Tracking politically motivated reasoning in the brain: the role of mentalizing, value-encoding, and error detection networks.

Susceptibility to misinformation and belief polarization often reflects people's tendency to incorporate information in a biased way. Despite the presence of competing theoretical models, the underlying neurocognitive mechanisms of motivated reasoning remain elusive as previous empirical work did not properly track the belief formation process. To address this problem, we employed a design that identifies motivated reasoning as directional deviations from a Bayesian benchmark of unbiased belief updating. We asked the members of a proimmigration or an anti-immigration group regarding the extent to which they endorse factual messages on foreign criminality, a polarizing political topic. Both groups exhibited a desirability bias by overendorsing attitude-consistent messages and underendorsing attitude-discrepant messages and an identity bias by overendorsing messages from in-group members and underendorsing messages from out-group members. In both groups, neural responses to the messages predicted subsequent expression of desirability and identity biases, suggesting a common neural basis of motivated reasoning across ideologically opposing groups. Specifically, brain regions implicated in encoding value, error detection, and mentalizing tracked the degree of desirability bias. Less extensive activation in the mentalizing network tracked the degree of identity bias. These findings illustrate the distinct neurocognitive architecture of desirability and identity biases and inform existing cognitive models of politically motivated reasoning.

Exploring the relationship between frequent cannabis use, belief updating under uncertainty and psychotic-like symptoms.

Background: Cannabis users present an important group for investigating putative mechanisms underlying psychosis, as cannabis-use is associated with an increased risk of psychosis. Recent work suggests that alterations in belief-updating under uncertainty underlie psychosis. We therefore compared belief updating under uncertainty between cannabis and non-cannabis users. Methods: 49 regular cannabis users and 52 controls completed the Space Game, via an online platform used for behavioral testing. In the task, participants were asked to predict the location of the stimulus based on previous information, under different uncertainty conditions. Mixed effects models were used to identify significant predictors of mean score, confidence, performance error and learning rate. Results: Both groups showed decreased confidence in high noise conditions, and increased belief updating in more volatile conditions, suggesting that they could infer the degree and sources of uncertainty. There were no significant effects of group on any of the performance indices. However, within the cannabis group, frequent users showed worse performance than less frequent users. Conclusion: Belief updating under uncertainty is not affected by cannabis use status but could be impaired in those who use cannabis more frequently. This finding could show a similarity between frequent cannabis use and psychosis risk, as predictors for abnormal belief-updating.

Understanding Cognitive Behavioral Therapy for Psychosis Through the Predictive Coding Framework.

Psychological treatments for persecutory delusions, particularly cognitive behavioral therapy for psychosis, are efficacious; however, mechanistic theories explaining why they work rarely bridge to the level of cognitive neuroscience. Predictive coding, a general brain processing theory rooted in cognitive and computational neuroscience, has increasing experimental support for explaining symptoms of psychosis, including the formation and maintenance of delusions. Here, we describe recent advances in cognitive behavioral therapy for psychosis-based psychotherapy for persecutory delusions, which targets specific psychological processes at the computational level of information processing. We outline how Bayesian learning models employed in predictive coding are superior to simple associative learning models for understanding the impact of cognitive behavioral interventions at the algorithmic level. We review hierarchical predictive coding as an account of belief updating rooted in prediction error signaling. We examine how this process is abnormal in psychotic disorders, garnering noisy sensory data that is made sense of through the development of overly strong delusional priors. We argue that effective cognitive behavioral therapy for psychosis systematically targets the way sensory data are selected, experienced, and interpreted, thus allowing for the strengthening of alternative beliefs. Finally, future directions based on these arguments are discussed.

Delusions are distressing and disabling psychiatric symptoms. Cognitive behavioral therapy for psychosis (CBTp) is the leading psychotherapeutic approach for treating delusions. Predictive coding is a contemporary cognitive neuroscience framework that is increasingly being used to explain mechanisms of delusions. In this article, we attempt to integrate CBTp within the predictive coding framework, outlining how effective CBTp techniques impact aspects of the predictive coding model to contribute to cutting-edge treatment and cognitive neuroscience research on delusions and inform recommendations for treatment advancement.

A second chance for first impressions: evidence for altered impression updating in borderline personality disorder.

