Spatial gradient in value representation along the medial prefrontal cortex reflects individual differences in prosociality

Causal involvement of dorsomedial prefrontal cortex in learning the predictability of observable actions

Social learning is well established across species. While recent neuroimaging studies show that dorsomedial prefrontal cortex (DMPFC/preSMA) activation correlates with observational learning signals, the precise computations that are implemented by DMPFC/preSMA have remained unclear. To identify whether DMPFC/preSMA supports learning from observed outcomes or observed actions, or possibly encodes even a higher order factor (such as the reliability of the demonstrator), we downregulate DMPFC/preSMA excitability with continuous theta burst stimulation (cTBS) and assess different forms of observational learning. Relative to a vertex-cTBS control condition, DMPFC/preSMA downregulation decreases performance during action-based learning but has no effect on outcome-based learning. Computational modeling reveals that DMPFC/preSMA cTBS disrupts learning the predictability, a proxy of reliability, of the demonstrator and modulates the rate of learning from observed actions. Thus, our results suggest that the DMPFC is causally involved in observational action learning, mainly by adjusting the speed of learning about the predictability of the demonstrator.

Neural Reward Representations Enable Utilitarian Welfare Maximization

From deciding which meal to prepare for our guests to trading off the proenvironmental effects of climate protection measures against their economic costs, we often must consider the consequences of our actions for the well-being of others (welfare). Vexingly, the tastes and views of others can vary widely. To maximize welfare according to the utilitarian philosophical tradition, decision-makers facing conflicting preferences of others should choose the option that maximizes the sum of the subjective value (utility) of the entire group. This notion requires comparing the intensities of preferences across individuals. However, it remains unclear whether such comparisons are possible at all and (if they are possible) how they might be implemented in the brain. Here, we show that female and male participants can both learn the preferences of others by observing their choices and represent these preferences on a common scale to make utilitarian welfare decisions. On the neural level, multivariate support vector regressions revealed that a distributed activity pattern in the ventromedial prefrontal cortex (VMPFC), a brain region previously associated with reward processing, represented the preference strength of others. Strikingly, also the utilitarian welfare of others was represented in the VMPFC and relied on the same neural code as the estimated preferences of others. Together, our findings reveal that humans can behave as if they maximized utilitarian welfare using a specific utility representation and that the brain enables such choices by repurposing neural machinery processing the reward others receive.

A neurocomputational account of the link between social perception and social action

People selectively help others based on perceptions of their merit or need. Here, we develop a neurocomputational account of how these social perceptions translate into social choice. Using a novel fMRI social perception task, we show that both merit and need perceptions recruited the brain's social inference network. A behavioral computational model identified two non-exclusive mechanisms underlying variance in social perceptions: a consistent tendency to perceive others as meritorious/needy (bias) and a propensity to sample and integrate normative evidence distinguishing high from low merit/need in other people (sensitivity). Variance in people's merit (but not need) bias and sensitivity independently predicted distinct aspects of altruism in a social choice task completed months later. An individual's merit bias predicted context-independent variance in people's overall other-regard during altruistic choice, biasing people towards prosocial actions. An individual's merit sensitivity predicted context-sensitive discrimination in generosity towards high and low merit recipients by influencing other-regard and self-regard during altruistic decision-making. This context-sensitive perception-action link was associated with activation in the right temporoparietal junction. Together, these findings point towards stable, biologically based individual differences in perceptual processes related to abstract social concepts like merit, and suggest that these differences may have important behavioral implications for an individual's tendency toward favoritism or discrimination in social settings.

Normative Processing Needs Multiple Levels of Explanation: From Algorithm to Implementation

Norms are the rules about what is allowed or forbidden by social groups. A key debate for norm psychology is whether these rules arise from mechanisms that are domain-specific and genetically inherited or domain-general and deployed for many other nonnorm processes. Here we argue for the importance of assessing and testing domain-specific and domain-general processes at multiple levels of explanation, from algorithmic (psychological) to implementational (neural). We also critically discuss findings from cognitive neuroscience supporting that social and nonsocial learning processes, essential for accounts of cultural evolution, can be dissociated at these two levels. This multilevel framework can generate new hypotheses and empirical tests of cultural evolution accounts of norm processing against purely domain-specific nativist alternatives.

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.

Perceived financial well-being and its association with frontostriatal functional connectivity, real-life anticipatory experiences, and everyday happiness

Perceived financial well-being (FWB) is an important aspect of life that can affect one's attitude toward future experiences and happiness. However, the relationship between FWB, anticipatory experiences, and happiness, and the brain's functional architecture underlying this relationship remain unknown. Here, we combined an experience sampling method, multilevel modeling, and functional neuroimaging to identify the neural correlates of FWB and their associations with real-world anticipatory experiences and everyday happiness. Behaviorally, we found that individuals with greater FWB felt more positive and more interested when they expected positive events to occur, which in turn resulted in increased everyday happiness. Furthermore, the level of FWB was significantly associated with the strength of functional connectivity (FC) between the nucleus accumbens (NAc) and ventromedial prefrontal cortex (vmPFC) and the local coherence within the vmPFC. The frontostriatal FC and local coherence within the vmPFC were further predictive of everyday happiness via the anticipatory response involving interestedness during positive expectations. Our findings suggest that individual differences in FWB could be reflected in the functional architecture of brain's reward system that may contribute to shaping positive anticipatory experiences and happiness in daily life.

