Seeking shared ground in space

language; communication; extraterrestria

Chronometry for the chorusing herd: Hamilton's legacy on context-dependent acoustic signalling—a comment on Herbers (2013)

Biology Letters’ special feature on Hamilton’s legacy pays due tribute to a brilliant mind. Herbers [1] and the other contributors paint a compelling picture of how Hamilton’s work on inclusive fitness anticipated much contemporary evolutionary thinking, although sometimes not acknowledged until much later. A more recent, although equally cited work by Hamilton is the ‘Geometry for the selfish herd’ [2], an elegant mathematical description of why individuals aggregate in space. In the spirit of this special feature [1], I illustrate why Hamilton’s herd model should be recognized as an early mathematical formal- ism applicable to unrelated, although crucial, biological phenomena. Notably, Hamilton’s model of gregarious behaviour can be directly applied to the prob- lem of context-dependent acoustic signalling as follows, with the potential to describe how interdependent individual calls combine into choruses

Darwin, sexual selection, and the origins of music

Humans devote ample time to produce and perceive music. How and why this behavioral propensity originated in our species is unknown. For centuries, speculation dominated the study of the evolutionary origins of musicality. Following Darwin’s early intuitions, recent empirical research is opening a new chapter to tackle this mystery

The evolutionary biology of dance without frills

Recently psychologists have taken up the question of whether dance is reliant on unique human adaptations, or whether it is rooted in neural and cognitive mechanisms shared with other species 1, 2. In its full cultural complexity, human dance clearly has no direct analog in animal behavior. Most definitions of dance include the consistent production of movement sequences timed to an external rhythm. While not sufficient for dance, modes of auditory-motor timing, such as synchronization and entrainment, are experimentally tractable constructs that may be analyzed and compared between species. In an effort to assess the evolutionary precursors to entrainment and social features of human dance, Laland and colleagues [2] have suggested that dance may be an incidental byproduct of adaptations supporting vocal or motor imitation — referred to here as the ‘imitation and sequencing’ hypothesis. In support of this hypothesis, Laland and colleagues rely on four convergent lines of evidence drawn from behavioral and neurobiological research on dance behavior in humans and rhythmic behavior in other animals. Here, we propose a less cognitive, more parsimonious account for the evolution of dance. Our ‘timing and interaction’ hypothesis suggests that dance is scaffolded off of broadly conserved timing mechanisms allowing both cooperative and antagonistic social coordination

Sonification of experimental parameters as a new method for efficient coding of behavior

Cognitive research is often focused on experimental condition-driven reactions. Ethological studies frequently rely on the observation of naturally occurring specific behaviors. In both cases, subjects are filmed during the study, so that afterwards behaviors can be coded on video. Coding should typically be blind to experimental conditions, but often requires more information than that present on video. We introduce a method for blindcoding of behavioral videos that takes care of both issues via three main innovations. First, of particular significance for playback studies, it allows creation of a “soundtrack” of the study, that is, a track composed of synthesized sounds representing different aspects of the experimental conditions, or other events, over time. Second, it facilitates coding behavior using this audio track, together with the possibly muted original video. This enables coding blindly to conditions as required, but not ignoring other relevant events. Third, our method makes use of freely available, multi-platform software, including scripts we developed

Evaluating the role of quantitative modeling in language evolution

Models are a flourishing and indispensable area of research in language evolution. Here we highlight critical issues in using and interpreting models, and suggest viable approaches. First, contrasting models can explain the same data and similar modelling techniques can lead to diverging conclusions. This should act as a reminder to use the extreme malleability of modelling parsimoniously when interpreting results. Second, quantitative techniques similar to those used in modelling language evolution have proven themselves inadequate in other disciplines. Cross-disciplinary fertilization is crucial to avoid mistakes which have previously occurred in other areas. Finally, experimental validation is necessary both to sharpen models' hypotheses, and to support their conclusions. Our belief is that models should be interpreted as quantitative demonstrations of logical possibilities, rather than as direct sources of evidence. Only an integration of theoretical principles, quantitative proofs and empirical validation can allow research in the evolution of language to progress

Rhythm and synchrony in animal movement and communication

Animal communication and motoric behavior develop over time. Often, this temporal dimension has communicative relevance and is organized according to structural patterns. In other words, time is a crucial dimension for rhythm and synchrony in animal movement and communication. Rhythm is defined as temporal structure at a second-millisecond time scale (Kotz et al. 2018). Synchrony is defined as precise co-occurrence of 2 behaviors in time (Ravignani 2017). Rhythm, synchrony, and other forms of temporal interaction are taking center stage in animal behavior and communication. Several critical questions include, among others: what species show which rhythmic predispositions? How does a species’ sensitivity for, or proclivity towards, rhythm arise? What are the species-specific functions of rhythm and synchrony, and are there functional trends across species? How did similar or different rhythmic behaviors evolved in different species? This Special Column aims at collecting and contrasting research from different species, perceptual modalities, and empirical methods. The focus is on timing, rhythm and synchrony in the second-millisecond range. Three main approaches are commonly adopted to study animal rhythms, with a focus on: 1) spontaneous individual rhythm production, 2) group rhythms, or 3) synchronization experiments. I concisely introduce them below (see also Kotz et al. 2018; Ravignani et al. 2018)