Human ventromedial prefrontal cortex is necessary for prosocial motivation.

Ventromedial prefrontal cortex (vmPFC) is vital for decision-making. Functional neuroimaging links vmPFC to processing rewards and effort, while parallel work suggests vmPFC involvement in prosocial behaviour. However, the necessity of vmPFC for these functions is unknown. Patients with rare focal vmPFC lesions (n = 25), patients with lesions elsewhere (n = 15) and healthy controls (n = 40) chose between rest and exerting effort to earn rewards for themselves or another person. vmPFC damage decreased prosociality across behavioural and computational measures. vmPFC patients earned less, discounted rewards by effort more, and exerted less force when another person benefited, compared to both control groups. Voxel-based lesion mapping revealed dissociations between vmPFC subregions. While medial damage led to antisocial behaviour, lateral damage increased prosocial behaviour relative to patients with damage elsewhere. vmPFC patients also showed reduced effort sensitivity overall, but reward sensitivity was limited to specific subregions. These results reveal multiple causal contributions of vmPFC to prosocial behaviour, effort and reward.

Acute stress reduces effortful prosocial behaviour.

Acute stress can change our cognition and emotions, but what specific consequences this has for human prosocial behaviour is unclear. Previous studies have mainly investigated prosociality with financial transfers in economic games and produced conflicting results. Yet a core feature of many types of prosocial behaviour is that they are effortful. We therefore examined how acute stress changes our willingness to exert effort that benefits others. Healthy male participants - half of whom were put under acute stress - made decisions whether to exert physical effort to gain money for themselves or another person. With this design, we could independently assess the effects of acute stress on prosocial, compared to self-benefitting, effortful behaviour. Compared to controls (n = 45), participants in the stress group (n = 46) chose to exert effort more often for self- than for other-benefitting rewards at a low level of effort. Additionally, the adverse effects of stress on prosocial effort were particularly pronounced in more selfish participants. Neuroimaging combined with computational modelling revealed a putative neural mechanism underlying these effects: more stressed participants showed increased activation to subjective value in the dorsal anterior cingulate cortex and anterior insula when they themselves could benefit from their exerted effort relative to when someone else could. By using an effort-based task that better approximates real-life prosocial behaviour and incorporating trait differences in prosocial tendencies, our study provides important insights into how acute stress affects prosociality and its associated neural mechanisms.

Reduced prosocial motivation and effort in adolescents with conduct problems and callous-unemotional traits.

BACKGROUND: Prosocial behaviours - acts that benefit others - are of crucial importance for many species including humans. However, adolescents with conduct problems (CP), unlike their typically developing (TD) peers, demonstrate markedly reduced engagement in prosocial behaviours. This pattern is particularly pronounced in adolescents with CP and high levels of callous-unemotional traits (CP/HCU) who are at increased risk of developing psychopathy in adulthood. While a substantial amount of research has investigated the cognitive-affective mechanisms thought to underlie antisocial behaviour, much less is known about the mechanisms that could explain reduced prosocial behaviours in adolescents with CP. METHODS: Here we examined the willingness to exert effort to benefit oneself (self) and another person (other, prosocial condition) in children with CP/HCU, CP and lower levels of CU traits (CP/LCU) and their TD peers. The task captured both prosocial choices, and actual effort exerted following prosocial choices, in adolescent boys aged 11-16 (27 CP/HCU; 34 CP/LCU; 33 TD). We used computational modelling to reveal the mechanistic processes involved when choosing prosocial acts. RESULTS: We found that both CP/HCU and CP/LCU groups were more averse to initiating effortful prosocial acts than TD adolescents - both at a cognitive and at a behavioural level. Strikingly, even if they chose to initiate a prosocial act, the CP/HCU group exerted less effort following this prosocial choice than other groups. CONCLUSIONS: Our findings indicate that reduced exertion of effort to benefit others may be an important factor that differentiates adolescents with CP/HCU from their peers with CP/LCU. They offer new insights into what might drive low prosocial behaviour in adolescents with CP, including vulnerabilities that may particularly characterise those with high levels of CU traits.

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.

Impaired Punishment Learning in Conduct Disorder.