Economic and social values in the brain: evidence from lesions to the human ventromedial prefrontal cortex

Making good economic and social decisions is essential for individual and social welfare. Decades of research have provided compelling evidence that damage to the ventromedial prefrontal cortex (vmPFC) is associated with dramatic personality changes and impairments in economic and social decision-making. However, whether the vmPFC subserves a unified mechanism in the social and non-social domains remains unclear. When choosing between economic options, the vmPFC is thought to guide decision by encoding value signals that reflect the motivational relevance of the options on a common scale. A recent framework, the "extended common neural currency" hypothesis, suggests that the vmPFC may also assign values to social factors and principles, thereby guiding social decision-making. Although neural value signals have been observed in the vmPFC in both social and non-social studies, it is yet to be determined whether they have a causal influence on behavior or merely correlate with decision-making. In this review, we assess whether lesion studies of patients with vmPFC damage offer evidence for such a causal role of the vmPFC in shaping economic and social behavior.

Social value orientation modulates behavioral and neural responses to social influence

Substantial studies have investigated the social influence effect; however, how individuals with different social value orientations (SVOs), prosocials and proselfs, respond to different social influences remains unknown. This study examines the impact of positive and negative social information on the responses of people with different SVOs. A face-attractiveness assessment task was employed to investigate the relationships between influence probability, memory, and event-related potentials of social influence. A significant interactional effect suggested that prosocials and proselfs reacted differently to positive (group rating was more attractive) and negative (group rating was less attractive) social influences. Specifically, proselfs demonstrated significantly higher influence probability, marginally better recall performance, smaller N400, and larger late positive potential on receiving negative influence information than on receiving positive influence information, while prosocials showed no significant differences. Overall, correlations between N400/LPP, influence probability, and recall performance were significant. The above results indicate the modulating role of SVO when responding to social influence. These findings have important implications for understanding how people conform and how prosocial behavior occurs.

Modulating the Activity of the Right Dorsolateral Prefrontal Cortex Alters Altruism in Situations of Advantageous Inequity

Altruism is highly valued and cherished by human society. However, human preferences and behavior are sensitive to inequality considerations. Currently, remarkably little is known about the neurobiological mechanisms underlying the process of altruistic acts in inequity situations. Therefore, to clarify the causal role of the right dorsolateral prefrontal cortex (rDLPFC) in altruism during situations of advantageous and disadvantageous inequity, we applied transcranial direct current stimulation (tDCS) to demonstrate the involvement of the rDLPFC in altruism in situations of inequity. A total of 71 participants (38 female and 33 male) received anodal tDCS at 1.5 mA over the rDLPFC (n = 38) or the primary visual cortex (n = 33) and subsequently participated in a modified dictator game that measures altruism. We found that anodal tDCS over the rDLPFC decreased subjects' sensitivity to altruistic efficiency and cost in situations of advantageous inequity. Our results suggested that the rDLPFC plays an important role in overriding self-interest to enforce altruism in situations of advantageous inequity.

On the relationship between the social brain, social connectedness, and wellbeing

The emergence of social neuroscience in the past two decades has offered a useful neurocognitive framework for understanding human social behavior. Of importance, social neuroscience research aimed to provide mechanistic explanations for the established link between wellbeing and social behavioral phenomena-particularly those reflective of social connectedness. Here, we provide an overview of the relevant literature focusing on recent work using functional magnetic resonance imaging (fMRI). In general, fMRI research demonstrated that aspects of social connectedness that are known to either positively (e.g., social acceptance) or negatively (e.g., social isolation) impact wellbeing also modulated the activity of subcortical reward system accordingly. Similar modulatory influence was found for the activity of other brain regions such as the medial prefrontal cortex, which are typically regarded as components of the "social brain" that support a wide range of functions related to social cognition and behavior. Elucidating such individual differences in brain activity may shed light onto the neural underpinnings of the link between social connectedness and wellbeing.

Behavioral and neuro-cognitive bases for emergence of norms and socially shared realities via dynamic interaction

In the digital era, new socially shared realities and norms emerge rapidly, whether they are beneficial or harmful to our societies. Although these are emerging properties from dynamic interaction, most research has centered on static situations where isolated individuals face extant norms. We investigated how perceptual norms emerge endogenously as shared realities through interaction, using behavioral and fMRI experiments coupled with computational modeling. Social interactions fostered convergence of perceptual responses among people, not only overtly but also at the covert psychophysical level that generates overt responses. Reciprocity played a critical role in increasing the stability (reliability) of the psychophysical function within each individual, modulated by neural activity in the mentalizing network during interaction. These results imply that bilateral influence promotes mutual cognitive anchoring of individual views, producing shared generative models at the collective level that enable endogenous agreement on totally new targets-one of the key functions of social norms.

Neural basis of prosocial behavior

The ability to behave in ways that benefit other individuals' well-being is among the most celebrated human characteristics crucial for social cohesiveness. Across mammalian species, animals display various forms of prosocial behaviors - comforting, helping, and resource sharing - to support others' emotions, goals, and/or material needs. In this review, we provide a cross-species view of the behavioral manifestations, proximate and ultimate drives, and neural mechanisms of prosocial behaviors. We summarize key findings from recent studies in humans and rodents that have shed light on the neural mechanisms underlying different processes essential for prosocial interactions, from perception and empathic sharing of others' states to prosocial decisions and actions.

