Computational substrates of social value in interpersonal collaboration

Callousness, exploitativeness, and tracking of cooperation incentives in the human default network

Human cognitive capacities that enable flexible cooperation may have evolved in parallel with the expansion of frontoparietal cortical networks, particularly the default network. Conversely, human antisocial behavior and trait antagonism are broadly associated with reduced activity, impaired connectivity, and altered structure of the default network. Yet, behaviors like interpersonal manipulation and exploitation may require intact or even superior social cognition. Using a reinforcement learning model of decision-making on a modified trust game, we examined how individuals adjusted their cooperation rate based on a counterpart's cooperation and social reputation. We observed that learning signals in the default network updated the predicted utility of cooperation or defection and scaled with reciprocal cooperation. These signals were weaker in callous (vs. compassionate) individuals but stronger in those who were more exploitative (vs. honest and humble). Further, they accounted for associations between exploitativeness, callousness, and reciprocal cooperation. Separately, behavioral sensitivity to prior reputation was reduced in callous but not exploitative individuals and selectively scaled with responses of the medial temporal subsystem of the default network. Overall, callousness was characterized by blunted behavioral and default network sensitivity to cooperation incentives. Exploitativeness predicted heightened sensitivity to others' cooperation but not social reputation. We speculate that both compassion and exploitativeness may reflect cognitive adaptations to social living, enabled by expansion of the default network in anthropogenesis.

The acquired dyad inclination and decreased interpersonal brain communication in the pursuit of collective benefit

People perform better collectively than individually, a phenomenon known as the collective benefit. To pursue the benefit, they may learn from previous behaviors, come to know whose initial opinion should be valued, and develop the inclination to take it as the collective one. Such learning may affect interpersonal brain communication. To test these hypotheses, this study recruited participant dyads to conduct a perceptual task on which they made individual decisions first and then the collective one. The enhanced interpersonal brain synchronization (IBS) between participants was explored when individual decisions were in disagreement vs. agreement. Computational modeling revealed that participant dyads developed the dyad inclination of taking the higher-able participants', not the lower-able ones' decisions as their collective ones. Brain analyses unveiled the enhanced IBS at frontopolar areas, premotor areas, supramarginal gyri, and right temporal-parietal junctions. The premotor IBS correlated negatively with dyad inclination and collective benefit in the absence of correction. The Granger causality analyses further supported the negative relation of dyad inclination with inter-brain communication. This study highlights that dyads learn to weigh individuals' decisions, resulting in dyad inclinations, and explores associated inter-brain communication, offering insights into the dynamics of collective decision-making.

Similarity Among Friends Serves as a Social Prior: The Assumption That "Birds of a Feather Flock Together" Shapes Social Decisions and Relationship Beliefs

Social interactions unfold within networks of relationships. How do beliefs about others' social ties shape-and how are they shaped by-expectations about how others will behave? Here, participants joined a fictive online game-playing community and interacted with its purported members, who varied in terms of their trustworthiness and apparent relationships with one another. Participants were less trusting of partners with untrustworthy friends, even after they consistently showed themselves to be trustworthy, and were less willing to engage with them in the future. To test whether people not only expect friends to behave similarly but also expect those who behave similarly to be friends, an incidental memory test was given. Participants were exceptionally likely to falsely remember similarly behaving partners as friends. Thus, people expect friendship to predict similar behavior and vice versa. These results suggest that knowledge of social networks and others' behavioral tendencies reciprocally interact to shape social thought and behavior.

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.

An fMRI Dataset on Social Reward Processing and Decision Making in Younger and Older Adults

Behavioural and neuroimaging research has shown that older adults are less sensitive to financial losses compared to younger adults. Yet relatively less is known about age-related differences in social decisions and social reward processing. As part of a pilot study, we collected behavioural and functional magnetic resonance imaging (fMRI) data from 50 participants (Younger: N = 26, ages 18-34 years; Older: N = 24, ages 63-80 years) who completed three tasks in the scanner: an economic trust game as the investor with three partners (computer, stranger, friend) as the investee; a card-guessing task with monetary gains and losses shared with three partners (computer, stranger, friend); and an ultimatum game as responder to three anonymous proposers (computer, age-similar adults, age-dissimilar adults). We also collected B0 field maps and high-resolution structural images (T1-weighted and T2-weighted images). These data could be reused to answer questions about moment-to-moment variability in fMRI signal, representational similarity between tasks, and brain structure.

Characterizing the mechanisms of social connection

Understanding how individuals form and maintain strong social networks has emerged as a significant public health priority as a result of the increased focus on the epidemic of loneliness and the myriad protective benefits conferred by social connection. In this review, we highlight the psychological and neural mechanisms that enable us to connect with others, which in turn help buffer against the consequences of stress and isolation. Central to this process is the experience of rewards derived from positive social interactions, which encourage the sharing of perspectives and preferences that unite individuals. Sharing affective states with others helps us to align our understanding of the world with another's, thereby continuing to reinforce bonds and strengthen relationships. These psychological processes depend on neural systems supporting reward and social cognitive function. Lastly, we also consider limitations associated with pursuing healthy social connections and outline potential avenues of future research.

Gradual Loss of Social Group Support during Competition Activates Anterior TPJ and Insula but Deactivates Default Mode Network

Group forming behaviors are common in many species to overcome environmental challenges. In humans, bonding, trust, group norms, and a shared past increase consolidation of social groups. Being a part of a social group increases resilience to mental stress; conversely, its loss increases vulnerability to depression. However, our knowledge on how social group support affects brain functions is limited. This study observed that default mode network (DMN) activity reduced with the loss of social group support from real-life friends in a challenging social competition. The loss of support induced anterior temporoparietal activity followed by anterior insula and the dorsal attentional network activity. Being a part of a social group and having support provides an environment for high cognitive functioning of the DMN, while the loss of group support acts as a threat signal and activates the anterior temporoparietal junction (TPJ) and insula regions of salience and attentional networks for individual survival.

