Andrea Ravignani

Publications

Displaying 1 - 8 of 8
  • Ravignani, A., & Thompson, B. (2017). A note on ‘Noam Chomsky – What kind of creatures are we? Language in Society, 46(3), 446-447. doi:10.1017/S0047404517000288.
  • Ravignani, A., Honing, H., & Kotz, S. A. (2017). Editorial: The evolution of rhythm cognition: Timing in music and speech. Frontiers in Human Neuroscience, 11: 303. doi:10.3389/fnhum.2017.00303.

    Abstract

    This editorial serves a number of purposes. First, it aims at summarizing and discussing 33 accepted contributions to the special issue “The evolution of rhythm cognition: Timing in music and speech.” The major focus of the issue is the cognitive neuroscience of rhythm, intended as a neurobehavioral trait undergoing an evolutionary process. Second, this editorial provides the interested reader with a guide to navigate the interdisciplinary contributions to this special issue. For this purpose, we have compiled Table 1, where methods, topics, and study species are summarized and related across contributions. Third, we also briefly highlight research relevant to the evolution of rhythm that has appeared in other journals while this special issue was compiled. Altogether, this editorial constitutes a summary of rhythm research in music and speech spanning two years, from mid-2015 until mid-2017
  • Ravignani, A., & Sonnweber, R. (2017). Chimpanzees process structural isomorphisms across sensory modalities. Cognition, 161, 74-79. doi:10.1016/j.cognition.2017.01.005.
  • Ravignani, A., Gross, S., Garcia, M., Rubio-Garcia, A., & De Boer, B. (2017). How small could a pup sound? The physical bases of signaling body size in harbor seals. Current Zoology, 63(4), 457-465. doi:10.1093/cz/zox026.

    Abstract

    Vocal communication is a crucial aspect of animal behavior. The mechanism which most mammals use to vocalize relies on three anatomical components. First, air overpressure is generated inside the lower vocal tract. Second, as the airstream goes through the glottis, sound is produced via vocal fold vibration. Third, this sound is further filtered by the geometry and length of the upper vocal tract. Evidence from mammalian anatomy and bioacoustics suggests that some of these three components may covary with an animal’s body size. The framework provided by acoustic allometry suggests that, because vocal tract length (VTL) is more strongly constrained by the growth of the body than vocal fold length (VFL), VTL generates more reliable acoustic cues to an animal’s size. This hypothesis is often tested acoustically but rarely anatomically, especially in pinnipeds. Here, we test the anatomical bases of the acoustic allometry hypothesis in harbor seal pups Phoca vitulina. We dissected and measured vocal tract, vocal folds, and other anatomical features of 15 harbor seals post-mortem. We found that, while VTL correlates with body size, VFL does not. This suggests that, while body growth puts anatomical constraints on how vocalizations are filtered by harbor seals’ vocal tract, no such constraints appear to exist on vocal folds, at least during puppyhood. It is particularly interesting to find anatomical constraints on harbor seals’ vocal tracts, the same anatomical region partially enabling pups to produce individually distinctive vocalizations.
  • Ravignani, A., & Norton, P. (2017). Measuring rhythmic complexity: A primer to quantify and compare temporal structure in speech, movement, and animal vocalizations. Journal of Language Evolution, 2(1), 4-19. doi:10.1093/jole/lzx002.

    Abstract

    Research on the evolution of human speech and phonology benefits from the comparative approach: structural, spectral, and temporal features can be extracted and compared across species in an attempt to reconstruct the evolutionary history of human speech. Here we focus on analytical tools to measure and compare temporal structure in human speech and animal vocalizations. We introduce the reader to a range of statistical methods usable, on the one hand, to quantify rhythmic complexity in single vocalizations, and on the other hand, to compare rhythmic structure between multiple vocalizations. These methods include: time series analysis, distributional measures, variability metrics, Fourier transform, auto- and cross-correlation, phase portraits, and circular statistics. Using computer-generated data, we apply a range of techniques, walking the reader through the necessary software and its functions. We describe which techniques are most appropriate to test particular hypotheses on rhythmic structure, and provide possible interpretations of the tests. These techniques can be equally well applied to find rhythmic structure in gesture, movement, and any other behavior developing over time, when the research focus lies on its temporal structure. This introduction to quantitative techniques for rhythm and timing analysis will hopefully spur additional comparative research, and will produce comparable results across all disciplines working on the evolution of speech, ultimately advancing the field.

    Additional information

    lzx002_Supp.docx
  • Ravignani, A. (2017). Interdisciplinary debate: Agree on definitions of synchrony [Correspondence]. Nature, 545, 158. doi:10.1038/545158c.
  • Ravignani, A., & Madison, G. (2017). The paradox of isochrony in the evolution of human rhythm. Frontiers in Psychology, 8: 1820. doi:10.3389/fpsyg.2017.01820.

    Abstract

    Isochrony is crucial to the rhythm of human music. Some neural, behavioral and anatomical traits underlying rhythm perception and production are shared with a broad range of species. These may either have a common evolutionary origin, or have evolved into similar traits under different evolutionary pressures. Other traits underlying rhythm are rare across species, only found in humans and few other animals. Isochrony, or stable periodicity, is common to most human music, but isochronous behaviors are also found in many species. It appears paradoxical that humans are particularly good at producing and perceiving isochronous patterns, although this ability does not conceivably confer any evolutionary advantage to modern humans. This article will attempt to solve this conundrum. To this end, we define the concept of isochrony from the present functional perspective of physiology, cognitive neuroscience, signal processing, and interactive behavior, and review available evidence on isochrony in the signals of humans and other animals. We then attempt to resolve the paradox of isochrony by expanding an evolutionary hypothesis about the function that isochronous behavior may have had in early hominids. Finally, we propose avenues for empirical research to examine this hypothesis and to understand the evolutionary origin of isochrony in general.
  • Ravignani, A. (2017). Visualizing and interpreting rhythmic patterns using phase space plots. Music Perception, 34(5), 557-568. doi:10.1525/MP.2017.34.5.557.

    Abstract

    STRUCTURE IN MUSICAL RHYTHM CAN BE MEASURED using a number of analytical techniques. While some techniques—like circular statistics or grammar induction—rely on strong top-down assumptions, assumption-free techniques can only provide limited insights on higher-order rhythmic structure. I suggest that research in music perception and performance can benefit from systematically adopting phase space plots, a visualization technique originally developed in mathematical physics that overcomes the aforementioned limitations. By jointly plotting adjacent interonset intervals (IOI), the motivic rhythmic structure of musical phrases, if present, is visualized geometrically without making any a priori assumptions concerning isochrony, beat induction, or metrical hierarchies. I provide visual examples and describe how particular features of rhythmic patterns correspond to geometrical shapes in phase space plots. I argue that research on music perception and systematic musicology stands to benefit from this descriptive tool, particularly in comparative analyses of rhythm production. Phase space plots can be employed as an initial assumption-free diagnostic to find higher order structures (i.e., beyond distributional regularities) before proceeding to more specific, theory-driven analyses.

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