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.

Learning under social versus nonsocial uncertainty: A meta-analytic approach

Much of the uncertainty that clouds our understanding of the world springs from the covert values and intentions held by other people. Thus, it is plausible that specialized mechanisms that compute learning signals under uncertainty of exclusively social origin operate in the brain. To test this hypothesis, we scoured academic databases for neuroimaging studies involving learning under uncertainty, and performed a meta‐analysis of brain activation maps that compared learning in the face of social versus nonsocial uncertainty. Although most of the brain activations associated with learning error signals were shared between social and nonsocial conditions, we found some evidence for functional segregation of error signals of exclusively social origin during learning in limited regions of ventrolateral prefrontal cortex and insula. This suggests that most behavioral adaptations to navigate social environments are reused from frontal and subcortical areas processing generic value representation and learning, but that a specialized circuitry might have evolved in prefrontal regions to deal with social context representation and strategic action.

Distinctive roles of mPFC subregions in forming impressions and guiding social interaction based on others' social behaviour

People can quickly form impressions of others from their social behaviour, which can guide their future social interactions. This study investigated how the type and timing of others' social decisions affect the impression formation and social interactions. In each trial, participants watched a responder's decision in an ultimatum game, decided whether to choose the responder as their next partner for proposer or responder and reported the perceived warmth, competence and likability of the responder. Participants preferred responders who accepted (i.e. accepters) unfair offers for the responder and those who rejected (i.e. rejecters) unfair offers for the proposer in their next ultimatum game, and the rostral medial prefrontal cortex (mPFC) activity encoded such a strategic context-dependent valuation when choosing partners. Slow rejecters were perceived as warmer than fast rejecters, which was mirrored by the anterior mid-cingulate cortex activity when watching others' decisions, possibly detecting and resolving conflicting impressions. Finally, those who perceived accepters vs rejecters as warmer showed higher ventral mPFC responses to accepters vs rejecters when choosing a partner, regardless of the context. The present study suggests that distinctive subregions of the mPFC may be differentially involved in forming impressions and guiding social interactions with others based on their social behaviours.

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.

Role of anterior midcingulate cortex in self-reward representation and reward allocation judgments within social context

Evaluating rewards for the self and others is essential for social interactions. Previous research has probed the neural substrates signaling rewards in social decision-making tasks as well as the differentiation between self- and other-reward representations. However, studies with different designs have yielded mixed results. After analyzing and comparing previous designs, we differentiated three components in this study: task (reward representation vs. social judgment of reward allocation), agency (self vs. other), and social context (without vs. within). Participants were asked to imagine various share sizes as a proposer in a dictator game during fMRI, and then rated their willingness and preference for these offers in a post-scan behavioral task. To differentiate the regions involved in processing rewards without and within context, we presented the reward to each agent in two sequential frames. Parametric analyses showed that, in the second frame (i.e., within social context), the anterior midcingulate cortex (aMCC) signaled self-reward and preferences for the offer, whereas the right insula tracked the likelihood of proposing the offer. Belief in a just world is positively associated with aMCC responses to self-reward. These results shed light on the role of the aMCC in coding self-reward within the social context to guide social behaviors.

Psychological Selfishness

Selfishness is central to many theories of human morality, yet its psychological nature remains largely overlooked. Psychologists often draw on classical conceptions of selfishness from evolutionary biology (i.e., selfish gene theory), economics (i.e., rational self-interest), and philosophy (i.e., psychological egoism), but such characterizations offer limited insight into the psychology of selfishness. To address this gap, we propose a novel framework in which selfishness is recast as a psychological construction. From this view, selfishness is perceived in ourselves and others when we detect a situation-specific desire to benefit the self that disregards others' desires and prevailing social expectations for the situation. We argue that detecting and deterring such psychological selfishness in both oneself and others is crucial in social life-facilitating the maintenance of social cohesion and close relationships. In addition, we show how using this psychological framework offers a richer understanding of the nature of human social behavior. Delineating a psychological construct of selfishness can promote coherence in interdisciplinary research on selfishness and provide insights for interventions to prevent or remediate the negative effects of selfishness.

Distinguishing the Roles of the Dorsomedial Prefrontal Cortex and Right Temporoparietal Junction in Altruism in Situations of Inequality: A Transcranial Direct Current Stimulation Study

The right temporoparietal junction (rTPJ) and dorsomedial prefrontal cortex (dmPFC), which are involved in social cognition, have been proposed to play key roles in guiding human altruistic behavior. However, no study has provided empirical evidence that the rTPJ and dmPFC play distinct roles in altruism under situations of inequality. A total of 107 healthy young adults were randomly assigned to receive anodal or sham transcranial direct current stimulation (tDCS) to either the dmPFC or rTPJ, and they participated in a modified dictator game. The stimulation of the dmPFC increased the level of altruistic behavior, while the stimulation of the rTPJ did not. Furthermore, we determined that the increase in altruism induced by tDCS of the dmPFC could be modulated by perspective taking. These results demonstrate that the dmPFC and rTPJ play distinct roles in the enhancement of altruism in situations of inequality; this finding is consistent with theories proposing that the dmPFC has evolved mechanisms dedicated to perspective taking.