Social Context and Reward Sensitivity Enhance Corticostriatal Function during Experiences of Shared Rewards

Although prior research has demonstrated enhanced striatal response when sharing rewards with close social connections, less is known about how individual differences affect ventral striatal (VS) activation and connectivity when experiencing rewards within social contexts. Given that self-reported reward sensitivity and level of substance use have been associated with differences in VS activation, we set out to investigate whether these factors would be independently associated with enhancements to neural reward responses within social contexts. In this pre-registered study, participants (N=45) underwent fMRI while playing a card guessing game in which correct or incorrect guesses resulted in monetary gains and losses that were shared evenly with either a close friend, stranger (confederate), or non-human partner. Consistent with our prior work, we found increased VS activation when sharing rewards with a socially close peer as opposed to an out-of-network stranger. As self-reported reward sensitivity increased, the difference in VS response to rewards shared with friends and strangers decreased. We also found enhanced connectivity between the VS and temporoparietal junction when sharing rewards with close friends as opposed to strangers. Finally, exploratory analyses revealed that as reward sensitivity and sub-clinical substance use increase, the difference in VS connectivity with the right fusiform face area increases as a function of social context. These findings demonstrate that responsivity to the context of close friends may be tied to individual reward sensitivity or sub-clinical substance use habits; together these factors may inform predictions of risk for future mental health disorders.

Impaired social learning in patients with major depressive disorder revealed by a reinforcement learning model

Background/objective

Patients with major depressive disorder (MDD) have altered learning rates for rewards and losses in non-social learning paradigms. However, it is not well understood whether the ability to learn from social interactions is altered in MDD patients. Using reinforcement learning during the repeated Trust Game (rTG), we investigated how MDD patients learn to trust newly-met partners in MDD patients.

Method

Sixty-eight MDD patients and fifty-four controls each played as 'investor' and interacted with ten different partners. We manipulated both the level of trustworthiness by varying the chance of reciprocity (10, 30, 50, 70 and 90%) and reputation disclosure, where partners' reputation was either pre-disclosed or hidden.

Results

Our reinforcement learning model revealed that MDD patients had significantly higher learning rates for losses than the controls in both the reputation disclosure and non-disclosure condition. The difference was larger when reputation was not disclosed than disclosed. We observed no difference in learning rates for gains in either condition.

Conclusions

Our findings highlight that abnormal learning for losses underlies the social learning process in MDD patients. This abnormality is higher when situational unpredictability is high versus low. Our findings provide novel insights into social rehabilitation of MDD.

Understanding guilt-related interpersonal dysfunction in obsessive-compulsive personality disorder through computational modeling of two social interaction tasks

BACKGROUND

Obsessive-compulsive personality disorder (OCPD) is a high-prevalence personality disorder characterized by subtle but stable interpersonal dysfunction. There have been only limited studies addressing the behavioral patterns and cognitive features of OCPD in interpersonal contexts. The purpose of this study was to investigate how behaviors differ between OCPD individuals and healthy controls (HCs) in the context of guilt-related interpersonal responses.

METHOD

A total of 113 participants were recruited, including 46 who were identified as having OCPD and 67 HCs. Guilt-related interpersonal responses were manipulated and measured with two social interactive tasks: the Guilt Aversion Task, to assess how anticipatory guilt motivates cooperation; and the Guilt Compensation Task, to assess how experienced guilt induces compensation behaviors. The guilt aversion model and Fehr-Schmidt inequity aversion model were adopted to analyze decision-making in the Guilt Aversion Task and the Guilt Compensation Task, respectively.

RESULTS

Computational model-based results demonstrated that, compared with HCs, the OCPD group exhibited less guilt aversion when making cooperative decisions as well as less guilt-induced compensation after harming others.

CONCLUSION

Our findings indicate that individuals with OCPD tend to be less affected by guilt than HCs. These impairments in guilt-related responses may prevent adjustments in behaviors toward compliance with social norms and thus result in interpersonal dysfunctions.

Social feedback promotes positive social sharing, trust, and closeness

Positive social sharing is an interpersonal emotion regulation strategy that enhances positive affect and social belonging, particularly when met with positive social feedback. Despite the ubiquity of positive social sharing both in person and online, what drives this behavior is not well understood. We hypothesized that positive social feedback serves as a reward that reinforces sharing behavior and strengthens social bonds. Participants made trial-by-trial choices about whether to share social media photos with peers who returned positive ("likes") or negative ("dislikes") feedback. Unbeknownst to participants, peer conditions were manipulated to yield varying amounts of positive and negative feedback. Social bonding was subsequently measured using a trust game and subjective closeness ratings. Participants shared more with peers who provided greater rates of positive feedback. This effect generalized to trust decisions and subjective feelings of closeness and varied individually as a function of interpersonal emotion regulation in daily life. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Social overshadowing: Revisiting cue-competition in social interactions

In a large variety of contexts, it is essential to use the available information to extract patterns and behave accordingly. When it comes to social interactions for instance, the information gathered about interaction partners across multiple encounters (e.g., trustworthiness) is crucial in guiding one's own behavior (e.g., approach the trustworthy and avoid the untrustworthy), a process akin to trial-by-trial learning. Building on associative learning and social cognition literatures, the present research adopts a domain-general approach to learning and explores whether the principles underlying associative learning also govern learning in social contexts. In particular, we examined whether overshadowing, a well-established cue-competition phenomenon, impacts learning of the cooperative behaviors of unfamiliar interaction partners. Across three experiments using an adaptation of the iterated Trust Game, we consistently observed a 'social overshadowing' effect, that is, a better learning about the cooperative tendencies of partners presented alone compared to those presented in a pair. This robust effect was not modulated by gender stereotypes or beliefs about the internal communication dynamics within a pair of partners. Drawing on these results, we argue that examining domain-general learning processes in social contexts is a useful approach to understanding human social cognition.

A neuro-computational social learning framework to facilitate transdiagnostic classification and treatment across psychiatric disorders

Social deficits are among the core and most striking psychiatric symptoms, present in most psychiatric disorders. Here, we introduce a novel social learning framework, which consists of neuro-computational models that combine reinforcement learning with various types of social knowledge structures. We outline how this social learning framework can help specify and quantify social psychopathology across disorders and provide an overview of the brain regions that may be involved in this type of social learning. We highlight how this framework can specify commonalities and differences in the social psychopathology of individuals with autism spectrum disorder (ASD), personality disorders (PD), and major depressive disorder (MDD) and improve treatments on an individual basis. We conjecture that individuals with psychiatric disorders rely on rigid social knowledge representations when learning about others, albeit the nature of their rigidity and the behavioral consequences can greatly differ. While non-clinical cohorts tend to efficiently adapt social knowledge representations to relevant environmental constraints, psychiatric cohorts may rigidly stick to their preconceived notions or overly coarse knowledge representations during learning.