BACKGROUND: Individuals with borderline personality disorder (BPD) frequently alter between idealizing and devaluing other persons, which has been linked to an increased tendency to update self-relevant beliefs and impressions. We hypothesized that increased impression updating could stem from reduced attitude contextualization, i.e., a process in which impression-disconfirming information is linked to contextual cues. METHODS: Individuals diagnosed with BPD and controls (recruited online, with unknown diagnostic status) completed an impression formation paradigm. They first learned about the positive or negative behaviors of others in one Context A (e.g., Person 1 is helpful), followed by learning about behaviors of the opposite valence in a second Context B (Person 1 is rude). We also manipulated between participants whether the observed behaviors were directed toward the study participants (self-relevant) or, more generally, at other people (other-relevant). The contexts were marked by differently-colored backgrounds (e.g., yellow vs. blue), to avoid influences of prior knowledge or experiences. After exposure to information in both contexts, participants rated their impressions of the persons in Context A, Context B, and, crucially, a previously unknown Context C (white background). We examined whether the initial or an updated impression (re-)emerged in Context C. RESULTS: Initial impressions remained stable and dominated the ratings of controls across contexts A, B, and C for both self-relevant and other-relevant behaviors, consistent with contextualizing impression-disconfirming information. As expected, however, individuals with BPD only showed updated impression ratings in Context C for self-relevant behaviors, consistent with the assumed reduced tendency to contextualize impression-disconfirming self-relevant information. Further exploratory analyses suggest that more severe BPD symptoms predicted more pronounced impression updating in the self-relevant condition. CONCLUSIONS: The findings help to illuminate the mechanisms underlying interpersonal problems in individuals with BPD. People with BPD are not just more inclined to discard positive first impressions but to re-evaluate disliked others when they behave positively, contributing to the volatility of interactions with others. Contextualization has known and modifiable antecedents, and the study may thus provide potential targets for therapeutic intervention. Future studies will need to replicate the findings with specified controls.

Lesions to the mediodorsal thalamus, but not orbitofrontal cortex, enhance volatility beliefs linked to paranoia.

Beliefs-attitudes toward some state of the environment-guide action selection and should be robust to variability but sensitive to meaningful change. Beliefs about volatility (expectation of change) are associated with paranoia in humans, but the brain regions responsible for volatility beliefs remain unknown. The orbitofrontal cortex (OFC) is central to adaptive behavior, whereas the magnocellular mediodorsal thalamus (MDmc) is essential for arbitrating between perceptions and action policies. We assessed belief updating in a three-choice probabilistic reversal learning task following excitotoxic lesions of the MDmc (n = 3) or OFC (n = 3) and compared performance with that of unoperated monkeys (n = 14). Computational analyses indicated a double dissociation: MDmc, but not OFC, lesions were associated with erratic switching behavior and heightened volatility belief (as in paranoia in humans), whereas OFC, but not MDmc, lesions were associated with increased lose-stay behavior and reward learning rates. Given the consilience across species and models, these results have implications for understanding paranoia.

Thinking about Believing: Can Metacognitive Reflection Encourage Belief Updating?

People often cling to their beliefs even in the face of counterevidence. The current study explored metacognitive reflection as a potential driver for belief updating. In a randomized controlled experiment (n = 155), participants rated their degree of agreement with a statement regarding genetic modification in humans. Following this, participants were presented with a passage containing an argument counter to their indicated belief. Participants in the metacognition condition were asked to deeply reflect on the ways in which the passage was similar to or different from their current beliefs. Participants in the control condition were asked to engage in more shallow reflection on the composition of the passage. After reflecting on the counterevidence, participants were asked to again rate their agreement with the statement regarding human gene modification. Both groups updated their initial beliefs to be more consistent with the presented counterevidence. Although greater belief updating was observed in those who metacognitively reflected on the passage, this effect did not reach significance (p = .055). These findings suggest that reflecting on counterevidence has the potential to encourage belief updating, regardless of whether that reflection is metacognitive in nature, and provide promise for future work investigating the role of metacognition in belief updating.

Large environmental changes reduce valence-dependent belief updating.

