Unravelling individual rhythmic abilities using machine learning.

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Bibliographic Details
Title: Unravelling individual rhythmic abilities using machine learning.
Authors: Dalla Bella S; International Laboratory for Brain, Music, and Sound Research (BRAMS), Montreal, Canada. simone.dalla.bella@umontreal.ca.; Department of Psychology, University of Montreal, Pavillon Marie-Victorin, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada. simone.dalla.bella@umontreal.ca.; Centre for Research on Brain, Language and Music (CRBLM), Montreal, Canada. simone.dalla.bella@umontreal.ca.; University of Economics and Human Sciences in Warsaw, Warsaw, Poland. simone.dalla.bella@umontreal.ca., Janaqi S; EuroMov Digital Health in Motion, IMT Mines Ales and University of Montpellier, Ales and Montpellier, France., Benoit CE; Inter-University Laboratory of Human Movement Biology, EA 7424, University Claude Bernard Lyon 1, 69 622, Villeurbanne, France., Farrugia N; IMT Atlantique, Brest, France., Bégel V; Université Paris Cité, Paris, France., Verga L; Comparative Bioacoustics Group, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.; Department of Neuropsychology & Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, P.O. 616, Maastricht, 6200 MD, The Netherlands., Harding EE; Department of Otorhinolaryngology/Head and Neck Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands., Kotz SA; Department of Neuropsychology & Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, P.O. 616, Maastricht, 6200 MD, The Netherlands. sonja.kotz@maastrichtuniversity.nl.; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. sonja.kotz@maastrichtuniversity.nl.
Source: Scientific reports [Sci Rep] 2024 Jan 11; Vol. 14 (1), pp. 1135. Date of Electronic Publication: 2024 Jan 11.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2045-2322
DOI:10.1038/s41598-024-51257-7