Neural Basis of Strategic Decision Making

The involvement of rTPJ in intention attribution during social decision making: A TMS study

The mini-Ultimatum Game (mini-UG) is a bargaining game used to assess the reactions of a responder to unfair offers made by a proposer under different intentionality conditions. Previous studies employing this task showed the activation of responders' right temporoparietal junction (rTPJ), which could be related to its involvement in judgments of intentionality. To verify this hypothesis, in the present study we applied online transcranial magnetic stimulation (TMS) over the rTPJ in responders during the mini-UG, in which we manipulated intention attribution implicitly. A cover story was employed to induce participants to believe they were interacting with another agent. We expected that interfering with the rTPJ could affect the ability of responders to assume proposers' perspective, producing higher rates of rejections of unfair offers when offers are perceived as independent from responders' intentionality to inequality. Twenty-six healthy women voluntarily participated in the study. In the mini-UG, an unfair distribution of the proposer (8/2 offer) was pitted against one of three alternative offers: fair-alternative (5/5), no-alternative (8/2), hyperfair-alternative (2/8). During the task, a train of TMS pulses was delivered at proposers' offer presentation in blocks of active (rTPJ) or control (Vertex) stimulation according to an ABAB design. As expected, findings showed that rejection of the no-alternative offers was higher under TMS stimulation of the rTPJ compared with the control TMS. This effect was modulated by the degree of trustworthiness in the cover story. These data contribute defining the mechanisms and brain areas underpinning social decision making as assessed by bargaining tasks.

Neurocomputational mechanisms involved in adaptation to fluctuating intentions of others

Humans frequently interact with agents whose intentions can fluctuate between competition and cooperation over time. It is unclear how the brain adapts to fluctuating intentions of others when the nature of the interactions (to cooperate or compete) is not explicitly and truthfully signaled. Here, we use model-based fMRI and a task in which participants thought they were playing with another player. In fact, they played with an algorithm that alternated without signaling between cooperative and competitive strategies. We show that a neurocomputational mechanism with arbitration between competitive and cooperative experts outperforms other learning models in predicting choice behavior. At the brain level, the fMRI results show that the ventral striatum and ventromedial prefrontal cortex track the difference of reliability between these experts. When attributing competitive intentions, we find increased coupling between these regions and a network that distinguishes prediction errors related to competition and cooperation. These findings provide a neurocomputational account of how the brain arbitrates dynamically between cooperative and competitive intentions when making adaptive social decisions.

Behavioral and neural responses to social rejection: Individual differences in developmental trajectories across childhood and adolescence

Dealing with social rejection is challenging, especially during childhood when behavioral and neural responses to social rejection are still developing. In the current longitudinal study, we used a Bayesian multilevel growth curve model to describe individual differences in the development of behavioral and neural responses to social rejection in a large sample (n > 500). We found a peak in aggression following negative feedback (compared to neutral feedback) during late childhood, as well as individual differences during this developmental phase, possibly suggesting a sensitive window for dealing with social rejection across late childhood. Moreover, we found evidence for individual differences in the linear development of neural responses to social rejection in our three brain regions of interest: The anterior insula, the medial prefrontal cortex, and the dorsolateral prefrontal cortex. In addition to providing insights in the individual trajectories of dealing with social rejection during childhood, this study also makes a meaningful methodological contribution: Our statistical analysis strategy (and can be found in this study's online supplementary materials at https://jeroendmulder.github.io/social-emotion-regulation/) can be used as an example on how to take into account the many complexities of developmental neuroimaging datasets, while still enabling researchers to answer interesting questions about individual-level relationships.

Observational reinforcement learning in children and young adults

Observational learning is essential for the acquisition of new behavior in educational practices and daily life and serves as an important mechanism for human cognitive and social-emotional development. However, we know little about its underlying neurocomputational mechanisms from a developmental perspective. In this study we used model-based fMRI to investigate differences in observational learning and individual learning between children and younger adults. Prediction errors (PE), the difference between experienced and predicted outcomes, related positively to striatal and ventral medial prefrontal cortex activation during individual learning and showed no age-related differences. PE-related activation during observational learning was more pronounced when outcomes were worse than predicted. Particularly, negative PE-coding in the dorsal medial prefrontal cortex was stronger in adults compared to children and was associated with improved observational learning in children and adults. The current findings pave the way to better understand observational learning challenges across development and educational settings.

A view-based decision mechanism for rewards in the primate amygdala

Primates make decisions visually by shifting their view from one object to the next, comparing values between objects, and choosing the best reward, even before acting. Here, we show that when monkeys make value-guided choices, amygdala neurons encode their decisions in an abstract, purely internal representation defined by the monkey's current view but not by specific object or reward properties. Across amygdala subdivisions, recorded activity patterns evolved gradually from an object-specific value code to a transient, object-independent code in which currently viewed and last-viewed objects competed to reflect the emerging view-based choice. Using neural-network modeling, we identified a sequence of computations by which amygdala neurons implemented view-based decision making and eventually recovered the chosen object's identity when the monkeys acted on their choice. These findings reveal a neural mechanism in the amygdala that derives object choices from abstract, view-based computations, suggesting an efficient solution for decision problems with many objects.