When updating beliefs, humans tend to integrate more desirable information than undesirable information. In stable environments (low uncertainty and high predictability), this asymmetry favors motivation towards action and perceived self-efficacy. However, in changing environments (high uncertainty and low predictability), this process can lead to risk underestimation and increase unwanted costs. Here, we examine how people (n = 388) integrate threatening information during an abrupt environmental change (mandatory quarantine during the COVID-19 pandemic). Given that anxiety levels are associated with the magnitude of the updating belief asymmetry; we explore its relationship during this particular context. We report a significant reduction in asymmetrical belief updating during a large environmental change as individuals integrated desirable and undesirable information to the same extent. Moreover, this result was supported by computational modeling of the belief update task. However, we found that the reduction in asymmetrical belief updating was not homogeneous among people with different levels of Trait-anxiety. Individuals with higher levels of Trait-anxiety maintained a valence-dependent updating, as it occurs in stable environments. On the other hand, updating behavior was not associated with acute anxiety (State-Anxiety), health concerns (Health-Anxiety), or having positive expectations (Trait-Optimism). These results suggest that highly uncertain environments can generate adaptive changes in information integration. At the same time, it reveals the vulnerabilities of individuals with higher levels of anxiety to adapt the way they learn.

Belief Updating during Social Interactions: Neural Dynamics and Causal Role of Dorsomedial Prefrontal Cortex.

In competitive interactions, humans have to flexibly update their beliefs about another person's intentions in order to adjust their own choice strategy, such as when believing that the other may exploit their cooperativeness. Here we investigate both the neural dynamics and the causal neural substrate of belief updating processes in humans. We used an adapted prisoner's dilemma game in which participants explicitly predicted the coplayer's actions, which allowed us to quantify the prediction error between expected and actual behavior. First, in an EEG experiment, we found a stronger medial frontal negativity (MFN) for negative than positive prediction errors, suggesting that this medial frontal ERP component may encode unexpected defection of the coplayer. The MFN also predicted subsequent belief updating after negative prediction errors. In a second experiment, we used transcranial magnetic stimulation (TMS) to investigate whether the dorsomedial prefrontal cortex (dmPFC) causally implements belief updating after unexpected outcomes. Our results show that dmPFC TMS impaired belief updating and strategic behavioral adjustments after negative prediction errors. Taken together, our findings reveal the time course of the use of prediction errors in social decisions and suggest that the dmPFC plays a crucial role in updating mental representations of others' intentions.

Different learning aberrations relate to delusion-like beliefs with different contents.

The prediction error account of delusions has had success. However, its explanation of delusions with different contents has been lacking. Persecutory delusions and paranoia are the common unfounded beliefs that others have harmful intentions towards us. Other delusions include believing that one's thoughts or actions are under external control or that events in the world have specific personal meaning. We compare learning in two different cognitive tasks, probabilistic reversal learning and Kamin blocking, that have relationships to paranoid and non-paranoid delusion-like beliefs, respectively. We find that clinical high-risk status alone does not result in different behavioural results in the probabilistic reversal learning task but that an individual's level of paranoia is associated with excessive switching behaviour. During the Kamin blocking task, paranoid individuals learned inappropriately about the blocked cue. However, they also had decreased learning about the control cue, suggesting more general learning impairments. Non-paranoid delusion-like belief conviction (but not paranoia) was associated with aberrant learning about the blocked cue but intact learning about the control cue, suggesting specific impairments in learning related to cue combination. We fit task-specific computational models separately to behavioural data to explore how latent parameters vary within individuals between tasks and how they can explain symptom-specific effects. We find that paranoia is associated with low learning rates in the probabilistic reversal learning task and the blocking task. Non-paranoid delusion-like belief conviction is instead related to parameters controlling the degree and direction of similarity between cue updating during simultaneous cue presentation. These results suggest that paranoia and other delusion-like beliefs involve dissociable deficits in learning and belief updating, which, given the transdiagnostic status of paranoia, might have differential utility in predicting psychosis.

Better social reversal learning is associated with a more social approach across time.

