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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crroyalsociety:10.1098/rspb.2019.2014 2024-09-30T14:36:19+00:00 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 http://dx.doi.org/10.1098/rspb.2019.2014 https://royalsocietypublishing.org/doi/pdf/10.1098/rspb.2019.2014 https://royalsocietypublishing.org/doi/full-xml/10.1098/rspb.2019.2014 en eng The Royal Society https://royalsociety.org/journals/ethics-policies/data-sharing-mining/ Proceedings of the Royal Society B: Biological Sciences volume 286, issue 1917, page 20192014 ISSN 0962-8452 1471-2954 journal-article 2019 crroyalsociety https://doi.org/10.1098/rspb.2019.2014 2024-09-17T04:34:49Z 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 The Royal Society Proceedings of the Royal Society B: Biological Sciences 286 1917 20192014 |
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The Royal Society |
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crroyalsociety |
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English |
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. |
spellingShingle |
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 |
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 |
publisher |
The Royal Society |
publishDate |
2019 |
url |
http://dx.doi.org/10.1098/rspb.2019.2014 https://royalsocietypublishing.org/doi/pdf/10.1098/rspb.2019.2014 https://royalsocietypublishing.org/doi/full-xml/10.1098/rspb.2019.2014 |
genre |
Humpback Whale Megaptera novaeangliae |
genre_facet |
Humpback Whale Megaptera novaeangliae |
op_source |
Proceedings of the Royal Society B: Biological Sciences volume 286, issue 1917, page 20192014 ISSN 0962-8452 1471-2954 |
op_rights |
https://royalsociety.org/journals/ethics-policies/data-sharing-mining/ |
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 |
_version_ |
1811639408695181312 |