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Assessing animal affect: an automated and self-initiated judgement bias task based on natural investigative behaviour

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Assessing animal affect : an automated and self-initiated judgement bias task based on natural investigative behaviour. / Jones, Samantha; Neville, Vikki; Higgs, Laura; Paul, Elizabeth S.; Dayan, Peter; Robinson, Emma S.J.; Mendl, Michael.

In: Scientific Reports, Vol. 8, 12400, 17.08.2018.

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@article{1fb4fdb6b9e54284b3a03cdb4f93e8fa,
title = "Assessing animal affect: an automated and self-initiated judgement bias task based on natural investigative behaviour",
abstract = "Scientific methods for assessing animal affect, especially affective valence (positivity or negativity), allow us to evaluate animal welfare and the effectiveness of 3Rs Refinements designed to improve wellbeing. Judgement bias tasks measure valence; however, task-training may be lengthy and/or require significant time from researchers. Here we develop an automated and self-initiated judgement bias task for rats which capitalises on their natural investigative behaviour. Rats insert their noses into a food trough to start trials. They then hear a tone and learn either to stay for 2 s to receive a food reward or to withdraw promptly to avoid an air-puff. Which contingency applies is signalled by two different tones. Judgement bias is measured by responses to intermediate ambiguous tones. In two experiments we show that rats learn the task in fewer sessions than other automated variants, generalise responses across ambiguous tones as expected, self-initiate 4–5 trials/min, and can be tested repeatedly. Affect manipulations generate main effect trends in the predicted directions, although not localised to ambiguous tones, so further construct validation is required. We also find that tone-reinforcer pairings and reinforcement or non-reinforcement of ambiguous trials can affect responses to ambiguity. This translatable task should facilitate more widespread uptake of judgement bias testing.",
author = "Samantha Jones and Vikki Neville and Laura Higgs and Paul, {Elizabeth S.} and Peter Dayan and Robinson, {Emma S.J.} and Michael Mendl",
year = "2018",
month = "8",
day = "17",
doi = "10.1038/s41598-018-30571-x",
language = "English",
volume = "8",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Springer Nature",

}

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TY - JOUR

T1 - Assessing animal affect

T2 - an automated and self-initiated judgement bias task based on natural investigative behaviour

AU - Jones, Samantha

AU - Neville, Vikki

AU - Higgs, Laura

AU - Paul, Elizabeth S.

AU - Dayan, Peter

AU - Robinson, Emma S.J.

AU - Mendl, Michael

PY - 2018/8/17

Y1 - 2018/8/17

N2 - Scientific methods for assessing animal affect, especially affective valence (positivity or negativity), allow us to evaluate animal welfare and the effectiveness of 3Rs Refinements designed to improve wellbeing. Judgement bias tasks measure valence; however, task-training may be lengthy and/or require significant time from researchers. Here we develop an automated and self-initiated judgement bias task for rats which capitalises on their natural investigative behaviour. Rats insert their noses into a food trough to start trials. They then hear a tone and learn either to stay for 2 s to receive a food reward or to withdraw promptly to avoid an air-puff. Which contingency applies is signalled by two different tones. Judgement bias is measured by responses to intermediate ambiguous tones. In two experiments we show that rats learn the task in fewer sessions than other automated variants, generalise responses across ambiguous tones as expected, self-initiate 4–5 trials/min, and can be tested repeatedly. Affect manipulations generate main effect trends in the predicted directions, although not localised to ambiguous tones, so further construct validation is required. We also find that tone-reinforcer pairings and reinforcement or non-reinforcement of ambiguous trials can affect responses to ambiguity. This translatable task should facilitate more widespread uptake of judgement bias testing.

AB - Scientific methods for assessing animal affect, especially affective valence (positivity or negativity), allow us to evaluate animal welfare and the effectiveness of 3Rs Refinements designed to improve wellbeing. Judgement bias tasks measure valence; however, task-training may be lengthy and/or require significant time from researchers. Here we develop an automated and self-initiated judgement bias task for rats which capitalises on their natural investigative behaviour. Rats insert their noses into a food trough to start trials. They then hear a tone and learn either to stay for 2 s to receive a food reward or to withdraw promptly to avoid an air-puff. Which contingency applies is signalled by two different tones. Judgement bias is measured by responses to intermediate ambiguous tones. In two experiments we show that rats learn the task in fewer sessions than other automated variants, generalise responses across ambiguous tones as expected, self-initiate 4–5 trials/min, and can be tested repeatedly. Affect manipulations generate main effect trends in the predicted directions, although not localised to ambiguous tones, so further construct validation is required. We also find that tone-reinforcer pairings and reinforcement or non-reinforcement of ambiguous trials can affect responses to ambiguity. This translatable task should facilitate more widespread uptake of judgement bias testing.

UR - http://www.scopus.com/inward/record.url?scp=85051696517&partnerID=8YFLogxK

U2 - 10.1038/s41598-018-30571-x

DO - 10.1038/s41598-018-30571-x

M3 - Article

VL - 8

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 12400

ER -