Moral judgment of objectionable online content: Reporting decisions and punishment preferences on social media.

Harmful and inappropriate online content is prevalent, necessitating the need to understand how individuals judge and wish to mitigate the spread of negative content on social media. In an online study with a diverse sample of social media users (n = 294), we sought to elucidate factors that influence individuals' evaluation of objectionable online content. Participants were presented with images varying in moral valence, each accompanied by an indicator of intention from an ostensible content poster. Half of the participants were assigned the role of user content moderator, while the remaining participants were instructed to respond as they normally would online. The study aimed to establish whether moral imagery, the intention of a content poster, and the perceived responsibility of social media users, affect judgments of objectionability, operationalized through both decisions to flag content and preferences to seek punishment of other users. Our findings reveal that moral imagery strongly influences users' assessments of what is appropriate online content, with participants almost exclusively choosing to report and punish morally negative images. Poster intention also plays a significant role in user's decisions, with greater objection shown to morally negative content when it has been shared by another user for the purpose of showing support for it. Bestowing a content moderation role affected reporting behaviour but not punishment preferences. We also explore individual user characteristics, finding a negative association between trust in social media platforms and reporting decisions. Conversely, a positive relationship was identified between trait empathy and reporting rates. Collectively, our insights highlight the complexity of social media users' moderation decisions and preferences. The results advance understanding of moral judgments and punishment preferences online, and offer insights for platforms and regulatory bodies aiming to better understand social media users' role in content moderation.

An experimental study of information transparency and social preferences on donation behaviors: the self-signaling model.

Certain segments of the population reply on charitable or other non-governmental organizations as their main source of support, with these organizations largely funded by those in society who can afford to give. The present study investigated to what extent information transparency influences donation decisions, and whether specific preferences for charities influences information seeking behavior. We recruited 114 participants via Prolific and employed a binary online Dictator Game to address these two study objectives. The results showed that participants' actual donation behavior was not influenced by their charity preference or the level of information transparency. However, they were more prone to seek out additional information when deciding about the most preferred category of charity. These results raise important questions as to whether the perceived anonymity of online choices may differ from choices carried out in person.

Beyond lottery-evoked ambiguity aversion: The neural signature of the types and the sources of uncertainty.

Studies on decision-making under uncertainty have mainly focused on understanding preferences for either risk or ambiguity using standard lottery designs. However, people often face uncertainty that directly stems from interacting with other people, which may be processed differently from lottery-based uncertainty. Here, we substantially extend the investigation of uncertainty by examining a fourfold pattern of the sources and the types of uncertainty, assessing behavioral and neural responses to both risk and ambiguity across both social and non-social contexts. A key element in our research design was to control for participants' naturally occurring social beliefs, and taking these a priori beliefs into account allow us to elicit individual preferences in accordance with economic approaches that stress the dynamics of ambiguity preference as a function of underlying likelihoods. Using this design, we find a behavioral main effect of ambiguity aversion, with increasing ambiguity aversion as a function of higher beliefs regarding the likelihood of reciprocity, and related neural activity in the right IPS. This brain region was primarily involved when participants experienced lottery-based uncertainty as opposed to social uncertainty. However, we found that the right IFG was more involved when participants made decisions under social, as compared to non-social, uncertainty. Overall, therefore, the IPS may activate an analytic mindset, which might resonate more with a lottery than a social context, whereas the IFG is engaged when the context requires players to resolve uncertainty, such as unraveling the intentions behind the choice of another person.

Moral strategies and psychopathic traits.