Flexibly updating behaviors towards others is crucial for adaptive social functioning. Previous studies have found that difficulties in flexibly updating behaviors are associated with social anxiety (SA). However, it is unclear whether such difficulties relate to actual social behaviors. The current study investigated the relationships between negative-to-positive social reversal learning, social approach behavior, and SA across time. Participants (MTurk, Time 1 = 275, Time 2 = 126, 16 weeks later) completed a performance-based social reversal-learning task. In the initial phase, participants learned that interactions with certain individuals are associated with negative outcomes, whereas interactions with other individuals are associated with positive outcomes. In the reversal phase, these associations were reversed, requiring participants to update their behaviors. The relationships between the performance in the task, SA severity, and social approach behavior reported by participants were assessed cross-sectionally and longitudinally. We found that negative-to-positive updating was negatively associated with SA severity. Furthermore, negative-to-positive updating was positively correlated with social approach behavior, both cross-sectionally and prospectively. Hence, individuals with better negative-to-positive updating at Time 1 reported significantly more social approach behaviors across time. The results support the role of negative-to-positive updating as a mechanism associated with SA and social approach, advancing and refining interpersonal and cognitive theories of SA.

Does disconfirmatory evidence shape safety-and danger-related beliefs of trauma-exposed individuals?

Recent accounts of predictive processing in posttraumatic stress disorder (PTSD) suggest that trauma-exposed individuals struggle to update trauma-related hypotheses predicting danger, which may be involved in the etiology and maintenance of this disorder. Initial research supports this account, documenting an association between trauma-exposure, impaired expectation updating, and PTSD symptoms. Yet, no study to date has examined biased belief updating in PTSD using a scenario-based approach.Objective: Here, we examined the predictive processing account among trauma-exposed and non-trauma-exposed individuals using a modified Trauma-Related version of the Bias Against Disconfirmatory Evidence task.Method: The task presents both danger-and safety-related scenarios highly relevant for trauma-exposed individuals. For each scenario, participants viewed several explanations and rated their plausibility. Their ability to update their initial interpretation following new-contradictory information was assessed.Results: Preregistered analyses did not reveal any significant findings. Based on indications that our sample may not have been sufficiently powered, we conducted exploratory analyses in an extended sample of participants. These analyses yielded a significant association between reduced belief updating and PTSD symptoms which was evident for disconfirming both safety and danger scenarios. However, the effect sizes we found were in the small-to-medium range.Conclusion: Although preliminary, our current findings support initial evidence that individuals with higher PTSD symptoms show a higher resistance to update their beliefs upon new disconfirmatory evidence. Our results should be interpreted cautiously in light of the extended sample and the limitations of the current study.

We developed a modified version of the Bias Against Disconfirmatory Evidence task.We found significant associations between PTSD symptoms and belief updating.The association was evident for disconfirming both safety and danger scenarios.

Updating beliefs about pain following advice: Trustworthiness of social advice predicts pain expectations and experience.

Prior expectations influence pain experience. These expectations, in turn, rely on prior pain experience, but they may also be socially influenced. Yet, most research has focused on self rather than social expectations about pain, and hardly any studies examined their combined effects on pain. Here, we adopted a Bayesian learning perspective to investigate how explicitly communicated social expectations ('advice about pain tolerance') affect own pain expectations, and ultimately pain tolerance, under varying conditions of social epistemic uncertainty (trustworthiness of the advice). N = 72 female participants took part in a coldpressor (cold water) task before (self-learning baseline) and after (socially-influenced learning) receiving advice about their likely pain tolerance from a confederate, the trustworthiness of whom was experimentally manipulated. We used path analysis to test the hypothesis that social advice from a highly trustworthy confederate would influence participants' expectations about pain more than advice from a less trustworthy source, and that the degree of this social influence would in turn predict pain tolerance. We further used a simplified, Bayesian learning, computational approach for explicit belief updating to examine the role of latent parameters of precision optimisation in how participants subsequently changed their future pain expectations (prospective posterior beliefs) based on the combined effect of the confederate's advice on their own pain expectations, and their own task experience. Results confirmed that participants adjusted their pain expectations towards the confederate's advice more in the high- vs. low-trustworthiness condition, and this advice taking predicted their pain tolerance. Furthermore, the confederate's trustworthiness influenced how participants weighted the confederate's advice in relation to their own expectations and task experience in forming prospective posterior beliefs. When participants received advice from a less trustworthy confederate, their own sensory experience was weighted more highly than their socially-influenced prior expectations. Thus, explicit social advice appears to impact pain by influencing one's own pain expectations, but low social trustworthiness leads to these expectations becoming more malleable to novel, sensory learning.

Can Invalid Information Be Ignored When It Is Detected?