Excitatory stimulation of the ventromedial prefrontal cortex reduces cognitive gambling biases via improved feedback learning

Humans are subject to a variety of cognitive biases, such as the framing-effect or the gambler's fallacy, that lead to decisions unfitting of a purely rational agent. Previous studies have shown that the ventromedial prefrontal cortex (vmPFC) plays a key role in making rational decisions and that stronger vmPFC activity is associated with attenuated cognitive biases. Accordingly, dysfunctions of the vmPFC are associated with impulsive decisions and pathological gambling. By applying a gambling paradigm in a between-subjects design with 33 healthy adults, we demonstrate that vmPFC excitation via transcranial direct current stimulation (tDCS) reduces the framing-effect and the gambler's fallacy compared to sham stimulation. Corresponding magnetoencephalographic data suggest improved inhibition of maladaptive options after excitatory vmPFC-tDCS. Our analyses suggest that the underlying mechanism might be improved reinforcement learning, as effects only emerge over time. These findings encourage further investigations of whether excitatory vmPFC-tDCS has clinical utility in treating pathological gambling or other behavioral addictions.

Structural Organization of Perisomatic Inhibition in the Mouse Medial Prefrontal Cortex

Perisomatic inhibition profoundly controls neural function. However, the structural organization of inhibitory circuits giving rise to the perisomatic inhibition in the higher-order cortices is not completely known. Here, we performed a comprehensive analysis of those GABAergic cells in the medial prefrontal cortex (mPFC) that provide inputs onto the somata and proximal dendrites of pyramidal neurons. Our results show that most GABAergic axonal varicosities contacting the perisomatic region of superficial (layer 2/3) and deep (layer 5) pyramidal cells express parvalbumin (PV) or cannabinoid receptor type 1 (CB1). Further, we found that the ratio of PV/CB1 GABAergic inputs is larger on the somatic membrane surface of pyramidal tract neurons in comparison with those projecting to the contralateral hemisphere. Our morphologic analysis of in vitro labeled PV+ basket cells (PVBC) and CCK/CB1+ basket cells (CCKBC) revealed differences in many features. PVBC dendrites and axons arborized preferentially within the layer where their soma was located. In contrast, the axons of CCKBCs expanded throughout layers, although their dendrites were found preferentially either in superficial or deep layers. Finally, using anterograde trans-synaptic tracing we observed that PVBCs are preferentially innervated by thalamic and basal amygdala afferents in layers 5a and 5b, respectively. Thus, our results suggest that PVBCs can control the local circuit operation in a layer-specific manner via their characteristic arborization, whereas CCKBCs rather provide cross-layer inhibition in the mPFC.SIGNIFICANCE STATEMENT Inhibitory cells in cortical circuits are crucial for the precise control of local network activity. Nevertheless, in higher-order cortical areas that are involved in cognitive functions like decision-making, working memory, and cognitive flexibility, the structural organization of inhibitory cell circuits is not completely understood. In this study we show that perisomatic inhibitory control of excitatory cells in the medial prefrontal cortex is performed by two types of basket cells endowed with different morphologic properties that provide inhibitory inputs with distinct layer specificity on cells projecting to disparate areas. Revealing this difference in innervation strategy of the two basket cell types is a key step toward understanding how they fulfill their distinct roles in cortical network operations.

Another in need enhances prosociality and modulates frontal theta oscillations in young adults

Introduction

Decision-making is a process that can be strongly affected by social factors. Evidence has shown how people deviate from traditional rational-choice predictions under different levels of social interactions. The emergence of prosocial decision-making, defined as any action that is addressed to benefit another individual even at the expense of personal benefits, has been reported as an example of such social influence. Furthermore, brain evidence has shown the involvement of structures such as the prefrontal cortex, anterior insula, and midcingulate cortex during decision settings in which a decision maker interacts with others under physical pain or distress or while being observed by others.

Methods

Using a slightly modified version of the dictator game and EEG recordings, we tested the hypothesis that the inclusion of another person into the decision setting increases prosocial decisions in young adults and that this increase is higher when the other person is associated with others in need. At the brain level, we hypothesized that the increase in prosocial decisions correlates with frontal theta activity.

Results and Discussion

The results showed that including another person in the decision, setting increased prosocial behavior only when this presence was associated with someone in need. This effect was associated with an increase in frontocentral theta-oscillatory activity. These results suggest that the presence of someone in need enhances empathy concerns and norm compliance, raising the participants' prosocial decision-making.

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

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

Competitive and cooperative games for probing the neural basis of social decision-making in animals

In a social environment, it is essential for animals to consider the behavior of others when making decisions. To quantitatively assess such social decisions, games offer unique advantages. Games may have competitive and cooperative components, modeling situations with antagonistic and shared objectives between players. Games can be analyzed by mathematical frameworks, including game theory and reinforcement learning, such that an animal's choice behavior can be compared against the optimal strategy. However, so far games have been underappreciated in neuroscience research, particularly for rodent studies. In this review, we survey the varieties of competitive and cooperative games that have been tested, contrasting strategies employed by non-human primates and birds with rodents. We provide examples of how games can be used to uncover neural mechanisms and explore species-specific behavioral differences. We assess critically the limitations of current paradigms and propose improvements. Together, the synthesis of current literature highlights the advantages of using games to probe the neural basis of social decisions for neuroscience studies.

