A novel test for evaluating horses’ spontaneous visual attention is predictive of attention in operant learning tasks

A novel test for evaluating horses’ spontaneous visual attention is predictive of attention in... Attention is described as the ability to process selectively one aspect of the environment over others. In this study, we characterized horses’ spontaneous attention by designing a novel visual attention test (VAT) that is easy to apply in the animal’s home environment. The test was repeated over three consecutive days and repeated again 6 months later in order to assess inter-individual variations and intra-individual stability. Different patterns of attention have been revealed: ‘overall’ attention when the horse merely gazed at the stimulus and ‘fixed’ attention characterized by fixity and orientation of at least the visual and auditory organs towards the stimulus. The individual attention characteristics remained consistent over time (after 6 months, Spearman correlation test, P < 0.05). The validity of this novel test as a predictor of individual attentional skills was assessed by comparing the results, for the same horses, with those obtained in both a ‘classical’ experimental attention test the ‘five-choice serial reaction time task’ (5-CSRTT) and a work situation (lunge working context). Our results revealed that (i) individual variations remained consistent across tests and (ii) the VAT attention measures were not only predictive of attentional skills but also of learning abilities. Differences appeared however between the first day of testing and the following test days: attention structure on the second day was predictive of learning abilities, attention performances in the 5-CSRRT and at work. The VAT appears as a promising easy-to-use tool to assess animals’ attention characteristics and the impact of different factors of variation on attention. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Naturwissenschaften Springer Journals

A novel test for evaluating horses’ spontaneous visual attention is predictive of attention in operant learning tasks

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by Springer-Verlag GmbH Germany
Subject
Life Sciences; Life Sciences, general; Environment, general
ISSN
0028-1042
eISSN
1432-1904
D.O.I.
10.1007/s00114-017-1480-6
Publisher site
See Article on Publisher Site

Abstract

Attention is described as the ability to process selectively one aspect of the environment over others. In this study, we characterized horses’ spontaneous attention by designing a novel visual attention test (VAT) that is easy to apply in the animal’s home environment. The test was repeated over three consecutive days and repeated again 6 months later in order to assess inter-individual variations and intra-individual stability. Different patterns of attention have been revealed: ‘overall’ attention when the horse merely gazed at the stimulus and ‘fixed’ attention characterized by fixity and orientation of at least the visual and auditory organs towards the stimulus. The individual attention characteristics remained consistent over time (after 6 months, Spearman correlation test, P < 0.05). The validity of this novel test as a predictor of individual attentional skills was assessed by comparing the results, for the same horses, with those obtained in both a ‘classical’ experimental attention test the ‘five-choice serial reaction time task’ (5-CSRTT) and a work situation (lunge working context). Our results revealed that (i) individual variations remained consistent across tests and (ii) the VAT attention measures were not only predictive of attentional skills but also of learning abilities. Differences appeared however between the first day of testing and the following test days: attention structure on the second day was predictive of learning abilities, attention performances in the 5-CSRRT and at work. The VAT appears as a promising easy-to-use tool to assess animals’ attention characteristics and the impact of different factors of variation on attention.

Journal

NaturwissenschaftenSpringer Journals

Published: Jul 5, 2017

References

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