Evidence map›Paper›PMID 25143037›Full record

ArticleProceedings. Biological sciences2014

Animal vocal sequences: not the Markov chains we thought they were.

Arik Kershenbaum, Ann E Bowles, Todd M Freeberg, Dezhe Z Jin, Adriano R Lameira, Kirsten Bohn

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed.

  1. Language-like properties in the vocal behavior of animals.Current opinion in neurobiology · 2026
    Review
  2. Article
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  7. Article
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  10. Language-like efficiency and structure in house finch song.Proceedings. Biological sciences · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Multi-level combinatoriality in magpie non-song vocalizations.Journal of the Royal Society, Interface · 2023
    Article
  16. Animal linguistics: a primer.Biological reviews of the Cambridge Philosophical Society · 2023
    Article
  17. Article
  18. Article
  19. Long-distance dependencies in birdsong syntax.Proceedings. Biological sciences · 2022
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Arik KershenbaumNational Institute for Mathematical and Biological Synthesis, Knoxville, TN, USA arik@nimbios.org.
Ann E BowlesHubbs SeaWorld Research Institute, San Diego, CA 92109, USA.
Todd M FreebergDepartment of Psychology, University of Tennessee, Knoxville, TN, USA.
Dezhe Z JinDepartment of Physics and the Center for Neural Engineering, Penn State University, University Park, PA, USA.
Adriano R LameiraInstitute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Sciencepark 904, 1098 XH, Amsterdam, The Netherlands Pongo Foundation, Papenhoeflaan 91, 3421 XN, Oudewater, The Netherlands.
Kirsten BohnDepartment of Biological Sciences, Florida International University, Miami, FL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many animals produce vocal sequences that appear complex. Most researchers assume that these sequences are well characterized as Markov chains (i.e. that the probability of a particular vocal element can be calculated from the history of only a finite number of preceding elements). However, this assumption has never been explicitly tested. Furthermore, it is unclear how language could evolve in a single step from a Markovian origin, as is frequently assumed, as no intermediate forms have been found between animal communication and human language. Here, we assess whether animal taxa produce vocal sequences that are better described by Markov chains, or by non-Markovian dynamics such as the 'renewal process' (RP), characterized by a strong tendency to repeat elements. We examined vocal sequences of seven taxa: Bengalese finches Lonchura striata domestica, Carolina chickadees Poecile carolinensis, free-tailed bats Tadarida brasiliensis, rock hyraxes Procavia capensis, pilot whales Globicephala macrorhynchus, killer whales Orcinus orca and orangutans Pongo spp. The vocal systems of most of these species are more consistent with a non-Markovian RP than with the Markovian models traditionally assumed. Our data suggest that non-Markovian vocal sequences may be more common than Markov sequences, which must be taken into account when evaluating alternative hypotheses for the evolution of signalling complexity, and perhaps human language origins.

Indexed as

Models, StatisticalAnimalsBiological EvolutionMammalsMarkov ChainsPasseriformesSound SpectrographySpecies SpecificityVocalization, Animallanguage evolutionrenewal processvocal complexity

Identifiers

PMID25143037
PMCPMC4150325

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.