Neuronal mechanisms of dynamic strategic competition

Competitive social interactions, as in chess or poker, often involve multiple moves and countermoves deployed tactically within a broader strategic plan. Such maneuvers are supported by mentalizing or theory-of-mind-reasoning about the beliefs, plans, and goals of an opponent. The neuronal mechanisms underlying strategic competition remain largely unknown. To address this gap, we studied humans and monkeys playing a virtual soccer game featuring continuous competitive interactions. Humans and monkeys deployed similar tactics within broadly identical strategies, which featured unpredictable trajectories and precise timing for kickers, and responsiveness to opponents for goalies. We used Gaussian Process (GP) classification to decompose continuous gameplay into a series of discrete decisions predicated on the evolving states of self and opponent. We extracted relevant model parameters as regressors for neuronal activity in macaque mid-superior temporal sulcus (mSTS), the putative homolog of human temporo-parietal junction (TPJ), an area selectively engaged during strategic social interactions. We discovered two spatially-segregated populations of mSTS neurons that signaled actions of self and opponent, sensitivities to state changes, and previous and current trial outcomes. Inactivating mSTS reduced kicker unpredictability and impaired goalie responsiveness. These findings demonstrate mSTS neurons multiplex information about the current states of self and opponent as well as history of previous interactions to support ongoing strategic competition, consistent with hemodynamic activity found in human TPJ.

Noninvasive stimulation of the ventromedial prefrontal cortex modulates rationality of human decision-making

The framing-effect is a bias that affects decision-making depending on whether the available options are presented with positive or negative connotations. Even when the outcome of two choices is equivalent, people have a strong tendency to avoid the negatively framed option. The ventromedial prefrontal cortex (vmPFC) is crucial for rational decision-making, and dysfunctions in this region have been linked to cognitive biases, impulsive behavior and gambling addiction. Using a financial decision-making task in combination with magnetoencephalographic neuroimaging, we show that excitatory compared to inhibitory non-invasive transcranial direct current stimulation (tDCS) of the vmPFC reduces framing-effects while improving the assessment of loss-probabilities, ultimately leading to increased overall gains. Behavioral and neural data consistently suggest that this improvement in rational decision-making is predominately due to an attenuation of biases towards negative affect (loss-aversion and risk-aversion). These findings recommend further research towards clinical applications of vmPFC-tDCS as in addictive disorders.

Strategic complexity and cognitive skills affect brain response in interactive decision-making

Deciding the best action in social settings requires decision-makers to consider their and others’ preferences, since the outcome depends on the actions of both. Numerous empirical investigations have demonstrated variability of behavior across individuals in strategic situations. While prosocial, moral, and emotional factors have been intensively investigated to explain this diversity, neuro-cognitive determinants of strategic decision-making and their relation with intelligence remain mostly unknown. This study presents a new model of the process of strategic decision-making in repeated interactions, first providing a precise measure of the environment’s complexity, and then analyzing how this complexity affects subjects’ performance and neural response. The results confirm the theoretical predictions of the model. The frequency of deviations from optimal behavior is explained by a combination of higher complexity of the strategic environment and cognitive skills of the individuals. Brain response correlates with strategic complexity, but only in the subgroups with higher cognitive skills. Furthermore, neural effects were only observed in a fronto-parietal network typically involved in single-agent tasks (the Multiple Demand Network), thus suggesting that neural processes dealing with cognitively demanding individual tasks also have a central role in interactive decision-making. Our findings contribute to understanding how cognitive factors shape strategic decision-making and may provide the neural pathway of the reported association between strategic sophistication and fluid intelligence.

Neurocomputations of strategic behavior: From iterated to novel interactions

Strategic interactions, where an individual's payoff depends on the decisions of multiple intelligent agents, are ubiquitous among social animals. They span a variety of important social behaviors such as competition, cooperation, coordination, and communication, and often involve complex, intertwining cognitive operations ranging from basic reward processing to higher‐order mentalization. Here, we review the progress and challenges in probing the neural and cognitive mechanisms of strategic behavior of interacting individuals, drawing an analogy to recent developments in studies of reward‐seeking behavior, in particular, how research focuses in the field of strategic behavior have been expanded from adaptive behavior based on trial‐and‐error to flexible decisions based on limited prior experience. We highlight two important research questions in the field of strategic behavior: (i) How does the brain exploit past experience for learning to behave strategically? and (ii) How does the brain decide what to do in novel strategic situations in the absence of direct experience? For the former, we discuss the utility of learning models that have effectively connected various types of neural data with strategic learning behavior and helped elucidate the interplay among multiple learning processes. For the latter, we review the recent evidence and propose a neural generative mechanism by which the brain makes novel strategic choices through simulating others' goal‐directed actions according to rational or bounded‐rational principles obtained through indirect social knowledge.

