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The multi-dimensional nature of vocal learning

How 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...

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Autores principales: Vernes, Sonja C., Kriengwatana, Buddhamas Pralle, Beeck, Veronika C., Fischer, Julia, Tyack, Peter L., ten Cate, Carel, Janik, Vincent M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419582/
https://www.ncbi.nlm.nih.gov/pubmed/34482723
http://dx.doi.org/10.1098/rstb.2020.0236
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author Vernes, Sonja C.
Kriengwatana, Buddhamas Pralle
Beeck, Veronika C.
Fischer, Julia
Tyack, Peter L.
ten Cate, Carel
Janik, Vincent M.
author_facet Vernes, Sonja C.
Kriengwatana, Buddhamas Pralle
Beeck, Veronika C.
Fischer, Julia
Tyack, Peter L.
ten Cate, Carel
Janik, Vincent M.
author_sort Vernes, Sonja C.
collection PubMed
description How 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. This article is part of the theme issue ‘Vocal learning in animals and humans’.
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spelling pubmed-84195822021-10-07 The multi-dimensional nature of vocal learning Vernes, Sonja C. Kriengwatana, Buddhamas Pralle Beeck, Veronika C. Fischer, Julia Tyack, Peter L. ten Cate, Carel Janik, Vincent M. Philos Trans R Soc Lond B Biol Sci Articles How 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. This article is part of the theme issue ‘Vocal learning in animals and humans’. The Royal Society 2021-10-25 2021-09-06 /pmc/articles/PMC8419582/ /pubmed/34482723 http://dx.doi.org/10.1098/rstb.2020.0236 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Articles
Vernes, Sonja C.
Kriengwatana, Buddhamas Pralle
Beeck, Veronika C.
Fischer, Julia
Tyack, Peter L.
ten Cate, Carel
Janik, Vincent M.
The multi-dimensional nature of vocal learning
title The multi-dimensional nature of vocal learning
title_full The multi-dimensional nature of vocal learning
title_fullStr The multi-dimensional nature of vocal learning
title_full_unstemmed The multi-dimensional nature of vocal learning
title_short The multi-dimensional nature of vocal learning
title_sort multi-dimensional nature of vocal learning
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419582/
https://www.ncbi.nlm.nih.gov/pubmed/34482723
http://dx.doi.org/10.1098/rstb.2020.0236
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