Value-based neural representations predict social decision preferences

Social decision-making is omnipresent in everyday life, carrying the potential for both positive and negative consequences for the decision-maker and those closest to them. While evidence suggests that decision-makers use value-based heuristics to guide choice behavior, very little is known about how decision-makers' representations of other agents influence social choice behavior. We used multivariate pattern expression analyses on fMRI data to understand how value-based processes shape neural representations of those affected by one's social decisions and whether value-based encoding is associated with social decision preferences. We found that stronger value-based encoding of a given close other (e.g. parent) relative to a second close other (e.g. friend) was associated with a greater propensity to favor the former during subsequent social decision-making. These results are the first to our knowledge to explicitly show that value-based processes affect decision behavior via representations of close others.

The bright and dark sides of egoism

Despite its negative reputation, egoism - the excessive concern for one's own welfare - can incite prosocial behavior. So far, however, egoism-based prosociality has received little attention. Here, we first provide an overview of the conditions under which egoism turns into a prosocial motive, review the benefits and limitations of egoism-based prosociality, and compare them with empathy-driven prosocial behavior. Second, we summarize studies investigating the neural processing of egoism-based prosocial decisions, studies investigating the neural processing of empathy-based prosocial decisions, and the small number of studies that compared the neural processing of prosocial decisions elicited by the different motives. We conclude that there is evidence for differential neural networks involved in egoism and empathy-based prosocial decisions. However, this evidence is not yet conclusive, because it is mainly based on the comparison of different experimental paradigms which may exaggerate or overshadow the effect of the different motivational states. Finally, we propose paradigms and research questions that should be tackled in future research that could help to specify how egoism can be used to enhance other prosocial behavior and motivation, and the how it could be tamed.

Incorporating social knowledge structures into computational models

To navigate social interactions successfully, humans need to continuously learn about the personality traits of other people (e.g., how helpful or aggressive is the other person?). However, formal models that capture the complexities of social learning processes are currently lacking. In this study, we specify and test potential strategies that humans can employ for learning about others. Standard Rescorla-Wagner (RW) learning models only capture parts of the learning process because they neglect inherent knowledge structures and omit previously acquired knowledge. We therefore formalize two social knowledge structures and implement them in hybrid RW models to test their usefulness across multiple social learning tasks. We name these concepts granularity (knowledge structures about personality traits that can be utilized at different levels of detail during learning) and reference points (previous knowledge formalized into representations of average people within a social group). In five behavioural experiments, results from model comparisons and statistical analyses indicate that participants efficiently combine the concepts of granularity and reference points-with the specific combinations in models depending on the people and traits that participants learned about. Overall, our experiments demonstrate that variants of RW algorithms, which incorporate social knowledge structures, describe crucial aspects of the dynamics at play when people interact with each other.

Social closeness modulates brain dynamics during trust anticipation

Anticipation of trust from someone with high social closeness is expected. However, if there is uncertainty in the interaction because a person is a stranger or because he has distrusted us on another occasion, we need to keep track of his behavior and intentions. Using functional Magnetic Resonance Imaging (fMRI) we wanted to find the brain regions related to trust anticipation from partners who differ in their level of social closeness. We designed an experiment in which 30 participants played an adapted trust game with three trustors: A computer, a stranger, and a real friend. We covertly manipulated their decisions in the game, so they trusted 75% of the trials and distrusted in remaining trials. Using a psychophysiological interaction analysis, we found increases in functional coupling between the anterior insula (AIns) and intra parietal sulcus (IPS) during trust anticipation between a high versus low social closeness partner. Also, the right parietal cortex was coupled with the fusiform gyrus (FG) and the inferior/middle temporal gyrus during trust anticipation of a friend versus a stranger. These results suggest that brain regions involved in encoding the intentions of others are recruited during trust anticipation from a friend compared to a stranger.

Learning whom to cooperate with: neurocomputational mechanisms for choosing cooperative partners

Cooperation is fundamental for survival and a functioning society. With substantial individual variability in cooperativeness, we must learn whom to cooperate with, and often make these decisions on behalf of others. Understanding how people learn about the cooperativeness of others, and the neurocomputational mechanisms supporting this learning, is therefore essential. During functional magnetic resonance imaging scanning, participants completed a novel cooperation-partner-choice task where they learned to choose between cooperative and uncooperative partners through trial-and-error both for themselves and vicariously for another person. Interestingly, when choosing for themselves, participants made faster and more exploitative choices than when choosing for another person. Activity in the ventral striatum preferentially responded to prediction errors (PEs) during self-learning, whereas activity in the perigenual anterior cingulate cortex (ACC) signaled both personal and vicarious PEs. Multivariate pattern analyses showed distinct coding of personal and vicarious choice-making and outcome processing in the temporoparietal junction (TPJ), dorsal ACC, and striatum. Moreover, in right TPJ the activity pattern that differentiated self and other outcomes was associated with individual differences in exploitation tendency. We reveal neurocomputational mechanisms supporting cooperative learning and show that this learning is reflected in trial-by-trial univariate signals and multivariate patterns that can distinguish personal and vicarious choices.

Choosing for others changes dissociable computational mechanisms underpinning risky decision-making

Choices under risk often have consequences for ourselves and others. Yet, it is unclear how the other's identity (stranger, close friend, etc.) influences risky choices made on their behalf. In a mixed within and between subjects design, two participant groups made three series of risky economic decisions: for themselves, another person, or for both themselves and another person (i.e., shared outcomes). One group made choices involving a same-sex stranger (n = 29), the other made choices involving a same-sex close friend (n = 28). Hierarchical Bayesian estimation of computations underlying risky decision-making revealed that relative to choosing for themselves, people were more risk averse, loss averse, and consistent when choices involved another person. Partner identity was additionally crucial: people became risk neutral and more consistent when choosing for friends relative to strangers. These findings establish that the complexity of the social world is mirrored in its nuanced consequences for our choices.