This article is categorized under:

Economics > Interactive Decision‐Making

Psychology > Reasoning and Decision Making

Neuroscience > Cognition

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

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

Strengths and challenges of longitudinal non-human primate neuroimaging

Longitudinal non-human primate neuroimaging has the potential to greatly enhance our understanding of primate brain structure and function. Here we describe its specific strengths, compared to both cross-sectional non-human primate neuroimaging and longitudinal human neuroimaging, but also its associated challenges. We elaborate on factors guiding the use of different analytical tools, subject-specific versus age-specific templates for analyses, and issues related to statistical power.

Formalizing planning and information search in naturalistic decision-making

Decisions made by mammals and birds are often temporally extended. They require planning and sampling of decision-relevant information. Our understanding of such decision-making remains in its infancy compared with simpler, forced-choice paradigms. However, recent advances in algorithms supporting planning and information search provide a lens through which we can explain neural and behavioral data in these tasks. We review these advances to obtain a clearer understanding for why planning and curiosity originated in certain species but not others; how activity in the medial temporal lobe, prefrontal and cingulate cortices may support these behaviors; and how planning and information search may complement each other as means to improve future action selection.

High-frequency burst spiking in layer 5 thick-tufted pyramids of rat primary somatosensory cortex encodes exploratory touch

Diversity of cell-types that collectively shape the cortical microcircuit ensures the necessary computational richness to orchestrate a wide variety of behaviors. The information content embedded in spiking activity of identified cell-types remain unclear to a large extent. Here, we recorded spike responses upon whisker touch of anatomically identified excitatory cell-types in primary somatosensory cortex in naive, untrained rats. We find major differences across layers and cell-types. The temporal structure of spontaneous spiking contains high-frequency bursts (≥100 Hz) in all morphological cell-types but a significant increase upon whisker touch is restricted to layer L5 thick-tufted pyramids (L5tts) and thus provides a distinct neurophysiological signature. We find that whisker touch can also be decoded from L5tt bursting, but not from other cell-types. We observed high-frequency bursts in L5tts projecting to different subcortical regions, including thalamus, midbrain and brainstem. We conclude that bursts in L5tts allow accurate coding and decoding of exploratory whisker touch.

In order to investigate the information encoded by spiking activity in different neuronal cell types in the primary somatosensory cortex, de Kock et al performed electrophysiological recordings in untrained rats. They demonstrated that an increase in high-frequency burst spiking in thick tufted pyramids in layer 5 of the cortex allow accurate encoding of exploratory whisker touch.

Dorsolateral and dorsomedial prefrontal cortex track distinct properties of dynamic social behavior

Understanding how humans make competitive decisions in complex environments is a key goal of decision neuroscience. Typical experimental paradigms constrain behavioral complexity (e.g. choices in discrete-play games), and thus, the underlying neural mechanisms of dynamic social interactions remain incompletely understood. Here, we collected fMRI data while humans played a competitive real-time video game against both human and computer opponents, and then, we used Bayesian non-parametric methods to link behavior to neural mechanisms. Two key cognitive processes characterized behavior in our task: (i) the coupling of one’s actions to another’s actions (i.e. opponent sensitivity) and (ii) the advantageous timing of a given strategic action. We found that the dorsolateral prefrontal cortex displayed selective activation when the subject’s actions were highly sensitive to the opponent’s actions, whereas activation in the dorsomedial prefrontal cortex increased proportionally to the advantageous timing of actions to defeat one’s opponent. Moreover, the temporoparietal junction tracked both of these behavioral quantities as well as opponent social identity, indicating a more general role in monitoring other social agents. These results suggest that brain regions that are frequently implicated in social cognition and value-based decision-making also contribute to the strategic tracking of the value of social actions in dynamic, multi-agent contexts.

Event-Related Potentials During Decision-Making in a Mixed-Strategy Game

The decisions we make are sometimes influenced by interactions with other agents. Previous studies have suggested that the prefrontal cortex plays an important role in decision-making and that the dopamine system underlies processes of motivation, motor preparation, and reinforcement learning. However, the physiological mechanisms underlying how the prefrontal cortex and the dopaminergic system are involved in decision-making remain largely unclear. The present study aimed to determine how decision strategies influence event-related potentials (ERPs). We also tested the effect of levodopa, a dopamine precursor, on decision-making and ERPs in a randomized double-blind placebo-controlled investigation. The subjects performed a matching-pennies task against an opposing virtual computer player by choosing between right and left targets while their ERPs were recorded. According to the rules of the matching-pennies task, the subject won the trial when they chose the same side as the opponent, and lost otherwise. We set three different task rules: (1) with the alternation (ALT) rule, the computer opponent made alternating choices of right and left in sequential trials; (2) with the random (RAND) rule, the opponent randomly chose between right and left; and (3) with the GAME rule, the opponent analyzed the subject's past choices to predict the subject's next choice, and then chose the opposite side. A sustained medial ERP became more negative toward the time of the subject's target choice. A biphasic potential appeared when the opponent's choice was revealed after the subject's response. The ERPs around the subject's choice were greater in RAND and GAME than in ALT, and the negative peak was enhanced by levodopa. In addition to these medial ERPs, we observed lateral frontal ERPs tuned to the choice direction. The signals emerged around the choice period selectively in RAND and GAME when levodopa was administered. These results suggest that decision processes are modulated by the dopamine system when a complex and strategic decision is required, which may reflect decision updating with dopaminergic prediction error signals.

