Observing others give & take: A computational account of bystanders' feelings and actions.

Social interactions influence people's feelings and behavior. Here, we propose that a person's well-being is influenced not only by interactions they experience themselves, but also by those they observe. In particular, we test and quantify the influence of observed selfishness and observed inequality on a bystanders' feelings and non-costly punishment decisions. We developed computational models that relate others' (un)selfish acts to observers' emotional reactions and punishment decisions. These characterize the rules by which others' interactions are transformed into bystanders' reactions, and successfully predict those reactions in out-of-sample participants. The models highlight the impact of two social values-'selfishness aversion' and 'inequality aversion'. As for the latter we find that even small violations from perfect equality have a disproportionately large impact on feelings and punishment. In this age of internet and social media we constantly observe others' online interactions, in addition to in-person interactions. Quantifying the consequences of such observations is important for predicting their impact on society.

Under Threat, Weaker Evidence Is Required to Reach Undesirable Conclusions.

Critical decisions, such as in domains ranging from medicine to finance, are often made under threatening circumstances that elicit stress and anxiety. The negative effects of such reactions on learning and decision-making have been repeatedly underscored. In contrast, here we show that perceived threat alters the process by which evidence is accumulated in a way that may be adaptive. Participants (n = 91) completed a sequential evidence sampling task in which they were incentivized to accurately judge whether they were in a desirable state, which was associated with greater rewards than losses, or an undesirable state, which was associated with greater losses than rewards. Before the task participants in the "threat group" experienced a social-threat manipulation. Results show that perceived threat led to a reduction in the strength of evidence required to reach an undesirable judgment. Computational modeling revealed this was because of an increase in the relative rate by which negative information was accumulated. The effect of the threat manipulation was global, as the alteration to evidence accumulation was observed for information which was not directly related to the cause of the threat. Requiring weaker evidence to reach undesirable conclusions in threatening environments may be adaptive as it can lead to increased precautionary action.SIGNIFICANCE STATEMENT To make good judgments, people gather information. As information is often unlimited, a decision has to be made as to when the data are sufficiently strong to reach a conclusion. Here, we show that this decision is significantly influenced by perceived threat. In particular, under threat, the rate of negative information accumulation increased, such that weaker evidence was required to reach an undesirable conclusion. Such modulation could be adaptive as it can result in enhanced cautious behavior in dangerous environments.

Valuation of knowledge and ignorance in mesolimbic reward circuitry.

The pursuit of knowledge is a basic feature of human nature. However, in domains ranging from health to finance people sometimes choose to remain ignorant. Here, we show that valence is central to the process by which the human brain evaluates the opportunity to gain information, explaining why knowledge may not always be preferred. We reveal that the mesolimbic reward circuitry selectively treats the opportunity to gain knowledge about future favorable outcomes, but not unfavorable outcomes, as if it has positive utility. This neural coding predicts participants' tendency to choose knowledge about future desirable outcomes more often than undesirable ones, and to choose ignorance about future undesirable outcomes more often than desirable ones. Strikingly, participants are willing to pay both for knowledge and ignorance as a function of the expected valence of knowledge. The orbitofrontal cortex (OFC), however, responds to the opportunity to receive knowledge over ignorance regardless of the valence of the information. Connectivity between the OFC and mesolimbic circuitry could contribute to a general preference for knowledge that is also modulated by valence. Our findings characterize the importance of valence in information seeking and its underlying neural computation. This mechanism could lead to suboptimal behavior, such as when people reject medical screenings or monitor investments more during bull than bear markets.

Evidence accumulation is biased by motivation: A computational account.

