Computing Social Value Conversion in the Human Brain

Simultaneous EEG-fMRI Investigation of Rhythm-Dependent Thalamo-Cortical Circuits Alteration in Schizophrenia

Schizophrenia is accompanied by aberrant interactions of intrinsic brain networks. However, the modulatory effect of electroencephalography (EEG) rhythms on the functional connectivity (FC) in schizophrenia remains unclear. This study aims to provide new insight into network communication in schizophrenia by integrating FC and EEG rhythm information. After collecting simultaneous resting-state EEG-functional magnetic resonance imaging data, the effect of rhythm modulations on FC was explored using what we term "dynamic rhythm information." We also investigated the synergistic relationships among three networks under rhythm modulation conditions, where this relationship presents the coupling between two brain networks with other networks as the center by the rhythm modulation. This study found FC between the thalamus and cortical network regions was rhythm-specific. Further, the effects of the thalamus on the default mode network (DMN) and salience network (SN) were less similar under alpha rhythm modulation in schizophrenia patients than in controls ([Formula: see text]). However, the similarity between the effects of the central executive network (CEN) on the DMN and SN under gamma modulation was greater ([Formula: see text]), and the degree of coupling was negatively correlated with the duration of disease ([Formula: see text], [Formula: see text]). Moreover, schizophrenia patients exhibited less coupling with the thalamus as the center and greater coupling with the CEN as the center. These results indicate that modulations in dynamic rhythms might contribute to the disordered functional interactions seen in schizophrenia.

How social information impacts action in rodents and humans: the role of the prefrontal cortex and its connections

Day-to-day choices often involve social information and can be influenced by prior social experience. When making a decision in a social context, a subject might need to: 1) recognize the other individual or individuals, 2) infer their intentions and emotions, and 3) weigh the values of all outcomes, social and non-social, prior to selecting an action. These elements of social information processing all rely, to some extent, on the medial prefrontal cortex (mPFC). Patients with neuropsychiatric disorders often have disruptions in prefrontal cortical function, likely contributing to deficits in social reasoning and decision making. To better understand these deficits, researchers have turned to rodents, which have revealed prefrontal cortical mechanisms for contending with the complex information processing demands inherent to making decisions in social contexts. Here, we first review literature regarding social decision making, and the information processing underlying it, in humans and patient populations. We then turn to research in rodents, discussing current procedures for studying social decision making, and underlying neural correlates.

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

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

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

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

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

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

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

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

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

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

Meta-learning, social cognition and consciousness in brains and machines

The intersection between neuroscience and artificial intelligence (AI) research has created synergistic effects in both fields. While neuroscientific discoveries have inspired the development of AI architectures, new ideas and algorithms from AI research have produced new ways to study brain mechanisms. A well-known example is the case of reinforcement learning (RL), which has stimulated neuroscience research on how animals learn to adjust their behavior to maximize reward. In this review article, we cover recent collaborative work between the two fields in the context of meta-learning and its extension to social cognition and consciousness. Meta-learning refers to the ability to learn how to learn, such as learning to adjust hyperparameters of existing learning algorithms and how to use existing models and knowledge to efficiently solve new tasks. This meta-learning capability is important for making existing AI systems more adaptive and flexible to efficiently solve new tasks. Since this is one of the areas where there is a gap between human performance and current AI systems, successful collaboration should produce new ideas and progress. Starting from the role of RL algorithms in driving neuroscience, we discuss recent developments in deep RL applied to modeling prefrontal cortex functions. Even from a broader perspective, we discuss the similarities and differences between social cognition and meta-learning, and finally conclude with speculations on the potential links between intelligence as endowed by model-based RL and consciousness. For future work we highlight data efficiency, autonomy and intrinsic motivation as key research areas for advancing both fields.

