Single-neuronal predictions of others' beliefs in humans

Shared representations of human actions across vision and language

Humans can recognize and communicate about many actions performed by others. How are actions organized in the mind, and is this organization shared across vision and language? We collected similarity judgments of human actions depicted through naturalistic videos and sentences, and tested four models of action categorization, defining actions at different levels of abstraction ranging from specific (action verb) to broad (action target: whether an action is directed towards an object, another person, or the self). The similarity judgments reflected a shared organization of action representations across videos and sentences, determined mainly by the target of actions, even after accounting for other semantic features. Furthermore, language model embeddings predicted the behavioral similarity of action videos and sentences, and captured information about the target of actions alongside unique semantic information. Together, our results show that action concepts are similarly organized in the mind across vision and language, and that this organization reflects socially relevant goals.

Role of Prefrontal Cortex Circuitry in Maintaining Social Homeostasis

Homeostasis is a fundamental concept in biology and ensures the stability of life by maintaining the constancy of physiological processes. Recent years have witnessed a surge in research interest in these physiological processes, with a growing focus on understanding the mechanisms underlying social homeostasis. This shift in focus underscores our increasing understanding of the importance of social interactions and their impact on individual well-being. In this review, we explore the interconnected research across three primary categories: understanding the neural mechanisms influencing set-points, defining contemporary factors that can disrupt social homeostasis, and identifying the potential contributions of social homeostatic failure in the development of psychiatric diseases. We also delve into the role of the prefrontal cortex and its circuitry in regulating social behavior, decision-making processes, and the manifestation of neuropsychiatric disorders such as depression and anxiety. Finally, we examine the influence of more recent factors such as growing social media exposure and the COVID-19 pandemic on mental health, highlighting their disruptive effects. We also identify gaps in current literature through the analysis of research trends and propose future research directions to advance our understanding of social homeostasis, with implications for mental health interventions.

Semantic encoding during language comprehension at single-cell resolution

From sequences of speech sounds1,2 or letters3, humans can extract rich and nuanced meaning through language. This capacity is essential for human communication. Yet, despite a growing understanding of the brain areas that support linguistic and semantic processing4-12, the derivation of linguistic meaning in neural tissue at the cellular level and over the timescale of action potentials remains largely unknown. Here we recorded from single cells in the left language-dominant prefrontal cortex as participants listened to semantically diverse sentences and naturalistic stories. By tracking their activities during natural speech processing, we discover a fine-scale cortical representation of semantic information by individual neurons. These neurons responded selectively to specific word meanings and reliably distinguished words from nonwords. Moreover, rather than responding to the words as fixed memory representations, their activities were highly dynamic, reflecting the words' meanings based on their specific sentence contexts and independent of their phonetic form. Collectively, we show how these cell ensembles accurately predicted the broad semantic categories of the words as they were heard in real time during speech and how they tracked the sentences in which they appeared. We also show how they encoded the hierarchical structure of these meaning representations and how these representations mapped onto the cell population. Together, these findings reveal a finely detailed cortical organization of semantic representations at the neuron scale in humans and begin to illuminate the cellular-level processing of meaning during language comprehension.

Lesions to the mediodorsal thalamus, but not orbitofrontal cortex, enhance volatility beliefs linked to paranoia

Beliefs-attitudes toward some state of the environment-guide action selection and should be robust to variability but sensitive to meaningful change. Beliefs about volatility (expectation of change) are associated with paranoia in humans, but the brain regions responsible for volatility beliefs remain unknown. The orbitofrontal cortex (OFC) is central to adaptive behavior, whereas the magnocellular mediodorsal thalamus (MDmc) is essential for arbitrating between perceptions and action policies. We assessed belief updating in a three-choice probabilistic reversal learning task following excitotoxic lesions of the MDmc (n = 3) or OFC (n = 3) and compared performance with that of unoperated monkeys (n = 14). Computational analyses indicated a double dissociation: MDmc, but not OFC, lesions were associated with erratic switching behavior and heightened volatility belief (as in paranoia in humans), whereas OFC, but not MDmc, lesions were associated with increased lose-stay behavior and reward learning rates. Given the consilience across species and models, these results have implications for understanding paranoia.

