Necessary, yet dissociable contributions of the insular and ventromedial prefrontal cortices to norm adaptation: computational and lesion evidence in humans

Late Acute Stress Effects on Decision-Making: The Magnified Attraction to Immediate Gains in the Iowa Gambling Task

Previous literature indicates that the later phases of the acute stress response may promote poor decision-making, characterized by riskier choices and a likely inclination towards immediate reward-seeking. However, all studies addressing the effect of this phase have treated decisional capacity as a singular dimension, without analyzing the underlying processes under decision making. Employing the Value-Plus-Perseveration (VPP) RL model, based on Bayesian logic, this study aims to gain specific insights into how late phase of acute stress impacts the cognitive processes underpinning decision-making in the Iowa Gambling Task (IGT), deciphering whether, as expected, gains are processed in a magnified manner. Seventy-three participants were randomly assigned to two groups, stress (N = 35) and control (N = 38). A virtual version of The Trier Social Stress Test (TSST-VR) was employed as a laboratory stressor. Decision-making was evaluated 35minutes after the stressor onset, by means of the IGT. Results showed that stressed participants, in comparison to control group, displayed more perseverant and consistent decision-making, enhanced memory, and reinforcement learning capabilities, yet were guided by a greater attraction to decks offering immediate high gains. These results are analyzed with the understanding that in the IGT, short-term decisions focused on instant rewards are seen as counterproductive. This suggests that stress could limit the ability to switch to strategies that are more cautious and offer greater long-term benefits.

Revisiting the role of computational neuroimaging in the era of integrative neuroscience

Computational models have become integral to human neuroimaging research, providing both mechanistic insights and predictive tools for human cognition and behavior. However, concerns persist regarding the ecological validity of lab-based neuroimaging studies and whether their spatiotemporal resolution is not sufficient for capturing neural dynamics. This review aims to re-examine the utility of computational neuroimaging, particularly in light of the growing prominence of alternative neuroscientific methods and the growing emphasis on more naturalistic behaviors and paradigms. Specifically, we will explore how computational modeling can both enhance the analysis of high-dimensional imaging datasets and, conversely, how neuroimaging, in conjunction with other data modalities, can inform computational models through the lens of neurobiological plausibility. Collectively, this evidence suggests that neuroimaging remains critical for human neuroscience research, and when enhanced by computational models, imaging can serve an important role in bridging levels of analysis and understanding. We conclude by proposing key directions for future research, emphasizing the development of standardized paradigms and the integrative use of computational modeling across neuroimaging techniques.

Aberrant neural computation of social controllability in nicotine-dependent humans

Social controllability, or the ability to exert control during social interactions, is crucial for optimal decision-making. Inability to do so might contribute to maladaptive behaviors such as smoking, which often takes place in social settings. Here, we examined social controllability in nicotine-dependent humans as they performed an fMRI task where they could influence the offers made by simulated partners. Computational modeling revealed that smokers under-estimated the influence of their actions and self-reported a reduced sense of control, compared to non-smokers. These findings were replicated in a large independent sample of participants recruited online. Neurally, smokers showed reduced tracking of forward projected choice values in the ventromedial prefrontal cortex, and impaired computation of social prediction errors in the midbrain. These results demonstrate that smokers were less accurate in estimating their personal influence when the social environment calls for control, providing a neurocomputational account for the social cognitive deficits in this population. Pre-registrations: OSF Registries|How interoceptive state interacts with value-based decision-making in addiction (fMRI study). OSF Registries|COVID-19: social cognition, mental health, and social distancing (online study).

Highly logical and non-emotional decisions in both risky and social contexts: understanding decision making in autism spectrum disorder through computational modeling

In risky contexts, autism spectrum disorder (ASD) individuals exhibit more logical consistency and non-emotional decisions than do typical adults (TAs). This way of deciding could be also prevailing in social contexts, leading to maladaptive decisions. This evidence is scarce and inconsistent, and further research is needed. Recent developments in computational modeling allow analysis of decisional subcomponents that could provide valuable information to understand the decision-making and help address inconsistencies. Twenty-seven individuals with ASD and 25 TAs were submitted to a framing-task and the ultimatum game (UG). The Rescorla-Wagner computational model was used to analyze UG decisions. Results showed that in the UG, the ASD group exhibited a higher utilitarianism, characterized by lower aversion to unfairness and higher acceptance of offers. Moreover, this way of deciding was predicted by the higher economic rationality found in the framing task, where people with ASD did not manifest emotional biases such as framing effect. These results could suggest an atypical decision making, highly logical and non-emotional, as a robust feature of ASD.

The neurocomputational signature of decision-making for unfair offers in females under acute psychological stress

Stress is a crucial factor affecting social decision-making. However, its impacts on the behavioral and neural processes of females' unfairness decision-making remain unclear. Combining computational modeling and functional near-infrared spectroscopy (fNIRS), this study attempted to illuminate the neurocomputational signature of unfairness decision-making in females. We also considered the effect of trait stress coping styles. Forty-four healthy young females (20.98 ± 2.89 years) were randomly assigned to the stress group (n = 21) and the control group (n = 23). Acute psychosocial stress was induced by the Trier Social Stress Test (TSST), and participants then completed the one-shot ultimatum game (UG) as responders. The results showed that acute psychosocial stress reduced the adaptability to fairness and lead to more random decision-making responses. Moreover, in the stress group, a high level of negative coping style predicted more deterministic decision. fNIRS results showed that stress led to an increase of oxy-hemoglobin (HbO) peak in the right temporoparietal junction (rTPJ), while decreased the activation of left middle temporal gyrus (lMTG) when presented the moderately unfair (MU) offers. This signified more involvement of the mentalization and the inhibition of moral processing. Moreover, individuals with higher negative coping scores showed more deterministic decision behaviors under stress. Taken together, our study emphasizes the role of acute psychosocial stress in affecting females' unfairness decision-making mechanisms in social interactions, and provides evidences for the "tend and befriend" pattern based on a cognitive neuroscience perspec.

Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchange

Dopamine and serotonin are hypothesized to guide social behaviours. In humans, however, we have not yet been able to study neuromodulator dynamics as social interaction unfolds. Here, we obtained subsecond estimates of dopamine and serotonin from human substantia nigra pars reticulata during the ultimatum game. Participants, who were patients with Parkinson's disease undergoing awake brain surgery, had to accept or reject monetary offers of varying fairness from human and computer players. They rejected more offers in the human than the computer condition, an effect of social context associated with higher overall levels of dopamine but not serotonin. Regardless of the social context, relative changes in dopamine tracked trial-by-trial changes in offer value-akin to reward prediction errors-whereas serotonin tracked the current offer value. These results show that dopamine and serotonin fluctuations in one of the basal ganglia's main output structures reflect distinct social context and value signals.

Diminished Adaptation, Satisfaction, and Neural Responses to Advantageous Social Signals in Anorexia Nervosa and Bulimia Nervosa

BACKGROUND

Development and recurrence of 2 eating disorders (EDs), anorexia nervosa and bulimia nervosa, are frequently associated with environmental stressors. Neurobehavioral responses to social learning signals were evaluated in both EDs.

METHODS

Women with anorexia nervosa (n = 25), women with bulimia nervosa (n = 30), or healthy comparison women (n = 38) played a neuroeconomic game in which the norm shifted, generating social learning signals (norm prediction errors [NPEs]) during a functional magnetic resonance imaging scan. A Bayesian logistic regression model examined how the probability of offer acceptance depended on cohort, block, and NPEs. Rejection rates, emotion ratings, and neural responses to NPEs were compared across groups.

RESULTS

Relative to the comparison group, both ED cohorts showed less adaptation (p = .028, ηp2 = 0.060), and advantageous signals (positive NPEs) led to higher rejection rates (p = .014, ηp2 = 0.077) and less positive emotion ratings (p = .004, ηp2 = 0.111). Advantageous signals increased neural activations in the orbitofrontal cortex for the comparison group but not for women with anorexia nervosa (p = .018, d = 0.655) or bulimia nervosa (p = .043, d = 0.527). More severe ED symptoms were associated with decreased activation of dorsomedial prefrontal cortex for advantageous signals.

CONCLUSIONS

Diminished neural processing of advantageous social signals and impaired norm adaptation were observed in both anorexia nervosa and bulimia nervosa, while no differences were found for disadvantageous social signals. Development of neurocognitive interventions to increase responsivity to advantageous social signals could augment current treatments, potentially leading to improved clinical outcomes for EDs.

The effects of awe on interpersonal forgiveness: the mediating role of small-self

Awe could increase prosocial behavior, but little is known about its effects on interpersonal forgiveness. This study aims to explore the potential impact of awe on interpersonal forgiveness and the underlying mechanism of this process, using a combination of questionnaires, economic game and computational modeling. In Study 1, we utilized Trait Awe Scale (TAS) and Forgiveness Trait Scale (FTS) to examine the association between trait awe and trait forgiveness. In Study 2, we employed pre-screened video to induce awe, happy and neutral emotions, then evaluated the effects of induced awe on small-self and interpersonal forgiveness in hypothetical interpersonal offensive situations (Study 2a) and two economic interaction situations (Study 2b). Results from Study 1 indicate that there is a positive correlation between trait awe and trait forgiveness. Study 2 reveal that awe can enhance interpersonal forgiveness in both interpersonal conflict situations and economic interaction situations, and this effect is mediated by the sense of small-self elicited by awe. Overall, these findings contribute to our understanding of the potential impact of awe on interpersonal forgiveness and provide valuable insights into the mechanisms through which awe may influence forgiveness. Further research in this area could help to elucidate the potential applications of awe-based interventions in promoting forgiveness and positive social interactions.

Aberrant neural computation of social controllability in nicotine-dependent humans

Social controllability, defined as the ability to exert influence when interacting with others, is crucial for optimal decision-making. Inability to do so might contribute to maladaptive behaviors such as drug use, which often takes place in social settings. Here, we examined nicotine-dependent humans using fMRI, as they made choices that could influence the proposals from simulated partners. Computational modeling revealed that smokers under-estimated the influence of their actions and self-reported a reduced sense of control, compared to non-smokers. These findings were replicated in a large independent sample of participants recruited online. Neurally, smokers showed reduced tracking of forward projected choice values in the ventromedial prefrontal cortex, and impaired computation of social prediction errors in the midbrain. These results demonstrate that smokers were less accurate in estimating their personal influence when the social environment calls for control, providing a neurocomputational account for the social cognitive deficits in this population.

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.

Connecting Circuits with Networks in Addiction Neuroscience: A Salience Network Perspective

Human neuroimaging has demonstrated the existence of large-scale functional networks in the cerebral cortex consisting of topographically distant brain regions with functionally correlated activity. The salience network (SN), which is involved in detecting salient stimuli and mediating inter-network communication, is a crucial functional network that is disrupted in addiction. Individuals with addiction display dysfunctional structural and functional connectivity of the SN. Furthermore, while there is a growing body of evidence regarding the SN, addiction, and the relationship between the two, there are still many unknowns, and there are fundamental limitations to human neuroimaging studies. At the same time, advances in molecular and systems neuroscience techniques allow researchers to manipulate neural circuits in nonhuman animals with increasing precision. Here, we describe attempts to translate human functional networks to nonhuman animals to uncover circuit-level mechanisms. To do this, we review the structural and functional connections of the salience network and its homology across species. We then describe the existing literature in which circuit-specific perturbation of the SN sheds light on how functional cortical networks operate, both within and outside the context of addiction. Finally, we highlight key outstanding opportunities for mechanistic studies of the SN.