Psychopathy is a personality construct encompassing impaired interpersonal-affective functioning, combined with the inclination to lead an erratic lifestyle and to engage in antisocial acts. Individuals with elevated psychopathic traits often make decisions that have a negative impact on others. Some findings suggest that a lack of empathy and guilt is a key explanatory factor, while other results point toward a decreased sense of fairness in individuals with elevated psychopathic traits. The goal of the present study was to directly compare these hypotheses. Eighty-six healthy individuals completed the Self-Report Psychopathy scale and performed the Hidden Multiplier Trust Game, a socioeconomic decision-making task designed to untangle the roles of guilt and fairness during decision-making. Computational modeling of choice data identified five types of moral decision strategies: inequity aversion, guilt aversion, moral opportunism, greed, and generosity. The model-free results demonstrated that psychopathic traits were associated with lower levels of reciprocity. The model-based results suggested that a reduced sense of fairness, associated with affective traits, was driving this behavior. Our findings stress the importance of treating guilt and fairness as independent concepts, and highlight the importance of improving conceptual precision in untangling the individual impact of fairness and guilt, as this could help explain the mixed results in moral decision-making literature. Elucidating the psychological motivations underlying the relationship between psychopathic traits and poor social decision-making opens new avenues for research on the underlying cognitive mechanisms. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Expect the Worst! Expectations and Social Interactive Decision Making.

Psychological studies have demonstrated that expectations can have substantial effects on choice behavior, although the role of expectations on social decision making in particular has been relatively unexplored. To broaden our knowledge, we examined the role of expectations on decision making when interacting with new game partners and then also in a subsequent interaction with the same partners. To perform this, 38 participants played an Ultimatum Game (UG) in the role of responders and were primed to expect to play with two different groups of proposers, either those that were relatively fair (a tendency to propose an equal split-the high expectation condition) or unfair (with a history of offering unequal splits-the low expectation condition). After playing these 40 UG rounds, they then played 40 Dictator Games (DG) as allocator with the same set of partners. The results showed that expectations affect UG decisions, with a greater proportion of unfair offers rejected from the high as compared to the low expectation group, suggesting that players utilize specific expectations of social interaction as a behavioral reference point. Importantly, this was evident within subjects. Interestingly, we also demonstrated that these expectation effects carried over to the subsequent DG. Participants allocated more money to the recipients of the high expectation group as well to those who made equal offers and, in particular, when the latter were expected to behave unfairly, suggesting that people tend to forgive negative violations and appreciate and reward positive violations. Therefore, both the expectations of others' behavior and their violations play an important role in subsequent allocation decisions. Together, these two studies extend our knowledge of the role of expectations in social decision making.

The Effect of Centralized Financial and Social Incentives on Cooperative Behavior and Its Underlying Neural Mechanisms.

Incentives are frequently used by governments and employers to encourage cooperation. Here, we investigated the effect of centralized incentives on cooperation, firstly in a behavioral study and then replicated in a subsequent neuroimaging (fMRI) study. In both studies, participants completed a novel version of the Public Goods Game, including experimental conditions in which the administration of centralized incentives was probabilistic and incentives were either of a financial or social nature. Behavioral results showed that the prospect of potentially receiving financial and social incentives significantly increased cooperation, with financial incentives yielding the strongest effect. Neuroimaging results showed that activation in the bilateral lateral orbitofrontal cortex and precuneus increased when participants were informed that incentives would be absent versus when they were present. Furthermore, activation in the medial orbitofrontal cortex increased when participants would potentially receive a social versus a financial incentive. These results speak to the efficacy of different types of centralized incentives in increasing cooperative behavior, and they show that incentives directly impact the neural mechanisms underlying cooperation.

Out of control: An altered parieto-occipital-cerebellar network for impulsivity in bipolar disorder.

Bipolar disorder is an affective disorder characterized by rapid fluctuations in mood ranging from episodes of depression to mania, as well as by increased impulsivity. Previous studies investigated the neural substrates of bipolar disorder mainly using univariate methods, with a particular focus on the neural circuitry underlying emotion regulation difficulties. In the present study, capitalizing on an innovative whole-brain multivariate method to structural analysis known as Source-based Morphometry, we investigated the neural substrates of bipolar disorder and their relation with impulsivity, assessed with both self-report measures and performance-based tasks. Structural images from 46 patients with diagnosis of bipolar disorder and 60 healthy controls were analysed. Compared to healthy controls, patients showed decreased gray matter concentration in a parietal-occipital-cerebellar network. Notably, the lower the gray matter concentration in this circuit, the higher the self-reported impulsivity. In conclusion, we provided new evidence of an altered brain network in bipolar disorder patients related to their abnormal impulsivity. Taken together, these findings extend our understanding of the neural and symptomatic characterization of bipolar disorder.