Reading between the lines: Listener's vmPFC simulates speaker cooperative choices in communication games

Humans have a remarkable ability to understand what is and is not being said by conversational partners. It has been hypothesized that listeners decode the intended meaning of a communicative signal by assuming speakers speak cooperatively, rationally simulating the speaker's choice process and inverting it to recover the speaker's most probable meaning. We investigated whether and how rational simulations of speakers are represented in the listener's brain, by combining referential communication games with functional neuroimaging. We show that listeners' ventromedial prefrontal cortex encodes the probabilistic inference of what a cooperative speaker should say given a communicative goal and context, even when such inferences are irrelevant for reference resolution. The listener's striatum encodes the amount of update on intended meaning, consistent with inverting a simulated mental model. These findings suggest a neural generative mechanism, subserved by the frontal-striatal circuits, that underlies our ability to understand communicative and, more generally, social actions.

The social dilemma: prefrontal control of mammalian sociability

Mammalian social interactions are orchestrated by a wide array of neural circuits. While some aspects of social behaviors are driven by subcortical circuits, and are considered to be highly conserved and hard-wired, others require dynamic and context-dependent modulation that integrates current state, past experience and goal-driven action selection. These cognitive social processes are known to be dependent on the integrity of the prefrontal cortex. However, the circuit mechanisms through which the prefrontal cortex supports complex social functions are still largely unknown, and it is unclear if and how they diverge from prefrontal control of behavior outside of the social domain. Here we review recent studies exploring the role of prefrontal circuits in mammalian social functions, and attempt to synthesize these findings to a holistic view of prefrontal control of sociability.

Neuronal correlates of strategic cooperation in monkeys

We recorded neural activity in male monkeys playing a variant of the game 'chicken' in which they made decisions to cooperate or not cooperate to obtain rewards of different sizes. Neurons in the middle superior temporal sulcus (mSTS)-previously implicated in social perception-signaled strategic information, including payoffs, intentions of the other player, reward outcomes and predictions about the other player. Moreover, a subpopulation of mSTS neurons selectively signaled cooperatively obtained rewards. Neurons in the anterior cingulate gyrus, previously implicated in vicarious reinforcement and empathy, carried less information about strategic variables, especially cooperative reward. Strategic signals were not reducible to perceptual information about the other player or motor contingencies. These findings suggest that the capacity to compute models of other agents has deep roots in the strategic social behavior of primates and that the anterior cingulate gyrus and the mSTS support these computations.

A voxel-based lesion symptom mapping analysis of chronic pain in multiple sclerosis

BACKGROUND

Pain is one of the most disabling symptoms in multiple sclerosis. Chronic pain in multiple sclerosis is often neuropathic in nature, although a clear-cut distinction with nociceptive pain is not easy.

OBJECTIVE

The aim of our study was to analyze the MRIs of multiple sclerosis patients with chronic pain in order to explore possible associations with lesion sites, on a voxel-by-voxel basis.

MATERIALS AND METHODS

We enrolled patients aged > 18 years with multiple sclerosis in accordance with the 2010 McDonald criteria. Patients meeting criteria for persistent pain (frequent or constant pain lasting > 3 months) were included in the "pain group". The other patients were included in the "no pain group". We outlined lesions on FLAIR MRI scans using a semi-automated edge finding tool. To detect the association between lesion localization and persistent pain, images were analysed with the voxel-based lesion symptom mapping methods implemented in the (nonparametric mapping software included into the MRIcron.

RESULTS

We enrolled 208 MS patients (140 F, mean age 55.2 ± 9.4 years; 176 RR, 28 progressive MS; mean EDSS 2.0 + 2.0). Pain group included 96 patients and no pain group 112 patients. Lesions of the right dorsolateral prefrontal area were significantly more prevalent in patients without pain, whereas periventricular posterior lesions were significantly more prevalent in patients with persistent pain.

CONCLUSION

Our data suggest a role of the right dorsolateral prefrontal cortex in the modulation of pain perception and in the occurrence of chronic pain in MS patients. Our data also support a hemispheric asymmetry in pain perception and modulation.

Effort shapes social cognition and behaviour: A neuro-cognitive framework

Theoretical accounts typically posit that variability in social behaviour is a function of capacity limits. We argue that many social behaviours are goal-directed and effortful, and thus variability is not just a function of capacity, but also motivation. Leveraging recent work examining the cognitive, computational and neural basis of effort processing, we put forward a framework for motivated social cognition. We argue that social cognition is demanding, people avoid its effort costs, and a core-circuit of brain areas that guides effort-based decisions in non-social situations may similarly evaluate whether social behaviours are worth the effort. Thus, effort sensitivity dissociates capacity limits from social motivation, and may be a driver of individual differences and pathological impairments in social cognition.

