Autonomous choice in the learning process of a turtle Chinemys reevesii

Shusaku Nomura, Yukio Pegio Gunji

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

We studied animal's learning of spatial discrimination in an experimental environment. Turtles, Chinemys reevesii, were employed for the study. We focused on two independent aspects: (1) turtle's success rate in the task, which is the most common criterion to estimate the ability of the animals, and (2) the statistical properties of the time interval of the task, which is independent on the spatial criterion. For a statistical analysis, we employed the scheme of power law distributions which was recently used to estimate animal behaviors in relation to the idea of the fractal. We addressed the basic problem of whether these two criteria, or any other criteria for this matter, could or could not exclude an observer who studies the animal behavior. To demonstrate inseparability of an observer and the object, we conducted three different learning experiments: (1) complete spatial discrimination, (2) incomplete spatial discrimination, (3) another, different, complete discrimination, in this order. The incomplete one was taken to mean incomplete only for an observer. Our experiments reveal that the same result (success rate) was perceived differently by the animal if the attitude of the observer to the experiments differed. This observation comes to suggest that the notion of autonomous choice on the part of an animal is contingent upon the inseparability between an observer and the object. (C) 2000 Elsevier Science Ireland Ltd.

Original languageEnglish
Pages (from-to)33-42
Number of pages10
JournalBioSystems
Volume56
Issue number1
DOIs
Publication statusPublished - 2000 Mar 1

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Keywords

  • Autonomous choice
  • Discrimination learning
  • Power law
  • Zipf analysis

ASJC Scopus subject areas

  • Statistics and Probability
  • Modelling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Applied Mathematics

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