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

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

Visuo-frontal interactions during social learning in freely moving macaques

Social interactions represent a ubiquitous aspect of our everyday life that we acquire by interpreting and responding to visual cues from conspecifics1. However, despite the general acceptance of this view, how visual information is used to guide the decision to cooperate is unknown. Here, we wirelessly recorded the spiking activity of populations of neurons in the visual and prefrontal cortex in conjunction with wireless recordings of oculomotor events while freely moving macaques engaged in social cooperation. As animals learned to cooperate, visual and executive areas refined the representation of social variables, such as the conspecific or reward, by distributing socially relevant information among neurons in each area. Decoding population activity showed that viewing social cues influences the decision to cooperate. Learning social events increased coordinated spiking between visual and prefrontal cortical neurons, which was associated with improved accuracy of neural populations to encode social cues and the decision to cooperate. These results indicate that the visual-frontal cortical network prioritizes relevant sensory information to facilitate learning social interactions while freely moving macaques interact in a naturalistic environment.

Repetitive deep TMS in alcohol dependent patients halts progression of white matter changes in early abstinence

AIM

Alcohol use disorder (AUD) is the most prevalent form of addiction, with a great burden on society and limited treatment options. A recent clinical trial reported significant clinical benefits of deep transcranial magnetic stimulations (Deep TMS) targeting midline frontocortical areas. However, the underlying biological substrate remained elusive. Here, we report the effect of Deep TMS on the microstructure of white matter.

METHODS

A total of 37 (14 females) AUD treatment-seeking patients were randomized to sham or active Deep TMS. Twenty (six females) age-matched healthy controls were included. White matter integrity was evaluated by fractional anisotropy (FA). Secondary measures included brain functional connectivity and self-reports of craving and drinking units in the 3 months of follow-up period.

RESULTS

White matter integrity was compromised in patients with AUD relative to healthy controls, as reflected by the widespread reduction in FA. This alteration progressed during early abstinence (3 weeks) in the absence of Deep TMS. However, stimulation of midline frontocortical areas arrested the progression of FA changes in association with decreased craving and relapse scores. Reconstruction of axonal tracts from white-matter regions showing preserved FA values identified cortical regions in the posterior cingulate and dorsomedial prefrontal cortices where functional connectivity was persistently modulated. These effects were absent in the sham-stimulated group.

CONCLUSIONS

By integrating brain structure and function to characterize the alcohol-dependent brain, this study provides mechanistic insights into the TMS effect, pointing to myelin plasticity as a possible mediator.

Single-neuronal elements of speech production in humans

Humans are capable of generating extraordinarily diverse articulatory movement combinations to produce meaningful speech. This ability to orchestrate specific phonetic sequences, and their syllabification and inflection over subsecond timescales allows us to produce thousands of word sounds and is a core component of language1,2. The fundamental cellular units and constructs by which we plan and produce words during speech, however, remain largely unknown. Here, using acute ultrahigh-density Neuropixels recordings capable of sampling across the cortical column in humans, we discover neurons in the language-dominant prefrontal cortex that encoded detailed information about the phonetic arrangement and composition of planned words during the production of natural speech. These neurons represented the specific order and structure of articulatory events before utterance and reflected the segmentation of phonetic sequences into distinct syllables. They also accurately predicted the phonetic, syllabic and morphological components of upcoming words and showed a temporally ordered dynamic. Collectively, we show how these mixtures of cells are broadly organized along the cortical column and how their activity patterns transition from articulation planning to production. We also demonstrate how these cells reliably track the detailed composition of consonant and vowel sounds during perception and how they distinguish processes specifically related to speaking from those related to listening. Together, these findings reveal a remarkably structured organization and encoding cascade of phonetic representations by prefrontal neurons in humans and demonstrate a cellular process that can support the production of speech.