Two distinct and separable processes underlie individual differences in algorithm adherence: Differences in predictions and differences in trust thresholds.

Algorithms play an increasingly ubiquitous and vitally important role in modern society. However, recent findings suggest substantial individual variability in the degree to which people make use of such algorithmic systems, with some users preferring the advice of algorithms whereas others selectively avoid algorithmic systems. The mechanisms that give rise to these individual differences are currently poorly understood. Previous studies have suggested two possible effects that may underlie this variability: users may differ in their predictions of the efficacy of algorithmic systems, and/or in the relative thresholds they hold to place trust in these systems. Based on a novel judgment task with a large number of within-subject repetitions, here we report evidence that both mechanisms exert an effect on experimental participant's degree of algorithm adherence, but, importantly, that these two mechanisms are independent from each-other. Furthermore, participants are more likely to place their trust in an algorithmically managed fund if their first exposure to the task was with an algorithmic manager. These findings open the door for future research into the mechanisms driving individual differences in algorithm adherence, and allow for novel interventions to increase adherence to algorithms.

Stable distribution of reciprocity motives in a population.

Evolutionary models show that human cooperation can arise through direct reciprocity relationships. However, it remains unclear which psychological mechanisms proximally motivate individuals to reciprocate. Recent evidence suggests that the psychological motives for choosing to reciprocate trust differ between individuals, which raises the question whether these differences have a stable distribution in a population or are rather an artifact of the experimental task. Here, we combine data from three independent trust game studies to find that the relative prevalence of different reciprocity motives is highly stable across participant samples. Furthermore, the distribution of motives is relatively unaffected by changes to the salient features of the experimental paradigm. Finally, the motive classification assigned by our computational modeling analysis corresponds to the participants' own subjective experience of their psychological decision process, and no existing models of social preference can account for the observed individual differences in reciprocity motives. These findings support the view that reciprocal decision-making is not just regulated by individual differences in 'pro-social' versus 'pro-self' tendencies, but also by trait-like differences across several alternative pro-social motives, whose distribution in a population is stable.

Neural Mechanisms of Choice Diversification.

When asked to select several options at once, people tend to choose a greater diversity of items than when they are asked to make these selections one at a time. Using functional magnetic resonance imaging (fMRI), we provide novel insight into the neural mechanisms underlying diversification in portfolio choices. We found that, as participants made multiple selections from a menu of different options, the current state of their choice portfolio (i.e., the previously selected options) dynamically modulates activity in the neural valuation system in response to the options under evaluation. More specifically, we found that activity in the ventral striatum (VS) decreases when the option has already been selected ("satiation"), while activity in the ventromedial prefrontal cortex increases when other options have previously been selected ("novelty-seeking"). Our findings reveal two processes that drive diversification in portfolio choices, and suggest that the context of previous selections strongly impacts how the brain evaluates current choice options.

Decoding dynamic affective responses to naturalistic videos with shared neural patterns.

This study explored the feasibility of using shared neural patterns from brief affective episodes (viewing affective pictures) to decode extended, dynamic affective sequences in a naturalistic experience (watching movie-trailers). Twenty-eight participants viewed pictures from the International Affective Picture System (IAPS) and, in a separate session, watched various movie-trailers. We first located voxels at bilateral occipital cortex (LOC) responsive to affective picture categories by GLM analysis, then performed between-subject hyperalignment on the LOC voxels based on their responses during movie-trailer watching. After hyperalignment, we trained between-subject machine learning classifiers on the affective pictures, and used the classifiers to decode affective states of an out-of-sample participant both during picture viewing and during movie-trailer watching. Within participants, neural classifiers identified valence and arousal categories of pictures, and tracked self-reported valence and arousal during video watching. In aggregate, neural classifiers produced valence and arousal time series that tracked the dynamic ratings of the movie-trailers obtained from a separate sample. Our findings provide further support for the possibility of using pre-trained neural representations to decode dynamic affective responses during a naturalistic experience.