To make good judgments people gather information. An important problem an agent needs to solve is when to continue sampling data and when to stop gathering evidence. We examine whether and how the desire to hold a certain belief influences the amount of information participants require to form that belief. Participants completed a sequential sampling task in which they were incentivized to accurately judge whether they were in a desirable state, which was associated with greater rewards than losses, or an undesirable state, which was associated with greater losses than rewards. While one state was better than the other, participants had no control over which they were in, and to maximize rewards they had to maximize accuracy. Results show that participants' judgments were biased towards believing they were in the desirable state. They required a smaller proportion of supporting evidence to reach that conclusion and ceased gathering samples earlier when reaching the desirable conclusion. The findings were replicated in an additional sample of participants. To examine how this behavior was generated we modeled the data using a drift-diffusion model. This enabled us to assess two potential mechanisms which could be underlying the behavior: (i) a valence-dependent response bias and/or (ii) a valence-dependent process bias. We found that a valence-dependent model, with both a response bias and a process bias, fit the data better than a range of other alternatives, including valence-independent models and models with only a response or process bias. Moreover, the valence-dependent model provided better out-of-sample prediction accuracy than the valence-independent model. Our results provide an account for how the motivation to hold a certain belief decreases the need for supporting evidence. The findings also highlight the advantage of incorporating valence into evidence accumulation models to better explain and predict behavior.

Updating Beliefs under Perceived Threat.

Humans are better at integrating desirable information into their beliefs than undesirable information. This asymmetry poses an evolutionary puzzle, as it can lead to an underestimation of risk and thus failure to take precautionary action. Here, we suggest a mechanism that can speak to this conundrum. In particular, we show that the bias vanishes in response to perceived threat in the environment. We report that an improvement in participants' tendency to incorporate bad news into their beliefs is associated with physiological arousal in response to threat indexed by galvanic skin response and self-reported anxiety. This pattern of results was observed in a controlled laboratory setting (Experiment I), where perceived threat was manipulated, and in firefighters on duty (Experiment II), where it naturally varied. Such flexibility in how individuals integrate information may enhance the likelihood of responding to warnings with caution in environments rife with threat, while maintaining a positivity bias otherwise, a strategy that can increase well-being.SIGNIFICANCE STATEMENT The human tendency to be overly optimistic has mystified scholars and lay people for decades: How could biased beliefs have been selected over unbiased beliefs? Scholars have suggested that although the optimism bias can lead to negative outcomes, including financial collapse and war, it can also facilitate health and productivity. Here, we demonstrate that a mechanism generating the optimism bias, namely asymmetric information integration, evaporates under threat. Such flexibility could result in enhanced caution in dangerous environments while supporting an optimism bias otherwise, potentially increasing well-being.

Social Information Is Integrated into Value and Confidence Judgments According to Its Reliability.

How much we like something, whether it be a bottle of wine or a new film, is affected by the opinions of others. However, the social information that we receive can be contradictory and vary in its reliability. Here, we tested whether the brain incorporates these statistics when judging value and confidence. Participants provided value judgments about consumer goods in the presence of online reviews. We found that participants updated their initial value and confidence judgments in a Bayesian fashion, taking into account both the uncertainty of their initial beliefs and the reliability of the social information. Activity in dorsomedial prefrontal cortex tracked the degree of belief update. Analogous to how lower-level perceptual information is integrated, we found that the human brain integrates social information according to its reliability when judging value and confidence.SIGNIFICANCE STATEMENT The field of perceptual decision making has shown that the sensory system integrates different sources of information according to their respective reliability, as predicted by a Bayesian inference scheme. In this work, we hypothesized that a similar coding scheme is implemented by the human brain to process social signals and guide complex, value-based decisions. We provide experimental evidence that the human prefrontal cortex's activity is consistent with a Bayesian computation that integrates social information that differs in reliability and that this integration affects the neural representation of value and confidence.

Optimistic update bias holds firm: Three tests of robustness following Shah et al.

A diverse body of research has demonstrated that people update their beliefs to a greater extent when receiving good news compared to bad news. Recently, a paper by Shah et al. claimed that this asymmetry does not exist. Here we carefully examine the experiments and simulations described in Shah et al. and follow their analytic approach on our data sets. After correcting for confounds we identify in the experiments of Shah et al., an optimistic update bias for positive life events is revealed. Contrary to claims made by Shah et al., we observe that participants update their beliefs in a more Bayesian manner after receiving good news than bad. Finally, we show that the parameters Shah et al. pre-selected for simulations are at odds with participants' data, making these simulations irrelevant to the question asked. Together this report makes a strong case for a true optimistic asymmetry in belief updating.

