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Journal Article

The multi-dimensional nature of vocal learning

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Vernes,  Sonja C.
Neurogenetics of Vocal Communication Group, MPI for Psycholinguistics, Max Planck Society;
University of St Andrews;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

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Citation

Vernes, S. C., Kriengwatana, B. P., Beeck, V. C., Fischer, J., Tyack, P. L., Ten Cate, C., et al. (2021). The multi-dimensional nature of vocal learning. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 376: 20200236. doi:10.1098/rstb.2020.0236.


Cite as: https://hdl.handle.net/21.11116/0000-0009-20BC-F
Abstract
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 pro-
duction 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 beha-
viours. 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’.