Logical decisions after a psychosocial stressor: The late phase of acute stress reduces loss aversion

Loss aversion, the principle that losses have a greater impact on decision-making than gains, can be modulated by stress. Most findings reported that stress reduces loss aversion, in line with the alignment hypothesis. Yet, decision-making was always assessed at the early stages of the stress response. Instead, the latter phase of the stress response enhances the salience-network and then, it could amplify the salience of losses, thereby increasing loss aversion. To our knowledge, it has never been studied how the latter stress response influences loss aversion and our aim is to fill this gap. 92 participants were divided into experimental and control group. The first one was exposed to the Trier Social Stress Test, and controls viewed a match-length distractor video. Both groups performed a mixed gamble task to measure loss aversion through a Bayesian-computational model. During and after the stressor, experimental group exhibited signs of both physiological and psychological stress which indicated that stress induction was effective. However, rather than increasing, loss aversion of stressed participants was lower. These results constitute a new evidence of stress influencing loss aversion and are discussed within the alignment hypothesis, according to which stress aligns sensitivity to gains and losses.

Later stages of acute stress impair reinforcement-learning and feedback sensitivity in decision making

Whereas the effects of the early stages of acute stress seem to improve learning and increase loss aversion in decision making, in later stages, the opposite has been found, an impairment in decision making probably due to higher reward-attraction, as the STARS approach suggests. This study aims to investigate the effects of the later stages of acute stress on decision making and its underlying processes using a computational model. We hypothesized that stress would affect underlying cognitive strategies during decision making. Ninety-five participants were randomly distributed into two groups, experimental (N = 46) and control (N = 49). A virtual version of The Trier Social Stress Test (TSST) was used as a laboratory stressor. After 20minutes, decision making was assessed by using the Iowa Gambling Task (IGT). The Value-Plus-Preservation (VPP) RL computational model was used to extract decision-making components. As expected, the stressed participants showed deficits in IGT performance on reinforcement-learning and feedback sensitivity. However, there was no gains attraction. These results are discussed by considering that decision making in later stages of acute stress could be based on impairments in prefrontal cortex functioning.

Towards a neurocomputational account of social controllability: From models to mental health

Controllability, or the influence one has over their surroundings, is crucial for decision-making and mental health. Traditionally, controllability is operationalized in sensorimotor terms as one's ability to exercise their actions to achieve an intended outcome (also termed "agency"). However, recent social neuroscience research suggests that humans also assess if and how they can exert influence over other people (i.e., their actions, outcomes, beliefs) to achieve desired outcomes ("social controllability"). In this review, we will synthesize empirical findings and neurocomputational frameworks related to social controllability. We first introduce the concepts of contextual and perceived controllability and their respective relevance for decision-making. Then, we outline neurocomputational frameworks that can be used to model social controllability, with a focus on behavioral economic paradigms and reinforcement learning approaches. Finally, we discuss the implications of social controllability for computational psychiatry research, using delusion and obsession-compulsion as examples. Taken together, we propose that social controllability could be a key area of investigation in future social neuroscience and computational psychiatry research.

Invasive Computational Psychiatry

Computational psychiatry, a relatively new yet prolific field that aims to understand psychiatric disorders with formal theories about the brain, has seen tremendous growth in the past decade. Despite initial excitement, actual progress made by computational psychiatry seems stagnant. Meanwhile, understanding of the human brain has benefited tremendously from recent progress in intracranial neuroscience. Specifically, invasive techniques such as stereotactic electroencephalography, electrocorticography, and deep brain stimulation have provided a unique opportunity to precisely measure and causally modulate neurophysiological activity in the living human brain. In this review, we summarize progress and drawbacks in both computational psychiatry and invasive electrophysiology and propose that their combination presents a highly promising new direction-invasive computational psychiatry. The value of this approach is at least twofold. First, it advances our mechanistic understanding of the neural computations of mental states by providing a spatiotemporally precise depiction of neural activity that is traditionally unattainable using noninvasive techniques with human subjects. Second, it offers a direct and immediate way to modulate brain states through stimulation of algorithmically defined neural regions and circuits (i.e., algorithmic targeting), thus providing both causal and therapeutic insights. We then present depression as a use case where the combination of computational and invasive approaches has already shown initial success. We conclude by outlining future directions as a road map for this exciting new field as well as presenting cautions about issues such as ethical concerns and generalizability of findings.

People conform to social norms when gambling with lives or money

Many consider moral decisions to follow an internal "moral compass", resistant to social pressures. Here we examine how social influence shapes moral decisions under risk, and how it operates in different decision contexts. We employed an adapted Asian Disease Paradigm where participants chose between certain losses/gains and probabilistic losses/gains in a series of moral (lives) or financial (money) decisions. We assessed participants' own risk preferences before and after exposing them to social norms that are generally risk-averse or risk-seeking. Our results showed that participants robustly shifted their own choices towards the observed risk preferences. This conformity holds even after a re-testing in three days. Interestingly, in the monetary domain, risk-averse norms have more influence on choices in the loss frame, whereas risk-seeking norms have more influence in the gain frame, presumably because norms that contradict default behavior are most informative. In the moral domain, risk-averse as opposed to risk-seeking norms are more effective in the loss frame but in the gain frame different norms are equally effective. Taken together, our results demonstrate conformity in risk preferences across contexts and highlight unique features of decisions and conformity in moral and monetary domains.

How do children adapt their fairness norm? Evidence from computational modeling

Adequate social functioning during childhood requires context-appropriate social decision-making. To make such decisions, children rely on their social norms, conceptualized as cognitive models of shared expectations. Since social norms are dynamic, children must adapt their models of shared expectations and modify their behavior in line with their social environment. This study aimed to investigate children's abilities to use social information to adapt their fairness norm and to identify the computational mechanism governing this process. Thirty children (7-11 years, M = 7.9 SD = 0.85, 11 girls) played the role of Responder in a modified version of the Ultimatum Game-a two-player game based on the fairness norm-in which they had to choose to accept or reject offers from different Proposers. Norm adaptation was assessed by comparing rejection rates before and after a conditioning block in which children received several low offers. Computational models were compared to test which best explains children's behavior during the game. Mean rejection rate decreased significantly after receiving several low offers suggesting that children have the ability to dynamically update their fairness norm and adapt to changing social environments. Model-based analyses suggest that this process involves the computation of norm-prediction errors. This is the first study on norm adaptation capacities in school-aged children that uses a computational approach. Children use implicit social information to adapt their fairness norm to changing environments and this process appears to be supported by a computational mechanism in which norm-prediction errors are used to update norms.

