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Cognitive bias and affective state

Author

Listed:
  • Emma J. Harding

    (Centre for Behavioural Biology, University of Bristol)

  • Elizabeth S. Paul

    (Centre for Behavioural Biology, University of Bristol)

  • Michael Mendl

    (Centre for Behavioural Biology, University of Bristol)

Abstract

Information processing by humans can be biased by their emotions — for example, anxious and depressed people tend to make negative judgements about events and to interpret ambiguous stimuli unfavourably1,2,3,4. Here we show that such a 'pessimistic' response bias can also be measured in rats that are housed in unpredictable conditions5,6. Our findings indicate that cognitive bias can be used as an indicator of affective state in animals, which should facilitate progress in animal-welfare studies.

Suggested Citation

  • Emma J. Harding & Elizabeth S. Paul & Michael Mendl, 2004. "Cognitive bias and affective state," Nature, Nature, vol. 427(6972), pages 312-312, January.
    • Handle: RePEc:nat:nature:v:427:y:2004:i:6972:d:10.1038_427312a
    DOI: 10.1038/427312a
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    Cited by:

    1. Neil Garrett & Tali Sharot, 2014. "How Robust Is the Optimistic Update Bias for Estimating Self-Risk and Population Base Rates?," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-8, June.
    2. Alessandro V. M. Oliveira & Bruno F. Oliveira & Moises D. Vassallo, 2024. "Airport service quality perception and flight delays: examining the influence of psychosituational latent traits of respondents in passenger satisfaction surveys," Papers 2401.02139, arXiv.org.
    3. Rafal Rygula & Helena Pluta & Piotr Popik, 2012. "Laughing Rats Are Optimistic," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-6, December.
    4. Vanessa Kloke & Rebecca S Schreiber & Carina Bodden & Julian Möllers & Hanna Ruhmann & Sylvia Kaiser & Klaus-Peter Lesch & Norbert Sachser & Lars Lewejohann, 2014. "Hope for the Best or Prepare for the Worst? Towards a Spatial Cognitive Bias Test for Mice," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-12, August.
    5. Naïma Kasbaoui & Jonathan Cooper & Daniel S Mills & Oliver Burman, 2016. "Effects of Long-Term Exposure to an Electronic Containment System on the Behaviour and Welfare of Domestic Cats," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-20, September.
    6. Sicong Liu & Qingcheng Fan & Shanghao Liu & Chunjiang Zhao, 2022. "DepthFormer: A High-Resolution Depth-Wise Transformer for Animal Pose Estimation," Agriculture, MDPI, vol. 12(8), pages 1-13, August.
    7. Claire A Hales & Emma S J Robinson & Conor J Houghton, 2016. "Diffusion Modelling Reveals the Decision Making Processes Underlying Negative Judgement Bias in Rats," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-25, March.
    8. Marko Bračić & Lena Bohn & Viktoria Siewert & Vanessa T von Kortzfleisch & Holger Schielzeth & Sylvia Kaiser & Norbert Sachser & S Helene Richter, 2022. "Once an optimist, always an optimist? Studying cognitive judgment bias in mice," Behavioral Ecology, International Society for Behavioral Ecology, vol. 33(4), pages 775-788.
    9. Oliveira, Alessandro V.M. & Oliveira, Bruno F. & Vassallo, Moisés D., 2023. "Airport service quality perception and flight delays: Examining the influence of psychosituational latent traits of respondents in passenger satisfaction surveys," Research in Transportation Economics, Elsevier, vol. 102(C).
    10. Melissa J Starling & Nicholas Branson & Denis Cody & Timothy R Starling & Paul D McGreevy, 2014. "Canine Sense and Sensibility: Tipping Points and Response Latency Variability as an Optimism Index in a Canine Judgement Bias Assessment," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-15, September.

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