Subjective Beliefs About Trust and Reciprocity Activate an Expected Reward Signal in the Ventral Striatum.

There is overwhelming evidence that the evaluation of both reward decisions and their associated outcomes are closely linked with bilateral activation of the ventral striatum, with these insights stemming from tasks such as the monetary incentive delay task for lotteries and multiround Trust Games for social settings. The essential element in these tasks is an externally provided cue associated with specific gains/trustworthy partners and losses/non-trustworthy partners. However, in reality people typically use their own beliefs to guide their decision-making and assess the likelihood of positive or and negative outcomes. As when participants assess the relationship between cues and rewards, individuals should anticipate rewards in correspondence to their beliefs, i.e., the higher the belief of obtaining a reward in the future, the higher the anticipation of reward. In this study, we use decision-makers' own, naturally occurring, beliefs about both social and non-social contexts to examine the subsequent outcome of their choices. We hypothesize that mechanisms of belief-mediated reward processing are mediated by neural activation in the ventral striatum. An essential feature of our design is the elicitation of individuals' beliefs prior to the decision-making task itself. Furthermore, our incentivized, non-deceptive, decision-making task distinguishes between social - implemented by a Trust Game - and non-social sources, as well as risk and ambiguity as underlying types of uncertainty. Our main result shows that individual beliefs regarding reciprocity likelihoods in both the Trust Game and the lottery influence the amount invested. Subsequently, only the investment amount in the Trust Game parametrically modulates anticipatory reward and outcome evaluation in the ventral striatum. This study demonstrates a first approach at using participants' subjective sets of beliefs to examine reward processing. We discuss its potential promise, outline some limitations, and propose follow-up studies to extend the current approach.

Neurocognitive mechanisms of reactions to second- and third-party justice violations.

The aim of the current study was threefold: (i) understand people's willingness to engage in either punishment of the perpetrator or compensation of the victim in order to counteract injustice; (ii) look into the differences between victims of and witnesses to injustice; (iii) investigate the different role played by social preference and affective experience in determining these choices. The sample tested here showed an equal preference for punishment and compensation; neuroimaging findings suggested that compensation, as opposed to punishment, was related to Theory of Mind. Partially supporting previous literature, choosing how to react to an injustice as victims, rather than witnesses, triggered a stronger affective response (striatal and prefrontal activation). Moreover, results supported the idea that deciding whether or not to react to an injustice and then how severely to react are two distinct decisional stages underpinned by different neurocognitive mechanisms, i.e., sensitivity to unfairness (anterior insula) and negative affectivity (amygdala). These findings provide a fine-grained description of the psychological mechanisms underlying important aspects of social norm compliance.

Psychopathic traits are related to diminished guilt aversion and reduced trustworthiness during social decision-making.

Individuals with high levels of psychopathic tendencies tend to show a lack of guilt, a lack of empathic concern, and a disregard for the impact of their decisions on others. However, how guilt influences social decision-making for those with high psychopathic traits is still unknown. Here, we investigated how psychopathic traits relate to the capacity to acquire knowledge about social expectations, and to what extent guilt aversion affects subsequent decision-making. 63 participants completed self-report measures of psychopathy, and then played a modified Trust Game in the role of the Trustee. Results showed that participants' self-reported beliefs about their partner's expectations were largely predictive of the amount of money they returned to the partner. These decisions were negatively correlated with the PPI-I scores. Furthermore, participants' degree of guilt aversion were negatively correlated with PPI total scores. Our findings suggest that individuals with higher psychopathic traits are indeed capable of understanding the expectations of others, but do not seem to directly utilise this knowledge in their social decision-making, and experience less anticipated guilt about this. The present study provides empirical evidence of intact social knowledge coupled with decreased reciprocity and diminished guilt aversion as levels of psychopathic traits increase.