OBJECTIVE: Conduct disorder (CD) has been associated with deficits in the use of punishment to guide reinforcement learning (RL) and decision making. This may explain the poorly planned and often impulsive antisocial and aggressive behavior in affected youths. Here, we used a computational modeling approach to examine differences in RL abilities between CD youths and typically developing controls (TDCs). Specifically, we tested 2 competing hypotheses that RL deficits in CD reflect either reward dominance (also known as reward hypersensitivity) or punishment insensitivity (also known as punishment hyposensitivity). METHOD: The study included 92 CD youths and 130 TDCs (aged 9-18 years, 48% girls) who completed a probabilistic RL task with reward, punishment, and neutral contingencies. Using computational modeling, we investigated the extent to which the 2 groups differed in their learning abilities to obtain reward and/or to avoid punishment. RESULTS: RL model comparisons showed that a model with separate learning rates per contingency explained behavioral performance best. Importantly, CD youths showed lower learning rates than TDCs specifically for punishment, whereas learning rates for reward and neutral contingencies did not differ. Moreover, callous-unemotional (CU) traits did not correlate with learning rates in CD. CONCLUSION: CD youths have a highly selective impairment in probabilistic punishment learning, regardless of their CU traits, whereas reward learning appears to be intact. In summary, our data suggest punishment insensitivity rather than reward dominance in CD. Clinically, the use of punishment-based intervention techniques to achieve effective discipline in patients with CD may be a less helpful strategy than reward-based techniques.

Action initiation and punishment learning differ from childhood to adolescence while reward learning remains stable.

Theoretical and empirical accounts suggest that adolescence is associated with heightened reward learning and impulsivity. Experimental tasks and computational models that can dissociate reward learning from the tendency to initiate actions impulsively (action initiation bias) are thus critical to characterise the mechanisms that drive developmental differences. However, existing work has rarely quantified both learning ability and action initiation, or it has relied on small samples. Here, using computational modelling of a learning task collected from a large sample (N = 742, 9-18 years, 11 countries), we test differences in reward and punishment learning and action initiation from childhood to adolescence. Computational modelling reveals that whilst punishment learning rates increase with age, reward learning remains stable. In parallel, action initiation biases decrease with age. Results are similar when considering pubertal stage instead of chronological age. We conclude that heightened reward responsivity in adolescence can reflect differences in action initiation rather than enhanced reward learning.

Probing apathy in children and adolescents with the Apathy Motivation Index-Child version.

Apathy is linked to mental health and altered neurocognitive functions such as learning and decision-making in healthy adults. Mental health problems typically begin to emerge during adolescence, yet little is known about how apathy develops due to an absence of quantitative measurements specific to young people. Here, we present and evaluate the Apathy Motivation Index-Child Version (AMI-CV) for children and adolescents. We show across two samples of young people (aged 8 to 17 years, total N = 191) tested in schools in the UK and on a smartphone app, that the AMI-CV is a short, psychometrically sound measure to assess levels of apathy and motivation in young people. Similar to adult versions, the AMI-CV captures three distinct apathy domains: Behavioural Activation, Social Motivation and Emotional Sensitivity. The AMI-CV showed excellent construct validity with an alternative measure of apathy and external validity replicating specific links with related mental health traits shown in adults. Our results provide a short measure of self-reported apathy in young people that enables research into apathy development. The AMI-CV can be used in conjunction with the adult version to investigate the impact of levels of apathy across the lifespan.

Social and moral psychology of COVID-19 across 69 countries.

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.

l-DOPA and oxytocin influence the neurocomputational mechanisms of self-benefitting and prosocial reinforcement learning.

Humans learn through reinforcement, particularly when outcomes are unexpected. Recent research suggests similar mechanisms drive how we learn to benefit other people, that is, how we learn to be prosocial. Yet the neurochemical mechanisms underlying such prosocial computations remain poorly understood. Here, we investigated whether pharmacological manipulation of oxytocin and dopamine influence the neurocomputational mechanisms underlying self-benefitting and prosocial reinforcement learning. Using a double-blind placebo-controlled cross-over design, we administered intranasal oxytocin (24 IU), dopamine precursor l-DOPA (100 mg + 25 mg carbidopa), or placebo over three sessions. Participants performed a probabilistic reinforcement learning task with potential rewards for themselves, another participant, or no one, during functional magnetic resonance imaging. Computational models of reinforcement learning were used to calculate prediction errors (PEs) and learning rates. Participants behavior was best explained by a model with different learning rates for each recipient, but these were unaffected by either drug. On the neural level, however, both drugs blunted PE signaling in the ventral striatum and led to negative signaling of PEs in the anterior mid-cingulate cortex, dorsolateral prefrontal cortex, inferior parietal gyrus, and precentral gyrus, compared to placebo, and regardless of recipient. Oxytocin (versus placebo) administration was additionally associated with opposing tracking of self-benefitting versus prosocial PEs in dorsal anterior cingulate cortex, insula and superior temporal gyrus. These findings suggest that both l-DOPA and oxytocin induce a context-independent shift from positive towards negative tracking of PEs during learning. Moreover, oxytocin may have opposing effects on PE signaling when learning to benefit oneself versus another.

Neural activity tracking identity and confidence in social information.