Superior bias in trust-related decisions

Trust is conditional. Many studies have revealed its relative conditions in different situations, but when social status is characteristic of the person who receives trust (the “trustee”), our knowledge of how social status affects trust still remains limited. In this study, we used the trust game in order to: (1) characterize the effect of trustees’ social hierarchy on trust-related decisions in different trustworthiness situations and (2) explore the underlying computational process regarding the impact that social status has on trust-related decisions by using the computational modeling approach to integrate social status into trust-related situations. In Experiment 1, using a one-shot trust game with no feedback of information about reciprocity, we found that compared with inferiors, superiors gained more trust-related behaviors (investments) in spite of the fact that they were not rated as having higher trustworthiness. Then, in Experiment 2, when we controlled the trustworthiness of different social status partners by providing the same neutral reciprocity rate (50%) in a repeated trust game, the high-status partner gained more trust than the low-status partner. This superior bias extended to Experiment 3a and 3b, in which we set different levels of trustworthiness to match the different social statuses of partners. With respect to modeling results, we found that higher status holds an additional social value independent of trust profit, resulting in superior bias. Ultimately, this study has shed light on the superior bias that commonly leads people to grant high-status individuals goodwill in social interactions.

A Neurodevelopmental Shift in Reward Circuitry from Mother's to Nonfamilial Voices in Adolescence

The social worlds of young children primarily revolve around parents and caregivers, who play a key role in guiding children's social and cognitive development. However, a hallmark of adolescence is a shift in orientation toward nonfamilial social targets, an adaptive process that prepares adolescents for their independence. Little is known regarding neurobiological signatures underlying changes in adolescents' social orientation. Using functional brain imaging of human voice processing in children and adolescents (ages 7-16), we demonstrate distinct neural signatures for mother's voice and nonfamilial voices across child and adolescent development in reward and social valuation systems, instantiated in nucleus accumbens and ventromedial prefrontal cortex. While younger children showed greater activity in these brain systems for mother's voice compared with nonfamilial voices, older adolescents showed the opposite effect with increased activity for nonfamilial compared with mother's voice. Findings uncover a critical role for reward and social valuative brain systems in the pronounced changes in adolescents' orientation toward nonfamilial social targets. Our approach provides a template for examining developmental shifts in social reward and motivation in individuals with pronounced social impairments, including adolescents with autism.SIGNIFICANCE STATEMENT Children's social worlds undergo a transformation during adolescence. While socialization in young children revolves around parents and caregivers, adolescence is characterized by a shift in social orientation toward nonfamilial social partners. Here we show that this shift is reflected in neural activity measured from reward processing regions in response to brief vocal samples. When younger children hear their mother's voice, reward processing regions show greater activity compared with when they hear nonfamilial, unfamiliar voices. Strikingly, older adolescents show the opposite effect, with increased activity for nonfamilial compared with mother's voice. Findings identify the brain basis of adolescents' switch in social orientation toward nonfamilial social partners and provides a template for understanding neurodevelopment in clinical populations with social and communication difficulties.

Decision neuroscience and neuroeconomics: Recent progress and ongoing challenges

In the past decade, decision neuroscience and neuroeconomics have developed many new insights in the study of decision making. This review provides an overarching update on how the field has advanced in this time period. Although our initial review a decade ago outlined several theoretical, conceptual, methodological, empirical, and practical challenges, there has only been limited progress in resolving these challenges. We summarize significant trends in decision neuroscience through the lens of the challenges outlined for the field and review examples where the field has had significant, direct, and applicable impacts across economics and psychology. First, we review progress on topics including reward learning, explore-exploit decisions, risk and ambiguity, intertemporal choice, and valuation. Next, we assess the impacts of emotion, social rewards, and social context on decision making. Then, we follow up with how individual differences impact choices and new exciting developments in the prediction and neuroforecasting of future decisions. Finally, we consider how trends in decision-neuroscience research reflect progress toward resolving past challenges, discuss new and exciting applications of recent research, and identify new challenges for the field. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Emotion and Motivation.

Age-Related Differences in Ventral Striatal and Default Mode Network Function During Reciprocated Trust

Social relationships change across the lifespan as social networks narrow and motivational priorities shift to the present. Interestingly, aging is also associated with changes in executive function, including decision-making abilities, but it remains unclear how age-related changes in both domains interact to impact financial decisions involving other people. To study this problem, we recruited 50 human participants (N_younger = 26, ages 18–34; N_older = 24, ages 63–80) to play an economic trust game as the investor with three partners (friend, stranger, and computer) who played the role of investee. Investors underwent functional magnetic resonance imaging (fMRI) during the trust game while investees were seated outside of the scanner. Building on our previous work with younger adults showing both enhanced striatal responses and altered default-mode network (DMN) connectivity as a function of social closeness during reciprocated trust, we predicted that these relations would exhibit age-related differences. We found that striatal responses to reciprocated trust from friends relative to strangers and computers were blunted in older adults relative to younger adults, thus supporting our primary pre-registered hypothesis regarding social closeness. We also found that older adults exhibited enhanced DMN connectivity with the temporoparietal junction (TPJ) during reciprocated trust from friends compared to computers while younger adults exhibited the opposite pattern. Taken together, these results advance our understanding of age-related differences in sensitivity to social closeness in the context of trusting others.

Computational and Motivational Mechanisms of Human Social Decision Making Involving Close Others

Every day, human beings make decisions with social consequences. These social consequences matter most when they impact those closest to us. Recent research has shown that humans exhibit reliable preferences when deciding between conflicting outcomes involving close others - for example, prioritizing the interests of one's family member over one's friend. However, virtually nothing is known about the mechanisms that drive these preferences. We conducted a pre-registered study in a large (maximum N=375) sample to quantify the computational and motivational mechanisms of human social decision-making preferences involving close others. By pairing assessment techniques from behavioral economics and psychological science with computational modeling and random coefficient regression, we show that value-based cognitive computations (e.g., risk and loss aversion) drive social decision-making preferences involving financial outcomes, whereas socioemotional motivations (e.g., relationship quality) underlie preferences involving social outcomes. These results imply mechanistic heterogeneity, underscoring a need for greater attention to contextual specificity in social decision-making.

