Optimism, pessimism and judgement bias in animals: A systematic review and meta-analysis

Lagisz, Malgorzata; Zidar, Josefina; Nakagawa, Shinichi; Neville, Vikki; Sorato, Enrico; Paul, Elizabeth S.; Bateson, Melissa; Mendl, Michael; Løvlie, Hanne

doi:10.1016/j.neubiorev.2020.07.012

Cited by 97 publications

(125 citation statements)

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“…Accordingly, the relationship between decision-making and both the average earning rate and previous outcomes would be consistent with previous findings from animal studies showing that risk and exploration can become greater as overall conditions become less favourable [51,52], a trend that may be explained by individuals in poorer conditions having 'little to lose'. Why this appears to be more evident in a short-time window (within-task) compared to a longertime window when less favourable pre-task conditions are often associated with less risky within-task decision-making [15] requires further investigation.…”

Section: Does Recent Experience Of Reward and Loss Modulate Decision-mentioning

confidence: 99%

“…This distinction is particularly pertinent in research where decisions on serial trials yielding reward or loss/punishment are used to probe the influence of affective states and disorders on risk-taking and reward sensitivity. The resulting decision-making profiles are proposed as markers of these states (e.g., Iowa Gambling task [5][6][7]; Balloon Analogue Risk Task [8][9][10]; Reward Responsiveness Task [11,12]; Judgement Bias Task [13][14][15]). In most studies, decision-making data across test sessions are summarised into single statistics such as the number of cards selected from more favourable decks, the average number of 'balloon' pumps, the overall response bias as a marker of reward responsiveness, or the proportion of 'optimistic' responses.…”

Section: Introductionmentioning

confidence: 99%

“…The judgement bias task was originally designed [13], and has since been widely used [14,15], as a translational paradigm in which decision-making under ambiguity could be used as an indicator of an individual's affective state. In the task, participants are trained to discriminate between two stimuli and make different responses to each (typically 'go' or 'stay'/'no-go') in order to either obtain a reward or avoid a punisher.…”

Section: Introductionmentioning

confidence: 99%

“…Decision-making in the judgement bias task, particularly trials with perceptually ambiguous stimuli, is considered to be indicative of a longer timescale notion of affective state, or 'mood'. Specifically, more 'optimistic' decision-making, as indicated by an excess proportion of 'optimistic' as opposed to 'pessimistic' decisions made across a test session, is typically associated with more positively valenced affect [14,15,24]. This decision-making profile is hypothesised to reflect approximate sufficient statistics about the characteristics of the individual's interaction with and experience of the rewarding and punishing features of their environment [22,25,26].…”

Section: Introductionmentioning

confidence: 99%

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Dissecting the links between reward and loss, decision-making, and self-reported affect using a computational approach

et al. 2021

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Links between affective states and risk-taking are often characterised using summary statistics from serial decision-making tasks. However, our understanding of these links, and the utility of decision-making as a marker of affect, needs to accommodate the fact that ongoing (e.g., within-task) experience of rewarding and punishing decision outcomes may alter future decisions and affective states. To date, the interplay between affect, ongoing reward and punisher experience, and decision-making has received little detailed investigation. Here, we examined the relationships between reward and loss experience, affect, and decision-making in humans using a novel judgement bias task analysed with a novel computational model. We demonstrated the influence of within-task favourability on decision-making, with more risk-averse/‘pessimistic’ decisions following more positive previous outcomes and a greater current average earning rate. Additionally, individuals reporting more negative affect tended to exhibit greater risk-seeking decision-making, and, based on our model, estimated time more poorly. We also found that individuals reported more positive affective valence during periods of the task when prediction errors and offered decision outcomes were more positive. Our results thus provide new evidence that (short-term) within-task rewarding and punishing experiences determine both future decision-making and subjectively experienced affective states.