Stressed individuals exhibit pessimistic bursting beliefs and a lower risk preference in the balloon analogue risk task

Stress alters decision-making by usually promoting risk-taking and reward-seeking, which could be advantageous in a context where risk is rewarded, such as the Balloon Analogue Risk Task (BART). However, previous studies addressing this issue showed inconsistencies which could emerge from assessing decision-making as a single dimension. Our aim is to study through computational modelling how stress influences cognitive subprocesses of the decision-making during the BART. For this purpose, 94 healthy participants were submitted to BART, but only half were exposed to the virtual Trier Social Stress Test (TSST-VR). The Experimental-Weight Mean-Variance (EWMV) model was used to gain insight into the subprocesses involved in risk-taking during BART. Rather than reward-seeking, our results showed a pessimistic prior belief about the balloons bursting likelihood, and a lower risk preference in the stressed participants. This cautious attitude could be attributable to an alertness state promoted by stress. Yet, since risk is rewarded in BART, it could also evidence a maladaptive decision-making derived from learning difficulties and altered feedback-processing under stress.

Computational mechanisms underlying illusion of control in delusional individuals

Humans navigate complex situations that require the accurate estimation of the controllability of the environment. Aberrant controllability computation might lead to maladaptive behaviors and poor mental health outcomes. Illusion of control, which refers to a heightened sense of control while the environment is uncontrollable, is one such manifestation and has been conceptually associated with delusional ideation. Nevertheless, this association has not yet been formally characterized in a computational framework. To address this, we used a computational psychiatry approach to quantify illusion of control in human participants with high (n = 125) or low (n = 126) trait delusion. Participants played a two-party exchange game in which their choices either did ("Controllable condition") or did not ("Uncontrollable condition") influence the future monetary offers made by simulated partners. We found that the two groups behaved similarly in model-agnostic measures (i.e., offer size, rejection rate). However, computational modeling revealed that compared to the low trait delusion group, the high delusion group overestimated their influence ("expected influence" parameter) over the offers made by their partners under the Uncontrollable condition. Highly delusional individuals also reported a stronger sense of control than those with low trait delusion in the Uncontrollable condition. Furthermore, the expected influence parameter and self-reported beliefs about controllability were significantly correlated in the Controllable condition in individuals with low trait delusion, whereas this relationship was diminished in those with high trait delusion. Collectively, these findings demonstrate that delusional ideation is associated with aberrant computation of and belief about environmental controllability, as well as a belief-behavior disconnect.

Characterization of the Core Determinants of Social Influence From a Computational and Cognitive Perspective

Most human decisions are made among social others, and in what social context the choices are made is known to influence individuals' decisions. Social influence has been noted as an important factor that may nudge individuals to take more risks (e.g., initiation of substance use), but ironically also help individuals to take safer actions (e.g., successful abstinence). Such bi-directional impacts of social influence hint at the complexity of social information processing. Here, we first review the recent computational approaches that shed light on neural and behavioral mechanisms underlying social influence following basic computations involved in decision-making: valuation, action selection, and learning. We next review the studies on social influence from various fields including neuroeconomics, developmental psychology, social psychology, and cognitive neuroscience, and highlight three dimensions of determinants-who are the recipients, how the social contexts are presented, and to what domains and processes of decisions the influence is applied-that modulate the extent to which individuals are influenced by others. Throughout the review, we also introduce the brain regions that were suggested as neural instantiations of social influence from a large body of functional neuroimaging studies. Finally, we outline the remaining questions to be addressed in the translational application of computational and cognitive theories of social influence to psychopathology and health.

Similar network compositions, but distinct neural dynamics underlying belief updating in environments with and without explicit outcomes

Classic decision theories typically assume the presence of explicit value-based outcomes after action selections to update beliefs about action-outcome contingencies. However, ecological environments are often opaque, and it remains unclear whether the neural dynamics underlying belief updating vary under conditions characterized by the presence or absence of such explicit value-based information, after each choice selection. We investigated this question in healthy humans (n = 28) using Bayesian inference and two multi-option fMRI tasks: a multi-armed bandit task, and a probabilistic perceptual task, respectively with and without explicit value-based feedback after choice selections. Model-based fMRI analysis revealed a network encoding belief updating which did not change depending on the task. More precisely, we found a confidence-building network that included anterior hippocampus, amygdala, and medial prefrontal cortex (mPFC), which became more active as beliefs about action-outcome probabilities were confirmed by newly acquired information. Despite these consistent responses across tasks, dynamic causal modeling estimated that the network dynamics changed depending on the presence or absence of trial-by-trial value-based outcomes. In the task deprived of immediate feedback, the hippocampus increased its influence towards both amygdala and mPFC, in association with increased strength in the confidence signal. However, the opposite causal relations were found (i.e., from both mPFC and amygdala towards the hippocampus), in presence of immediate outcomes. This finding revealed an asymmetric relationship between decision confidence computations, which were based on similar computational models across tasks, and neural implementation, which varied depending on the availability of outcomes after choice selections.

Neurocomputational mechanisms engaged in moral choices and moral learning

The neural circuitry involved in moral decisions has been studied since the early days of cognitive neuroscience, mainly using moral dilemma. However, the neurocomputational mechanisms describing how the human brain makes moral decisions and learns in various moral contexts are only starting to be established. Here we review recent results from an emerging field using model-based fMRI, which describes moral choices at a mechanistic level. These findings unify the field of moral decision making, extend a conceptual framework previously developed for value-based decision making and characterize how moral processes are computed in the brain. Moral dilemma can be modeled as value-based decisions that weigh self-interests against moral costs/harm to others and different types of prediction errors can be distinguished in different aspects of moral learning. These key computational signals help to describe moral choices and moral learning at an algorithmic level and to reveal how these cognitive operations are implemented in the brain. This researches provide a foundation to account for the neurocomputational mechanisms underlying moral decision making.

