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Updated: Feb 10, 2026

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Social information in equine movement gestalts.

Christoph D Dahl1, Christa Wyss2, Klaus Zuberbühler3,4

  • 1Institute of Biology, University of Neuchâtel, Rue Emile-Argand 11, 2000, Neuchâtel, Switzerland. christoph.dahl@unine.ch.

Animal Cognition
|May 26, 2018
PubMed
Summary

Horses

Keywords:
Animal communicationHorse cognitionMovement gestaltPhylogenetic ritualizationSignal evolution

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Area of Science:

  • Ethology and Animal Behavior
  • Evolutionary Biology
  • Machine Learning in Biology

Background:

  • Signal evolution theories propose that behaviors can gain communicative value detached from original functions.
  • This transition may be constrained by signaling costs, such as predation risk.
  • Understanding social information transfer in group-living animals is crucial.

Purpose of the Study:

  • To investigate if kinematic movement patterns in horses convey rich social information.
  • To explore the potential of machine learning in analyzing animal movement for behavioral insights.
  • To examine how movement gestalts relate to signal evolution theories.

Main Methods:

  • Collected inertial movement sensing data from free-ranging horses (Equus caballus) at multiple locations.
  • Applied a machine learning algorithm to extract kinematic gestalt profiles from movement data.
  • Analyzed movement patterns to identify individual characteristics and social information.

Main Results:

  • Successfully extracted multi-layered information from horse movement patterns.
  • Discriminated between individual horses based on identity, breed, sex, and personality traits from movement data.
  • Demonstrated that movement gestalts provide a rich source of passively available social information.

Conclusions:

  • Domestic horses, and likely other group-living animals, can access substantial social information through movement gestalts.
  • Movement patterns serve as a reliable, passively transmitted source of information about conspecifics.
  • Findings contribute to understanding signal evolution, particularly concerning the communicative value of movement.