A Modular Approach to Vocal Learning: Disentangling the Diversity of a Complex Behavioral Trait

Publication Type:Journal Article
Year of Publication:2019
Authors:Wirthlin, Chang, Knörnschild, Krubitzer, Mello, Miller, Pfenning, Vernes, Tchernichovski, Yartsev
Journal:Neuron
Volume:104
Issue:1
Pagination:87 - 99
Date Published:Jan-10-2019
ISSN:08966273
Abstract:

Vocal learning is a behavioral trait in which the social and acoustic environment shapes the vocal repertoire of individuals. Over the past century, the study of vocal learning has progressed at the intersection of ecology, physiology, neuroscience, molecular biology, genomics, and evolution. Yet, despite the complexity of this trait, vocal learning is frequently described as a binary trait, with species being classified as either vocal learners or vocal non-learners. As a result, studies have largely focused on a handful of species for which strong evidence for vocal learning exists. Recent studies, however, suggest a continuum in vocal learning capacity across taxa. Here, we further suggest that vocal learning is a multi-component behavioral phenotype comprised of distinct yet interconnected modules. Discretizing the vocal learning phenotype into its constituent modules would facilitate integration of findings across a wider diversity of species, taking advantage of the ways in which each excels in a particular module, or in a specific combination of features. Such comparative studies can improve understanding of the mechanisms and evolutionary origins of vocal learning. We propose an initial set of vocal learning modules supported by behavioral and neurobiological data and highlight the need for diversifying the field in order to disentangle the complexity of the vocal learning phenotype.

DOI:10.1016/j.neuron.2019.09.036
Short Title:Neuron
BioAcoustica ID: 
Scratchpads developed and conceived by (alphabetical): Ed Baker, Katherine Bouton Alice Heaton Dimitris Koureas, Laurence Livermore, Dave Roberts, Simon Rycroft, Ben Scott, Vince Smith