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  Modelling animal interactive rhythms in communication

Ravignani, A., & De Reus, K. (2019). Modelling animal interactive rhythms in communication. Evolutionary Bioinformatics, 15, 1-14. doi:10.1177/1176934318823558.

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Ravignani_DeReus_2019_Modelling animal interactive rhythms in communication.pdf (Publisher version), 2MB
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Ravignani_DeReus_2019_Modelling animal interactive rhythms in communication.pdf
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This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
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Ravignani_DeReus_2019suppl_Modelling animal interactive rhythms in communication.pdf (Supplementary material), 88KB
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 Creators:
Ravignani, Andrea1, 2, Author           
De Reus, Koen3, Author           
Affiliations:
1Vrije Universiteit Brussel, Brussels, Belgium, ou_persistent22              
2Comparative Bioacoustics, MPI for Psycholinguistics, Max Planck Society, ou_3217299              
3Erasmus University Rotterdam, Rotterdam, Netherlands, ou_persistent22              

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 Abstract: Time is one crucial dimension conveying information in animal communication. Evolution has shaped animals’ nervous systems to produce signals with temporal properties fitting their socio-ecological niches. Many quantitative models of mechanisms underlying rhythmic behaviour exist, spanning insects, crustaceans, birds, amphibians, and mammals. However, these computational and mathematical models are often presented in isolation. Here, we provide an overview of the main mathematical models employed in the study of animal rhythmic communication among conspecifics. After presenting basic definitions and mathematical formalisms, we discuss each individual model. These computational models are then compared using simulated data to uncover similarities and key differences in the underlying mechanisms found across species. Our review of the empirical literature is admittedly limited. We stress the need of using comparative computer simulations – both before and after animal experiments – to better understand animal timing in interaction. We hope this article will serve as a potential first step towards a common computational framework to describe temporal interactions in animals, including humans.

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Language(s): eng - English
 Dates: 2019
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: DOI: 10.1177/1176934318823558
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Title: Evolutionary Bioinformatics
Source Genre: Journal
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Publ. Info: London, England : Sage Publications Ltd.
Pages: - Volume / Issue: 15 Sequence Number: - Start / End Page: 1 - 14 Identifier: Other: 1176-9343
CoNE: https://pure.mpg.de/cone/journals/resource/1176-9343