Understanding identification-based trust in the light of affiliative bonding: Meta-analytic neuroimaging evidence

Trust is vital for establishing social relationships and is a crucial precursor for affiliative bonds. Investigations explored the neuropsychological bases of trust separately (e.g., measured by the trust game) and affiliative bonding (e.g., measured by parental care, pair-bonding, or friendship). However, direct empirical support for the shared neural mechanisms between trust and affiliative bonding is missing. Here, we conducted a coordinate-based meta-analysis on functional magnetic resonance imaging studies on interpersonal trust and affiliative bonding using the activation likelihood estimation method. Our results demonstrated that decisions to trust strangers in repeated interactions (i.e., identification-based trust) engaged the ventral striatum (vSTR, part of the mesolimbic dopaminergic pathway), likely signaling the reward anticipation. Further, both feedbacks in repeated interactions and affiliative bonding engaged the dorsal striatum (dSTR, part of the nigrostriatal dopaminergic pathway), likely encoding learning dynamics. Our findings suggest that identification-based trust can be understood in the light of affiliative bonding, involving the mesocorticolimbic "reward" pathway (vSTR) and nigrostriatal "habit formation" pathway (dSTR) in building and sustaining social relationships.

How Adolescents and Adults Learn About Changes in the Trustworthiness of Others Through Dynamic Interaction

Whether to trust or distrust another individual is a complex interpersonal challenge, especially when such individuals behave inconsistently. It is still unclear as to how individuals learn and adapt to fluctuations in the trustworthiness of others and how this process changes from adolescence to adulthood. To address these issues, we implemented repeated rounds of a trust game within the context of a complicated and changeable interpersonal environment. Specifically, adolescents and adults played the role of trustors who had to decide whether to invest money in two anonymous partners carrying the risk of no reciprocation. Unbeknownst to participants, these two partners had different trustworthiness profiles: one partner initially yielded a higher initial return rate (70%) while the other initially yielded a lower initial return rate (30%). Crucially, over repeated rounds, these two partners gradually changed their responses to the point where, finally, return rates were both neutral (50%). Results indicated that all participants showed less updating in the negative direction in response to good-to-neutral partners while more updating in the positive direction in response to the bad-to-neutral partner. Compared to adults, this behavioral disparity in responses to good-to-neutral and bad-to-neutral partners was less pronounced in adolescents. Based on the computational modeling approach, the potential mechanisms underlying their behavioral patterns were revealed: the higher learning rate promoted flexible adaptions in participants to untrustworthy trustees as they changed to neutral. The less pronounced distinction between good-to-neutral and bad-to-neutral partners in adolescents was related to their lower learning rate. Overall, our study extends the understanding of trust behavior to a fluctuating social context and highlights the role of social learning in social emotion and interaction.

Neurocomputational models of altruistic decision-making and social motives: Advances, pitfalls, and future directions

This article discusses insights from computational models and social neuroscience into motivations, precursors, and mechanisms of altruistic decision-making and other-regard. We introduce theoretical and methodological tools for researchers who wish to adopt a multilevel, computational approach to study behaviors that promote others' welfare. Using examples from recent studies, we outline multiple mental and neural processes relevant to altruism. To this end, we integrate evidence from neuroimaging, psychology, economics, and formalized mathematical models. We introduce basic mechanisms-pertinent to a broad range of value-based decisions-and social emotions and cognitions commonly recruited when our decisions involve other people. Regarding the latter, we discuss how decomposing distinct facets of social processes can advance altruistic models and the development of novel, targeted interventions. We propose that an accelerated synthesis of computational approaches and social neuroscience represents a critical step towards a more comprehensive understanding of altruistic decision-making. We discuss the utility of this approach to study lifespan differences in social preference in late adulthood, a crucial future direction in aging global populations. Finally, we review potential pitfalls and recommendations for researchers interested in applying a computational approach to their research. This article is categorized under: Economics > Interactive Decision-Making Psychology > Emotion and Motivation Neuroscience > Cognition Economics > Individual Decision-Making.

A Feature-Based Network Analysis and fMRI Meta-Analysis Reveal Three Distinct Types of Prosocial Decisions

Tasks that measure correlates of prosocial decision-making share one common feature: agents can make choices that increase the welfare of a beneficiary. However, prosocial decisions vary widely as a function of other task features. The diverse ways that prosociality is defined and the heterogeneity of prosocial decisions have created challenges for interpreting findings across studies and identifying their neural correlates. To overcome these challenges, we aimed to organize the prosocial decision-making task space of neuroimaging studies. We conducted a systematic search for studies in which participants made decisions to increase the welfare of others during functional magnetic resonance imaging. We identified shared and distinct features of these tasks and employed an unsupervised graph-based approach to assess how various forms of prosocial decision-making are related in terms of their low-level components (e.g. task features like potential cost to the agent or potential for reciprocity). Analyses uncovered three clusters of prosocial decisions, which we labeled as cooperation, equity and altruism. This feature-based representation of the task structure was supported by results of a neuroimaging meta-analysis that each type of prosocial decisions recruited diverging neural systems. Results clarify some of the existing heterogeneity in how prosociality is conceptualized and generate insight for future research and task paradigm development.

Suicidality and self-injurious behavior among adolescent social media users at psychiatric hospitalization

BACKGROUND

The current study sought to examine the relationship between documented social media use and suicidality and self-injurious behaviors in adolescents at the time of psychiatric hospitalization.

METHODS

We retrospectively identified adolescents (aged 12-17 years) hospitalized on an inpatient psychiatric unit during 1 year. Abstracted information included documented social media use, demographic variables, documented self-injurious behaviors, the Patient Health Questionnaire-9, and the Suicide Status Form-II. Logistic regression was implemented to examine the effect of social media use on the risk of self-injurious behaviors and suicidality.

RESULTS

Fifty-six adolescents who used social media were identified and matched with 56 non-social media users. Those with reported social media use had significantly greater odds of self-injurious behaviors at admission (odds ratio, 2.55; 95% confidence intervals, 1.17-5.71; P = .02) vs youth without reported social media use. Adolescents with reported social media use also had greater odds of increased suicidal ideation and suicide risk than those with no reported use, but these relationships were not statistically significant.

CONCLUSIONS

Social media use in adolescents with a psychiatric admission may be associated with the risk of self-injurious behaviors and could be a marker of impulsivity. Further work should guide the assessment of social media use as part of a routine adolescent psychiatric history.