Humans use forward thinking to exploit social controllability

The controllability of our social environment has a profound impact on our behavior and mental health. Nevertheless, neurocomputational mechanisms underlying social controllability remain elusive. Here, 48 participants performed a task where their current choices either did (Controllable), or did not (Uncontrollable), influence partners’ future proposals. Computational modeling revealed that people engaged a mental model of forward thinking (FT; i.e., calculating the downstream effects of current actions) to estimate social controllability in both Controllable and Uncontrollable conditions. A large-scale online replication study (n=1342) supported this finding. Using functional magnetic resonance imaging (n=48), we further demonstrated that the ventromedial prefrontal cortex (vmPFC) computed the projected total values of current actions during forward planning, supporting the neural realization of the forward-thinking model. These findings demonstrate that humans use vmPFC-dependent FT to estimate and exploit social controllability, expanding the role of this neurocomputational mechanism beyond spatial and cognitive contexts.

Hippocampal contributions to social and cognitive deficits in autism spectrum disorder

Autism spectrum disorder (ASD) is characterized by hallmark impairments in social functioning. Nevertheless, nonsocial cognition, including hippocampus-dependent spatial reasoning and episodic memory, is also commonly impaired in ASD. ASD symptoms typically emerge between 12 and 24 months of age, a time window associated with critical developmental events in the hippocampus. Despite this temporal overlap and evidence of hippocampal structural abnormalities in ASD individuals, relatively few human studies have focused on hippocampal function in ASD. Herein, we review the existing evidence for the involvement of the hippocampus in ASD and highlight the hippocampus as a promising area of interest for future research in ASD.

Lesion Evidence for a Causal Role of the Insula in Aversion to Social Inequity

Humans resist unequal distributions of goods in their social interactions, even if it requires foregoing personal gains. Functional neuroimaging studies implicate the insula in this aversion to social inequity and in fairness-related decisions, but a causal contribution has not yet been established. We compared the responses of 30 patients with lesions to the insula on a multiple-trial version of the one-shot Ultimatum Game, a neuroeconomic social exchange paradigm where a sum of money is split between two players, to those of 30 matched patients with brain injuries sparing the insula. Insula lesion patients accepted offers of an unequal disadvantageous split significantly more often than comparison lesion patients. Computational modeling confirmed that this difference in choice behavior was due to decreased aversion to disadvantageous inequity following insula damage, rather than due to increased decision noise or non-consideration of inequity. Our results provide novel evidence that the insula is causally involved in aversion to inequity and in value-based choices in the context of social interactions.

Arbitration between insula and temporoparietal junction subserves framing-induced boosts in generosity during social discounting

Generosity toward others declines across the perceived social distance to them. Here, participants chose between selfish and costly generous options in two conditions: in the gain frame, a generous choice yielded a gain to the other; in the loss frame, it entailed preventing the loss of a previous endowment to the other. Social discounting was reduced in the loss compared to the gain frame, implying increased generosity toward strangers. Using neuroimaging tools, we found that while activity in the temporoparietal junction (TPJ) and the ventromedial prefrontal cortex (VMPFC) was associated with generosity in the gain frame, the insular cortex was selectively recruited during generous choices in the loss frame. We provide support for a network-model according to which TPJ and insula differentially subserve generosity by modulating value signals in the VMPFC in a frame-dependent fashion. These results extend our understanding of the insula role in nudging prosocial behavior in humans.

An insula-driven network computes decision uncertainty and promotes abstinence in chronic cocaine users

The anterior insular cortex (AIC) and its interconnected brain regions have been associated with both addiction and decision-making under uncertainty. However, the causal interactions in this uncertainty-encoding neurocircuitry and how these neural dynamics impact relapse remain elusive. Here, we used model-based fMRI to measure choice uncertainty in a motor decision task in 61 individuals with cocaine use disorder (CUD) and 25 healthy controls. CUD participants were assessed before discharge from a residential treatment program and followed for up to 24 weeks. We found that choice uncertainty was tracked by the AIC, dorsal anterior cingulate cortex (dACC) and ventral striatum (VS), across participants. Stronger activations in these regions measured pre-discharge predicted longer abstinence after discharge in individuals with CUD. Dynamic causal modeling revealed an AIC-to-dACC-directed connectivity modulated by uncertainty in controls, but a dACC-to-AIC connectivity in CUD participants. This reversal was mostly driven by early relapsers (<30 days). Furthermore, CUD individuals who displayed a stronger AIC-to-dACC excitatory connection during uncertainty encoding remained abstinent for longer periods. These findings reveal a critical role of an AIC-driven, uncertainty-encoding neurocircuitry in protecting against relapse and promoting abstinence.

A Value-Based Framework for Understanding Cooperation

Understanding the roots of human cooperation, a social phenomenon embedded in pressing issues including climate change and social conflict, requires an interdisciplinary perspective. We propose a unifying value-based framework for understanding cooperation that integrates neuroeconomic models of decision-making with psychological variables involved in cooperation. We propose that the ventromedial prefrontal cortex serves as a neural integration hub for value computation during cooperative decisions, receiving inputs from various neurocognitive processes such as attention, memory, and learning. Next, we describe findings from social and personality psychology highlighting factors that shape the value of cooperation, including research on contexts and norms, personal and social identity, and intergroup relations. Our approach advances theoretical debates about cooperation by highlighting how previous findings are accommodated within a general value-based framework and offers novel predictions.

Neuropsychiatric Effects on Decision-Making in Early Alzheimer Disease

BACKGROUND

Neuropsychiatric symptoms can impact decision-making in patients with Alzheimer disease (AD).