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

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

Task-related neural mechanisms of persecutory ideation in schizophrenia and community monozygotic twin-pairs

Perceptions of spiteful behavior are common, distinct from rational fear, and may undergird persecutory ideation. To test this hypothesis and investigate neural mechanisms of persecutory ideation, we employed a novel economic social decision‐making task, the Minnesota Trust Game (MTG), during neuroimaging in patients with schizophrenia (n = 30) and community monozygotic (MZ) twins (n = 38; 19 pairs). We examined distinct forms of mistrust, task‐related brain activation and connectivity, and investigated relationships with persecutory ideation. We tested whether co‐twin discordance on these measurements was correlated to reflect a common source of underlying variance. Across samples persecutory ideation was associated with reduced trust only during the suspiciousness condition, which assessed spite sensitivity given partners had no monetary incentive to betray. Task‐based activation contrasts for specific forms of mistrust were limited and unrelated to persecutory ideation. However, task‐based connectivity contrasts revealed a dorsal cingulate anterior insula network sensitive to suspicious mistrust, a left frontal–parietal (lF‐P) network sensitive to rational mistrust, and a ventral medial/orbital prefrontal (vmPFC/OFC) network that was sensitive to the difference between these forms of mistrust (all p < .005). Higher persecutory ideation was predicted only by reduced connectivity between the vmPFC/OFC and lF‐P networks (p = .005), which was only observed when the intentions of the other player were relevant. Moreover, co‐twin differences in persecutory ideation predicted co‐twin differences in both spite sensitivity and in vmPFC/OFC–lF‐P connectivity. This work found that interconnectivity may be particularly important to the complex neurobiology underlying persecutory ideation, and that unique environmental variance causally linked persecutory ideation, decision‐making, and brain connectivity.

Neural Representation in mPFC Reveals Hidden Selfish Motivation in White Lies

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

Social isolation impairs the prefrontal-nucleus accumbens circuit subserving social recognition in mice

Although medial prefrontal cortex (mPFC) is known to play important roles in social behaviors, how early social experiences affect the mPFC and its subcortical circuit remains unclear. We report that mice singly housed (SH) for 8 weeks after weaning show a social recognition deficit, even after 4 weeks of resocialization. In SH mice, prefrontal infralimbic (IL) neurons projecting to the shell region of nucleus accumbens (NAcSh) show decreased excitability compared with group-housed (GH) mice. NAcSh-projecting IL neurons are activated when GH mice encounter a familiar conspecific, which is not observed in SH mice. Chemogenetic inhibition of NAcSh-projecting IL neurons in normal mice impairs social recognition without affecting social preference, whereas activation of these neurons reverses social recognition deficit in SH mice. Our findings demonstrate that early social experience critically affects mPFC IL-NAcSh projection, the activation of which is required for social recognition by encoding information for social familiarity.

Functional specialization within the inferior parietal lobes across cognitive domains

The inferior parietal lobe (IPL) is a key neural substrate underlying diverse mental processes, from basic attention to language and social cognition, that define human interactions. Its putative domain-global role appears to tie into poorly understood differences between cognitive domains in both hemispheres. Across attentional, semantic, and social cognitive tasks, our study explored functional specialization within the IPL. The task specificity of IPL subregion activity was substantiated by distinct predictive signatures identified by multivariate pattern-learning algorithms. Moreover, the left and right IPL exerted domain-specific modulation of effective connectivity among their subregions. Task-evoked functional interactions of the anterior and posterior IPL subregions involved recruitment of distributed cortical partners. While anterior IPL subregions were engaged in strongly lateralized coupling links, both posterior subregions showed more symmetric coupling patterns across hemispheres. Our collective results shed light on how under-appreciated hemispheric specialization in the IPL supports some of the most distinctive human mental capacities.

Subcortical encoding of agent-relevant associative signals for adaptive social behavior in the macaque

Primates are group-living creatures that constantly face the challenges posed by complex social demands. To date, the cortical mechanisms underlying social information processing have been the major focus of attention. However, emerging evidence suggests that subcortical regions also mediate the collection and processing of information from other agents. Here, we review the literature supporting the hypothesis that behavioral variables important for decision-making, i.e., stimulus, action, and outcome, are associated with agent information (self and other) in subcortical regions, such as the amygdala, striatum, lateral hypothalamus, and dopaminergic midbrain nuclei. Such self-relevant and other-relevant associative signals are then integrated into a social utility signal, presumably at the level of midbrain dopamine neurons. This social utility signal allows decision makers to organize their optimal behavior in accordance with social demands. Determining how self-relevant and other-relevant signals might be altered in psychiatric and neurodevelopmental disorders will be fundamental to better understand how social behaviors are dysregulated in disease conditions.