Humans learn about the environment either directly by interacting with it or indirectly by seeking information about it from social sources such as conspecifics. The degree of confidence in the information obtained through either route should determine the impact that it has on adapting and changing behaviour. We examined whether and how behavioural and neural computations differ during non-social learning as opposed to learning from social sources. Trial-wise confidence judgements about non-social and social information sources offered a window into this learning process. Despite matching exactly the statistical features of social and non-social conditions, confidence judgements were more accurate and less changeable when they were made about social as opposed to non-social information sources. In addition to subjective reports of confidence, differences were also apparent in the Bayesian estimates of participants' subjective beliefs. Univariate activity in dorsomedial prefrontal cortex and posterior temporoparietal junction more closely tracked confidence about social as opposed to non-social information sources. In addition, the multivariate patterns of activity in the same areas encoded identities of social information sources compared to non-social information sources.

People's decisions are influenced by their beliefs, which may be based on advice from other humans or, alternatively, on information from non-human sources such as road signs. But which sources do we find more reliable? Although scientists have studied the importance of social context in the way we process information, it is not fully understood how the brain processes information differently depending on who provides it. Trudel et al. investigated the differences in the way humans evaluate information from human sources, such as advisors, compared to non-human sources, like inanimate objects, by monitoring brain activity and analyzing the results using a computational approach. In the experiments, 24 participants received a reward for locating a hidden dot on a circle under two different conditions: they either received a clue on the dot's location from an image of a human face (social condition), representing an advisor, or from an inanimate object (non-social condition). Participants received information from many different advisors and inanimate objects, and the accuracy of the clues given by any of them varied from source to source. Each time, participants reported whether they thought the advice was reliable. The results of monitoring the participants' brain activity showed that they used different strategies when assessing the reliability of advice from a human than when the information came from a non-human source. Additionally, participants based their judgments about an advisor more strongly on past experiences with them, that is, if an advisor had given them good advice in the past, they were more likely to rely on their advice. Conversely, judgments about an inanimate object were based more strongly on recent experiences with that object. Interestingly, participants were more certain when making judgments about the accuracy of cues given by advisors compared to inanimate objects, and they also updated their assessment of human sources less according to new evidence that contradicted their initial belief. This suggests that people may form more stable opinions about the reliability of sources when they receive information in social contexts, possibly because they expect more consistent behavior from humans. This stability in judgments about advisors was also reflected in the signal of brain areas that are often involved when interacting with others. The work of Trudel et al. shows that even the suggestion that the source of a piece of advice is human can change how we process the information. This is especially important because humans spend increasingly more time in the digital world. Awareness of our biased assessment of human sources will have implications for designing interactive tools to guide human decision-making as well as strategies to develop critical thinking.

Neural representations of vicarious rewards are linked to interoception and prosocial behaviour.

Every day we constantly observe other people receiving rewards. Theoretical accounts posit that vicarious reward processing might be linked to people's sensitivity to internal body states (interoception) and facilitates a tendency to act prosocially. However, the neural processes underlying the links between vicarious reward processing, interoception, and prosocial behaviour are poorly understood. Previous research has linked vicarious reward processing to the anterior cingulate gyrus (ACCg) and the anterior insula (AI). Can we predict someone's propensity to be prosocial or to be aware of interoceptive signals from variability in how the ACCg and AI process rewards? Here, participants monitored rewards being delivered to themselves or a stranger during functional magnetic resonance imaging. Later, they performed a task measuring their willingness to exert effort to obtain rewards for others, and a task measuring their propensity to be aware and use interoceptive respiratory signals. Using multivariate similarity analysis, we show that people's willingness to be prosocial is predicted by greater similarity between self and other representations in the ACCg. Moreover, greater dissimilarity in self-other representations in the AI is linked to interoceptive propensity. These findings highlight that vicarious reward is linked to bodily signals in AI, and foster prosocial tendencies through the ACCg.

Age Differences in Prosocial Behavior Depend on Effort Costs.

OBJECTIVES: This study examined age differences in willingness to engage in effortful and effortless prosocial behavior for a fully anonymous recipient. METHOD: Participants were recruited through the Prolific online recruitment platform. In Experiment 1, older (N = 46) and younger (N = 65) adults completed the "pay-it-forward" effortful decision-making task with fixed effort demands and a version of the Dictator Game, an effortless prosocial decision-making task. In Experiment 2, older (N = 38) and younger (N = 42) adults completed the Dictator Game and a modified pay-it-forward decision-making task in which effort demands were calibrated to one's ability. RESULTS: In both Experiments 1 and 2, older adults were more prosocial than younger adults on the effortless Dictator Game. In Experiment 1, older adults were less prosocial across all trials of the effortful pay-it-forward task. However, when the task was more achievable in Experiment 2, older adults were only less prosocial when the probability of a reward was low. DISCUSSION: In everyday life, many prosocial contexts depend on effort expenditure. When prosocial activities are effortful, older adults are less willing to engage in prosocial behavior, particularly when reward likelihood is low, and instead focus on resource conservation. In the absence of such effort costs, older adults are more prosocial than younger adults. This work suggests that older adults may prefer to engage in prosocial behavior more than younger adults, but physical resource constraints may limit their ability to engage in such effortful prosocial activities.