The prefrontal cortex and (uniquely) human cooperation: a comparative perspective

Humans have an exceptional ability to cooperate relative to many other species. We review the neural mechanisms supporting human cooperation, focusing on the prefrontal cortex. One key feature of human social life is the prevalence of cooperative norms that guide social behavior and prescribe punishment for noncompliance. Taking a comparative approach, we consider shared and unique aspects of cooperative behaviors in humans relative to nonhuman primates, as well as divergences in brain structure that might support uniquely human aspects of cooperation. We highlight a medial prefrontal network common to nonhuman primates and humans supporting a foundational process in cooperative decision-making: valuing outcomes for oneself and others. This medial prefrontal network interacts with lateral prefrontal areas that are thought to represent cooperative norms and modulate value representations to guide behavior appropriate to the local social context. Finally, we propose that more recently evolved anterior regions of prefrontal cortex play a role in arbitrating between cooperative norms across social contexts, and suggest how future research might fruitfully examine the neural basis of norm arbitration.

Increased Ventromedial Prefrontal Cortex Activity in Adolescence Benefits Prosocial Reinforcement Learning

Learning which of our behaviors benefit others contributes to forming social relationships. An important period for the development of (pro)social behavior is adolescence, which is characterized by transitions in social connections. It is, however, unknown how learning to benefit others develops across adolescence and what the underlying cognitive and neural mechanisms are. In this functional neuroimaging study, we assessed learning for self and others (i.e., prosocial learning) and the concurring neural tracking of prediction errors across adolescence (ages 9-21, N = 74). Participants performed a two-choice probabilistic reinforcement learning task in which outcomes resulted in monetary consequences for themselves, an unknown other, or no one. Participants from all ages were able to learn for themselves and others, but learning for others showed a more protracted developmental trajectory. Prediction errors for self were observed in the ventral striatum and showed no age-related differences. However, prediction error coding for others showed an age-related increase in the ventromedial prefrontal cortex. These results reveal insights into the computational mechanisms of learning for others across adolescence, and highlight that learning for self and others show different age-related patterns.

Reduced frontal cortical tracking of conflict between self-beneficial versus prosocial motives in Narcissistic Personality Disorder

Narcissistic Personality Disorder (NPD) entails severe impairments in interpersonal functioning that are likely driven by self-beneficial and exploitative behavior. Here, we investigate the underlying motivational and neural mechanisms of prosocial decision-making by experimentally manipulating motivational conflict between self-beneficial and prosocial incentives. One group of patients diagnosed with NPD and a group of healthy controls (CTL) were scanned using functional magnetic resonance imaging while performing a prosocial decision-making task. In this task, we systematically varied the level of conflict between self-beneficial and prosocial options on each trial. We analyzed choice behavior, response times, and neural activity in regions associated with conflict monitoring to test how motivational conflict drives prosocial choice behavior. Participants in the NPD group behaved less prosocially than the CTL group overall. Varying degrees of motivational conflict between self-beneficial and prosocial options induced response variability in both groups, but more so in the CTL group. The NPD group responded faster than the CTL group, unless choosing prosocially, which slowed response times to a level comparable to the CTL group. Additionally, neural activity tracking motivational conflict in dorsomedial prefrontal cortex was reduced in the NPD group. Collectively, low generosity in NPD appears to arise from reduced consideration of prosocial motives, which obviates motivational conflict with self-beneficial motives and entails reduced activity in neural conflict monitoring systems. Yet, our data also indicate that NPD is not marked by an absolute indifference to others' needs. This points to potentials for improving interpersonal relationships, effectively supporting the well-being of patients and their peers.

Computational modelling of social cognition and behaviour-a reinforcement learning primer

Social neuroscience aims to describe the neural systems that underpin social cognition and behaviour. Over the past decade, researchers have begun to combine computational models with neuroimaging to link social computations to the brain. Inspired by approaches from reinforcement learning theory, which describes how decisions are driven by the unexpectedness of outcomes, accounts of the neural basis of prosocial learning, observational learning, mentalizing and impression formation have been developed. Here we provide an introduction for researchers who wish to use these models in their studies. We consider both theoretical and practical issues related to their implementation, with a focus on specific examples from the field.

Seven computations of the social brain

The social environment presents the human brain with the most complex information processing demands. The computations that the brain must perform occur in parallel, combine social and nonsocial cues, produce verbal and nonverbal signals and involve multiple cognitive systems, including memory, attention, emotion and learning. This occurs dynamically and at timescales ranging from milliseconds to years. Here, we propose that during social interactions, seven core operations interact to underwrite coherent social functioning; these operations accumulate evidence efficiently-from multiple modalities-when inferring what to do next. We deconstruct the social brain and outline the key components entailed for successful human-social interaction. These include (i) social perception; (ii) social inferences, such as mentalizing; (iii) social learning; (iv) social signaling through verbal and nonverbal cues; (v) social drives (e.g. how to increase one's status); (vi) determining the social identity of agents, including oneself and (vii) minimizing uncertainty within the current social context by integrating sensory signals and inferences. We argue that while it is important to examine these distinct aspects of social inference, to understand the true nature of the human social brain, we must also explain how the brain integrates information from the social world.