Intermittent Theta Burst Stimulation (iTBS) as an Optimal Treatment for Schizophrenia Risk Decision: an ERSP Study

Objective: People with schizophrenia have serious impairments in social function, especially in decision-making ability. Transcranial magnetic stimulation modified intermittent theta burst transcranial magnetic stimulation (iTBS) has been shown to regulate the functional connection of brain networks. Our study explored the therapeutic effect of iTBS on decision-making disorders in schizophrenia. Methods: Participants were pseudorandomized and assigned to iTBS (n = 16) or sham (n = 16) group. iTBS group was administered 1,800 pulses on the target of the left dorsol lateral prefrontal cortex (L-DLPFC) per day for 14 consecutive days. We compared Iowa gambling task performance and associated event-related spectral perturbation results (ERSP) among two groups. Results: The results show that participants' performance in the high-lose in the iTBS group had stronger stimulation of theta spectral power than those in the sham group. Specifically, we found that under high-risk conditions, compared with the control group, the iTBS group showed significant activation of the theta spectrum power in the FPZ, FZ, FCZ, and CZ regions after treatment. Conclusions: Our results provide evidence that long-term iTBS stimulation effectively improves the decision-making ability of schizophrenia. After receiving negative feedback, patients can turn to safety options. These findings support that iTBS may be a potential treatment for clinical decision-making disorders.

Links Between the Neurobiology of Oxytocin and Human Musicality

The human species possesses two complementary, yet distinct, universal communication systems—language and music. Functional imaging studies have revealed that some core elements of these two systems are processed in closely related brain regions, but there are also clear differences in brain circuitry that likely underlie differences in functionality. Music affects many aspects of human behavior, especially in encouraging prosocial interactions and promoting trust and cooperation within groups of culturally compatible but not necessarily genetically related individuals. Music, presumably via its impact on the limbic system, is also rewarding and motivating, and music can facilitate aspects of learning and memory. In this review these special characteristics of music are considered in light of recent research on the neuroscience of the peptide oxytocin, a hormone that has both peripheral and central actions, that plays a role in many complex human behaviors, and whose expression has recently been reported to be affected by music-related activities. I will first briefly discuss what is currently known about the peptide’s physiological actions on neurons and its interactions with other neuromodulator systems, then summarize recent advances in our knowledge of the distribution of oxytocin and its receptor (OXTR) in the human brain. Next, the complex links between oxytocin and various social behaviors in humans are considered. First, how endogenous oxytocin levels relate to individual personality traits, and then how exogenous, intranasal application of oxytocin affects behaviors such as trust, empathy, reciprocity, group conformity, anxiety, and overall social decision making under different environmental conditions. It is argued that many of these characteristics of oxytocin biology closely mirror the diverse effects that music has on human cognition and emotion, providing a link to the important role music has played throughout human evolutionary history and helping to explain why music remains a special prosocial human asset. Finally, it is suggested that there is a potential synergy in combining oxytocin- and music-based strategies to improve general health and aid in the treatment of various neurological dysfunctions.

Psychotherapy in pain management: New viewpoints and treatment targets based on a brain theory

The current paper provides an explanation of neurophysiological pain processing based the Dimensional Systems Model (DSM), a theory of higher cortical functions in which the cortical column is considered the binary digit for all cortical functions. Within the discussion, novel views on the roles of the basal ganglia, cerebellum, and cingulate cortex are presented. Additionally, an applied Clinical Biopsychological Model (CBM) based on the DSM will be discussed as related to psychological treatment with chronic pain patients. Three specific areas that have not been adequately addressed in the psychological treatment of chronic pain patients will be discussed based on the CBM. The treatment approaches have been effectively used in a clinical setting. Conclusions focus on a call for researchers and clinicians to fully evaluate the value of both the DSM and CBM.

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

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

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.