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Section: Does Recent Experience Of Reward and Loss Modulate Decision-mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dissecting the links between reward and loss, decision-making, and self-reported affect using a computational approach

et al. 2021

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“…It is now widely agreed that a positive affective state (comprising both the longer term background mood state and shorter-term discrete emotions [ 1 ]), and not only physical health, is a crucial component of animal well-being [ 1 ]. Animal welfare science and biomedical research have attempted to establish scientific and reliable measures of affective states in non-human animals, with the cognitive bias approach being one of the most commonly applied tests across species (for reviews see [ 2 – 5 ]; for critical analyses see [ 6 , 7 ]; for a meta-analysis on how pharmacological manipulations influence judgment bias see [ 8 ]). Cognitive bias theories concern the influence of emotional states on cognitive functions (such as attention, memory and judgment) [ 3 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Using judgment bias test in pet and shelter dogs (Canis familiaris): Methodological and statistical caveats

et al. 2020

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It is now widely agreed that a positive affective state is a crucial component of animal well-being. The judgment bias test represents a widespread tool used to assess animals’ optimistic/pessimistic attitude and to evaluate their emotional state and welfare. Judgment bias tests have been used several times with dogs ( Canis familiaris ), in most cases using a spatial test with a bowl placed in ambiguous positions located between a relatively positive trained location (P) which contains a baited bowl and a relatively negative trained location (N) which contains an empty bowl. The latency to approach the bowl in the ambiguous locations is an indicator of the dog’s expectation of a positive/negative outcome. However, results from such tests are often inconclusive. For the present study, the judgment bias test performance of 51 shelter dogs and 40 pet dogs was thoroughly analysed. A pattern emerged with shelter dogs behaving in a more pessimistic-like way than pet dogs. However, this difference between the two populations was detected only when analysing the raw latencies to reach the locations and not the more commonly applied adjusted score (i.e. average latency values). Furthermore, several methodological caveats were found. First of all, a non-negligible percentage of dogs did not pass the training phase, possibly due to the experimental paradigm not being fully suited for this species. Second, results showed a high intra-dog variability in response to the trained locations, i.e. the dogs’ responses were not consistent throughout the test, suggesting that animals may not have fully learned the association between locations and their outcomes. Third, dogs did not always behave differently towards adjacent locations, raising doubts about the animals’ ability to discriminate between locations. Finally, a potential influence of the researcher’s presence on dogs’ performance emerged from analyses. The implications of these findings and potential solutions are discussed.

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The Affective Bias Test and Reward Learning Assay: Neuropsychological Models for Depression Research and Investigating Antidepressant Treatments in Rodents

Hinchcliffe,

Robinson

2024

Current Protocols

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The Affective Bias Test (ABT) quantifies acute changes in affective state based on the affective biases they generate in an associative reward learning task. The Reward Learning Assay (RLA) provides a control assay for the ABT and reward‐induced biases generated in this model are sensitive to changes in core affective state. Both tasks involve training animals to associate a specific digging substrate with a food reward. Animals learn to discriminate between two digging substrates placed in ceramic bowls, one rewarded and one unrewarded. In the ABT, the animal learns two independent substrate‐reward associations with a fixed reward value following either an affective state or drug manipulation, or under control conditions. Affective biases generated are quantified in a choice test where the animals exhibit a bias (make more choices) for one of the substrates which is specifically related to affective state at the time of learning. The ABT is used to investigate biases generated during learning as well as modulation of biases associated with past experiences. The RLA follows a similar protocol, but the animal remains in the same affective state throughout and a reward‐induced bias is generated by pairing one substrate with a higher value reward. The RLA provides a control to determine if drug treatments affect memory retrieval more generally. Studies in depression models and following environmental enrichment suggest that reward‐induced biases are sensitive to core changes in affective state. Each task offers different insights into affective processing mechanisms and may help improve the translational validity of animal studies and benefit pre‐clinical drug development. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC.Basic Protocol 1: Bowl digging and discrimination trainingBasic Protocol 2: The reward learning assayBasic Protocol 3: The affective bias test ‐ new learningBasic Protocol 4: The affective bias test ‐ modulation of affective biases associated with past experiences

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Optimism, pessimism and judgement bias in animals: A systematic review and meta-analysis

Cited by 97 publications

References 71 publications

Dissecting the links between reward and loss, decision-making, and self-reported affect using a computational approach

Dissecting the links between reward and loss, decision-making, and self-reported affect using a computational approach

Using judgment bias test in pet and shelter dogs (Canis familiaris): Methodological and statistical caveats

The Affective Bias Test and Reward Learning Assay: Neuropsychological Models for Depression Research and Investigating Antidepressant Treatments in Rodents

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