The computational psychiatry of antisocial behaviour and psychopathy.

Antisocial behaviours such as disobedience, lying, stealing, destruction of property, and aggression towards others are common to multiple disorders of childhood and adulthood, including conduct disorder, oppositional defiant disorder, psychopathy, and antisocial personality disorder. These disorders have a significant negative impact for individuals and for society, but whether they represent clinically different phenomena, or simply different approaches to diagnosing the same underlying psychopathology is highly debated. Computational psychiatry, with its dual focus on identifying different classes of disorder and health (data-driven) and latent cognitive and neurobiological mechanisms (theory-driven), is well placed to address these questions. The elucidation of mechanisms that might characterise latent processes across different disorders of antisocial behaviour can also provide important advances. In this review, we critically discuss the contribution of computational research to our understanding of various antisocial behaviour disorders, and highlight suggestions for how computational psychiatry can address important clinical and scientific questions about these disorders in the future.

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.

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning.

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution-individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.

Distinct neural representations for prosocial and self-benefiting effort.

Prosocial behaviors-actions that benefit others-are central to individual and societal well-being. Although the mechanisms underlying the financial and moral costs of prosocial behaviors are increasingly understood, this work has often ignored a key influence on behavior: effort. Many prosocial acts are effortful, and people are averse to the costs of exerting them. However, how the brain encodes effort costs when actions benefit others is unknown. During fMRI, participants completed a decision-making task where they chose in each trial whether to "work" and exert force (30%-70% of maximum grip strength) or "rest" (no effort) for rewards (2-10 credits). Crucially, on separate trials, they made these decisions either to benefit another person or themselves. We used a combination of multivariate representational similarity analysis and model-based univariate analysis to reveal how the costs of prosocial and self-benefiting efforts are processed. Strikingly, we identified a unique neural signature of effort in the anterior cingulate gyrus (ACCg) for prosocial acts, both when choosing to help others and when exerting force to benefit them. This pattern was absent for self-benefiting behaviors. Moreover, stronger, specific representations of prosocial effort in the ACCg were linked to higher levels of empathy and higher subsequent exerted force to benefit others. In contrast, the ventral tegmental area and ventral insula represented value preferentially when choosing for oneself and not for prosocial acts. These findings advance our understanding of the neural mechanisms of prosocial behavior, highlighting the critical role that effort has in the brain circuits that guide helping others.

Oxytocin modulates neurocomputational mechanisms underlying prosocial reinforcement learning.

Humans often act in the best interests of others. However, how we learn which actions result in good outcomes for other people and the neurochemical systems that support this 'prosocial learning' remain poorly understood. Using computational models of reinforcement learning, functional magnetic resonance imaging and dynamic causal modelling, we examined how different doses of intranasal oxytocin, a neuropeptide linked to social cognition, impact how people learn to benefit others (prosocial learning) and whether this influence could be dissociated from how we learn to benefit ourselves (self-oriented learning). We show that a low dose of oxytocin prevented decreases in prosocial performance over time, despite no impact on self-oriented learning. Critically, oxytocin produced dose-dependent changes in the encoding of prediction errors (PE) in the midbrain-subgenual anterior cingulate cortex (sgACC) pathway specifically during prosocial learning. Our findings reveal a new role of oxytocin in prosocial learning by modulating computations of PEs in the midbrain-sgACC pathway.

National identity predicts public health support during a global pandemic.

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = -0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.

Prosocial behavior is associated with transdiagnostic markers of affective sensitivity in multiple domains.

Prosocial behaviors-actions that benefit others-fundamentally shape our interpersonal interactions. Psychiatric disorders have been suggested to be related to prosocial disturbances, which may underlie many of their social impairments. However, broader affective traits, present to different degrees in both psychiatric and healthy populations, also have been linked to variability in prosociality. Therefore, it is unclear to what extent prosocial variability is explained by specific psychiatric disorders relative to broad affective traits. Using a computational, transdiagnostic approach in two online studies, we found that participants who reported being more affectively reactive across a broad cluster of traits manifested greater frequencies of prosocial actions in two different contexts: They reported being more averse to harming others for profit, and they were more willing to exert effort to benefit others. These findings help illuminate the profile of prosociality across psychiatric conditions as well as the architecture of prosocial behavior in healthy individuals. (PsycInfo Database Record (c) 2022 APA, all rights reserved).