, E., Caclin, A., Carretti, B., Drai-Zerbib, V., Ferreri, L., Gambarota, F., Grahn, J., Guiotto Nai Fovino, L., Roccato, M., Rodriguez-Fornells, A., Swaminathan, S., Tillmann, B., Vuust, P., Wilbiks, J., Zentner, M., Aguilar, K., ... Kotz, S. A. (2026). Music Ensemble: a large dataset on musicianship, cognition, and personality in musicians and nonmusicians. Scientific data, 13(1), Article 473. https://doi.org/10.1038/s41597-026-06654-0

@article{5d5208ee4c38464e8963ab015e770f51,

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

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.",

keywords = "PLASTICITY, SOPHISTICATION, INTELLIGENCE, VALIDATION, INSTRUMENT, MODEL",

author = "Francesca Talamini and Massimo Grassi and Gianmarco Altoe and Elvira Brattico and Anne Caclin and Barbara Carretti and Veronique Drai-Zerbib and Laura Ferreri and Filippo Gambarota and Jessica Grahn and \{Guiotto Nai Fovino\}, Lucrezia and Marco Roccato and Antoni Rodriguez-Fornells and Swathi Swaminathan and Barbara Tillmann and Peter Vuust and Jonathan Wilbiks and Marcel Zentner and Karla Aguilar and Aryanto, \{Christ B.\} and \{Assis Leite\}, \{Frederico C.\} and Balde, \{Aissa M.\} and Deniz Baskent and Laura Bishop and Graziela Bortz and Bouwer, \{Fleur L.\} and Axelle Calcus and Giulio Carraturo and Antonia Ceric and Antonio Criscuolo and Leo Dairain and \{Dalla Bella\}, Simone and Oscar Daniel and Anne Danielsen and \{De Parcevaux\}, Anne-Isabelle and Delphine Dellacherie and Veronica Detlefsen and Tor Endestad and Victor Cepero-Escribano and Fialho, \{Juliana L. D. B.\} and Caitlin Fitzpatrick and Anna Fiveash and Juliette Fortier and Fram, \{Noah R.\} and Eleonora Fullone and Stefanie Gloggengiesser and \{Gonzalez Sanchez\}, Lucia and Gordon, \{Reyna L.\} and Mathilde Groussard and Assal Habibi and \{Et al.\} and Kotz, \{Sonja A.\}",

year = "2026",

month = feb,

day = "18",

doi = "10.1038/s41597-026-06654-0",

language = "English",

volume = "13",

journal = "Scientific data",

issn = "2052-4463",

publisher = "Nature Research",

number = "1",

}

Talamini, F, Grassi, M, Altoe, G, Brattico, E, Caclin, A, Carretti, B, Drai-Zerbib, V, Ferreri, L, Gambarota, F, Grahn, J, Guiotto Nai Fovino, L, Roccato, M, Rodriguez-Fornells, A, Swaminathan, S, Tillmann, B, Vuust, P, Wilbiks, J, Zentner, M, Aguilar, K, Aryanto, CB, Assis Leite, FC, Balde, AM, Baskent, D, Bishop, L, Bortz, G, Bouwer, FL, Calcus, A, Carraturo, G, Ceric, A, Criscuolo, A, Dairain, L, Dalla Bella, S, Daniel, O, Danielsen, A, De Parcevaux, A-I, Dellacherie, D, Detlefsen, V, Endestad, T, Cepero-Escribano, V, Fialho, JLDB, Fitzpatrick, C, Fiveash, A, Fortier, J, Fram, NR, Fullone, E, Gloggengiesser, S, Gonzalez Sanchez, L, Gordon, RL, Groussard, M, Habibi, A, Et al. & Kotz, SA 2026, 'Music Ensemble: a large dataset on musicianship, cognition, and personality in musicians and nonmusicians', Scientific data, vol. 13, no. 1, 473. https://doi.org/10.1038/s41597-026-06654-0

TY - JOUR

T1 - Music Ensemble

T2 - a large dataset on musicianship, cognition, and personality in musicians and nonmusicians

AU - Talamini, Francesca

AU - Grassi, Massimo

AU - Altoe, Gianmarco

AU - Brattico, Elvira

AU - Caclin, Anne

AU - Carretti, Barbara

AU - Drai-Zerbib, Veronique

AU - Ferreri, Laura

AU - Gambarota, Filippo

AU - Grahn, Jessica

AU - Guiotto Nai Fovino, Lucrezia

AU - Roccato, Marco

AU - Rodriguez-Fornells, Antoni

AU - Swaminathan, Swathi

AU - Tillmann, Barbara

AU - Vuust, Peter

AU - Wilbiks, Jonathan

AU - Zentner, Marcel

AU - Aguilar, Karla

AU - Aryanto, Christ B.

AU - Assis Leite, Frederico C.

AU - Balde, Aissa M.

AU - Baskent, Deniz

AU - Bishop, Laura

AU - Bortz, Graziela

AU - Bouwer, Fleur L.

AU - Calcus, Axelle

AU - Carraturo, Giulio

AU - Ceric, Antonia

AU - Criscuolo, Antonio

AU - Dairain, Leo

AU - Dalla Bella, Simone

AU - Daniel, Oscar

AU - Danielsen, Anne

AU - De Parcevaux, Anne-Isabelle

AU - Dellacherie, Delphine

AU - Detlefsen, Veronica

AU - Endestad, Tor

AU - Cepero-Escribano, Victor

AU - Fialho, Juliana L. D. B.

AU - Fitzpatrick, Caitlin

AU - Fiveash, Anna

AU - Fortier, Juliette

AU - Fram, Noah R.

AU - Fullone, Eleonora

AU - Gloggengiesser, Stefanie

AU - Gonzalez Sanchez, Lucia

AU - Gordon, Reyna L.

AU - Groussard, Mathilde

AU - Habibi, Assal

AU - Et al.

AU - Kotz, Sonja A.

PY - 2026/2/18

Y1 - 2026/2/18

N2 - 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.

AB - 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.

KW - PLASTICITY

KW - SOPHISTICATION

KW - INTELLIGENCE

KW - VALIDATION

KW - INSTRUMENT

KW - MODEL

U2 - 10.1038/s41597-026-06654-0

DO - 10.1038/s41597-026-06654-0

M3 - Article

SN - 2052-4463

VL - 13

JO - Scientific data

JF - Scientific data

IS - 1

M1 - 473

ER -

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

Abstract

Keywords

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