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When deciding whether to reciprocate trust, people are typically strongly influenced by how much trust their interaction partner has originally shown them. If a partner has placed a lot of trust in you, there is a strong motivation to reciprocate, and indeed this factor often outweighs pro-self considerations to maximize one's own financial payout. However, one important unanswered question in this regard is what people decide to do when this prior information is ambiguous; that is, when they do not know for sure exactly how trusting their partner has been. How then do people decide to reciprocate? This study utilizes a novel version of the Trust Game to directly address this question. Here, we develop, and validate, a computational model-based approach to quantify and categorize how participants assessed the trustworthiness of an unfamiliar partner when making reciprocity decisions. We find that participants spontaneously use their prior experience about the trustingness of game partners in general to inform their reciprocity decisions, even when they had the opportunity to strategically assume that their new, unfamiliar, partners were untrusting, and hence could have justified lower reciprocation rates. [ABSTRACT FROM AUTHOR]

Humans often face the challenge of making decisions between ambiguous options. The level of ambiguity in decision-making has been linked to activity in the parietal cortex, but its exact computational role remains elusive. To test the hypothesis that the parietal cortex plays a causal role in computing ambiguous probabilities, we conducted consecutive fMRI and TMS-EEG studies. We found that participants assigned unknown probabilities to objective probabilities, elevating the uncertainty of their decisions. Parietal cortex activity correlated with the objective degree of ambiguity and with a process that underestimates the uncertainty during decision-making. Conversely, the midcingulate cortex (MCC) encodes prediction errors and increases its connectivity with the parietal cortex during outcome processing. Disruption of the parietal activity increased the uncertainty evaluation of the options, decreasing cingulate cortex oscillations during outcome evaluation and lateral frontal oscillations related to value ambiguous probability. These results provide evidence for a causal role of the parietal cortex in computing uncertainty during ambiguous decisions made by humans. Humans often face the challenge of making decisions between ambiguous options. The level of ambiguity in decision-making has been linked to activity in the parietal cortex, but what is its actual role? This study uses fMRI and TMS-EEG to show that the parietal cortex is causally involved in a computational processes that underestimate uncertainty during decision-making under ambiguity. [ABSTRACT FROM AUTHOR]

Charities differ, among other things, alongside the likelihood that their interventions succeed and produce the desired outcomes and alongside the extent that such likelihood can even be articulated numerically. In this paper, we investigate what best explains charitable giving behaviour regarding charities that have interventions that will succeed with a quantifiable and high probability (sure-thing charities) and charities that have interventions that only have a small and hard to quantify probability of bringing about the desired end (probabilistic charities). We study individual differences in risk/ambiguity attitudes, empathy, numeracy, optimism, and donor type (warm glow vs. pure altruistic donor type) as potential predictors of this choice. We conduct a money incentivised, pre-registered experiment on Prolific on a representative UK sample (n = 1,506) to investigate participant choices (i) between these two types of charities and (ii) about one randomly selected charity. Overall, we find little to no evidence that individual differences predict choices regarding decisions about sure-thing and probabilistic charities, with the exception that a purely altruistic donor type predicts donations to probabilistic charities when participants were presented with a randomly selected charity in (ii). Conducting exploratory equivalence tests, we find that the data provide robust evidence in favour of the absence of an effect (or a negligibly small effect) where we fail to reject the null. This is corroborated by exploratory Bayesian analyses. We take this paper to be contributing to the literature on charitable giving via this comprehensive null-result in pursuit of contributing to a cumulative science. [ABSTRACT FROM AUTHOR]

Esports is an often time-consuming activity that has become increasingly popular with billions of players all over the world. The objective of this study was to investigate if there is a relationship between skill level in the strategy video game Dota 2, a game that places many demands on decision making to be successful, and decision making under ambiguity and experience as measured by performance in the Iowa Gambling Task (IGT), a task known to have ecological validity. Two indicators of players' performance in Dota 2, namely match-making rating (MMR) and Medal, were used as predictors of performance in the IGT in path models. Results showed that Medal was a significant predictor of performance in IGT, while MMR score was borderline significant. The cognitive reflection task, included in the models as an indicator of the ability to engage in conscious, analytical, rational, and logical thinking, was a significant predictor of performance in IGT, and was significantly and positively related to MMR. The findings from this study give insight into the cognitive demands related to performance in Dota 2. Although results suggest that strategy video gaming may be a factor that contributes to increased decision making abilities, a reversed relationship is also possible, whereby individuals who are better at decision making are also more likely to become successful in Dota-2. More studies, preferably longitudinal, are needed to replicate the findings of this study and to establish the directionality between factors. [ABSTRACT FROM AUTHOR]