Human Frontal-Subcortical Circuit and Asymmetric Belief Updating.

How humans integrate information to form beliefs about reality is a question that has engaged scientists for centuries, yet the biological system supporting this process is not well understood. One of the most salient attributes of information is valence. Whether a piece of news is good or bad is critical in determining whether it will alter our beliefs. Here, we reveal a frontal-subcortical circuit in the left hemisphere that is simultaneously associated with enhanced integration of favorable information into beliefs and impaired integration of unfavorable information. Specifically, for favorable information, stronger white matter connectivity within this system, particularly between the left inferior frontal gyrus (IFG) and left subcortical regions (including the amygdala, hippocampus, thalamus, putamen, and pallidum), as well as insular cortex, is associated with greater change in belief. However, for unfavorable information, stronger connectivity within this system, particularly between the left IFG and left pallidum, putamen, and insular cortex, is associated with reduced change in beliefs. These novel results are consistent with models suggesting that partially separable processes govern learning from favorable and unfavorable information. SIGNIFICANCE STATEMENT: Beliefs of what may happen in the future are important, because they guide decisions and actions. Here, we illuminate how structural brain connectivity is related to the generation of subjective beliefs. We focus on how the valence of information is related to people's tendency to alter their beliefs. By quantifying the extent to which participants update their beliefs in response to desirable and undesirable information and relating those measures to the strength of white matter connectivity using diffusion tensor imaging, we characterize a left frontal-subcortical system that is associated simultaneously with greater belief updating in response to favorable information and reduced belief updating in response to unfavorable information. This neural architecture may allow valence to be incorporated into belief updating.

Models of Affective Decision Making: How Do Feelings Predict Choice?

Intuitively, how you feel about potential outcomes will determine your decisions. Indeed, an implicit assumption in one of the most influential theories in psychology, prospect theory, is that feelings govern choice. Surprisingly, however, very little is known about the rules by which feelings are transformed into decisions. Here, we specified a computational model that used feelings to predict choices. We found that this model predicted choice better than existing value-based models, showing a unique contribution of feelings to decisions, over and above value. Similar to the value function in prospect theory, our feeling function showed diminished sensitivity to outcomes as value increased. However, loss aversion in choice was explained by an asymmetry in how feelings about losses and gains were weighted when making a decision, not by an asymmetry in the feelings themselves. The results provide new insights into how feelings are utilized to reach a decision.

Human development of the ability to learn from bad news.

Humans show a natural tendency to discount bad news while incorporating good news into beliefs (the "good news-bad news effect"), an effect that may help explain seemingly irrational risk taking. Understanding how this bias develops with age is important because adolescents are prone to engage in risky behavior; thus, educating them about danger is crucial. We reveal a striking valence-dependent asymmetry in how belief updating develops with age. In the ages tested (9-26 y), younger age was associated with inaccurate updating of beliefs in response to undesirable information regarding vulnerability. In contrast, the ability to update beliefs accurately in response to desirable information remained relatively stable with age. This asymmetry was mediated by adequate computational use of positive but not negative estimation errors to alter beliefs. The results are important for understanding how belief formation develops and might help explain why adolescents do not respond adequately to warnings.

Brain substrates of recovery from misleading influence.

Humans are strongly influenced by their environment, a dependence that can lead to errors in judgment. Although a rich literature describes how people are influenced by others, little is known regarding the factors that predict subsequent rectification of misleading influence. Using a mediation model in combination with brain imaging, we propose a model for the correction of misinformation. Specifically, our data suggest that amygdala modulation of hippocampal mnemonic representations, during the time of misleading social influence, is associated with reduced subsequent anterior-lateral prefrontal cortex activity that reflects correction. These findings illuminate the process by which erroneous beliefs are, or fail to be, rectified and highlight how past influence constrains subsequent correction.

The brain's temporal dynamics from a collective decision to individual action.