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.

Human dorsomedial prefrontal cortex delineates the self and other against the tendency to form interdependent social representations

In this issue of Neuron, using non-invasive brain stimulation, Wittmann et al. (2021) highlight a causal role of the dorsomedial prefrontal cortex in keeping separate estimations for the self and others, protecting against a default human tendency to form interdependent social representations.

Neural coding of human values is underpinned by brain areas representing the core self in the cortical midline region

The impact of human values on our choices depends on their nature. Self-Transcendence values motivate us to act for the benefit of others and care for the environment. Self-Enhancement values motivate us to act for our benefit. The present study examines differences in the neural processes underlying these two value domains. Extending our previous research, we used fMRI to explore first of all neural correlates of Self-Transcendence vs Self-Enhancement values, with a particular focus on the putative role of the medial prefrontal cortex (MPFC), which has been linked to a self-transcendent mind-set. Additionally, we investigated the neural basis of Openness to Change vs Conservation values. We asked participants to reflect on and rate values as guiding principles in their lives while undergoing fMRI. Mental processing of Self-Transcendence values was associated with higher brain activity in the dorsomedial (BA9, BA8) and ventromedial (BA10) prefrontal cortices, as compared to Self-Enhancement values. The former involved activation and the latter deactivation of those regions. We did not detect differences in brain activation between Openness to Change vs Conservation values. Self-Transcendence values thus shared brain regions with social processes that have previously been linked to a self-transcendent mind-set, and the "core self" representation.

Neuroscience and climate change: How brain recordings can help us understand human responses to climate change

There is little published neuroscience research on the psychology of climate change. This review outlines how carefully designed experiments that measure key neural processes, linked to specific cognitive processes, can provide powerful tools to answer research questions in climate change psychology. We review relevant literature from social neuroscience that can be applicable to environmental research-the neural correlates of fairness and cooperation, altruistic behaviour and personal values-and discuss important factors when translating environmental psychology constructs to neuroscientific measurement. We provide a practical overview of how to implement environmental neuroscience using electroencephalography, summarising important event-related potential components and how they can be used to answer questions in climate change psychology. Challenges for the field include accurate attribution of findings, both within and between studies, the need for interdisciplinary collaboration, peer review and reporting processes.

Neural Representation in mPFC Reveals Hidden Selfish Motivation in White Lies

Identifying true motivation for Pareto lies, which are mutually beneficial for both the liar and others, can be challenging because different covert motivations can lead to identical overt behavior. In this study, we adopted a brain-fingerprinting approach, combining both univariate and multivariate analyses to estimate individual measures of selfish motivation in Pareto lies by the degree of multivoxel neural representation in the mPFC for Pareto lies conforming with those for selfish versus altruistic lies in human participants of either sex. An increase in selfish motivation for Pareto lies was associated with higher mean-level activity in both ventral and rostral mPFC. The former showed an increased pattern similarity to selfish lies, and the latter showed a decreased pattern similarity to altruistic lies. Higher ventral mPFC pattern similarity predicted faster response time in Pareto lies. Our findings demonstrated that hidden selfish motivation in white lies can be revealed by neural representation in the mPFC.SIGNIFICANCE STATEMENT True motivation for dishonesty serving both self and others cannot be accurately discerned from observed behaviors. Here we showed that fMRI combining both univariate and multivariate analyses can be effectively used to reveal hidden selfish motivation of Pareto lies serving both self and others. The present study suggests that selfish motivation for prosocial dishonesty is encoded primarily by increased activity of the ventromedial and the rostromedial prefrontal cortex, representing intuitive self-serving valuation and strategic switching of motivation depending on beneficiary of dishonesty, respectively.

Determinants and modulators of human social decisions

Social decision making is a highly complex process that involves diverse cognitive mechanisms, and it is driven by the precise processing of information from both the environment and from the internal state. On the one hand, successful social decisions require close monitoring of others' behavior, in order to track their intentions; this can guide not only decisions involving other people, but also one's own choices and preferences. On the other hand, internal states such as own reward or changes in hormonal and neurotransmitter states shape social decisions and their underlying neural function. Here, we review the current literature on modulators and determinants of human social decisions.

Causal manipulation of self-other mergence in the dorsomedial prefrontal cortex

To navigate social environments, people must simultaneously hold representations about their own and others’ abilities. During self-other mergence, people estimate others’ abilities not only on the basis of the others’ past performance, but the estimates are also influenced by their own performance. For example, if we perform well, we overestimate the abilities of those with whom we are co-operating and underestimate competitors. Self-other mergence is associated with specific activity patterns in the dorsomedial prefrontal cortex (dmPFC). Using a combination of non-invasive brain stimulation, functional magnetic resonance imaging, and computational modeling, we show that dmPFC neurostimulation silences these neural signatures of self-other mergence in relation to estimation of others’ abilities. In consequence, self-other mergence behavior increases, and our assessments of our own performance are projected increasingly onto other people. This suggests an inherent tendency to form interdependent social representations and a causal role of the dmPFC in separating self and other representations.

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During self-other mergence (SOM), people confuse one’s own with another’s performance

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Brain stimulation over dorsomedial prefrontal cortex (dmPFC) alters neural SOM

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Brain stimulation over dmPFC simultaneously alters behavioral SOM

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This suggests a causal role of dmPFC in separating self and other representations

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.