With the rapid spread of information via social media, individuals are prone to misinformation exposure that they may utilize when forming beliefs. Over five experiments (total N = 815 adults, recruited through Amazon Mechanical Turk in the United States), we investigated whether people could ignore quantitative information when they judged for themselves that it was misreported. Participants recruited online viewed sets of values sampled from Gaussian distributions to estimate the underlying means. They attempted to ignore invalid information, which were outlier values inserted into the value sequences. Results indicated participants were able to detect outliers. Nevertheless, participants' estimates were still biased in the direction of the outlier, even when they were most certain that they detected invalid information. The addition of visual warning cues and different task scenarios did not fully eliminate systematic over- and underestimation. These findings suggest that individuals may incorporate invalid information they meant to ignore when forming beliefs.

Are depressive symptoms linked to a reduced pupillary response to novel positive information?-An eye tracking proof-of-concept study.

Introduction: Depressive symptoms have been linked to difficulties in revising established negative beliefs in response to novel positive information. Recent predictive processing accounts have suggested that this bias in belief updating may be related to a blunted processing of positive prediction errors at the neural level. In this proof-of-concept study, pupil dilation in response to unexpected positive emotional information was examined as a psychophysiological marker of an attenuated processing of positive prediction errors associated with depressive symptoms. Methods: Participants (N = 34) completed a modified version of the emotional Bias Against Disconfirmatory Evidence (BADE) task in which scenarios initially suggest negative interpretations that are later either confirmed or disconfirmed by additional information. Pupil dilation in response to the confirmatory and disconfirmatory information was recorded. Results: Behavioral results showed that depressive symptoms were related to difficulties in revising negative interpretations despite disconfirmatory positive information. The eye tracking results pointed to a reduced pupil response to unexpected positive information among people with elevated depressive symptoms. Discussion: Altogether, the present study demonstrates that the adapted emotional BADE task can be appropriate for examining psychophysiological aspects such as changes in pupil size along with behavioral responses. Furthermore, the results suggest that depression may be characterized by deviations in both behavioral (i.e., reduced updating of negative beliefs) and psychophysiological (i.e., decreased pupil dilation) responses to unexpected positive information. Future work should focus on a larger sample including clinically depressed patients to further explore these findings.

Intellectual humility as a tool to combat false beliefs: An individual-based approach to belief revision.

False beliefs pose significant societal threats, including health risks, political polarization and even violence. In two studies (N = 884) we explored the efficacy of an individual-based approach to correcting false beliefs. We examined whether the character virtue of intellectual humility (IH)-an appreciation of one's intellectual boundaries-encourages revising one's false beliefs in response to counter-information. Our research produced encouraging but also mixed findings. Among participants who held false beliefs about the risks of vaccines (Study 1) and the 2020 US Election being rigged (Study 2), those with higher IH explored more information opposing these false beliefs. This exploration of opposing information, in turn, predicted updating away from these inaccurate health and political beliefs. IH did not directly predict updating away from false beliefs, however, suggesting that this effect-if it exists-may not be particularly powerful. Taken together, these results provide moderate support for IH as a character trait that can foster belief revision but, simultaneously, suggest that alternate pathways to combat false beliefs and misinformation may be preferred.

People with a tobacco use disorder exhibit misaligned Bayesian belief updating by falsely attributing non-drug cues as worse predictors of positive outcomes compared to drug cues.

Adaptive behaviours depend on dynamically updating internal representations of the world based on the ever-changing environmental contingencies. People with a substance use disorder (pSUD) show maladaptive behaviours with high persistence in drug-taking, despite severe negative consequences. We recently proposed a salience misattribution model for addiction (SMMA; Kalhan et al., 2021), arguing that pSUD have aberrations in their updating processes where drug cues are misattributed as strong predictors of positive outcomes, but weaker predictors of negative outcomes. We also argued that conversely, non-drug cues are misattributed as weak predictors of positive outcomes, but stronger predictors of negative outcomes. We tested these hypotheses using a multi-cue reversal learning task, with reversals in whether drug or non-drug cues are relevant in predicting the outcome (monetary win or loss). We show that people with a tobacco use disorder (pTUD), do form misaligned internal representations. We found that pTUD updated less towards learning the drug cue's relevance in predicting a loss. Further, when neither drug nor non-drug cue predicted a win, pTUD updated more towards the drug cue being relevant predictors of that win. Our Bayesian belief updating model revealed that pTUD had a low estimated likelihood of non-drug cues being predictors of wins, compared to drug cues, which drove the misaligned updating. Overall, several hypotheses of the SMMA were supported, but not all. Our results implicate that strengthening the non-drug cue association with positive outcomes may help restore the misaligned internal representation in pTUD, and offers a quantifiable, computational account of these updating processes.

