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

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.

Impulsivity and Emotional Dysregulation Predict Choice Behavior During a Competitive Multiplayer Game in Adolescents with Borderline Personality Disorder

“…Impulsivity, given the inherently rapid and dynamic nature of the task that involves learning and updating the value of available actions (actionoutcome contingencies) based on reinforcement history (Lee & Seo, 2007;Vickery et al, 2011) and translating this information into goal-directed actions; 2. Emotional dysregulation, given that affective sources of information are used to update value representations (Neville et al, 2021;Paulus et al, 2005), and 3. Interpersonal dysfunction, given that our task may recruit mentalization processes required to predict and draw inferences about the behavior of the opponent.…”

“…Impaired affective and RL processes could contribute to strategic choice behavior through outcome evaluation processes in the following ways; 1. Blunted reward prediction error (RPE) and/or affective signaling (Hüpen et al, 2020;Neville et al, 2021) that could lead to insensitivity to changing reward contingencies and/or a deficit updating the value of actions on a trial-bytrial basis, which in this context, may actually result in fewer choice biases (and therefore, potentially enhanced performance as one may better evade exploitation by the opponent); and/or 2. Exacerbated RPE and/or affective signals could lead to amplified biases (and therefore, potentially diminished performance as the opponent would exploit these biases as they emerge), either of which may be more prominent for either positive (WS) and/or negative (LS) outcomes (Neville et al, 2021;Paret et al, 2016;Schuermann et al, 2011).…”

“…We further hypothesized that group differences would be more pronounced in individuals with higher levels of impulsivity in either group, measured using the BIS (Patton et al, 1995), and emotion dysregulation in the BPD group, measured using the DERS (Gratz & Roemer, 2004). Given evidence suggesting that emotion dysregulation and negative affect may partially exacerbate impulsivity in BPD (Neville et al, 2021;Sharp et al, 2011), we tested whether DERS mediated the relationship between impulsivity and choice behavior in BPD. Last, we conducted exploratory analyses to assess whether individual differences in self-report strategies contribute to the observed relationships between impulsivity (both groups) and difficulties in emotional regulation (BPD group) and choice behavior.…”

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

“…Using this novel variant of the judgment bias task alongside computational modeling, we additionally aimed to elucidate the extent to which latent processes underlying decision-making might relate to subjective experiences of affect, reward, and punishment within the task. We hypothesized that more positive reported affect would be associated with model parameters characterizing biases toward the "optimistic" response and that, consistent with previous research (Neville et al, 2021;Rutledge, Skandali, Dayan, & Dolan, 2014), the absolute favorability (i.e., average earning rate) of within-task experience would inform decision-making and the relative favorability (i.e., reward prediction error) of within-task experience would inform reported affective valence.…”

“…However, human judgment bias studies to date have painted a mixed picture. Whereas some studies have found that "pessimism" correlates with subjective reports of more negative affect (Positive and Negative Affect Schedule [Paul et al, 2010], State-Trait Anxiety Inventory [Aylward, Hales, Robinson, & Robinson, 2020;Anderson, Hardcastle, Munafò, & Robinson, 2012], Beck Depression Inventory [Daniel-Watanabe, McLaughlin, Gormley, & Robinson, 2020], Visual Analog Scale for anxiety [Anderson et al, 2012]), other studies have found no relationship between reported affect and judgment bias (affect grid and Positive and Negative Affect Schedule [Iigaya et al, 2016], State-Trait Anxiety Inventory [Daniel-Watanabe et al, 2020]) or even that "optimistic" decisionmaking is associated with more negative reported affect (affect grid [Neville, Dayan, Gilchrist, Paul, & Mendl, 2021]).…”