Social animals constantly make decisions together. What determines if individuals will subsequently adjust their behavior to align with collective choices? Here, using functional magnetic resonance imaging in humans, we characterize a novel temporal model of brain response from the time a collective decision is made to the time an individual action is required. We reveal that whether a behavioral modification will occur is determined not necessarily by the brain's response to the initial social influence, but by how that response (specifically in the orbitofrontal cortex; OFC) is mirrored at a later time when the individual selects their own action. This result suggests that the OFC may reconstitute an initial state of collective influence when individual action is subsequently needed. Importantly, these dynamics vary across individuals as a function of trait conformity and mediate the relationship between this personality characteristic and behavioral adjustment toward the group.

Selectively altering belief formation in the human brain.

Humans form beliefs asymmetrically; we tend to discount bad news but embrace good news. This reduced impact of unfavorable information on belief updating may have important societal implications, including the generation of financial market bubbles, ill preparedness in the face of natural disasters, and overly aggressive medical decisions. Here, we selectively improved people's tendency to incorporate bad news into their beliefs by disrupting the function of the left (but not right) inferior frontal gyrus using transcranial magnetic stimulation, thereby eliminating the engrained "good news/bad news effect." Our results provide an instance of how selective disruption of regional human brain function paradoxically enhances the ability to incorporate unfavorable information into beliefs of vulnerability.

Action controls dopaminergic enhancement of reward representations.

Dopamine is widely observed to signal anticipation of future rewards and thus thought to be a key contributor to affectively charged decision making. However, the experiments supporting this view have not dissociated rewards from the actions that lead to, or are occasioned by, them. Here, we manipulated dopamine pharmacologically and examined the effect on a task that explicitly dissociates action and reward value. We show that dopamine enhanced the neural representation of rewarding actions, without significantly affecting the representation of reward value as such. Thus, increasing dopamine levels with levodopa selectively boosted striatal and substantia nigra/ventral tegmental representations associated with actions leading to reward, but not with actions leading to the avoidance of punishment. These findings highlight a key role for dopamine in the generation of appetitively motivated actions.

"How" web searches change under stress.

To adjust to stressful environments, people seek information. Here, we show that in response to stressful public and private events the high-level features of information people seek online alter, reflecting their motives for seeking knowledge. We first show that when people want information to guide action they selectively ask "How" questions. Next, we reveal that "How" searches submitted to Google increased dramatically during the pandemic (controlling for search volume). Strikingly, the proportion of these searches predicted weekly self-reported stress of ~ 17K individuals. To rule out third factors we manipulate stress and find that "How" searches increase in response to stressful, personal, events. The findings suggest that under stress people ask questions to guide action, and mental state is reflected in features that tap into why people seek information rather than the topics they search for. Tracking such features may provide clues regrading population stress levels.

Neural mechanisms mediating optimism bias.

Humans expect positive events in the future even when there is no evidence to support such expectations. For example, people expect to live longer and be healthier than average, they underestimate their likelihood of getting a divorce, and overestimate their prospects for success on the job market. We examined how the brain generates this pervasive optimism bias. Here we report that this tendency was related specifically to enhanced activation in the amygdala and in the rostral anterior cingulate cortex when imagining positive future events relative to negative ones, suggesting a key role for areas involved in monitoring emotional salience in mediating the optimism bias. These are the same regions that show irregularities in depression, which has been related to pessimism. Across individuals, activity in the rostral anterior cingulate cortex was correlated with trait optimism. The current study highlights how the brain may generate the tendency to engage in the projection of positive future events, suggesting that the effective integration and regulation of emotional and autobiographical information supports the projection of positive future events in healthy individuals, and is related to optimism.

There is no belief update bias for neutral events: failure to replicate Burton et al. (2022).

In a recent paper, Burton et al. claim that individuals update beliefs to a greater extent when learning an event is less likely compared to more likely than expected. Here, we investigate Burton's et al.'s, findings. First, we show how Burton et al.'s data do not in fact support a belief update bias for neutral events. Next, in an attempt to replicate their findings, we collect a new data set employing the original belief update task design, but with neutral events. A belief update bias for neutral events is not observed. Finally, we highlight the statistical errors and confounds in Burton et al.'s design and analysis. This includes mis-specifying a reinforcement learning approach to model the data and failing to follow standard computational model fitting sanity checks such as parameter recovery, model comparison and out of sample prediction. Together, the results find little evidence for biased updating for neutral events.