Across a wide range of domains, experts make probabilistic judgments under conditions of uncertainty to support decision-making. These judgments are often conveyed using linguistic expressions (e.g., x is likely). Seeking to foster shared understanding of these expressions between senders and receivers, the US intelligence community implemented a communication standard that prescribes a set of probability terms and assigns each term an equivalent numerical probability range. In an earlier PLOS ONE article, [1] tested whether access to the standard improves shared understanding and also explored the efficacy of various enhanced presentation formats. Notably, they found that embedding numeric equivalents in text (e.g., x is likely [55–80%]) substantially outperformed the status-quo approach in terms of the percentage overlap between participants' interpretations of linguistic probabilities (defined in terms of the numeric range equivalents they provided for each term) and the numeric ranges in the standard. These results have important prescriptive implications, yet Wintle et al.'s percentage overlap measure of agreement may be viewed as unfairly punitive because it penalizes individuals for being more precise than the stipulated guidelines even when the individuals' interpretations fall perfectly within the stipulated ranges. Arguably, subjects' within-range precision is a positive attribute and should not be penalized in scoring interpretive agreement. Accordingly, in the present article, we reanalyzed Wintle et al.'s data using an alternative measure of percentage overlap that does not penalize in-range precision. Using the alternative measure, we find that percentage overlap is substantially elevated across conditions. More importantly, however, the effects of presentation format and probability level are highly consistent with the original study. By removing the ambiguity caused by Wintle et al.'s unduly punitive measure of agreement, these findings buttress Wintle et al.'s original claim that the methods currently used by intelligence organizations are ineffective at coordinating the meaning of uncertainty expressions between intelligence producers and intelligence consumers. Future studies examining agreement between senders and receivers are also encouraged to reflect carefully on the most appropriate measures of agreement to employ in their experiments and to explicate the bases for their methodological choices. [ABSTRACT FROM AUTHOR]

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. Author summary: Affective states, such as happiness, are key to well-being. They are thought to reflect characteristics of the environment such as the availability of reward and the inevitability of punishment. However, there is a lack of agreement about: (i) the time scales over which these characteristics are measured; (ii) how and in what combinations actual or expected outcomes influence affect; (iii) how affect itself influences decision-making. A particular stance on the last issue underpins the judgement bias task, which, by measuring an individual's willingness to make 'optimistic' or 'pessimistic' choices that are rendered risky by perceptual ambiguity, is one of the few cross-species tests for affect. Here we apply a novel computational analysis to a novel judgement bias task to examine all three issues. We reveal a rich interplay between affect and rewards, punishments, and uncertainty. [ABSTRACT FROM AUTHOR]

Experimental evidence suggests that the frequency with which individuals get feedback information on their investments has an effect on their risk-taking behavior. In particular, when they are given information sufficiently often, they take less risks compared with a situation in which they are informed less frequently. We find that this result still holds when subjects do not know the probabilities of the lotteries they are betting upon. We also detect significant gender effects, in that the frequency with which information is disclosed mostly affects male betting behavior, and that males become more risk-seeking after experiencing a loss. [ABSTRACT FROM AUTHOR]

Previous studies have reported that trait anxiety (TA) affects decision making. However, results remain largely inconsistent across studies. The aim of the current study was to further address the interaction between TA and decision making. 304 subjects without depression from a sample consisting of 642 participants were grouped into high TA (HTA), medium TA (MTA) and low TA (LTA) groups based on their TA scores from State Trait Anxiety Inventory. All subjects were assessed with the Iowa Gambling Task (IGT) that measures decision making under ambiguity and the Game of Dice Task (GDT) that measures decision making under risk. While the HTA and LTA groups performed worse on the IGT compared to the MTA group, performances on the GDT between the three groups did not differ. Furthermore, the LTA and HTA groups showed different individual deck level preferences in the IGT: the former showed a preference for deck B indicating that these subjects focused more on the magnitude of rewards, and the latter showed a preference for deck A indicating significant decision making impairment. Our findings suggest that trait anxiety has effect on decision making under ambiguity but not decision making under risk and different levels of trait anxiety related differently to individual deck level preferences in the IGT. [ABSTRACT FROM AUTHOR]

When asked to indicate which items from a set of candidates belong to a particular natural language category inter-individual differences occur: Individuals disagree which items should be considered category members. The premise of this paper is that these inter-individual differences in semantic categorization reflect both ambiguity and vagueness. Categorization differences are said to be due to ambiguity when individuals employ different criteria for categorization. For instance, individuals may disagree whether hiking or darts is the better example of sports because they emphasize respectively whether an activity is strenuous and whether rules apply. Categorization differences are said to be due to vagueness when individuals employ different cut-offs for separating members from non-members. For instance, the decision to include hiking in the sports category or not, may hinge on how strenuous different individuals require sports to be. This claim is supported by the application of a mixture model to categorization data for eight natural language categories. The mixture model can identify latent groups of categorizers who regard different items likely category members (i.e., ambiguity) with categorizers within each of the groups differing in their propensity to provide membership responses (i.e., vagueness). The identified subgroups are shown to emphasize different sets of category attributes when making their categorization decisions. [ABSTRACT FROM AUTHOR]