A frontopolar-temporal circuit determines the impact of social information in macaque decision making

When choosing, primates are guided not only by personal experience of objects but also by social information such as others' attitudes toward the objects. Crucially, both sources of information-personal and socially derived-vary in reliability. To choose optimally, one must sometimes override choice guidance by personal experience and follow social cues instead, and sometimes one must do the opposite. The dorsomedial frontopolar cortex (dmFPC) tracks reliability of social information and determines whether it will be attended to guide behavior. To do this, dmFPC activity enters specific patterns of interaction with a region in the mid-superior temporal sulcus (mSTS). Reversible disruption of dmFPC activity with transcranial ultrasound stimulation (TUS) led macaques to fail to be guided by social information when it was reliable but to be more likely to use it when it was unreliable. By contrast, mSTS disruption uniformly downregulated the impact of social information on behavior.

Electrode Development for Epilepsy Diagnosis and Treatment

Recording neural activity has been a critical aspect in the diagnosis and treatment of patients with epilepsy. For those with intractable epilepsy, intracranial neural monitoring has been of substantial importance. Clinically, however, methods for recording neural information have remained essentially unchanged for decades. Over the last decade or so, rapid advances in electrode technology have begun to change this landscape. New systems allow for the observation of neural activity with high spatial resolution and, in some cases, at the level of the activity of individual neurons. These new tools have contributed greatly to our understanding of brain function and dysfunction. Here, the authors review the primary technologies currently in use in humans. The authors discuss other possible systems, some of the challenges which come along with these devices, and how they will become incorporated into the clinical workflow. Ultimately, the expectation is that these new, high-density, high-spatial-resolution recording systems will become a valuable part of the clinical arsenal used in the diagnosis and surgical management of epilepsy.

Modified Neuropixels probes for recording human neurophysiology in the operating room

Neuropixels are silicon-based electrophysiology-recording probes with high channel count and recording-site density. These probes offer a turnkey platform for measuring neural activity with single-cell resolution and at a scale that is beyond the capabilities of current clinically approved devices. Our team demonstrated the first-in-human use of these probes during resection surgery for epilepsy or tumors and deep brain stimulation electrode placement in patients with Parkinson's disease. Here, we provide a better understanding of the capabilities and challenges of using Neuropixels as a research tool to study human neurophysiology, with the hope that this information may inform future efforts toward regulatory approval of Neuropixels probes as research devices. In perioperative procedures, the major concerns are the initial sterility of the device, maintaining a sterile field during surgery, having multiple referencing and grounding schemes available to de-noise recordings (if necessary), protecting the silicon probe from accidental contact before insertion and obtaining high-quality action potential and local field potential recordings. The research team ensures that the device is fully operational while coordinating with the surgical team to remove sources of electrical noise that could otherwise substantially affect the signals recorded by the sensitive hardware. Prior preparation using the equipment and training in human clinical research and working in operating rooms maximize effective communication within and between the teams, ensuring high recording quality and minimizing the time added to the surgery. The perioperative procedure requires ~4 h, and the entire protocol requires multiple weeks.

Task-independent neural bases of peer presence effect on cognition in children and adults

There is ample behavioral evidence that others' mere presence can affect any behavior in human and non-human animals, generally facilitating the expression of mastered responses while impairing the acquisition of novel ones. Much less is known about i) how the brain orchestrates the modulation of such a wide array of behaviors by others' presence and ii) when these neural underpinnings mature during development. To address these issues, fMRI data were collected in children and adults alternately observed and unobserved by a familiar peer. Subjects performed a numerosity comparison task and a phonological comparison task. While the former involves number-processing brain areas, the latter involves language-processing areas. Consistent with previous behavioral findings, adults' and children's performance improved in both tasks when observed by a peer. Across all participants, task-specific brain regions showed no reliable change in activity under peer observation. Rather, we found task-independent changes in domain-general brain regions typically involved in mentalizing, reward, and attention. Bayesian analyses singled out the attention network as the exception to the close child-adult resemblance of peer observation neural substrates. These findings suggest that i) social facilitation of some human education-related skills is primarily orchestrated by domain-general brain networks, rather than by task-selective substrates, and ii) apart from attention, peer presence neural processing is largely mature in children.