Shifting prosocial intuitions: neurocognitive evidence for a value-based account of group-based cooperation

Cooperation is necessary for solving numerous social issues, including climate change, effective governance and economic stability. Value-based decision models contend that prosocial tendencies and social context shape people’s preferences for cooperative or selfish behavior. Using functional neuroimaging and computational modeling, we tested these predictions by comparing activity in brain regions previously linked to valuation and executive function during decision-making—the ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC), respectively. Participants played Public Goods Games with students from fictitious universities, where social norms were selfish or cooperative. Prosocial participants showed greater vmPFC activity when cooperating and dlPFC-vmPFC connectivity when acting selfishly, whereas selfish participants displayed the opposite pattern. Norm-sensitive participants showed greater dlPFC-vmPFC connectivity when defying group norms. Modeling expectations of cooperation was associated with activity near the right temporoparietal junction. Consistent with value-based models, this suggests that prosocial tendencies and contextual norms flexibly determine whether people prefer cooperation or defection.

Developmental asymmetries in learning to adjust to cooperative and uncooperative environments

Learning to successfully navigate social environments is a critical developmental goal, predictive of long-term wellbeing. However, little is known about how people learn to adjust to different social environments, and how this behaviour emerges across development. Here, we use a series of economic games to assess how children, adolescents, and young adults learn to adjust to social environments that differ in their level of cooperation (i.e., trust and coordination). Our results show an asymmetric developmental pattern: adjustment requiring uncooperative behaviour remains constant across adolescence, but adjustment requiring cooperative behaviour improves markedly across adolescence. Behavioural and computational analyses reveal that age-related differences in this social learning are shaped by age-related differences in the degree of inequality aversion and in the updating of beliefs about others. Our findings point to early adolescence as a phase of rapid change in cooperative behaviours, and highlight this as a key developmental window for interventions promoting well-adjusted social behaviour.

The Role of Social Reward and Corticostriatal Connectivity in Substance Use

This report describes an ongoing R03 grant that explores the links between trait reward sensitivity, substance use, and neural responses to social and nonsocial reward. Although previous research has shown that trait reward sensitivity and neural responses to reward are linked to substance use, whether this relationship is impacted by how people process social stimuli remains unclear. We are investigating these questions via a neuroimaging study with college-aged participants, using individual difference measures that examine the relation between substance use, social context, and trait reward sensitivity with tasks that measure reward anticipation, strategic behavior, social reward consumption, and the influence of social context on reward processing. We predict that substance use will be tied to distinct patterns of striatal dysfunction. Specifically, reward hyposensitive individuals will exhibit blunted striatal responses to social and non-social reward and enhanced connectivity with the orbitofrontal cortex; in contrast, reward hypersensitive individuals will exhibit enhanced striatal responses to social and non-social reward and blunted connectivity with the orbitofrontal cortex. We also will examine the relation between self-reported reward sensitivity, substance use, and striatal responses to social reward and social context. We predict that individuals reporting the highest levels of substance use will show exaggerated striatal responses to social reward and social context, independent of self-reported reward sensitivity. Examining corticostriatal responses to reward processing will help characterize the relation between reward sensitivity, social context and substance use while providing a foundation for understanding risk factors and isolating neurocognitive mechanisms that may be targeted to increase the efficacy of interventions.

God Spots in the Brain: Nine Categories of Unasked, Unanswered Questions

Neurotheology is an emerging academic discipline that examines mind-brain relationships in terms of the inter-relatedness of neuroscience, spirituality, and religion. Neurotheology originated from brain-scan studies that revealed specific correlations between certain religious thoughts and localized activated brain areas known as “God Spots.” This relatively young scholarly discipline lacks clear consensus on its definition, ideology, purpose, or prospects for future research. Of special interest is the consideration of the next steps using brain scans to develop this field of research. This review proposes nine categories of future research that could build on the foundation laid by the prior discoveries of God Spots. Specifically, this analysis identifies some sparsely addressed issues that could be usefully explored with new kinds of brain-scan studies: neural network operations, the cognitive neuroscience of prayer, biology of belief, measures of religiosity, role of the self, learning and memory, religious and secular cognitive commonalities, static and functional anatomy, and recruitment of neural processing circuitry. God Spot research is poised to move beyond observation to robust hypothesis generation and testing.

Neurocomputational mechanisms of adaptive learning in social exchanges

Prior work on prosocial and self-serving behavior in human economic exchanges has shown that counterparts' high social reputations bias striatal reward signals and elicit cooperation, even when such cooperation is disadvantageous. This phenomenon suggests that the human striatum is modulated by the other's social value, which is insensitive to the individual's own choices to cooperate or defect. We tested an alternative hypothesis that, when people learn from their interactions with others, they encode prediction error updates with respect to their own policy. Under this policy update account striatal signals would reflect positive prediction errors when the individual's choices correctly anticipated not only the counterpart's cooperation but also defection. We examined behavior in three samples using reinforcement learning and model-free analyses and performed an fMRI study of striatal learning signals. In order to uncover the dynamics of goal-directed learning, we introduced reversals in the counterpart's behavior and provided counterfactual (would-be) feedback when the individual chose not to engage with the counterpart. Behavioral data and model-derived prediction error maps (in both whole-brain and a priori striatal region of interest analyses) supported the policy update model. Thus, as people continually adjust their rate of cooperation based on experience, their behavior and striatal learning signals reveal a self-centered instrumental process corresponding to reciprocal altruism.

A stronger relationship between reward responsivity and trustworthiness evaluations emerges in healthy aging

Older adults (OA) evaluate faces to be more trustworthy than do younger adults (YA), yet the processes supporting these more positive evaluations are unclear. This study identified neural mechanisms spontaneously engaged during face perception that differentially relate to OA' and YA' later trustworthiness evaluations. We examined two mechanisms: salience (reflected by amygdala activation) and reward (reflected by caudate activation) - both of which are implicated in evaluating trustworthiness. We emphasized the salience and reward value of specific faces by having OA and YA evaluate ingroup male White and outgroup Black and Asian faces. Participants perceived faces during fMRI and made trustworthiness evaluations after the scan. OA rated White and Black faces as more trustworthy than YA. OA had a stronger positive relationship between caudate activity and trustworthiness than YA when perceiving ingroup, but not outgroup, faces. Ingroup cues might intensify how trustworthiness is rewarding to OA, potentially reinforcing their overall positivity.