A scarcity mindset alters neural processing underlying consumer decision making.

Not having enough of what one needs has long been shown to have detrimental consequences for decision making. Recent work suggests that the experience of insufficient resources can create a "scarcity" mindset; increasing attention toward the scarce resource itself, but at the cost of attention for unrelated aspects. To investigate the effects of a scarcity mindset on consumer choice behavior, as well as its underlying neural mechanisms, we used an experimental manipulation to induce both a scarcity and an abundance mindset within participants and examined the effects of both mindsets on participants' willingness to pay for familiar food items while being scanned using fMRI. Results demonstrated that a scarcity mindset affects neural mechanisms related to consumer decision making. When in a scarcity mindset compared with an abundance mindset, participants had increased activity in the orbitofrontal cortex, a region often implicated in valuation processes. Moreover, again compared with abundance, a scarcity mindset decreased activity in dorsolateral prefrontal cortex, an area well known for its role in goal-directed choice. This effect was predominant in the group of participants who experienced scarcity following abundance, suggesting that the effects of scarcity are largest when they are compared with previous situations when resources were plentiful. More broadly, these data suggest a potential neural locus for a scarcity mindset and demonstrate how these changes in brain activity might underlie goal-directed decision making.

The computational and neural substrates of moral strategies in social decision-making.

Individuals employ different moral principles to guide their social decision-making, thus expressing a specific 'moral strategy'. Which computations characterize different moral strategies, and how might they be instantiated in the brain? Here, we tackle these questions in the context of decisions about reciprocity using a modified Trust Game. We show that different participants spontaneously and consistently employ different moral strategies. By mapping an integrative computational model of reciprocity decisions onto brain activity using inter-subject representational similarity analysis of fMRI data, we find markedly different neural substrates for the strategies of 'guilt aversion' and 'inequity aversion', even under conditions where the two strategies produce the same choices. We also identify a new strategy, 'moral opportunism', in which participants adaptively switch between guilt and inequity aversion, with a corresponding switch observed in their neural activation patterns. These findings provide a valuable view into understanding how different individuals may utilize different moral principles.

Catecholaminergic modulation of trust decisions.

RATIONALE: Trust is a key component of social interactions. In order to assess the trustworthiness of others, people rely on both information learned from previous encounters, as well as on implicit biases associated with specific facial features. OBJECTIVE: Here, we investigated the role of catecholamine (dopamine and noradrenaline) transmission on trust decisions as a function of both experienced behavior and facial features. METHODS: To increase catecholamine levels, methylphenidate (MPH, i.e., Ritalin®, 20 mg) was administered to participants (N = 24) prior to their playing a well-studied economic task, namely the Trust Game (Berg et al. 1995). We measured the amount of money invested with a variety of game partners. Across game partners, we manipulated two aspects of trust: the facial trust level (high facial trust, low facial trust, and non-social) and the likelihood of reciprocation (high, low). RESULTS: Results demonstrated no main effect of MPH on investments, but rather a selective lowering of investments under MPH as compared with placebo with the game partners who were low on facial trustworthiness and were low reciprocators. CONCLUSION: These results provide evidence that MPH administration impacts social trust decision-making, but does so in a context-specific manner.

Expectations in the Ultimatum Game: Distinct Effects of Mean and Variance of Expected Offers.