Teachers recruit mentalizing regions to represent learners' beliefs

Teaching enables humans to impart vast stores of culturally specific knowledge and skills. However, little is known about the neural computations that guide teachers' decisions about what information to communicate. Participants (N = 28) played the role of teachers while being scanned using fMRI; their task was to select examples that would teach learners how to answer abstract multiple-choice questions. Participants' examples were best described by a model that selects evidence that maximizes the learner's belief in the correct answer. Consistent with this idea, participants' predictions about how well learners would do closely tracked the performance of an independent sample of learners (N = 140) who were tested on the examples they had provided. In addition, regions that play specialized roles in processing social information, namely the bilateral temporoparietal junction and middle and dorsal medial prefrontal cortex, tracked learners' posterior belief in the correct answer. Our results shed light on the computational and neural architectures that support our extraordinary abilities as teachers.

A scale-free universal relational information matrix (N-space) reconciles the information problem: N-space as the fabric of reality

Cellular measurement is a crucial faculty in living systems, and exaptations are acknowledged as a significant source of evolutionary innovation. However, the possibility that the origin of biological order is predicated on an exaptation of the measurement of information from the abiotic realm has not been previously explored. To support this hypothesis, the existence of a universal holographic relational information space-time matrix is proposed as a scale-free unification of abiotic and biotic information systems. In this framework, information is a universal property representing the interactions between matter and energy that can be subject to observation. Since observers are also universally distributed, information can be deemed the fundamental fabric of the universe. The novel concept of compartmentalizing this universal N-space information matrix into separate N-space partitions as nodes of informational density defined by Markov blankets and boundaries is introduced, permitting their applicability to both abiotic and biotic systems. Based on these N-space partitions, abiotic systems can derive meaningful information from the conditional settlement of quantum entanglement asymmetries and coherences between separately bounded quantum informational reference frames sufficient to be construed as a form of measurement. These conditional relationships are the precursor of the reiterating nested architecture of the N-space-derived information fields that characterize life and account for biological order. Accordingly, biotic measurement and biological N-space partitioning are exaptations of preexisting information processes within abiotic systems. Abiotic and biotic states thereby reconcile as differing forms of measurement of fundamental universal information. The essential difference between abiotic and biotic states lies within the attributes of the specific observer/detectors, thereby clarifying several contentious aspects of self-referential consciousness.

Human acute microelectrode array recordings with broad cortical access, single-unit resolution, and parallel behavioral monitoring

There are vast gaps in our understanding of the organization and operation of the human nervous system at the level of individual neurons and their networks. Here, we report reliable and robust acute multichannel recordings using planar microelectrode arrays (MEAs) implanted intracortically in awake brain surgery with open craniotomies that grant access to large parts of the cortical hemisphere. We obtained high-quality extracellular neuronal activity at the microcircuit, local field potential level and at the cellular, single-unit level. Recording from the parietal association cortex, a region rarely explored in human single-unit studies, we demonstrate applications on these complementary spatial scales and describe traveling waves of oscillatory activity as well as single-neuron and neuronal population responses during numerical cognition, including operations with uniquely human number symbols. Intraoperative MEA recordings are practicable and can be scaled up to explore cellular and microcircuit mechanisms of a wide range of human brain functions.

Resolving the prefrontal mechanisms of adaptive cognitive behaviors: A cross-species perspective

The prefrontal cortex (PFC) enables a staggering variety of complex behaviors, such as planning actions, solving problems, and adapting to new situations according to external information and internal states. These higher-order abilities, collectively defined as adaptive cognitive behavior, require cellular ensembles that coordinate the tradeoff between the stability and flexibility of neural representations. While the mechanisms underlying the function of cellular ensembles are still unclear, recent experimental and theoretical studies suggest that temporal coordination dynamically binds prefrontal neurons into functional ensembles. A so far largely separate stream of research has investigated the prefrontal efferent and afferent connectivity. These two research streams have recently converged on the hypothesis that prefrontal connectivity patterns influence ensemble formation and the function of neurons within ensembles. Here, we propose a unitary concept that, leveraging a cross-species definition of prefrontal regions, explains how prefrontal ensembles adaptively regulate and efficiently coordinate multiple processes in distinct cognitive behaviors.

