Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song

Vocal communication systems have a set of rules that govern the arrangement of acoustic signals, broadly defined as ‘syntax’. However, there is a limited understanding of potentially shared or analogous rules across vocal displays in different taxa. Recent work on songbirds has investigated syntax u...

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Published in:Proceedings of the Royal Society B: Biological Sciences
Main Authors: Allen, Jenny A., Garland, Ellen C., Dunlop, Rebecca A., Noad, Michael J.
Format: Article in Journal/Newspaper
Language:English
Published: 2019
Subjects:
Online Access:https://risweb.st-andrews.ac.uk/portal/en/researchoutput/network-analysis-reveals-underlying-syntactic-features-in-a-vocally-learnt-mammalian-display-humpback-whale-song(e80ce595-4020-4a6b-ac9e-17b88ca3f7c9).html
https://doi.org/10.1098/rspb.2019.2014
https://research-repository.st-andrews.ac.uk/bitstream/10023/19288/1/Allen_2019_PRSB_Networkanalysis_AAM.pdf
https://research-repository.st-andrews.ac.uk/bitstream/10023/19288/2/SupplMaterial_PRSB.pdf
id ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/e80ce595-4020-4a6b-ac9e-17b88ca3f7c9
record_format openpolar
spelling ftunstandrewcris:oai:risweb.st-andrews.ac.uk:publications/e80ce595-4020-4a6b-ac9e-17b88ca3f7c9 2023-05-15T16:35:56+02:00 Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song Allen, Jenny A. Garland, Ellen C. Dunlop, Rebecca A. Noad, Michael J. 2019-12-18 application/pdf https://risweb.st-andrews.ac.uk/portal/en/researchoutput/network-analysis-reveals-underlying-syntactic-features-in-a-vocally-learnt-mammalian-display-humpback-whale-song(e80ce595-4020-4a6b-ac9e-17b88ca3f7c9).html https://doi.org/10.1098/rspb.2019.2014 https://research-repository.st-andrews.ac.uk/bitstream/10023/19288/1/Allen_2019_PRSB_Networkanalysis_AAM.pdf https://research-repository.st-andrews.ac.uk/bitstream/10023/19288/2/SupplMaterial_PRSB.pdf eng eng info:eu-repo/semantics/openAccess Allen , J A , Garland , E C , Dunlop , R A & Noad , M J 2019 , ' Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song ' , Proceedings of the Royal Society B: Biological Sciences , vol. 286 , no. 1917 , 20192014 . https://doi.org/10.1098/rspb.2019.2014 Vocal learning Network modelling Syntax Humpback whale Song article 2019 ftunstandrewcris https://doi.org/10.1098/rspb.2019.2014 2021-12-26T14:35:56Z Vocal communication systems have a set of rules that govern the arrangement of acoustic signals, broadly defined as ‘syntax’. However, there is a limited understanding of potentially shared or analogous rules across vocal displays in different taxa. Recent work on songbirds has investigated syntax using network-based modelling. This technique quantifies features such as connectivity (adjacent signals in a sequence) and recurring patterns. Here, we apply network-based modelling to the complex, hierarchically structured songs of humpback whales ( Megaptera novaeangliae ) from east Australia. Given the song's annual evolving pattern and the cultural conformity of males within a population, network modelling captured the patterns of multiple song types over 13 consecutive years. Song arrangements in each year displayed clear ‘small-world’ network structure, characterized by clusters of highly connected sounds. Transitions between these connected sounds further suggested a combination of both structural stability and variability. Small-world network structure within humpback songs may facilitate the characteristic and persistent vocal learning observed. Similar small-world structures and transition patterns are found in several birdsong displays, indicating common syntactic patterns among vocal learning in multiple taxa. Understanding the syntactic rules governing vocal displays in multiple, independently evolving lineages may indicate what rules or structural features are important to the evolution of complex communication, including human language. Article in Journal/Newspaper Humpback Whale Megaptera novaeangliae University of St Andrews: Research Portal Proceedings of the Royal Society B: Biological Sciences 286 1917 20192014
institution Open Polar
collection University of St Andrews: Research Portal
op_collection_id ftunstandrewcris
language English
topic Vocal learning
Network modelling
Syntax
Humpback whale
Song
spellingShingle Vocal learning
Network modelling
Syntax
Humpback whale
Song
Allen, Jenny A.
Garland, Ellen C.
Dunlop, Rebecca A.
Noad, Michael J.
Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
topic_facet Vocal learning
Network modelling
Syntax
Humpback whale
Song
description Vocal communication systems have a set of rules that govern the arrangement of acoustic signals, broadly defined as ‘syntax’. However, there is a limited understanding of potentially shared or analogous rules across vocal displays in different taxa. Recent work on songbirds has investigated syntax using network-based modelling. This technique quantifies features such as connectivity (adjacent signals in a sequence) and recurring patterns. Here, we apply network-based modelling to the complex, hierarchically structured songs of humpback whales ( Megaptera novaeangliae ) from east Australia. Given the song's annual evolving pattern and the cultural conformity of males within a population, network modelling captured the patterns of multiple song types over 13 consecutive years. Song arrangements in each year displayed clear ‘small-world’ network structure, characterized by clusters of highly connected sounds. Transitions between these connected sounds further suggested a combination of both structural stability and variability. Small-world network structure within humpback songs may facilitate the characteristic and persistent vocal learning observed. Similar small-world structures and transition patterns are found in several birdsong displays, indicating common syntactic patterns among vocal learning in multiple taxa. Understanding the syntactic rules governing vocal displays in multiple, independently evolving lineages may indicate what rules or structural features are important to the evolution of complex communication, including human language.
format Article in Journal/Newspaper
author Allen, Jenny A.
Garland, Ellen C.
Dunlop, Rebecca A.
Noad, Michael J.
author_facet Allen, Jenny A.
Garland, Ellen C.
Dunlop, Rebecca A.
Noad, Michael J.
author_sort Allen, Jenny A.
title Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
title_short Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
title_full Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
title_fullStr Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
title_full_unstemmed Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
title_sort network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
publishDate 2019
url https://risweb.st-andrews.ac.uk/portal/en/researchoutput/network-analysis-reveals-underlying-syntactic-features-in-a-vocally-learnt-mammalian-display-humpback-whale-song(e80ce595-4020-4a6b-ac9e-17b88ca3f7c9).html
https://doi.org/10.1098/rspb.2019.2014
https://research-repository.st-andrews.ac.uk/bitstream/10023/19288/1/Allen_2019_PRSB_Networkanalysis_AAM.pdf
https://research-repository.st-andrews.ac.uk/bitstream/10023/19288/2/SupplMaterial_PRSB.pdf
genre Humpback Whale
Megaptera novaeangliae
genre_facet Humpback Whale
Megaptera novaeangliae
op_source Allen , J A , Garland , E C , Dunlop , R A & Noad , M J 2019 , ' Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song ' , Proceedings of the Royal Society B: Biological Sciences , vol. 286 , no. 1917 , 20192014 . https://doi.org/10.1098/rspb.2019.2014
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1098/rspb.2019.2014
container_title Proceedings of the Royal Society B: Biological Sciences
container_volume 286
container_issue 1917
container_start_page 20192014
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