ArticleEvolutionary bioinformatics online2019
Modelling Animal Interactive Rhythms in Communication.
Article in Evolutionary bioinformatics online, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Social Context Matters for Turn-Taking Dynamics: A Comparative Study of Autistic and Typically Developing Children.Cognitive science · 2025Article
- The Development of Turn-Taking Skills in Typical Development and Autism.Cognitive science · 2025Article
- Rhythmic Roots: The Adaptive Functions of Vocal Isochrony and Its Role in Human Music and Language Evolution.Psihologijske teme = Psychological themes = Psychological topics · 2025Article
- Rhythm and synchrony in animal movement and communication.Current zoology · 2019Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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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