Perception of color in primates: A conceptual color neurons hypothesis

Perception of color by humans and other primates is a complex problem, studied by neurophysiology, psychophysiology, psycholinguistics, and even philosophy. Being mostly trichromats, simian primates have three types of opsin proteins, expressed in cone neurons in the eye, which allow for the sensing of color as the physical wavelength of light. Further, in neural networks of the retina, the coding principle changes from three types of sensor proteins to two opponent channels: activity of one type of neuron encode the evolutionarily ancient blue-yellow axis of color stimuli, and another more recent evolutionary channel, encoding the axis of red-green color stimuli. Both color channels are distinctive in neural organization at all levels from the eye to the neocortex, where it is thought that the perception of color (as philosophical qualia) emerges from the activity of some neuron ensembles. Here, using data from neurophysiology as a starting point, we propose a hypothesis on how the perception of color can be encoded in the activity of certain neurons in the neocortex. These conceptual neurons, herein referred to as 'color neurons', code only the hue of the color of visual stimulus, similar to place cells and number neurons, already described in primate brains. A case study with preliminary, but direct, evidence for existing conceptual color neurons in the human brain was published in 2008. We predict that the upcoming studies in non-human primates will be more extensive and provide a more detailed description of conceptual color neurons.

Using Nonhuman Primate Models to Reverse-Engineer Prefrontal Circuit Failure Underlying Cognitive Deficits in Schizophrenia

In this chapter, I review studies in nonhuman primates that emulate the circuit failure in prefrontal cortex responsible for working memory and cognitive control deficits in schizophrenia. These studies have characterized how synaptic malfunction, typically induced by blockade of NMDAR, disrupts neural function and computation in prefrontal networks to explain errors in cognitive tasks that are seen in schizophrenia. This work is finding causal relationships between pathogenic events of relevance to schizophrenia at vastly different levels of scale, from synapses, to neurons, local, circuits, distributed networks, computation, and behavior. Pharmacological manipulation, the dominant approach in primate models, has limited construct validity for schizophrenia pathogenesis, as the disease results from a complex interplay between environmental, developmental, and genetic factors. Genetic manipulation replicating schizophrenia risk is more advanced in rodent models. Nonetheless, gene manipulation in nonhuman primates is rapidly advancing, and primate developmental models have been established. Integration of large scale neural recording, genetic manipulation, and computational modeling in nonhuman primates holds considerable potential to provide a crucial schizophrenia model moving forward. Data generated by this approach is likely to fill several crucial gaps in our understanding of the causal sequence leading to schizophrenia in humans. This causal chain presents a vexing problem largely because it requires understanding how events at very different levels of scale relate to one another, from genes to circuits to cognition to social interactions. Nonhuman primate models excel here. They optimally enable discovery of causal relationships across levels of scale in the brain that are relevant to cognitive deficits in schizophrenia. The mechanistic understanding of prefrontal circuit failure they promise to provide may point the way to more effective therapeutic interventions to restore function to prefrontal networks in the disease.

Theory of mind tested by implicit false belief: a simple and full-fledged mental state attribution

About 40 years have passed since 'theory of mind (ToM)' research started. The false-belief test is used as a litmus test for ToM ability. The implicit false-belief test has renewed views of ToM in several disciplines, including psychology, psychiatry, and neuroscience. Many important questions have been considered via the paradigm of implicit false belief. We recently addressed the phylogenetic and physiological aspects of ToM using a version of this paradigm combined with the chemogenetic technique on Old World monkeys. We sought to create animal models for autism that exhibit behavioral phenotypes similar to human symptoms. The simultaneous manipulation of neural circuits and assessments of changes in phenotypes can help identify the causal neural substrate of ToM.

