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dc.contributor.authorVernes, Sonja
dc.contributor.authorKriengwatana, Buddhamas Pralle
dc.contributor.authorBeeck, Veronika
dc.contributor.authorFischer, Julia
dc.contributor.authorTyack, Peter Lloyd
dc.contributor.authorten Cate, Carel
dc.contributor.authorJanik, Vincent M.
dc.date.accessioned2021-09-07T09:30:10Z
dc.date.available2021-09-07T09:30:10Z
dc.date.issued2021-10-25
dc.identifier274299666
dc.identifierdc8ce0d1-ec30-4493-9efa-b8314f9b2824
dc.identifier000693558500003
dc.identifier85115818216
dc.identifier.citationVernes , S , Kriengwatana , B P , Beeck , V , Fischer , J , Tyack , P L , ten Cate , C & Janik , V M 2021 , ' The multi-dimensional nature of vocal learning ' , Philosophical Transactions of the Royal Society. B, Biological Sciences , vol. 376 , no. 1836 , 20200236 . https://doi.org/10.1098/rstb.2020.0236en
dc.identifier.issn0962-8436
dc.identifier.urihttps://hdl.handle.net/10023/23911
dc.descriptionFunding; S.C.V. was supported by a Max Planck Research Group (MPRG), a Human Frontiers Science Program (HFSP) Research grant (grant no. RGP0058/2016) and a UKRI Future Leaders Fellowship (grant no. MR/T021985/1). P.L.T. was supported by US Office of Naval Research (ONR) grant nos N00014-18-1-2062 and N00014-20-1-2709. B.P.K. was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 751356. V.C.B. was supported by the DK Cognition and Communication by the Austrian Science Fund (FWF) grant no. W1262-B29.en
dc.description.abstractHow learning affects vocalizations is a key question in the study of animal communication and human language. Parallel efforts in birds and humans have taught us much about how vocal learning works on a behavioural and neurobiological level. Subsequent efforts have revealed a variety of cases among mammals in which experience also has a major influence on vocal repertoires. Janik and Slater (Anim. Behav.60, 1–11. (doi:10.1006/anbe.2000.1410)) introduced the distinction between vocal usage and production learning, providing a general framework to categorize how different types of learning influence vocalizations. This idea was built on by Petkov and Jarvis (Front. Evol. Neurosci.4, 12. (doi:10.3389/fnevo.2012.00012)) to emphasize a more continuous distribution between limited and more complex vocal production learners. Yet, with more studies providing empirical data, the limits of the initial frameworks become apparent. We build on these frameworks to refine the categorization of vocal learning in light of advances made since their publication and widespread agreement that vocal learning is not a binary trait. We propose a novel classification system, based on the definitions by Janik and Slater, that deconstructs vocal learning into key dimensions to aid in understanding the mechanisms involved in this complex behaviour. We consider how vocalizations can change without learning, and a usage learning framework that considers context specificity and timing. We identify dimensions of vocal production learning, including the copying of auditory models (convergence/divergence on model sounds, accuracy of copying), the degree of change (type and breadth of learning) and timing (when learning takes place, the length of time it takes and how long it is retained). We consider grey areas of classification and current mechanistic understanding of these behaviours. Our framework identifies research needs and will help to inform neurobiological and evolutionary studies endeavouring to uncover the multi-dimensional nature of vocal learning.
dc.format.extent15
dc.format.extent554429
dc.language.isoeng
dc.relation.ispartofPhilosophical Transactions of the Royal Society. B, Biological Sciencesen
dc.subjectVocal learningen
dc.subjectSongbirden
dc.subjectCognitionen
dc.subjectBehaviouren
dc.subjectEvolutionen
dc.subjectLanguageen
dc.subjectQH301 Biologyen
dc.subjectQL Zoologyen
dc.subjectT-DASen
dc.subject.lccQH301en
dc.subject.lccQLen
dc.titleThe multi-dimensional nature of vocal learningen
dc.typeJournal itemen
dc.contributor.sponsorUK Research and Innovationen
dc.contributor.institutionUniversity of St Andrews. St Andrews Bioinformatics Uniten
dc.contributor.institutionUniversity of St Andrews. School of Biologyen
dc.contributor.institutionUniversity of St Andrews. Sea Mammal Research Uniten
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. Institute of Behavioural and Neural Sciencesen
dc.contributor.institutionUniversity of St Andrews. Centre for Social Learning & Cognitive Evolutionen
dc.contributor.institutionUniversity of St Andrews. Bioacoustics groupen
dc.identifier.doihttps://doi.org/10.1098/rstb.2020.0236
dc.description.statusPeer revieweden
dc.identifier.grantnumberMR/T021985/1en


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