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.

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.

A comparative fMRI meta-analysis of altruistic and strategic decisions to give.

The decision to share resources is fundamental for cohesive societies. Humans can be motivated to give for many reasons. Some generosity incurs a definite cost, with no extrinsic reward to the act, but instead provides intrinsic satisfaction (labelled here as 'altruistic' giving). Other giving behaviours are done with the prospect of improving one's own situation via reciprocity, reputation, or public good (labelled here as 'strategic' giving). These contexts differ in the source, certainty, and timing of rewards as well as the inferences made about others' mental states. We executed a combined statistical map and coordinate-based fMRI meta-analysis of decisions to give (36 studies, 1150 participants). Methods included a novel approach for accommodating variable signal dropout between studies in meta-analysis. Results reveal consistent, cross-paradigm neural correlates of each decision type, commonalities, and informative differences. Relative to being selfish, altruistic and strategic giving activate overlapping reward networks. However, strategic decisions showed greater activity in striatal regions than altruistic choices. Altruistic giving, more than strategic, activated subgenual anterior cingulate cortex (sgACC). Ventromedial prefrontal cortex (vmPFC) is consistently involved during generous decisions and processing across a posterior to anterior axis differentiates the altruistic/strategic context. Posterior vmPFC was preferentially recruited during altruistic decisions. Regions of the 'social brain' showed distinct patterns of activity between choice types, reflecting the different use of theory of mind in the two contexts. We provide the consistent neural correlates of decisions to give, and show that many will depend on the source of incentives.

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.

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.

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.

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.

Older adults across the globe exhibit increased prosocial behavior but also greater in-group preferences.

Population aging is a global phenomenon with substantial implications across society1,2. Prosocial behaviors-actions that benefit others-promote mental and physical health across the lifespan3,4 and can save lives during the COVID-19 pandemic. We examined whether age predicts prosociality in a preregistered global study (46,576 people aged 18-99 across 67 countries) using two acutely relevant measures: distancing during COVID-19 and willingness to donate to hypothetical charities. Age positively predicted prosociality on both measures, with increased distancing and donations among older adults. However, older adults were more in-group focused than younger adults in choosing who to help, making larger donations to national over international charities and reporting increased in-group preferences. In-group preferences helped explain greater national over international donations. Results were robust to several control analyses and internal replication. Our findings have vital implications for predicting the social and economic impacts of aging populations, increasing compliance with public health measures and encouraging charitable donations.

Ageing is associated with disrupted reinforcement learning whilst learning to help others is preserved.

Reinforcement learning is a fundamental mechanism displayed by many species. However, adaptive behaviour depends not only on learning about actions and outcomes that affect ourselves, but also those that affect others. Using computational reinforcement learning models, we tested whether young (age 18-36) and older (age 60-80, total n = 152) adults learn to gain rewards for themselves, another person (prosocial), or neither individual (control). Detailed model comparison showed that a model with separate learning rates for each recipient best explained behaviour. Young adults learned faster when their actions benefitted themselves, compared to others. Compared to young adults, older adults showed reduced self-relevant learning rates but preserved prosocial learning. Moreover, levels of subclinical self-reported psychopathic traits (including lack of concern for others) were lower in older adults and the core affective-interpersonal component of this measure negatively correlated with prosocial learning. These findings suggest learning to benefit others is preserved across the lifespan with implications for reinforcement learning and theories of healthy ageing.

Selective effects of serotonin on choices to gather more information.

BACKGROUND: Gathering and evaluating information leads to better decisions, but often at cost. The balance between information seeking and exploitation features in neurodevelopmental, mood, psychotic and substance-related disorders. Serotonin's role has been highlighted by experimental reduction of its precursor, tryptophan. AIMS: We tested the boundaries and applicability of this role by asking whether changes to information sampling would be observed following acute doses of serotonergic and catecholaminergic clinical treatments. We used a variant of the Information Sampling Task (IST) to measure how much information a person requires before they make a decision. This task allows participants to sample information until satisfied to make a choice. METHODS: In separate double-blind placebo-controlled experiments, we tested 27 healthy participants on/off 20 mg of the serotonin reuptake inhibitor (SRI) citalopram, and 22 participants on/off 40 mg of the noradrenergic reuptake inhibitor atomoxetine. The IST variant minimised effects of temporal impulsivity and loss aversion. Analyses used a variety of participant prior expectations of sampling spaces in the IST, including a new prior that accounts for learning of likely states across trials. We analysed behaviour by a new method that also accounts for baseline individual differences of risk preference. RESULTS: Baseline preferences demonstrated risk aversion. Citalopram decreased the expected utility of choices and probability of being correct based on informational content of samples collected, suggesting participants collected less useful information before making a choice. Atomoxetine did not influence information seeking. CONCLUSION: Acute changes of serotonin activity by way of a single SRI dose alter information-seeking behaviour.

Resilience during uncertainty? Greater social connectedness during COVID-19 lockdown is associated with reduced distress and fatigue.

BACKGROUND: Social connections are crucial for our health and well-being. This is especially true during times of high uncertainty and distress, such as during the COVID-19 lockdown. This period was characterized by unprecedented physical distancing (often communicated as social distancing) measures resulting in significant changes to people's usual social lives. Given the potential effects of this disruption on people's well-being, it is crucial to identify factors which are associated with negative health outcomes, and conversely, those that promote resilience during times of adversity. AIMS: We examined the relationship between individuals' levels of social connectedness during lockdown and self-reported stress, worry, and fatigue. METHOD: Survey data were collected from 981 individuals in a representative sample of Austrian citizens. Data collection occurred during the last week of a six-week nationwide lockdown due to the COVID-19 pandemic. The final sample consisted of 902 participants. Participants were asked to complete validated questionnaires to assess levels of social connectedness as well as measures of perceived stress, worry-both general and COVID-19 specific-and symptoms of fatigue during the previous two weeks. RESULTS: Our results demonstrate that greater social connectedness during the lockdown period was associated with lower levels of perceived stress, as well as general and COVID-19-specific worries. Furthermore, we found a negative relationship between fatigue and social connectedness, which was mediated by feelings of stress, general worries, and COVID-19-specific worries-respectively, indicating that individuals with smaller network sizes, who were highly distressed during the pandemic, were also likely to report feeling more fatigued. CONCLUSION: Our findings highlight the important role that social connections play in promoting resilience by buffering against negative physical and mental health outcomes, particularly in times of adversity in times of adversity.