Modelling Animal Interactive Rhythms in Communication

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.

Interactive rhythms in the wild, in the brain, and in silico.

“…Alternative, competing hypotheses on how the seal pup would react to rhythmic playbacks included 1) an arousal mechanism, by which an individual hearing more calls responds with more calls, with no rhythmic adaptation at all; the focal animal and the playback stimulus might have the same number of calls, which, however, do not have a systematic relation between their onsets; 2) adaptive synchrony, as often seen in human movement, by which an individual modifies the rate and delay of its behaviors so that they occur at the same time as those of a conspecific; 3) phase delay, as attested in bush crickets, which is based on a simple internal oscillator triggering sound production that gets reset every time a conspecific is heard; and 4) antisynchrony, as indirectly predicted by a classical theoretical model, by which an individual will modify the rate and delay of its calls so that they occur at a fraction of the period of a conspecific (Hamilton, 1971; Merker, Madison, & Eckerdal, 2009; Ravignani, 2014; Ravignani & de Reus, 2019).…”

Rhythm and synchrony in animal movement and communication

“…If these conditions hold, circular statistics enable testing the relative phase delay of an individual behavior with respect to the constant period length of another individual’s behavior (see e.g., Cook et al. 2013; Ravignani and de Reus in press). A possible visual counterpart of circular statistics is the rose plot (e.g., Cook et al.…”

“…A possible visual counterpart of circular statistics is the rose plot (e.g., Cook et al. 2013; Ravignani and de Reus in press): a clock-like histogram showing how often an individual phase delay occurs relative to another individual or a metronomic stimulus. Finally, a few techniques from physics, such as the Allan Factor and burstiness, appear quite promising for quantifying rhythmicity and interactivity of behaviors in time (Goh and Barabási 2008; Kello et al.…”

“…Fifth, rhythmic interactivity appears to have taken center stage (see also Pika et al 2018; Ravignani and de Reus in press; Ruch et al 2018). All papers in this issue, together with several others which appeared over the last few years, deal with interactive rhythms.…”