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

2020 ◽  
Author(s):  
Vikki Neville ◽  
Peter Dayan ◽  
Iain Donald Gilchrist ◽  
Elizabeth S. Paul ◽  
Michael Mendl
Keyword(s):  
Decision Making ◽  
Prediction Errors ◽  
Affective States ◽  
Affective Valence ◽  
Judgement Bias ◽  
Decision Outcomes ◽  
Loss Experience ◽  
Average Earning ◽  
Task Experience ◽  
New Evidence

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.

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

2021 ◽  
Vol 17 (1) ◽  
pp. e1008555
Author(s):  
Vikki Neville ◽  
Peter Dayan ◽  
Iain D. Gilchrist ◽  
Elizabeth S. Paul ◽  
Michael Mendl
Keyword(s):  
Decision Making ◽  
Prediction Errors ◽  
Affective States ◽  
Affective Valence ◽  
Judgement Bias ◽  
Decision Outcomes ◽  
Loss Experience ◽  
Average Earning ◽  
Task Experience ◽  
New Evidence

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.

scholarly journals Using Primary Reinforcement to Enhance Translatability of a Human Affect and Decision-Making Judgment Bias Task

2021 ◽  
pp. 1-13
Author(s):  
Vikki Neville ◽  
Peter Dayan ◽  
Iain D. Gilchrist ◽  
Elizabeth S. Paul ◽  
Michael Mendl
Keyword(s):  
Decision Making ◽  
Affective State ◽  
Lapse Rate ◽  
Prediction Errors ◽  
Affective Valence ◽  
Behavioral Measures ◽  
Judgment Bias ◽  
Affective Arousal ◽  
Nonhuman Animals ◽  
Positive Valence

Abstract Good translatability of behavioral measures of affect (emotion) between human and nonhuman animals is core to comparative studies. The judgment bias (JB) task, which measures “optimistic” and “pessimistic” decision-making under ambiguity as indicators of positive and negative affective valence, has been used in both human and nonhuman animals. However, one key disparity between human and nonhuman studies is that the former typically use secondary reinforcers (e.g., money) whereas the latter typically use primary reinforcers (e.g., food). To address this deficiency and shed further light on JB as a measure of affect, we developed a novel version of a JB task for humans using primary reinforcers. Data on decision-making and reported affective state during the JB task were analyzed using computational modeling. Overall, participants grasped the task well, and as anticipated, their reported affective valence correlated with trial-by-trial variation in offered volume of juice. In addition, previous findings from monetary versions of the task were replicated: More positive prediction errors were associated with more positive affective valence, a higher lapse rate was associated with lower affective arousal, and affective arousal decreased as a function of number of trials completed. There was no evidence that more positive valence was associated with greater “optimism,” but instead, there was evidence that affective valence influenced the participants' decision stochasticity, whereas affective arousal tended to influence their propensity for errors. This novel version of the JB task provides a useful tool for investigation of the links between primary reward and punisher experience, affect, and decision-making, especially from a comparative perspective.

scholarly journals Assessing and Enhancing the Welfare of Animals with Equivocal and Reliable Cues

Animals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 680
Author(s):  
Jason V. Watters ◽  
Bethany L. Krebs
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Affective State ◽  
Well Being ◽  
Reward Sensitivity ◽  
Affective States ◽  
Judgement Bias ◽  
Anticipatory Behavior ◽  
Human Care ◽  
Decision Making Behavior

The actions of human caretakers strongly influence animals living under human care. Here, we consider how intentional and unintentional signals provided by caretakers can inform our assessment of animals’ well-being as well as help to support it. Our aim is to assist in further developing techniques to learn animals’ affective state from their behavior and to provide simple suggestions for how animal caretakers’ behavior can support animal welfare. We suggest that anticipatory behavior towards expected rewards is related to decision-making behavior as viewed through the cognitive bias lens. By considering the predictions of the theories associated with anticipatory behavior and cognitive bias, we propose to use specific cues to probe the cumulative affective state of animals. Additionally, our commentary draws on the logic of reward sensitivity and judgement bias theories to develop a framework that suggests how reliable and equivocal signals may influence animals’ affective states. Application of this framework may be useful in supporting the welfare of animals in human care.

