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Developing a 3-choice serial reaction time task for examining neural and cognitive function in an equine model.

Kirsty Roberts1, Andrew J Hemmings1, Sebastian D McBride2

  • 1Royal Agricultural University, Stroud Road, Cirencester, Gloucestershire GL7 6JS, United Kingdom.

Journal of Neuroscience Methods
|February 10, 2017
PubMed
Summary

A novel automated system was developed to assess cognitive function in horses, a large animal model for human neurological disorders. This technology successfully validated cognitive testing in horses, supporting their use in research.

Keywords:
3-CSRTTCognitionHorseLearningOperantTourette’s syndrome

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Area of Science:

  • Neuroscience
  • Animal Cognition
  • Comparative Psychology

Background:

  • Large animal models offer advantages over rodents for studying human neurological disorders due to their complex neuroanatomy and longevity.
  • Horses exhibit spontaneous stereotypic behaviors analogous to compulsive and impulsive actions seen in human neurological conditions like Tourette's syndrome.
  • Cognitive testing in horses provides a non-invasive method to investigate brain function relevant to human neurological and psychiatric conditions.

Purpose of the Study:

  • To develop and validate a fully-automated, mobile operant system for assessing cognitive function in horses.
  • To establish horses as a viable large animal model for studying human neurological dysfunction.

Main Methods:

  • Development of a mobile automated operant system capable of presenting visual and auditory stimuli and delivering food rewards.
  • Validation of the system using a three-choice serial reaction time task (3-CSRTT) with ten horses.
  • This represents the first mobile, fully automated system for cognitive examination in horses.

Main Results:

  • All ten horses successfully learned the cognitive task, reaching the learning criterion within an average of 16.30±0.79 sessions over three days.
  • Consistent high performance was maintained during six probe sessions, with accuracy levels at 80.67±0.57% (mean±SEM).

Conclusions:

  • A fully-automated operant system for mobile cognitive assessment in large animal models, specifically horses, has been successfully designed and validated.
  • Horses serve as a valuable complementary model to rodents for investigating human neurological disorders.