ArticlePLoS computational biology2021
Dissecting the links between reward and loss, decision-making, and self-reported affect using a computational approach.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Neural signatures of risk-taking adaptions across health, bipolar disorder, and lithium treatment.Molecular psychiatry · 2025Trial
- Relevance of state-behaviour feedbacks for animal welfare.Biological reviews of the Cambridge Philosophical Society · 2025Review
- Examining neuroanatomical correlates of win-stay, lose-shift behaviour.Brain structure & function · 2025Article
- Affective integration in experience, judgment, and decision-making.Communications psychology · 2024Review
- You are How You Eat: Foraging Behavior as a Potential Novel Marker of Rat Affective State.Affective science · 2024Article
- A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals.Cognitive, affective & behavioral neuroscience · 2024Article
- A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals.Cognitive, affective & behavioral neuroscience · 2024Article
- Mood and Emotions among Inmates after COVID-19 Pandemic.International journal of environmental research and public health · 2023Article
- The effects of induced positive and negative affect on Pavlovian-instrumental interactions.Cognition & emotion · 2022Article
- A model of mood as integrated advantage.Psychological review · 2022Article
- Impulsivity and Emotional Dysregulation Predict Choice Behavior During a Mixed-Strategy Game in Adolescents With Borderline Personality Disorder.Frontiers in neuroscience · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.