Is There a 'Social' Brain? Implementations and Algorithms

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

A Neuro-computational Account of Arbitration between Choice Imitation and Goal Emulation during Human Observational Learning

When individuals learn from observing the behavior of others, they deploy at least two distinct strategies. Choice imitation involves repeating other agents' previous actions, whereas emulation proceeds from inferring their goals and intentions. Despite the prevalence of observational learning in humans and other social animals, a fundamental question remains unaddressed: how does the brain decide which strategy to use in a given situation? In two fMRI studies (the second a pre-registered replication of the first), we identify a neuro-computational mechanism underlying arbitration between choice imitation and goal emulation. Computational modeling, combined with a behavioral task that dissociated the two strategies, revealed that control over behavior was adaptively and dynamically weighted toward the most reliable strategy. Emulation reliability, the model's arbitration signal, was represented in the ventrolateral prefrontal cortex, temporoparietal junction, and rostral cingulate cortex. Our replicated findings illuminate the computations by which the brain decides to imitate or emulate others.

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

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

One cranium, two brains not yet introduced: Distinct but complementary views of the social brain

Social behavior is pervasive across the animal kingdom, and elucidating how the brain enables animals to respond to social contexts is of great interest and profound importance. Our understanding of 'the social brain' has been fractured as it has matured. Two drastically different conceptualizations of the social brain have emerged with relatively little awareness of each other. In this review, we briefly recount the history behind the two dominant definitions of a social brain. The divide that has emerged between these visions can, in part, be attributed to differential attention to cortical or sub-cortical regions in the brain, and differences in methodology, comparative perspectives, and emphasis on functional specificity or generality. We discuss how these factors contribute to a lack of communication between research efforts, and propose ways in which each version of the social brain can benefit from the perspectives, tools, and approaches of the other. Interface between the two characterizations of social brain networks is sure to provide essential insight into what the social brain encompasses.

A novel fMRI paradigm to dissociate the behavioral and neural components of mixed-strategy decision making from non-strategic decisions in humans

During competitive interactions, such as predator-prey or team sports, the outcome of one's actions is dependent on both their own choices and those of their opponents. Success in these rivalries requires that individuals choose dynamically and unpredictably, often adopting a mixed strategy. Understanding the neural basis of strategic decision making is complicated by the fact that it recruits various cognitive processes that are often shared with non-strategic forms of decision making, such as value estimation, working memory, response inhibition, response selection, and reward processes. Although researchers have explored neural activity within key brain regions during mixed-strategy games, how brain activity differs in the context of strategic interactions versus non-strategic choices is not well understood. We developed a novel behavioral paradigm to dissociate choice behavior during mixed-strategy interactions from non-strategic choices, and we used task-based functional magnetic resonance imaging (fMRI) to contrast brain activation. In a block design, participants competed in the classic mixed-strategy game, "matching pennies," against a dynamic computer opponent designed to exploit predictability in players' response patterns. Results were contrasted with a non-strategic task that had comparable sensory input, motor output, and reward rate; thus, differences in behavior and brain activation reflect strategic processes. The mixed-strategy game was associated with activation of a distributed cortico-striatal network compared to the non-strategic task. We propose that choosing in mixed-strategy contexts requires additional cognitive demands present to a lesser degree during the control task, illustrating the strength of this design in probing function of cognitive systems beyond core sensory, motor, and reward processes.

Loss of Prefrontal Cortical Higher Cognition with Uncontrollable Stress: Molecular Mechanisms, Changes with Age, and Relevance to Treatment

The newly evolved prefrontal cortex (PFC) generates goals for "top-down" control of behavior, thought, and emotion. However, these circuits are especially vulnerable to uncontrollable stress, with powerful, intracellular mechanisms that rapidly take the PFC "off-line." High levels of norepinephrine and dopamine released during stress engage α1-AR and D1R, which activate feedforward calcium-cAMP signaling pathways that open nearby potassium channels to weaken connectivity and reduce PFC cell firing. Sustained weakening with chronic stress leads to atrophy of dendrites and spines. Understanding these signaling events helps to explain the increased susceptibility of the PFC to stress pathology during adolescence, when dopamine expression is increased in the PFC, and with advanced age, when the molecular "brakes" on stress signaling are diminished by loss of phosphodiesterases. These mechanisms have also led to pharmacological treatments for stress-related disorders, including guanfacine treatment of childhood trauma, and prazosin treatment of veterans and civilians with post-traumatic stress disorder.

Primate Amygdala Neurons Simulate Decision Processes of Social Partners

By observing their social partners, primates learn about reward values of objects. Here, we show that monkeys' amygdala neurons derive object values from observation and use these values to simulate a partner monkey's decision process. While monkeys alternated making reward-based choices, amygdala neurons encoded object-specific values learned from observation. Dynamic activities converted these values to representations of the recorded monkey's own choices. Surprisingly, the same activity patterns unfolded spontaneously before partner's choices in separate neurons, as if these neurons simulated the partner's decision-making. These "simulation neurons" encoded signatures of mutual-inhibitory decision computation, including value comparisons and value-to-choice conversions, resulting in accurate predictions of partner's choices. Population decoding identified differential contributions of amygdala subnuclei. Biophysical modeling of amygdala circuits showed that simulation neurons emerge naturally from convergence between object-value neurons and self-other neurons. By simulating decision computations during observation, these neurons could allow primates to reconstruct their social partners' mental states.

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.

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.