Neural arbitration between social and individual learning systems

Decision making requires integrating knowledge gathered from personal experiences with advice from others. The neural underpinnings of the process of arbitrating between information sources has not been fully elucidated. In this study, we formalized arbitration as the relative precision of predictions, afforded by each learning system, using hierarchical Bayesian modeling. In a probabilistic learning task, participants predicted the outcome of a lottery using recommendations from a more informed advisor and/or self-sampled outcomes. Decision confidence, as measured by the number of points participants wagered on their predictions, varied with our definition of arbitration as a ratio of precisions. Functional neuroimaging demonstrated that arbitration signals were independent of decision confidence and involved modality-specific brain regions. Arbitrating in favor of self-gathered information activated the dorsolateral prefrontal cortex and the midbrain, whereas arbitrating in favor of social information engaged the ventromedial prefrontal cortex and the amygdala. These findings indicate that relative precision captures arbitration between social and individual learning systems at both behavioral and neural levels.

The role of right temporoparietal junction in processing social prediction error across relationship contexts

How do people update their impressions of close others? Although people may be motivated to maintain their positive impressions, they may also update their impressions when their expectations are violated (i.e. prediction error). Combining neuroimaging and computational modeling, we test the hypothesis that brain regions associated with theory of mind, especially right temporoparietal junction (rTPJ), underpin both motivated impression maintenance and impression updating evoked by prediction error. Participants had money either given to or taken away from them by a friend or a stranger and were then asked to rate each partner on trustworthiness and closeness across trials. Overall, participants engaged in less impression updating for friends vs strangers. Decreased rTPJ activity in response to a friend’s negative behavior (taking money) was associated with reduced negative updating and increased positive ratings of the friend. However, to the extent that participants did update their impressions (more negative ratings) of friends, this behavioral pattern was explained by greater prediction error and greater rTPJ activity. These findings suggest that rTPJ recruitment represents the integration of prediction error signals and the capacity to overcome people’s motivation to maintain positive impressions of friends in the face of conflicting evidence.

The influence of relationship closeness on default-mode network connectivity during social interactions

Reciprocated trust plays a critical role in forming and maintaining relationships, and has consistently been shown to implicate neural circuits involved in reward-related processing and social cognition. Less is known about neural network connectivity during social interactions involving trust, however, particularly as a function of closeness between an investor and a trustee. We examined network reactivity and connectivity in participants who played an economic trust game with close friends, strangers and a computer. Network reactivity analyses showed enhanced activation of the default-mode network (DMN) to social relative to non-social outcomes. A novel network psychophysiological interaction (nPPI) analysis revealed enhanced connectivity between the DMN and the superior frontal gyrus and superior parietal lobule when experiencing reciprocated vs violated trust from friends relative to strangers. Such connectivity tracked with differences in self-reported social closeness with these partners. Interestingly, reactivity of the executive control network (ECN), involved in decision processes, demonstrated no social vs non-social preference, and ECN-ventral striatum connectivity did not track social closeness. Taken together, these novel findings suggest that DMN interacts with components of attention and control networks to signal the relative importance of positive experiences with close others vs strangers.

Grant Report on Social Reward Learning in Schizophrenia †

We report on the ongoing R21 project “Social Reward Learning in Schizophrenia”. Impairments in social cognition are a hallmark of schizophrenia. However, little work has been done on social reward learning deficits in schizophrenia. The overall goal of the project is to assess social reward learning in schizophrenia. A probabilistic reward learning (PRL) task is being used in the MRI scanner to evaluate reward learning to negative and positive social feedback. Monetary reward learning is used as a comparison to assess specificity. Behavioral outcomes and brain areas, included those involved in reward, are assessed in patients with schizophrenia or schizoaffective disorder and controls. It is also critical to determine whether decreased expected value (EV) of social stimuli and/or reward prediction error (RPE) learning underlie social reward learning deficits to inform potential treatment pathways. Our central hypothesis is that the pattern of social learning deficits is an extension of a more general reward learning impairment in schizophrenia and that social reward learning deficits critically contribute to deficits in social motivation and pleasure. We hypothesize that people with schizophrenia will show impaired behavioral social reward learning compared to controls, as well as decreased ventromedial prefrontal cortex (vmPFC) EV signaling at time of choice and decreased striatal RPE signaling at time of outcome, with potentially greater impairment to positive than negative feedback. The grant is in its second year. It is hoped that this innovative approach may lead to novel and more targeted treatment approaches for social cognitive impairments, using cognitive remediation and/or brain stimulation.

Breaking human social decision making into multiple components and then putting them together again

Most of our waking time as human beings is spent interacting with other individuals. In order to make good decisions in this social milieu, it is often necessary to make inferences about the internal states, traits and intentions of others. Recently, some progress has been made toward uncovering the neural computations underlying human social decision-making by combining functional magnetic resonance neuroimaging (fMRI) with computational modeling of behavior. Modeling of behavioral data allows us to identify the key computations necessary for social decision-making and to determine how these computations are integrated. Furthermore, by correlating these variables against neuroimaging data, it has become possible to elucidate where in the brain various computations are implemented. Here we review the current state of knowledge in the domain of social computational neuroscience. Findings to date have emphasized that social decisions are driven by multiple computations conducted in parallel, and implemented in distinct brain regions. We suggest that further progress is going to depend on identifying how and where such variables get integrated in order to yield a coherent behavioral output.

The Psychology of Motivated versus Rational Impression Updating

People's beliefs about others are often impervious to new evidence: we continue to cooperate with ingroup defectors and refuse to see outgroup enemies as rehabilitated. Resistance to updating beliefs with new information has historically been interpreted as reflecting bias or motivated cognition, but recent work in Bayesian inference suggests that belief maintenance can be compatible with procedural rationality. We propose a mentalizing account of belief maintenance, which holds that protecting strong priors by generating alternative explanations for surprising information involves more mentalizing about the target than nonrational discounting. We review the neuroscientific evidence supporting this approach, and discuss how both types of processing can lead to fitness benefits.