METHODS

Using a simple decision-making task, a variant of the ultimatum game (UG) modified to control feelings of unfairness, this study investigated rejection responses among responders to unfair offers. The UG was administered to 11 patients with AD, 10 comparably demented patients with behavioral variant frontotemporal dementia (bvFTD), and 9 healthy controls (HC). The results were further compared with differences on the caregiver Neuropsychiatric Inventory (NPI).

RESULTS

Overall, patients with AD significantly rejected more total offers than did the patients with bvFTD and the HC (P < .01). On the NPI, the only domain that was significantly worse among the patients with AD compared to the other groups was dysphoria/depression.

CONCLUSIONS

These results suggest that early AD can be distinguished based on increased rejections of offers in decision-making, possibly consequent to a heightened sense of unfairness from dysphoria/depression.

Beyond a rod through the skull: A systematic review of lesion studies of the human ventromedial frontal lobe

Neuropsychological studies from the past century have associated damage to the ventromedial frontal lobes (VMF) with impairments in a variety of domains, including memory, executive function, emotion, social cognition, and valuation. A central question in the literature is whether these seemingly distinct functions are subserved by different sub-regions within the VMF, or whether VMF supports a broader cognitive process that is crucial to these varied domains. In this comprehensive review of the neuropsychological literature from the last two decades, we present a qualitative synthesis of 184 papers that have examined the psychological impairments that result from VMF damage. We discuss these findings in the context of several theoretical frameworks and advocate for the view that VMF is critical for the formation and representation of schema and cognitive maps.

Intranasal oxytocin reduces reactive aggression in men but not in women: A computational approach

Aggression is an important behaviour that concerns individual survival and large-scale social stability. It comprises a variety of psychological subcomponents and is modulated by different biological factors. Two factors in particular, gender and oxytocin, appear to play a robust role in aggressive behaviour. However, whether these two factors interact to impact aggressive behaviour is not currently known. The current study investigated the modulating effect of gender on the relationship between oxytocin and aggression and characterized its underlying mechanisms by combining behavioural economic, pharmacological, and computational approaches. Specifically, we employed a double-blind, randomized, placebo-controlled, between-subjects design, in which one hundred participants (50 men and 50 women) completed a norm-training version of the multi-round one-shot ultimatum game (UG) after intranasal oxytocin or placebo administration. Rejection rates in the UG were adopted as an indicator of reactive aggression. The results indicated that oxytocin compared with placebo administration decreased aggression among men but not among women. Further analyses suggested that this decrease in aggression was a result of changes in men's sensitivity to provocation and positive affect, rather than norm adaptation rates or concerns about the cost of aggression. These findings highlight the role of gender in the relationship between oxytocin and reactive aggression and reveal its underlying psychological and computational mechanisms.

Born for fairness: evidence of genetic contribution to a neural basis of fairness intuition

Human beings often curb self-interest to develop and enforce social norms, such as fairness, as exemplified in the ultimatum game (UG). Inspired by the dual-system account for the responder's choice during the UG, we investigated whether the neural basis of psychological process induced by fairness is under genetic control using a twin fMRI study (62 monozygotic, 48 dizygotic; mean age: 19.32 ± 1.38 years). We found a moderate genetic contribution to the rejection rate of unfair proposals (24%-35%), independent of stake size or proposer type, during the UG. Using a voxel-level analysis, we found that genetic factors moderately contributed to unfairness-evoked activation in the bilateral anterior insula (AI), regions representing the intuition of fairness norm violations (mean heritability: left 37%, right 40%). No genetic contributions were found in regions related to deliberate, controlled processes in the UG. This study provides the first evidence that evoked brain activity by unfairness in the bilateral AI is influenced by genes and sheds light on the genetic basis of brain processes underlying costly punishment.

Dissociation between Private and Social Counterfactual Value Signals Following Ventromedial Prefrontal Cortex Damage

Individuals learn by comparing the outcome of chosen and unchosen actions. A negative counterfactual value signal is generated when this comparison is unfavorable. This can happen in private as well as in social settings—where the foregone outcome results from the choice of another person. We hypothesized that, despite sharing similar features such as supporting learning, these two counterfactual signals might implicate distinct brain networks. We conducted a neuropsychological study on the role of private and social counterfactual value signals in risky decision-making. Patients with lesions in the ventromedial prefrontal cortex (vmPFC), lesion controls, and healthy controls repeatedly chose between lotteries. In private trials, participants could observe the outcomes of their choices and the outcomes of the unselected lotteries. In social trials, participants could also see the other player's choices and outcome. At the time of outcome, vmPFC patients were insensitive to private counterfactual value signals, whereas their responses to social comparison were similar to those of control participants. At the time of choice, intact vmPFC was necessary to integrate counterfactual signals in decisions, although amelioration was observed during the course of the task, possibly driven by social trials. We conclude that if the vmPFC is critical in processing private counterfactual signals and in integrating those signals in decision-making, then distinct brain areas might support the processing of social counterfactual signals.