Social Feedback Modulates Neural Response Associated With Cognitive Bias in Individuals Expressing Anxious Symptoms

BACKGROUND

Social anxiety is characterized by a tendency to overestimate the likelihood of negative outcomes and consequences before, during, and after interpersonal interactions with social partners. Recent evidence suggests that a network of brain regions critical for perspective-taking, threat appraisal, and uncertainty resolution may function atypically in those prone to social anxiety. In this study, we used functional magnetic resonance imaging to examine neural activity in specific regions of interest in a sample of young adults who endorsed high or low levels of social anxiety.

METHODS

We recruited 31 college student volunteers (age: 18-28 years), categorized as having high or low anxiety based on their Liebowitz Social Anxiety Scale-Self Report scores. These participants were each scanned while playing the iterated Prisoner's Dilemma game with three computerized confederates, two of whom they were deceived to believe were human co-players. This study focuses on data collected during play with the presumed humans. Regions of interest were defined for the temporoparietal junction, anterior midcingulate, and dorsomedial prefrontal cortex. Average weighted mean blood-oxygen-level-dependent signals for each subject were extracted and analyzed using mixed design analyses of variance to detect group differences in activation during decision-making, anticipation, and appraisal of round outcomes during the game.

RESULTS

Behavior analysis revealed that the high-anxiety group was more likely to defect than the low-anxiety group. Neuroimaging analysis showed that the high-anxiety group exhibited elevated blood-oxygen-level-dependent activity relative to the low-anxiety group in all three regions during the social feedback appraisal phase but not during decision-making or the anticipation of interaction outcomes.

CONCLUSIONS

These findings provide evidence that some behaviors linked to cognitive biases associated with social anxiety may be mediated by a network of regions involved in recognizing and processing directed social information. Future investigation of the neural basis of cognition and bias in social anxiety using the prisoner's dilemma and other economic-exchange tasks is warranted. These tasks appear to be highly effective, functional magnetic resonance imaging-compatible methods of probing altered cognition and behavior associated with anxiety and related conditions.

Balancing selfishness and norm conformity can explain human behavior in large-scale prisoner's dilemma games and can poise human groups near criticality

Cooperation is central to the success of human societies as it is crucial for overcoming some of the most pressing social challenges of our time; still, how human cooperation is achieved and may persist is a main puzzle in the social and biological sciences. Recently, scholars have recognized the importance of social norms as solutions to major local and large-scale collective action problems, from the management of water resources to the reduction of smoking in public places to the change in fertility practices. Yet a well-founded model of the effect of social norms on human cooperation is still lacking. Using statistical-physics techniques and integrating findings from cognitive and behavioral sciences, we present an analytically tractable model in which individuals base their decisions to cooperate both on the economic rewards they obtain and on the degree to which their action complies with social norms. Results from this parsimonious model are in agreement with observations in recent large-scale experiments with humans. We also find the phase diagram of the model and show that the experimental human group is poised near a critical point, a regime where recent work suggests living systems respond to changing external conditions in an efficient and coordinated manner.

The application of computational models to social neuroscience: promises and pitfalls

Interactions with conspecifics are key to any social species. In order to navigate this social world, it is crucial for individuals to learn from and about others. From learning new skills by observing parents perform them to making complex collective decisions, understanding the mechanisms underlying social cognitive processes has been of considerable interest to psychologists and neuroscientists. Here, we review studies that have used computational modelling techniques, combined with neuroimaging, to shed light on how people learn and make decisions in social contexts. As opposed to standard social neuroscience methods, the computational approach allows one to directly examine where in the brain particular computations, as estimated by models of behavior, are implemented. Findings suggest that people use several strategies to learn from others: vicarious reward learning, where one learns from observing the reward outcomes of another agent; action imitation, which relies on encoding a prediction error between the expected and actual actions of the other agent; and social inference, where one learns by inferring the goals and intentions of others. These computations are implemented in distinct neural networks, which may be recruited adaptively depending on task demands, the environment and other social factors.

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.

Neuronal Correlates of Serial Decision-Making in the Supplementary Eye Field

Human behavior is influenced by serial decision-making: past decisions affect choices that set the context for selecting future options. A primate brain region that may be involved in linking decisions across time is the supplementary eye field (SEF), which, in addition to its well known visual responses and saccade-related activity, also signals the rules that govern flexible decisions and the outcomes of those decisions. Our hypotheses were that SEF neurons encode events during serial decision-making and link the sequential decisions with sustained activity. We recorded from neurons in the SEF of two rhesus monkeys (Macaca mulatta, one male, one female) that performed a serial decision-making task. The monkeys used saccades to select a rule that had to be applied later in the same trial to discriminate between visual stimuli. We found, first, that SEF neurons encoded the spatial parameters of saccades during rule selection but not during visual discrimination, suggesting a malleability to their movement-related tuning. Second, SEF activity linked the sequential decisions of rule selection and visual discrimination, but not continuously. Instead, rule-encoding activity appeared in a "just-in-time" manner before the visual discrimination. Third, SEF neurons encoded trial outcomes both prospectively, before decisions within a trial, and retrospectively, across multiple trials. The results thus identify neuronal correlates of rule selection and application in the SEF, including transient signals that link these sequential decisions. Its activity patterns suggest that the SEF participates in serial decision-making in a contextually dependent manner as part of a broader network.SIGNIFICANCE STATEMENT Much research has gone into studying the neurobiological basis of single, isolated decisions. An important next step is to understand how the brain links multiple decisions to generate a coherent stream of thought and behavior. We studied neural activity related to serial decision-making in an area of frontal cortex known as the supplementary eye field (SEF). Neural recordings were conducted in monkeys that performed a serial decision-making task in which they selected and applied rules. We found that SEF neurons convey signals for serial decision-making, including transient encoding of one decision at the time it is needed for the next one and longer-term representations of trial outcomes, suggesting that the region plays a role in continuity of cognition and behavior.