Although I know it: Social anxiety is associated with a deficit in positive updating even when the cost of avoidance is Obvious.

Social anxiety (SA) is associated with difficulties in positively updating negative social information when new information and feedback about chosen options (actual decisions) are received. However, it is unclear whether this difficulty persists when hidden information regarding unchosen options is explicitly presented. The aim of the current study was to address this gap. Participants (Mturk; n = 191) completed a two-phases novel task. In the task, participants chose to approach or avoid people, represented by images of faces. During the initial (learning) phase, participants learned, in a probabilistic context, which people are associated with negative outcomes and should be avoided, and which are associated with positive outcomes and should be approached. During the subsequent updating phase, people previously associated with negative outcomes became associated with positive outcomes and vice versa. Importantly, participants received feedback not only on their approach (actual) decisions, but also on their avoidance (counter-factual) decisions (e.g., approaching this person would have been beneficial). The results revealed that even when the consequences of avoidance were explicitly presented, SA was associated with difficulty in positive updating of social information. The findings support the view that biased updating of social information is a change-resistant mechanism that may underlie the maintenance of SA.

Motivated Cognition in Cooperation.

Successful cooperation is tightly linked to individuals' beliefs about their interaction partners, the decision setting, and existing norms, perceptions, and values. This article reviews and integrates findings from judgment and decision-making, social and cognitive psychology, political science, and economics, developing a systematic overview of the mechanisms underlying motivated cognition in cooperation. We elaborate on how theories and concepts related to motivated cognition developed in various disciplines define the concept and describe its functionality. We explain why beliefs play such an essential role in cooperation, how they can be distorted, and how this fosters or harms cooperation. We also highlight how individual differences and situational factors change the propensity to engage in motivated cognition. In the form of a construct map, we provide a visualization of the theoretical and empirical knowledge structure regarding the role of motivated cognition, including its many interdependencies, feedback loops, and moderating influences. We conclude with a brief suggestion for a future research agenda based on this compiled evidence.

Belief updating when confronted with scientific evidence: Examining the role of trust in science.

In one exploratory study (N = 985) and one preregistered study (N = 1100), we investigated whether trust in science influences belief change on a medico-scientific issue when laypersons are confronted with scientific evidence. Moreover, we tested whether individuals with high trust in science trust science "blindly," meaning that their trust in a scientific claim's source prevents them from adequately evaluating the claim itself. Participants read eight fictitious studies on the efficacy of acupuncture, which were experimentally manipulated regarding direction (evidence favoring acupuncture vs diverging evidence) and quality (high vs low; only Study 2). Acupuncture-related beliefs were measured before and after reading. Moderator and mediator analyses showed that the magnitude of belief change indeed depends on trust in science. Furthermore, we found that people with high trust in science are better able to evaluate the quality of scientific studies, which, in turn, protects them from being influenced by low-quality evidence.

Negative mood and optimism bias: An experimental investigation of sadness and belief updating.

BACKGROUND AND OBJECTIVES: Understanding how individuals integrate new information to form beliefs under changing emotional conditions is crucial to describing decision-making processes. Previous research suggests that although most people demonstrate bias toward optimistic appraisals of new information when updating beliefs, individuals with dysphoric psychiatric conditions (e.g., major depression) do not demonstrate this same bias. Despite these findings, limited research has investigated the relationship between affective states and belief updating processes. METHODS: We induced neutral and sad moods in participants and had them complete a belief-updating paradigm by estimating the likelihood of negative future events happening to them, viewing the actual likelihood, and then re-estimating their perceived likelihood. RESULTS: We observed that individuals updated their beliefs more after receiving desirable information relative to undesirable information under neutral conditions. Further, we found that individuals did not demonstrate unrealistic optimism under negative affective conditions. LIMITATIONS: This study incorporated a population of university students under laboratory conditions and would benefit from replication and extension in clinical populations and naturalistic settings. CONCLUSIONS: These findings suggest that momentary fluctuations in mood affect how individuals integrate information to form beliefs.