Computing Social Value Conversion in the Human Brain

Social signals play powerful roles in shaping self-oriented reward valuation and decision making. These signals activate social and valuation/decision areas, but the core computation for their integration into the self-oriented decision machinery remains unclear. Here, we study how a fundamental social signal, social value (others' reward value), is converted into self-oriented decision making in the human brain. Using behavioral analysis, modeling, and neuroimaging, we show three-stage processing of social value conversion from the offer to the effective value and then to the final decision value. First, a value of others' bonus on offer, called offered value, was encoded uniquely in the right temporoparietal junction (rTPJ) and also in the left dorsolateral prefrontal cortex (ldlPFC), which is commonly activated by offered self-bonus value. The effective value, an intermediate value representing the effective influence of the offer on the decision, was represented in the right anterior insula (rAI), and the final decision value was encoded in the medial prefrontal cortex (mPFC). Second, using psychophysiological interaction and dynamic causal modeling analyses, we demonstrated three-stage feedforward processing from the rTPJ and ldPFC to the rAI and then from rAI to the mPFC. Further, we showed that these characteristics of social conversion underlie distinct sociobehavioral phenotypes. We demonstrate that the variability in the conversion underlies the difference between prosocial and selfish subjects, as seen from the differential strength of the rAI and ldlPFC coupling to the mPFC responses, respectively. Together, these findings identified fundamental neural computation processes for social value conversion underlying complex social decision making behaviors.SIGNIFICANCE STATEMENT In daily life, we make decisions based on self-interest, but also in consideration for others' status. These social influences modulate valuation and decision signals in the brain, suggesting a fundamental process called value conversion that translates social information into self-referenced decisions. However, little is known about the conversion process and its underlying brain mechanisms. We investigated value conversion using human fMRI with computational modeling and found three essential stages in a progressive brain circuit from social to empathic and decision areas. Interestingly, the brain mechanism of conversion differed between prosocial and individualistic subjects. These findings reveal how the brain processes and merges social information into the elemental flow of self-interested decision making.

Anterior insular cortex plays a critical role in interoceptive attention

Accumulating evidence indicates that the anterior insular cortex (AIC) mediates interoceptive attention which refers to attention towards physiological signals arising from the body. However, the necessity of the AIC in this process has not been demonstrated. Using a novel task that directs attention toward breathing rhythm, we assessed the involvement of the AIC in interoceptive attention in healthy participants using functional magnetic resonance imaging and examined the necessity of the AIC in interoceptive attention in patients with AIC lesions. Results showed that interoceptive attention was associated with increased AIC activation, as well as enhanced coupling between the AIC and somatosensory areas along with reduced coupling between the AIC and visual sensory areas. In addition, AIC activation was predictive of individual differences in interoceptive accuracy. Importantly, AIC lesion patients showed disrupted interoceptive discrimination accuracy and sensitivity. These results provide compelling evidence that the AIC plays a critical role in interoceptive attention.

Patients with basal ganglia damage show preserved learning in an economic game

Both basal ganglia (BG) and orbitofrontal cortex (OFC) have been widely implicated in social and non-social decision-making. However, unlike OFC damage, BG pathology is not typically associated with disturbances in social functioning. Here we studied the behavior of patients with focal lesions to either BG or OFC in a multi-strategy competitive game known to engage these regions. We find that whereas OFC patients are significantly impaired, BG patients show intact learning in the economic game. By contrast, when information about the strategic context is absent, both cohorts are significantly impaired. Computational modeling further shows a preserved ability in BG patients to learn by anticipating and responding to the behavior of others using the strategic context. These results suggest that apparently divergent findings on BG contribution to social decision-making may instead reflect a model where higher-order learning processes are dissociable from trial-and-error learning, and can be preserved despite BG damage.

Neuroimaging evidence implicates basal ganglia (BG) in social decision-making, yet causal evidence remains lacking. Here, the authors show that learning in strategic (but not non-strategic) games is spared in patients with BG damage, suggesting social decision making is not fully reliant on the BG.

Early childhood investment impacts social decision-making four decades later

Early childhood educational investment produces positive effects on cognitive and non-cognitive skills, health, and socio-economic success. However, the effects of such interventions on social decision-making later in life are unknown. We recalled participants from one of the oldest randomized controlled studies of early childhood investment-the Abecedarian Project (ABC)-to participate in well-validated interactive economic games that probe social norm enforcement and planning. We show that in a repeated-play ultimatum game, ABC participants who received high-quality early interventions strongly reject unequal division of money across players (disadvantageous or advantageous) even at significant cost to themselves. Using a multi-round trust game and computational modeling of social exchange, we show that the same intervention participants also plan further into the future. These findings suggest that high quality early childhood investment can result in long-term changes in social decision-making and promote social norm enforcement in order to reap future benefits.

Distinguishing neural correlates of context-dependent advantageous- and disadvantageous-inequity aversion

Humans can integrate social contextual information into decision-making processes to adjust their responses toward inequity. This context dependency emerges when individuals receive more (i.e., advantageous inequity) or less (i.e., disadvantageous inequity) than others. However, it is not clear whether context-dependent processing of advantageous and disadvantageous inequity involves differential neurocognitive mechanisms. Here, we used fMRI to address this question by combining an interactive game that modulates social contexts (e.g., interpersonal guilt) with computational models that enable us to characterize individual weights on inequity aversion. In each round, the participant played a dot estimation task with an anonymous coplayer. The coplayer would receive pain stimulation with 50% probability when either of them responded incorrectly. At the end of each round, the participant completed a variant of dictator game, which determined payoffs for him/herself and the coplayer. Computational modeling demonstrated the context dependency of inequity aversion: when causing pain to the coplayer (i.e., guilt context), participants cared more about the advantageous inequity and became more tolerant of the disadvantageous inequity, compared with other conditions. Consistently, neuroimaging results suggested the two types of inequity were associated with differential neurocognitive substrates. While the context-dependent processing of advantageous inequity was associated with social- and mentalizing-related processes, involving left anterior insula, right dorsolateral prefrontal cortex, and dorsomedial prefrontal cortex, the context-dependent processing of disadvantageous inequity was primarily associated with emotion- and conflict-related processes, involving left posterior insula, right amygdala, and dorsal anterior cingulate cortex. These results extend our understanding of decision-making processes related to inequity aversion.

Klüver & Bucy syndrome: an investigation of social and affective cognition

Klüver-Bucy syndrome (KBS) leads to important behavioral symptoms and social maladaptation. Rarely described, no previous study has investigated its social and affective cognitive profile. We report the case of ASP, a patient who developed a complete KBS at 9 years that evolved into an incomplete KBS. Orbitofrontal and temporal damages were evidenced. While a classic neuropsychological assessment showed a preserved global functioning, an extensive evaluation of her social and affective cognition (reversal learning, decision-making, emotion recognition, theory of mind, creative thinking) showed remarkable deficits. The relevancy of such findings for the characterization KBS and the field of neuropsychology are discussed.