scholarly journals Neural basis of decision making guided by emotional outcomes

2015 ◽  
Vol 113 (9) ◽  
pp. 3056-3068 ◽  
Author(s):  
Kentaro Katahira ◽  
Yoshi-Taka Matsuda ◽  
Tomomi Fujimura ◽  
Kenichi Ueno ◽  
Takeshi Asamizuya ◽  
...  
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Prediction Error ◽  
Brain Regions ◽  
Parahippocampal Gyrus ◽  
Prediction Errors ◽  
Neural Basis ◽  
Decision Outcomes ◽  
Gain Loss ◽  
Emotional Events

Emotional events resulting from a choice influence an individual's subsequent decision making. Although the relationship between emotion and decision making has been widely discussed, previous studies have mainly investigated decision outcomes that can easily be mapped to reward and punishment, including monetary gain/loss, gustatory stimuli, and pain. These studies regard emotion as a modulator of decision making that can be made rationally in the absence of emotions. In our daily lives, however, we often encounter various emotional events that affect decisions by themselves, and mapping the events to a reward or punishment is often not straightforward. In this study, we investigated the neural substrates of how such emotional decision outcomes affect subsequent decision making. By using functional magnetic resonance imaging (fMRI), we measured brain activities of humans during a stochastic decision-making task in which various emotional pictures were presented as decision outcomes. We found that pleasant pictures differentially activated the midbrain, fusiform gyrus, and parahippocampal gyrus, whereas unpleasant pictures differentially activated the ventral striatum, compared with neutral pictures. We assumed that the emotional decision outcomes affect the subsequent decision by updating the value of the options, a process modeled by reinforcement learning models, and that the brain regions representing the prediction error that drives the reinforcement learning are involved in guiding subsequent decisions. We found that some regions of the striatum and the insula were separately correlated with the prediction error for either pleasant pictures or unpleasant pictures, whereas the precuneus was correlated with prediction errors for both pleasant and unpleasant pictures.

scholarly journals Event-related brain potentials reflect predictive coding of anticipated economic change

2020 ◽  
Vol 20 (5) ◽  
pp. 961-982
Author(s):  
Diamantis Petropoulos Petalas ◽  
Stefan Bos ◽  
Paul Hendriks Vettehen ◽  
Hein T. van Schie
Keyword(s):  
Decision Making ◽  
Predictive Coding ◽  
Prediction Errors ◽  
Brain Potentials ◽  
Attentional Processing ◽  
Economic Changes ◽  
Financial Decisions ◽  
Economic Decision Making ◽  
Decision Outcomes ◽  
Economic Forecasts

Abstract Research has demonstrated the importance of economic forecasts for financial decisions at the aggregate economic level. However, little is known about the psychological and neurophysiological mechanisms that economic forecasts activate at the level of individual decision-making. In the present study, we used event-related brain potentials (ERPs) to test the hypothesis that economic forecasts influence individuals’ internal model of the economy and their subsequent decision behavior. Using a simple economic decision-making game, the Balloon Analogue of Risk Task (BART) and predictive messages about possible economic changes in the game before each block, we test the idea that brain potentials time-locked to decision outcomes can vary as a function of exposure to economic forecasts. Behavioural results indicate that economic forecasts influenced the amount of risk that participants were willing to take. Analyses of brain potentials indicated parametric increases of the N1, P2, P3a, and P3b amplitudes as a function of the level of risk in subsequent inflation steps in the BART. Mismatches between economic forecasts and decision outcomes in the BART (i.e., reward prediction errors) were reflected in the amplitude of the P2, P3a, and P3b, suggesting increased attentional processing of unexpected outcomes. These electrophysiological results corroborate the idea that economic messages may indeed influence people’s beliefs about the economy and bias their subsequent financial decision-making. Our findings present a first important step in the development of a low-level neurophysiological model that may help to explain the self-fulfilling prophecy effect of economic news in the larger economy.