An association between biased impression updating and relationship facilitation: A behavioral and fMRI investigation

Is ingroup bias associated with any benefit for maintaining close relationships? We examined the link between biased impression updating for ingroup members (i.e., friends) and relationship maintenance, as measured by the number of friends participants reported having (Studies 1 and 2). We also investigated the underlying neural basis of this possible effect, focusing on activity in the right temporo-parietal junction (RTPJ), a region of the social brain involved in moral updating (Study 2). Specifically, we tested whether selectively discounting negative information about close others, manifested in reduced impression updating, and indexed by reduced RTPJ activity, is related to maintaining close relationships. In Study 1, after imagining a friend and a stranger performing different positive and negative behaviors, participants who were reluctant to update how close they felt to their friend (friend-closeness) reported having more friends in real life. In Study 2, participants were led to believe that a friend and a stranger gave money to them or took money away from them, while they were in the scanner. Participants who engaged in less negative updating of friends versus strangers reported having more friends. Participants who engaged in less friend-closeness updating also showed reduced RTPJ activity when their friend took money from them, and this neural pattern was associated with reports of having more friends. Together, these findings suggest that selectively discounting close others' negative behavior is linked to maintaining close relationships, indicating a potential social benefit of ingroup bias.

Neurocognitive Adaptation and Mental Health Vulnerability Following Maltreatment: The Role of Social Functioning

Childhood maltreatment is associated with a lifetime increase in risk of mental health disorder. We propose that such vulnerability may stem in large part from altered patterns of social functioning. Here, we highlight key findings from the psychological and epidemiological literature indicating that early maltreatment experience compromises social functioning and attenuates social support in ways that increase mental health vulnerability. We then review the extant neuroimaging studies of children and adolescents, focusing on three domains implicated in social functioning: threat processing, reward processing, and emotion regulation. We discuss how adaptations in these domains may increase latent vulnerability to mental health problems by impacting on social functioning via increased stress susceptibility as well as increased stress generation. Finally, we explore how computational psychiatry approaches, alongside systematically reported measures of social functioning, can complement studies of neural function in the creation of a mechanistic framework aimed at informing approaches to prevention and intervention.

Delineating the social valuation network in adolescents

Adolescents strive for peer approval, and an increased sensitivity to peers' opinions is normative. However, among vulnerable adolescents, peer evaluation can be detrimental, contributing to affective disorders. It is, therefore, critical to improve our understanding of neural underpinnings of peer evaluation. Prior research has investigated averaged neural responses to peer acceptance or rejection, neglecting to probe trial-by-trial computations that mirror real-time updating of daily activities. In non-social decision-making, a common neural valuation system centered on the medial prefrontal cortex (mPFC) has emerged, which evaluates different reward types on a common scale to guide choices. However, it is unclear whether the mPFC also tracks complex social scenarios involving peer feedback. To address this gap, we acquired fMRI data from 55 healthy adolescents during the Chatroom Task, which probes peer evaluation, and implemented a computational approach to characterize trial-by-trial social value, thereby allowing us to interrogate the neural correlates of social value. Consistent with our hypothesis, social value signals were encoded in the mPFC. Interestingly, analyses also revealed a wider social-specific valuation network including the precuneus and amygdala. Understanding how adolescents make social decisions and neural markers associated with it, may, ultimately, help us clarify promising targets for intervention.

Neural signatures of cooperation enforcement and violation: a coordinate-based meta-analysis

The social norms of fairness and reciprocity are fundamental to cooperation and constitute core behavioral principles. Warm glow theory suggests that cooperative behavior is driven by positive emotions, whereas inequity aversion theory proposes that cooperative behavior is necessary to avoid negative feelings. However, the precise characteristics underlying the enforcement (fairness or reciprocity) and violation (unfairness or betrayal) of cooperation remain elusive. Moreover, whether the neural mechanism of cooperation as a partner or a spectator is the same remains unclear. To resolve the above issues, we summarized the findings of human cooperation neuroimaging studies through a meta-analysis. Based on our results, cooperation enforcement activates reward-related brain areas, such as the striatum and orbitofrontal cortex, only during other-cooperation. In contrast, cooperation violation is associated with the negative emotion-related insula in both self- and other-noncooperation. Thus, people expect others to cooperate rather than themselves; however, people are disgusted when cooperation is violated by themselves or others. Taken together, cooperative behavior might be mainly driven by a process designed to avoid negative emotion, which supports the inequity aversion theory but not the warm glow theory, thereby improving our understanding of cooperation theory.

Neurobehavioral Mechanisms Supporting Trust and Reciprocity

Trust and reciprocity are cornerstones of human nature, both at the levels of close interpersonal relationships and economic/societal structures. Being able to both place trust in others and decide whether to reciprocate trust placed in us is rooted in implicit and explicit processes that guide expectations of others, help reduce social uncertainty, and build relationships. This review will highlight neurobehavioral mechanisms supporting trust and reciprocity, through the lens of implicit and explicit social appraisal and learning processes. Significant consideration will be given to the neural underpinnings of these implicit and explicit processes, and special focus will center on the underlying neurocomputational mechanisms facilitating the integration of implicit and explicit signals supporting trust and reciprocity. Finally, this review will conclude with a discussion of how we can leverage findings regarding the neurobehavioral mechanisms supporting trust and reciprocity to better inform our understanding of mental health disorders characterized by social dysfunction.

To believe or not to believe? How voice and accent information in speech alter listener impressions of trust

Our decision to believe what another person says can be influenced by vocally expressed confidence in speech and by whether the speaker–listener are members of the same social group. The dynamic effects of these two information sources on neurocognitive processes that promote believability impressions from vocal cues are unclear. Here, English Canadian listeners were presented personal statements ( She has access to the building) produced in a confident or doubtful voice by speakers of their own dialect (in-group) or speakers from two different “out-groups” (regional or foreign-accented English). Participants rated how believable the speaker is for each statement and event-related potentials (ERPs) were analysed from utterance onset. Believability decisions were modulated by both the speaker’s vocal confidence level and their perceived in-group status. For in-group speakers, ERP effects revealed an early differentiation of vocally expressed confidence (i.e., N100, P200), highlighting the motivational significance of doubtful voices for drawing believability inferences. These early effects on vocal confidence perception were qualitatively different or absent when speakers had an accent; evaluating out-group voices was associated with increased demands on contextual integration and re-analysis of a non-native representation of believability (i.e., increased N400, late negativity response). Accent intelligibility and experience with particular out-group accents each influenced how vocal confidence was processed for out-group speakers. The N100 amplitude was sensitive to out-group attitudes and predicted actual believability decisions for certain out-group speakers. We propose a neurocognitive model in which vocal identity information (social categorization) dynamically influences how vocal expressions are decoded and used to derive social inferences during person perception.

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.