Social Preferences Correlate with Cortical Thickness of the Orbito-Frontal Cortex

Humans differ in their preferences for personal rewards, fairness and others’ welfare. Such social preferences predict trust, public goods provision and mutual gains bargaining and have been linked to neural activity in regions involved in reward computation, cognitive control and perspective-taking. Although shaped by culture, social preferences are relatively stable across time, raising the question whether differences in brain anatomy predict social preferences and their key components—concern for personal outcomes and concern for others’ outcomes. Here, we examine this possibility by linking social preferences measured with incentivized economic games to 74 cortical parcels in 194 healthy humans. Neither concerns for personal outcomes nor concerns for the outcomes of others in isolation were related to anatomical differences. However, fitting earlier findings, social preferences positively scaled with cortical thickness in the left olfactory sulcus, a structure in the orbital frontal cortex previously shown to be involved in value-based decision-making. Consistent with work showing that heavier usage corresponds to larger brain volume, findings suggest that pro-social preferences relate to cortical thickness in the left olfactory sulcus because of heavier reliance on the orbital frontal cortex during social decision-making.

Multivariable pattern classification differentiates relational self-esteem from personal self-esteem

Relational self-esteem (RSE) refers to one’s sense of self-worth based on the relationship with significant others, such as family and best friends. Although previous neuroimaging research has investigated the neural processes of RSE, it is less clear how RSE is represented in multivariable neural patterns. Being able to identify a stable RSE signature could contribute to knowledge about relational self-worth. Here, using multivariate pattern classification to differentiate RSE from personal self-esteem (PSE), which pertains to self-worth derived from personal attributes, we obtained a stable diagnostic signature of RSE relative to PSE. We found that multivariable neural activities in the superior/middle temporal gyrus, precuneus, posterior cingulate cortex, dorsal medial Prefrontal Cortex (dmPFC) and temporo-parietal junction were responsible for diagnosis of RSE, suggesting that the evaluation of RSE involves the retrieval of relational episodic memory, perspective-taking and value calculation. Further, these diagnostic neural signatures were able to sensitively decode neural activities related to RSE in another independent test sample, indicating the reliability of the brain state represented. By providing a reliable multivariate brain pattern for RSE relative to PSE, our results informed more cognitively prominent processing of RSE than that of PSE and enriched our knowledge about how relational self-worth is generated in the brain.

The Role of the Medial Prefrontal Cortex in Moderating Neural Representations of Self and Other in Primates

As a frontal node in the primate social brain, the medial prefrontal cortex (MPFC) plays a critical role in coordinating one's own behavior with respect to that of others. Current literature demonstrates that single neurons in the MPFC encode behavior-related variables such as intentions, actions, and rewards, specifically for self and other, and that the MPFC comes into play when reflecting upon oneself and others. The social moderator account of MPFC function can explain maladaptive social cognition in people with autism spectrum disorder, which tips the balance in favor of self-centered perspectives rather than taking into consideration the perspective of others. Several strands of evidence suggest a hypothesis that the MPFC represents different other mental models, depending on the context at hand, to better predict others' emotions and behaviors. This hypothesis also accounts for aberrant MPFC activity in autistic individuals while they are mentalizing others.

Ventral-Dorsal Subregions in the Posterior Cingulate Cortex Represent Pay and Interest, Two Key Attributes of Job Value

Career choices affect not only our financial status but also our future well-being. When making these choices, individuals evaluate their willingness to obtain a job (i.e., job values), primarily driven by simulation of future pay and interest. Despite the importance of these decisions, their underlying neural mechanisms remain unclear. In this study, we examined the neural representation of pay and interest. Forty students were presented with 80 job names and asked to evaluate their job values while undergoing functional magnetic resonance imaging (fMRI). Following fMRI, participants rated the jobs in terms of pay and interest. The fMRI data revealed that the ventromedial prefrontal cortex (vmPFC) was associated with job value representation, and the ventral and dorsal regions of the posterior cingulate cortex (PCC) were associated with pay and interest representations, respectively. These findings suggest that the neural computations underlying job valuation conform to a multi-attribute decision-making framework, with overall value signals represented in the vmPFC and the attribute values (i.e., pay and interest) represented in specific regions outside the vmPFC, in the PCC. Furthermore, anatomically distinct representations of pay and interest in the PCC may reflect the differing roles of the two subregions in future simulations.

The neural underpinnings of allocentric thinking in a novel signaling task

The ability to adopt the perspectives of others is fundamental to effective communication in social interactions. However, the neural correlates of allocentric thinking in communicative signaling remain unclear. We adapted a novel signaling task in which the signaler was given the target word and must choose a one-word signal to help the receiver guess the target. Behavioral results suggest that speakers can use allocentric thinking to choose signals that are salient from the perspective of the receiver rather than their own point of view. At the neural level, functional magnetic resonance imaging (fMRI) data reveal that the medial prefrontal cortex (mPFC), ventral striatum, and temporal-parietal junction are more activated when signalers engage in allocentric than egocentric thinking. Moreover, functional connectivity between the mPFC and ventral striatum predicted individuals' perspective-taking ability during successful communication. These findings reveal that neural representations in the mPFC-striatum network support perspective-taking in complex social decision making, providing a new perspective on how the brain arbitrates between allocentric thinking and egocentric thinking in communication and social coordination.