Sensitivity to intrinsic rewards is domain general and related to mental health.

Humans frequently engage in intrinsically rewarding activities (for example, consuming art, reading). Despite such activities seeming diverse, we show that sensitivity to intrinsic rewards is domain general and associated with mental health. In this cross-sectional study, participants online (N = 483) were presented with putative visual, cognitive and social intrinsic rewards as well as monetary rewards and neutral stimuli. All rewards elicited positive feelings (were 'liked'), generated consummatory behaviour (were 'wanted') and increased the likelihood of the action leading to them (were 'reinforcing'). Factor analysis revealed that ~40% of response variance across stimuli was explained by a general sensitivity to all rewards, but not to neutral stimuli. Affective aspects of mental health were associated with sensitivity to intrinsic, but not monetary, rewards. These results may help explain thriving and suffering: individuals with high reward sensitivity will engage in a variety of intrinsically rewarding activities, eventually finding those they excel at, whereas low sensitivity individuals will not.

Changing the incentive structure of social media platforms to halt the spread of misinformation.

The powerful allure of social media platforms has been attributed to the human need for social rewards. Here, we demonstrate that the spread of misinformation on such platforms is facilitated by existing social 'carrots' (e.g., 'likes') and 'sticks' (e.g., 'dislikes') that are dissociated from the veracity of the information shared. Testing 951 participants over six experiments, we show that a slight change to the incentive structure of social media platforms, such that social rewards and punishments are contingent on information veracity, produces a considerable increase in the discernment of shared information. Namely, an increase in the proportion of true information shared relative to the proportion of false information shared. Computational modeling (i.e., drift-diffusion models) revealed the underlying mechanism of this effect is associated with an increase in the weight participants assign to evidence consistent with discerning behavior. The results offer evidence for an intervention that could be adopted to reduce misinformation spread, which in turn could reduce violence, vaccine hesitancy and political polarization, without reducing engagement.

In recent years, the amount of untrue information, or 'misinformation', shared online has increased rapidly. This can have profound effects on society and has been linked to violence, political extremism, and resistance to climate action. One reason for the spread of misinformation is the lack of incentives for users to share true content and avoid sharing false content. People tend to select actions that they believe will lead to positive feedback ('carrots') and try to avoid actions that lead to negative feedback ('sticks'). On most social media sites, these carrots and sticks come in the form of 'like' and 'dislike' reactions, respectively. Stories that users think will attract 'likes' are most likely to be shared with other users. However, because the number of likes a post receives is not representative of how accurate it is, users share information even if they suspect it may not be accurate. As a result, misinformation can spread rapidly. Measures aimed at slowing the spread of misinformation have been introduced to some social media sites, such as removing a few virulent spreaders of falsities and flagging misleading content. However, measures that change the incentive structure of sites so that positive and negative feedback is based on the trustworthiness of the information have not yet been explored. To test this approach, Globig et al. set up a simulated social media site that included 'trust' and 'distrust' buttons, as well as the usual 'like' and 'dislike' options. The site featured up to one hundred news stories, half of which were untrue. More than 900 participants viewed the news posts and could react using the new buttons as well as repost the stories. The experiment showed that participants used the 'trust' and 'distrust' buttons to differentiate between true and false posts more than the other options. As a result, to receive more 'trust' responses and less 'distrust' responses from other users, participants were more likely to repost true stories than false ones. This led to a large reduction in the amount of misinformation being spread. Computational modeling revealed that the participants were paying more attention to how reliable a news story appeared to be when deciding whether to repost it. Globig et al. showed that adding buttons to highlight the trustworthiness of posts on social media sites reduces the spread of misinformation, without reducing user engagement. This measure could be easily incorporated into existing social media sites and could have a positive impact on issues that are often fuelled by misinformation, such as vaccine hesitancy and resistance to climate action.