Evaluating Risk-Propensity Assessment Methods: Patterns in Repeated Exposure to Emotional Stimuli

2020 ◽  
Vol 64 (1) ◽  
pp. 283-287
Author(s):  
Sahinya Susindar ◽  
Harrison Wissel-Littmann ◽  
Terry Ho ◽  
Thomas K. Ferris
Keyword(s):  
Decision Making ◽  
Emotion Regulation ◽  
Assessment Method ◽  
Decision Makers ◽  
Decision Task ◽  
Emotional States ◽  
Affective States ◽  
Risk Propensity ◽  
Emotional Stimuli ◽  
Comparison Results

In studying naturalistic human decision-making, it is important to understand how emotional states shape decision-making processes and outcomes. Emotion regulation techniques can improve the quality of decisions, but there are several challenges to evaluating these techniques in a controlled research context. Determining the effectiveness of emotion regulation techniques requires methodology that can: 1) reliably elicit desired emotions in decision-makers; 2) include decision tasks with response measures that are sensitive to emotional loading; and 3) support repeated exposures/trials with relatively-consistent emotional loading and response sensitivity. The current study investigates one common method, the Balloon Analog Risk Task (BART), for its consistency and reliability in measuring the risk-propensity of decision-makers, and specifically how the method’s effectiveness might change over the course of repeated exposures. With the PANASX subjective assessment serving for comparison, results suggest the BART assessment method, when applied over repeated exposures, is reduced in its sensitivity to emotional stimuli and exhibits decision task-related learning effects which influence the observed trends in response data in complex ways. This work is valuable for researchers in decision-making and to guide design for humans with consideration for their affective states.

scholarly journals Chameleonic knowledge: a study of ex ante analysis in large infrastructure policy processes

2021 ◽  
Author(s):  
Lars Dorren ◽  
Wouter Van Dooren
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Policy Outcomes ◽  
Knowledge Use ◽  
Short Term ◽  
Cost Overruns ◽  
Substantive Content ◽  
Infrastructure Policy ◽  
Decision Outcomes ◽  
Ex Ante

AbstractUsing ex ante analysis to predict policy outcomes is common practice in the world of infrastructure planning. However, accounts of its uses and merits vary widely. Advisory agencies and government think tanks advocate this practice to prevent cost overruns, short-term decision-making and suboptimal choices. Academic studies on knowledge use, on the other hand, are critical of how knowledge can be used in decision making. Research has found that analyses often have no impact at all on decision outcomes or are mainly conducted to provide decision makers with the confidence to decide rather than with objective facts. In this paper, we use an ethnographic research design to understand how it is possible that the use of ex ante analysis can be depicted in such contradictory ways. We suggest that the substantive content of ex ante analysis plays a limited role in understanding its depictions and uses. Instead, it is the process of conducting an ex ante analysis itself that unfolds in such a manner that the analysis can be interpreted and used in many different and seemingly contradictory ways. In policy processes, ex ante analysis is like a chameleon, figuratively changing its appearance based on its environment.

scholarly journals Temperament, Plasticity, and Emotions in Defensive Behaviour of Paca (Mammalia, Hystricognatha)

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 293
Author(s):  
Selene S. C. Nogueira ◽  
Sérgio L. G. Nogueira-Filho ◽  
José M. B. Duarte ◽  
Michael Mendl
Keyword(s):  
Conservation Status ◽  
Behavioural Plasticity ◽  
Affective States ◽  
Defensive Behaviour ◽  
Rapid Adaptation ◽  
Behavioural Responses ◽  
Judgement Bias ◽  
Temperament Dimension ◽  
Ambiguous Cue

Within a species, some individuals are better able to cope with threatening environments than others. Paca (Cuniculus paca) appear resilient to over-hunting by humans, which may be related to the behavioural plasticity shown by this species. To investigate this, we submitted captive pacas to temperament tests designed to assess individual responses to short challenges and judgement bias tests (JBT) to evaluate individuals’ affective states. Results indicated across-time and context stability in closely correlated “agitated”, “fearful” and “tense” responses; this temperament dimension was labelled “restless”. Individual “restless” scores predicted responses to novelty, although not to simulated chasing and capture by humans in a separate modified defence test battery (MDTB). Restless animals were more likely to show a greater proportion of positive responses to an ambiguous cue during JBT after the MDTB. Plasticity in defensive behaviour was inferred from changes in behavioural responses and apparently rapid adaptation to challenge in the different phases of the MDTB. The results indicate that both temperament and behavioural plasticity may play a role in influencing paca responses to risky situations. Therefore, our study highlights the importance of understanding the role of individual temperament traits and behavioural plasticity in order to better interpret the animals’ conservation status and vulnerabilities.

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