Interindividual differences in intergenerational sustainable behavior are associated with cortical thickness of the dorsomedial and dorsolateral prefrontal cortex

Intergenerational sustainability requires people of the present generation to make sacrifices today to benefit others of future generations (e.g. mitigating climate change, reducing public debt). Individuals vary greatly in their intergenerational sustainability, and the cognitive and neural sources of these interindividual differences are not yet well understood. We here combined neuroscientific and behavioral methods by assessing interindividual differences in cortical thickness and by using a common-pool resource paradigm with intergenerational contingencies. This enabled us to look for objective, stable, and trait-like neural markers of interindividual differences in consequential intergenerational behavior. We found that individuals behaving sustainably (vs. unsustainably) were marked by greater cortical thickness of the dorsomedial and dorsolateral prefrontal cortex. Given that these brain areas are involved in perspective-taking and self-control and supported by mediation analyses, we speculate that greater cortical thickness of these brain areas better enable individuals to take the perspective of future generations and to resist temptations to maximize personal benefits that incur costs for future generations. By meeting recent calls for the contribution of neuroscience to sustainability research, it is our hope that the present study advances the transdisciplinary understanding of interindividual differences in intergenerational sustainability.

The (un)learning of social functions and its significance for mental health

Social interactions are dynamic, context-dependent, and reciprocal events that influence prospective strategies and require constant practice and adaptation. This complexity of social interactions creates several research challenges. We propose a new framework encouraging future research to investigate not only individual differences in capacities relevant for social functioning and their underlying mechanisms, but also the flexibility to adapt or update one's social abilities. We suggest three key capacities relevant for social functioning: (1) social perception, (2) sharing emotions or empathizing, and (3) mentalizing. We elaborate on how adaptations in these capacities may be investigated on behavioral and neural levels. Research on these flexible adaptations of one's social behavior is needed to specify how humans actually "learn to be social". Learning to adapt implies plasticity of the relevant brain networks involved in the underlying social processes, indicating that social abilities are malleable for different contexts. To quantify such measures, researchers need to find ways to investigate learning through dynamic changes in adaptable social paradigms and examine several factors influencing social functioning within the three aformentioned social key capacities. This framework furthers insight concerning individual differences, provides a holistic approach to social functioning, and may improve interventions for ameliorating social abilities in patients.

Timing matters: disentangling the neurocognitive sequence of mentalizing

A recent electrocorticographic study by Tan et al. makes an important contribution to understanding the processes involved in mentalizing by adding the temporal dimension to the brain network of mentalizing. Combined with multivariate methods, this approach has the potential to unveil the precise representations underlying mentalizing and their functional interplay.

Neural basis of prosocial behavior

The ability to behave in ways that benefit other individuals' well-being is among the most celebrated human characteristics crucial for social cohesiveness. Across mammalian species, animals display various forms of prosocial behaviors - comforting, helping, and resource sharing - to support others' emotions, goals, and/or material needs. In this review, we provide a cross-species view of the behavioral manifestations, proximate and ultimate drives, and neural mechanisms of prosocial behaviors. We summarize key findings from recent studies in humans and rodents that have shed light on the neural mechanisms underlying different processes essential for prosocial interactions, from perception and empathic sharing of others' states to prosocial decisions and actions.

Mirror neurons 30 years later: implications and applications

Mirror neurons (MNs) were first described in a seminal paper in 1992 as a class of monkey premotor cells discharging during both action execution and observation. Despite their debated origin and function, recent studies in several species, from birds to humans, revealed that beyond MNs properly so called, a variety of cell types distributed among multiple motor, sensory, and emotional brain areas form a 'mirror mechanism' more complex and flexible than originally thought, which has an evolutionarily conserved role in social interaction. Here, we trace the current limits and envisage the future trends of this discovery, showing that it inspired translational research and the development of new neurorehabilitation approaches, and constitutes a point of no return in social and affective neuroscience.

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

Medial and orbital frontal cortex in decision-making and flexible behavior

The medial frontal cortex and adjacent orbitofrontal cortex have been the focus of investigations of decision-making, behavioral flexibility, and social behavior. We review studies conducted in humans, macaques, and rodents and argue that several regions with different functional roles can be identified in the dorsal anterior cingulate cortex, perigenual anterior cingulate cortex, anterior medial frontal cortex, ventromedial prefrontal cortex, and medial and lateral parts of the orbitofrontal cortex. There is increasing evidence that the manner in which these areas represent the value of the environment and specific choices is different from subcortical brain regions and more complex than previously thought. Although activity in some regions reflects distributions of reward and opportunities across the environment, in other cases, activity reflects the structural relationships between features of the environment that animals can use to infer what decision to take even if they have not encountered identical opportunities in the past.