Ventral anterior cingulate cortex and social decision-making

Studies in the field of social neuroscience have recently made use of computational models of decision-making to provide new insights into how we learn about the self and others during social interactions. Importantly, these studies have increasingly drawn attention to brain areas outside of classical cortical "social brain" regions that may be critical for social processing. In particular, two portions of the ventral anterior cingulate cortex (vACC), subgenual anterior cingulate cortex and perigenual anterior cingulate cortex, have been linked to social and self learning signals, respectively. Here we discuss the emerging parallels between these studies. Uncovering the function of vACC during social interactions could provide important new avenues to understand social decision-making in health and disease.

Neural Mechanisms of Social Cognition in Primates

Activity in a network of areas spanning the superior temporal sulcus, dorsomedial frontal cortex, and anterior cingulate cortex is concerned with how nonhuman primates negotiate the social worlds in which they live. Central aspects of these circuits are retained in humans. Activity in these areas codes for primates' interactions with one another, their attempts to find out about one another, and their attempts to prevent others from finding out too much about themselves. Moreover, important features of the social world, such as dominance status, cooperation, and competition, modulate activity in these areas. We consider the degree to which activity in these regions is simply encoding an individual's own actions and choices or whether this activity is especially and specifically concerned with social cognition. Recent advances in comparative anatomy and computational modeling may help us to gain deeper insights into the nature and boundaries of primate social cognition.

Heritability of aggression following social evaluation in middle childhood: An fMRI study

Middle childhood marks an important phase for developing and maintaining social relations. At the same time, this phase is marked by a gap in our knowledge of the genetic and environmental influences on brain responses to social feedback and their relation to behavioral aggression. In a large developmental twin sample (509 7‐ to 9‐year‐olds), the heritability and neural underpinnings of behavioral aggression following social evaluation were investigated, using the Social Network Aggression Task (SNAT). Participants viewed pictures of peers that gave positive, neutral, or negative feedback to the participant's profile. Next, participants could blast a loud noise toward the peer as an index of aggression. Genetic modeling revealed that aggression following negative feedback was influenced by both genetics and environmental (shared as well as unique environment). On a neural level (n = 385), the anterior insula and anterior cingulate cortex gyrus (ACCg) responded to both positive and negative feedback, suggesting they signal for social salience cues. The medial prefrontal cortex (mPFC) and inferior frontal gyrus (IFG) were specifically activated during negative feedback, whereas positive feedback resulted in increased activation in caudate, supplementary motor cortex (SMA), and dorsolateral prefrontal cortex (DLPFC). Decreased SMA and DLPFC activation during negative feedback was associated with more aggressive behavior after negative feedback. Moreover, genetic modeling showed that 13%–14% of the variance in dorsolateral PFC activity was explained by genetics. Our results suggest that the processing of social feedback is partly explained by genetic factors, whereas shared environmental influences play a role in behavioral aggression following feedback.

Right-wing authoritarianism and stereotype-driven expectations interact in shaping intergroup trust in one-shot vs multiple-round social interactions

Trust towards unrelated individuals is often conditioned by information about previous social interactions that can be derived from either personal or vicarious experience (e.g., reputation). Intergroup stereotypes can be operationalized as expectations about other groups' traits/attitudes/behaviors that heavily influence our behavioral predictions when interacting with them. In this study we investigated the role of perceived social dimensions of the Stereotype Content Model (SCM)-Warmth (W) and Competence (C)-in affecting trusting behavior towards different European national group members during the Trust Game. Given the well-known role of ideological attitudes in regulating stereotypes, we also measured individual differences in right-wing authoritarianism (RWA). In Experiment 1, we designed an online survey to study one-shot intergroup trust decisions by employing putative members of the European Union states which were also rated along SCM dimensions. We found that low-RWA participants' trusting behavior was driven by perceived warmth (i.e., the dimension signaling the benevolence of social intentions) when interacting with low-C groups. In Experiment 2, we investigated the dynamics of trust in a multiple-round version of the European Trust Game. We found that in low-RWA participants trusting behavior decreased over time when interacting with high-W groups (i.e., expected to reciprocate trust), but did not change when interacting with low-W groups (i.e., expected not to reciprocate trust). Moreover, we found that high-RWA participants' trusting behavior decreased when facing low-W groups but not high-W ones. This suggests that low-RWA individuals employ reputational priors but are also permeable to external evidence when learning about others' trustworthiness. In contrast, high-RWA individuals kept relying on stereotypes despite contextual information. These results confirm the pivotal role played by reputational priors triggered by perceived warmth in shaping social interactions.