Multivariate spatial feature selection in fMRI

Multivariate neuroimaging analyses constitute a powerful class of techniques to identify psychological representations. However, not all psychological processes are represented at the same spatial scale throughout the brain. This heterogeneity is apparent when comparing hierarchically organized local representations of perceptual processes to flexible transmodal representations of more abstract cognitive processes such as social and affective operations. An open question is how the spatial scale of analytic approaches interacts with the spatial scale of the representations under investigation. In this article, we describe how multivariate analyses can be viewed as existing on a spatial spectrum, anchored by searchlights used to identify locally distributed patterns of information on one end, whole brain approach used to identify diffuse neural representations at the other and region-based approaches in between. We describe how these distinctions are an important and often overlooked analytic consideration and provide heuristics to compare these different techniques to choose based on the analyst’s inferential goals.

Neural responses reveal associations between personal values and value-based decisions

Personal values are thought to modulate value-based decisions, but the neural mechanisms underlying this influence remain unclear. Using a Lottery Choice Task functional brain imaging experiment, we examined the associations between personal value for hedonism and security (based on the Schwartz Value Survey) and subjective neurocognitive processing of reward and loss probability and magnitude objectively coded in stimuli. Hedonistic individuals accepted more losing stakes and showed increased right dorsolateral prefrontal and striatal and left parietal responses with increasing probability of losing. Individuals prioritizing security rejected more stakes and showed reduced right inferior frontal and amygdala responses with increasing stake magnitude, but increased precuneus responses for high-magnitude high-winning probability. With higher hedonism, task-related functional connectivity with the whole brain was higher in right insula and lower in bilateral habenula. For those with higher security ratings, whole-brain functional connectivity was higher in bilateral insula, supplementary motor areas, right superior frontal gyrus, dorsal anterior cingulate cortex, and lower in right middle occipital gyrus. These findings highlight distinct neural engagement across brain systems involved in reward and affective processing, and cognitive control that subserves how individual differences in personal value for gaining rewards or maintaining status quo modulate value-based decisions

The Neurobehavioral Mechanisms Underlying Attitudes Toward People With Mental or Physical Illness

Social factors play a significant role in the health outcomes of those struggling with mental or physical health issues. People with mental illness experience more social stigmatization and receive less concern for their welfare than do those with physical illness. However, the cognitive and neural mechanisms by which such a bias in attitude arises remain unclear. This functional MRI study examined whether a lack of self-other similarity during mental state attribution affects perceivers' theory of mind and, subsequently, how they value a patient's welfare. During scanning, participants were asked to respond to an expression of caring and sympathetic concern from either their own perspective or while adopting the perspective of patients labeled physically ill or mentally ill. Participants reported that physically ill patients would share their affective responses to the situations, but mentally ill patients would not. Furthermore, mentalizing about physically ill patients was associated with increased activity in the ventromedial prefrontal cortex (vmPFC), a critical region for empathic concern and value-based decisions. In contrast, mentalizing about mentally ill patients preferentially engaged the dorsal anterior cingulate cortex (dACC) and anterior insula, regions previously implicated in empathic distress, in which activity correlated with individual differences in prejudice control. The findings indicate that a lack of perceived self-other similarity poses a challenge to the theory of mind and thus requires greater cognitive resources and neural computations. This might give rise to stereotyped beliefs about and prejudice against the mentally ill and failure to respond with appropriate empathy and care.

A gradient from long-term memory to novel cognition: Transitions through default mode and executive cortex

Human cognition flexibly guides decision-making in familiar and novel situations. Although these decisions are often treated as dichotomous, in reality, situations are neither completely familiar, nor entirely new. Contemporary accounts of brain organization suggest that neural function is organized along a connectivity gradient from unimodal regions of sensorimotor cortex, through executive regions to transmodal default mode network. We examined whether this graded view of neural organization helps to explain how decision-making changes across situations that vary in their alignment with long-term knowledge. We used a semantic judgment task, which parametrically varied the global semantic similarity of items within a feature matching task to create a 'task gradient', from conceptual combinations that were highly overlapping in long-term memory to trials that only shared the goal-relevant feature. We found the brain's response to the task gradient varied systematically along the connectivity gradient, with the strongest response in default mode network when the probe and target items were highly overlapping conceptually. This graded functional change was seen in multiple brain regions and within individual brains, and was not readily explained by task difficulty. Moreover, the gradient captured the spatial layout of networks involved in semantic processing, providing an organizational principle for controlled semantic cognition across the cortex. In this way, the cortex is organized to support semantic decision-making in both highly familiar and less familiar situations.

