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Exploring if Eyespot Tests can Replace Cognitive Judgement Bias Tasks when Assessing Affective State in Red Junglefowl chicks

We can describe cognition as the mental processes involved when processing signals and information from our surroundings. Despite being vital for our actions, these processes can be biased by emotions, which results in a judgement bias of ambiguous information. Depressed individuals tend to be pessimistic about such ambiguous information, while individuals under normal or good condition, tend to be optimistic. This is true also for animals. Based on this, cognitive judgement bias tests are developed to measure the affective state of individuals. However, cognitive judgement bias tests require extensive pre-test training for animals to learn positive and negative reference cues. An alternative to using responses to pre-learnt cues could be to use naturally aversive stimuli instead. Eyespot patterns on lepidopterans can be aversive to birds. However, it is scarcely investigated if eyespot patterns can be used to measure affective state. The aim of my study was therefore to investigate if eyespots patterns can replace classic cues in cognitive judgment bias tests measuring affective state. I did so by comparing behavioural responses of red junglefowl chicks (Gallus gallus) to both eyespot patterns and classical cues in a cognitive judgement bias test. Responses correlated between some cues in the two tests, suggesting that eyespot patterns may work as a replacement of pre-learnt cues. However, no differences in responses to the eyespot patterns was found, and so further work is needed to improve the design of eyespot cues to obtain a clearer correlation between responses to eyespot patterns and classical pre-learnt cues in cognitive judgement bias tests. As less training is needed, such improved tests could have positive implications, and be a simpler and more user-friendly way to measure affective state in animals.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-183000
Date January 2022
CreatorsGalmor, Vanessa
PublisherLinköpings universitet, Institutionen för fysik, kemi och biologi
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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