Meta-analysis of human prediction error for incentives, perception, cognition, and action

Prediction errors (PEs) are a keystone for computational neuroscience. Their association with midbrain neural firing has been confirmed across species and has inspired the construction of artificial intelligence that can outperform humans. However, there is still much to learn. Here, we leverage the wealth of human PE data acquired in the functional neuroimaging setting in service of a deeper understanding, using an MKDA (multi-level kernel-based density) meta-analysis. Studies were identified with Google Scholar, and we included studies with healthy adult participants that reported activation coordinates corresponding to PEs published between 1999-2018. Across 264 PE studies that have focused on reward, punishment, action, cognition, and perception, consistent with domain-general theoretical models of prediction error we found midbrain PE signals during cognitive and reward learning tasks, and an insula PE signal for perceptual, social, cognitive, and reward prediction errors. There was evidence for domain-specific error signals--in the visual hierarchy during visual perception, and the dorsomedial prefrontal cortex during social inference. We assessed bias following prior neuroimaging meta-analyses and used family-wise error correction for multiple comparisons. This organization of computation by region will be invaluable in building and testing mechanistic models of cognitive function and dysfunction in machines, humans, and other animals. Limitations include small sample sizes and ROI masking in some included studies, which we addressed by weighting each study by sample size, and directly comparing whole brain vs. ROI-based results.

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.

Social-affective features drive human representations of observed actions

Humans observe actions performed by others in many different visual and social settings. What features do we extract and attend when we view such complex scenes, and how are they processed in the brain? To answer these questions, we curated two large-scale sets of naturalistic videos of everyday actions and estimated their perceived similarity in two behavioral experiments. We normed and quantified a large range of visual, action-related, and social-affective features across the stimulus sets. Using a cross-validated variance partitioning analysis, we found that social-affective features predicted similarity judgments better than, and independently of, visual and action features in both behavioral experiments. Next, we conducted an electroencephalography experiment, which revealed a sustained correlation between neural responses to videos and their behavioral similarity. Visual, action, and social-affective features predicted neural patterns at early, intermediate, and late stages, respectively, during this behaviorally relevant time window. Together, these findings show that social-affective features are important for perceiving naturalistic actions and are extracted at the final stage of a temporal gradient in the brain.

Metacognition and mentalizing are associated with distinct neural representations of decision uncertainty

Metacognition and mentalizing are both associated with meta-level mental state representations. Conventionally, metacognition refers to monitoring one’s own cognitive processes, while mentalizing refers to monitoring others’ cognitive processes. However, this self-other dichotomy is insufficient to delineate the 2 high-level mental processes. We here used functional magnetic resonance imaging (fMRI) to systematically investigate the neural representations of different levels of decision uncertainty in monitoring different targets (the current self, the past self [PS], and others) performing a perceptual decision-making task. Our results reveal diverse formats of internal mental state representations of decision uncertainty in mentalizing, separate from the associations with external cue information. External cue information was commonly represented in the right inferior parietal lobe (IPL) across the mentalizing tasks. However, the internal mental states of decision uncertainty attributed to others were uniquely represented in the dorsomedial prefrontal cortex (dmPFC), rather than the temporoparietal junction (TPJ) that also represented the object-level mental states of decision inaccuracy attributed to others. Further, the object-level and meta-level mental states of decision uncertainty, when attributed to the PS, were represented in the precuneus and the lateral frontopolar cortex (lFPC), respectively. In contrast, the dorsal anterior cingulate cortex (dACC) represented currently experienced decision uncertainty in metacognition, and also uncertainty about the estimated decision uncertainty (estimate uncertainty), but not the estimated decision uncertainty per se in mentalizing. Hence, our findings identify neural signatures to clearly delineate metacognition and mentalizing and further imply distinct neural computations on internal mental states of decision uncertainty during metacognition and mentalizing.