Temporal dynamics of resting EEG networks are associated with prosociality

As prosociality is key to facing many of our societies' global challenges (such as fighting a global pandemic), we need to better understand why some individuals are more prosocial than others. The present study takes a neural trait approach, examining whether the temporal dynamics of resting EEG networks are associated with inter-individual differences in prosociality. In two experimental sessions, we collected 55 healthy males' resting EEG, their self-reported prosocial concern and values, and their incentivized prosocial behavior across different reward domains (money, time) and social contexts (collective, individual). By means of EEG microstate analysis we identified the temporal coverage of four canonical resting networks (microstates A, B, C, and D) and their mutual communication in order to examine their association with an aggregated index of prosociality. Participants with a higher coverage of microstate A and more transitions from microstate C to A were more prosocial. Our study demonstrates that temporal dynamics of intrinsic brain networks can be linked to complex social behavior. On the basis of previous findings on links of microstate A with sensory processing, our findings suggest that participants with a tendency to engage in bottom-up processing during rest behave more prosocially than others.

Is There a 'Social' Brain? Implementations and Algorithms

A fundamental question in psychology and neuroscience is the extent to which cognitive and neural processes are specialised for social behaviour, or are shared with other 'non-social' cognitive, perceptual, and motor faculties. Here we apply the influential framework of Marr (1982) across research in humans, monkeys, and rodents to propose that information processing can be understood as 'social' or 'non-social' at different levels. We argue that processes can be socially specialised at the implementational and/or the algorithmic level, and that changing the goal of social behaviour can also change social specificity. This framework could provide important new insights into the nature of social behaviour across species, facilitate greater integration, and inspire novel theoretical and empirical approaches.

Anterior cingulate cortex: A brain system necessary for learning to reward others?

Helping a friend move house, donating to charity, volunteering assistance during a crisis. Humans and other species alike regularly undertake prosocial behaviors—actions that benefit others without necessarily helping ourselves. But how does the brain learn what acts are prosocial? Basile and colleagues show that removal of the anterior cingulate cortex (ACC) prevents monkeys from learning what actions are prosocial but does not stop them carrying out previously learned prosocial behaviors. This highlights that the ability to learn what actions are prosocial and choosing to perform helpful acts may be distinct cognitive processes, with only the former depending on ACC.

How do we learn which actions benefit others? This Primer discusses a recent study showing that removal of the anterior cingulate cortex prevents monkeys from learning new actions that benefit others, but does not stop them from carrying out previously learned prosocial acts.

Aesthetics and morality judgments share cortical neuroarchitecture

Philosophers have predominantly regarded morality and aesthetics judgments as fundamentally different. However, whether this claim is empirically founded has remained unclear. In a novel task, we measured brain activity of participants judging the aesthetic beauty of artwork or the moral goodness of actions depicted. To control for the content of judgments, participants assessed the age of the artworks and the speed of depicted actions. Univariate analyses revealed whole-brain corrected, content-controlled common activation for aesthetics and morality judgments in frontopolar, dorsomedial and ventrolateral prefrontal cortex. Temporoparietal cortex showed activation specific for morality judgments, occipital cortex for aesthetics judgments. Multivariate analyses revealed both common and distinct whole-brain corrected representations for morality and aesthetics judgments in temporoparietal and prefrontal regions. Overall, neural commonalities are more pronounced than predominant philosophical views would predict. They are compatible with minority accounts that stress commonalities between aesthetics and morality judgments, such as sentimentalism and a valuation framework.

The neural basis of shared preference learning

During our daily lives, we often learn about the similarity of the traits and preferences of others to our own and use that information during our social interactions. However, it is unclear how the brain represents similarity between the self and others. One possible mechanism is to track similarity to oneself regardless of the identity of the other (Similarity account); an alternative is to track each other person in terms of consistency of their choice similarity with respect to the choices they have made before (consistency account). Our study combined functional Magnetic Resonance Imaging (fMRI) and computational modelling of reinforcement learning (RL) to investigate the neural processes that underlie learning about preference similarity. Participants chose which of two pieces of artwork they preferred and saw the choices of one agent who usually shared their preference and another agent who usually did not. We modelled neural activation with RL models based on the similarity and consistency accounts. Our results showed that activity in brain areas linked to reward and social cognition followed the consistency account. Our findings suggest that impressions of other people can be calculated in a person-specific manner, which assumes that each individual behaves consistently with their past choices.

Stability or Plasticity? - A Hierarchical Allostatic Regulation Model of Medial Prefrontal Cortex Function for Social Valuation

The medial prefrontal cortex (mPFC) has long been recognized as the key component of the neurocircuitry involved in various social as well as non-social behaviors, however, little is known regarding the organizing principle of distinctive subregions in the mPFC that integrates a wide range of mPFC functions. The present study proposes a hierarchical model of mPFC functionality, where three functionally dissociable subregions, namely, the ventromedial prefrontal cortex (vmPFC), rostromedial prefrontal cortex (rmPFC), and dorsomedial prefrontal cortex (dmPFC), are differentially involved in computing values of decision-making. According to this model, the mPFC subregions interact with each other in such a way that more dorsal regions utilize additional external sensory information from environment to predict and prevent conflicts occurring in more ventral regions tuned to internal bodily signals, thereby exerting the hierarchically organized allostatic regulatory control over homeostatic reflexes. This model also emphasizes the role of the thalamic reticular nucleus (TRN) in arbitrating the transitions between different thalamo-cortical loops, detecting conflicts between competing options for decision-making, and in shifting flexibly between decision modes. The hierarchical architecture of the mPFC working in conjunction with the TRN may play a key role in adjusting the internal (bodily) needs to suit the constraints of external (environmental) variables better, thus effectively addressing the stability-plasticity dilemma.