Not on my team: Medial prefrontal cortex responses to ingroup fusion and unfair monetary divisions

OBJECTIVE

People are highly attuned to fairness, with people willingly suffering personal costs to prevent others benefitting from unfair acts. Are fairness judgments influenced by group alignments? A new theory posits that we favor ingroups and denigrate members of rival outgroups when our personal identity is fused to a group. Although the mPFC has been separately implicated in group membership and fairness processing, it is unclear whether group alignments affect medial prefrontal cortex (mPFC) activity in response to fairness. Here, we examine the contribution of different regions of the mPFC to processing from ingroup and outgroup members and test whether its response differs depending on how fused we are to an ingroup.

METHODS

Subjects performed rounds of the Ultimatum Game, being offered fair or unfair divisions of money from supporters of the same soccer team (ingroup), the fiercest rival (outgroup) or neutral individuals whilst undergoing functional Magnetic Resonance Imaging (fMRI).

RESULTS

Strikingly, people willingly suffered personal costs to prevent outgroup members benefitting from both unfair and fair offers. Activity across dorsal and ventral (VMPFC) portions of the mPFC reflected an interaction between fairness and group membership. VMPFC activity in particular was consistent with it coding one's fusion to a group, with the fairness by group membership interaction correlating with the extent that the responder's identity was fused to the ingroup.

CONCLUSIONS

The influence of fusion on social behavior therefore seems to be linked to processing in the VMPFC.

A dual-fMRI investigation of the iterated Ultimatum Game reveals that reciprocal behaviour is associated with neural alignment

Dyadic interactions often involve a dynamic process of mutual reciprocity; to steer a series of exchanges towards a desired outcome, both interactants must adapt their own behaviour according to that of their interaction partner. Understanding the brain processes behind such bidirectional reciprocity is therefore central to social neuroscience, but this requires measurement of both individuals' brains during real-world exchanges. We achieved this by performing functional magnetic resonance imaging (fMRI) on pairs of male individuals simultaneously while they interacted in a modified iterated Ultimatum Game (iUG). In this modification, both players could express their intent and maximise their own monetary gain by reciprocating their partner's behaviour - they could promote generosity through cooperation and/or discourage unfair play with retaliation. By developing a novel model of reciprocity adapted from behavioural economics, we then show that each player's choices can be predicted accurately by estimating expected utility (EU) not only in terms of immediate payoff, but also as a reaction to their opponent's prior behaviour. Finally, for the first time we reveal that brain signals implicated in social decision making are modulated by these estimates of EU, and become correlated more strongly between interacting players who reciprocate one another.

Human substantia nigra and ventral tegmental area involvement in computing social error signals during the ultimatum game

As models of shared expectations, social norms play an essential role in our societies. Since our social environment is changing constantly, our internal models of it also need to change. In humans, there is mounting evidence that neural structures such as the insula and the ventral striatum are involved in detecting norm violation and updating internal models. However, because of methodological challenges, little is known about the possible involvement of midbrain structures in detecting norm violation and updating internal models of our norms. Here, we used high-resolution cardiac-gated functional magnetic resonance imaging and a norm adaptation paradigm in healthy adults to investigate the role of the substantia nigra/ventral tegmental area (SN/VTA) complex in tracking signals related to norm violation that can be used to update internal norms. We show that the SN/VTA codes for the norm’s variance prediction error (PE) and norm PE with spatially distinct regions coding for negative and positive norm PE. These results point to a common role played by the SN/VTA complex in supporting both simple reward-based and social decision making.

Contributions of the Medial Prefrontal Cortex to Social Influence in Economic Decision-Making

Economic decisions are guided by highly subjective reward valuations (SVs). Often these SVs are over-ridden when individuals conform to social norms. Yet, the neural mechanisms that underpin the distinct processing of such normative reward valuations (NVs) are poorly understood. The dorsomedial and ventromedial portions of the prefrontal cortex (dmPFC/vmPFC) are putatively key regions for processing social and economic information respectively. However, the contribution of these regions to economic decisions guided by social norms is unclear. Using functional magnetic resonance imaging and computational modeling we examine the neural mechanisms underlying the processing of SVs and NVs. Subjects (n = 15) indicated either their own economic preferences or made similar choices based on a social norm-learnt during a training session. We found that that the vmPFC and dmPFC make dissociable contributions to the processing of SV and NV. Regions of the dmPFC processed "only" the value of rewards when making normative choices. In contrast, we identify a novel mechanism in the vmPFC for the coding of value. This region signaled both subjective and normative valuations, but activity was scaled positively for SV and negatively for NV. These results highlight some of the key mechanisms that underpin conformity and social influence in economic decision-making.

Social comparison in the brain: A coordinate-based meta-analysis of functional brain imaging studies on the downward and upward comparisons

Social comparison is ubiquitous across human societies with dramatic influence on people's well-being and decision making. Downward comparison (comparing to worse-off others) and upward comparison (comparing to better-off others) constitute two types of social comparisons that produce different neuropsychological consequences. Based on studies exploring neural signatures associated with downward and upward comparisons, the current study utilized a coordinate-based meta-analysis to provide a refinement of understanding about the underlying neural architecture of social comparison. We identified consistent involvement of the ventral striatum and ventromedial prefrontal cortex in downward comparison and consistent involvement of the anterior insula and dorsal anterior cingulate cortex in upward comparison. These findings fit well with the "common-currency" hypothesis that neural representations of social gain or loss resemble those for non-social reward or loss processing. Accordingly, we discussed our findings in the framework of general reinforcement learning (RL) hypothesis, arguing how social gain/loss induced by social comparisons could be encoded by the brain as a domain-general signal (i.e., prediction errors) serving to adjust people's decisions in social settings. Although the RL account may serve as a heuristic framework for the future research, other plausible accounts on the neuropsychological mechanism of social comparison were also acknowledged. Hum Brain Mapp 39:440-458, 2018. © 2017 Wiley Periodicals, Inc.