Being treated fairly by others is an important need in everyday life. Experimentally, fairness can be studied using the Ultimatum Game, where the decision to reject a low, but non-zero offer is seen as a way to punish the other player for an unacceptable offer. The canonical explanation of such behavior is inequity aversion: people prefer equal outcomes over personal gains. However, there is abundant evidence that people's decision to reject a low offer can be changed by contextual factors and their emotional state, which cannot be explained by the inequity aversion model. Here, we expand a recent alternative explanation: rejections are driven by deviations from expectations: the larger the difference between the actual offer and the expected offer, the more likely one is to reject the offer. Specifically, we provided participants with explicit information on what kind of offers to expect using histograms depicting distribution of offers given in a previous experiment by the same proposers. Crucially, we showed four different distributions, manipulating both the mean and the variance of these expected sets of offers. We found that 50% of our participants clearly and systematically changed their behavior as a function of their expectations (11% followed the standard-economic model of pure self-interest and 39% where not distinguishable from the inequity-aversion model). Using a logistic mixed-model analysis, we found that the mean and variance differently affect the decision to reject an offer. Specifically, the mean expected offer affected the threshold of what offers are acceptable, while the expected variance of offers changed how strict participants were about this threshold. Together, these results suggest that social expectations have a more complex nature as current theories propose.

Neurobiological Mechanisms of Responding to Injustice.

People are particularly sensitive to injustice. Accordingly, deeper knowledge regarding the processes that underlie the perception of injustice, and the subsequent decisions to either punish transgressors or compensate victims, is of important social value. By combining a novel decision-making paradigm with functional neuroimaging, we identified specific brain networks that are involved with both the perception of, and response to, social injustice, with reward-related regions preferentially involved in punishment compared with compensation. Developing a computational model of punishment allowed for disentangling the neural mechanisms and psychological motives underlying decisions of whether to punish and, subsequently, of how severely to punish. Results show that the neural mechanisms underlying punishment differ depending on whether one is directly affected by the injustice, or whether one is a third-party observer of a violation occurring to another. Specifically, the anterior insula was involved in decisions to punish following harm, whereas, in third-party scenarios, we found amygdala activity associated with punishment severity. Additionally, we used a pharmacological intervention using oxytocin, and found that oxytocin influenced participants' fairness expectations, and in particular enhanced the frequency of low punishments. Together, these results not only provide more insight into the fundamental brain mechanisms underlying punishment and compensation, but also illustrate the importance of taking an explorative, multimethod approach when unraveling the complex components of everyday decision-making.SIGNIFICANCE STATEMENT The perception of injustice is a fundamental precursor to many disagreements, from small struggles at the dinner table to wasteful conflict between cultures and countries. Despite its clear importance, relatively little is known about how the brain processes these violations. Taking an interdisciplinary approach, we combine methods from neuroscience, psychology, and economics to explore the neurobiological mechanisms involved in both the perception of injustice as well as the punishment and compensation decisions that follow. Using a novel behavioral paradigm, we identified specific brain networks, developed a computational model of punishment, and found that administrating the neuropeptide oxytocin increases the administration of low punishments of norm violations in particular. Results provide valuable insights into the fundamental neurobiological mechanisms underlying social injustice.

Why we stay with our social partners: Neural mechanisms of stay/leave decision-making.

How do we decide to keep interacting (e.g., stay) with a social partner or to switch (e.g., leave) to another? This paper investigated the neural mechanisms of stay/leave decision-making. We hypothesized that these decisions fit within a framework of value-based decision-making, and explored four potential mechanisms underlying a hypothesized bias to stay. Twenty-six participants underwent functional Magnetic Resonance Imaging (fMRI) while completing social and nonsocial versions of a stay/leave decision-making task. On each trial, participants chose between four alternative options, after which they received a monetary reward. Crucially, in the social condition, reward magnitude was ostensibly determined by the generosity of social partners, whereas in the nonsocial condition, reward amounts were ostensibly determined in a pre-programmed manner. Results demonstrated that participants were more likely to stay with options of relatively high expected value, with these values updated through Reinforcement Learning mechanisms and represented neurally within ventromedial prefrontal cortex. Moreover, we demonstrated that greater brain activity in ventromedial prefrontal cortex, caudate nucleus, and septo-hypothalamic regions for social versus nonsocial decisions to stay may underlie a bias towards staying with social partners in particular. These findings complement existing social psychological theories by investigating the neural mechanisms of actual stay/leave decisions.