The relationship between metacognition and mentalizing is still a matter of debate, as both are associated with meta-representations. This study adapts a task paradigm used in metacognition to apply in mentalizing and compares the neural representations of decision uncertainty in metacognition and mentalizing.

Prefrontal cortex

The prefrontal cortex is a well-studied but, in terms of understanding what it is for, deeply divisive part of the brain located at the front of the head. Perhaps the least controversial feature of the prefrontal cortex is its complexity. The prefrontal cortex is anatomically, functionally, and computationally complex. It is anatomically complex, containing a number of subregions each sending and receiving projections to a unique set of other cortical and subcortical areas. This interconnectivity presents a serious challenge to efforts to localize function to prefrontal cortex, because it can seem as though information flows everywhere all at once in prefrontal networks. Perhaps as a result, prefrontal cortex is also computationally complex: working memory, abstraction, sensory attention, value-based decision making, planning, and motor control are all functions that have been attributed to the prefrontal cortex. This diversity of functions is likely to reflect the diversity of brain regions that prefrontal cortex communicates with while carrying out the computations it performs to influence behavior.

Resting functional connectivity of the left inferior frontal gyrus with the dorsomedial prefrontal cortex and temporoparietal junction reflects the social network size for active interactions

The size of an individual active social network is a key parameter of human social behavior and is correlated with subjective well-being. However, it remains unknown how the social network size of active interactions is represented in the brain. Here, we examined whether resting-state functional magnetic resonance imaging (fMRI) connectivity is associated with the social network size of active interactions using behavioral data of a large sample (N = 222) on Twitter. Region of interest (ROI)-to-ROI analysis, graph theory analysis, seed-based analysis, and decoding analysis together provided compelling evidence that people who have a large social network size of active interactions, as measured by "reply," show higher fMRI connectivity of the left inferior frontal gyrus with the dorsomedial prefrontal cortex and temporoparietal junction, which represents the core of the theory of mind network. These results demonstrated that people who have a large social network size of active interactions maintain activity of the identified functional connectivity in daily life, possibly providing a mechanism for efficient information transmission between the brain networks related to language and theory-of-mind.

Lacking Social Support is Associated With Structural Divergences in Hippocampus-Default Network Co-Variation Patterns

Elaborate social interaction is a pivotal asset of the human species. The complexity of people’s social lives may constitute the dominating factor in the vibrancy of many individuals’ environment. The neural substrates linked to social cognition thus appear especially susceptible when people endure periods of social isolation: here, we zoom in on the systematic inter-relationships between two such neural substrates, the allocortical hippocampus (HC) and the neocortical default network (DN). Previous human social neuroscience studies have focused on the DN, while HC subfields have been studied in most detail in rodents and monkeys. To bring into contact these two separate research streams, we directly quantified how DN subregions are coherently co-expressed with specific HC subfields in the context of social isolation. A two-pronged decomposition of structural brain scans from ∼40 000 UK Biobank participants linked lack of social support to mostly lateral subregions in the DN patterns. This lateral DN association co-occurred with HC patterns that implicated especially subiculum, presubiculum, CA2, CA3 and dentate gyrus. Overall, the subregion divergences within spatially overlapping signatures of HC–DN co-variation followed a clear segregation into the left and right brain hemispheres. Separable regimes of structural HC–DN co-variation also showed distinct associations with the genetic predisposition for lacking social support at the population level.

Modeling multiscale causal interactions between spiking and field potential signals during behavior

Objective. Brain recordings exhibit dynamics at multiple spatiotemporal scales, which are measured with spike trains and larger-scale field potential signals. To study neural processes, it is important to identify and model causal interactions not only at a single scale of activity, but also across multiple scales, i.e. between spike trains and field potential signals. Standard causality measures are not directly applicable here because spike trains are binary-valued but field potentials are continuous-valued. It is thus important to develop computational tools to recover multiscale neural causality during behavior, assess their performance on neural datasets, and study whether modeling multiscale causalities can improve the prediction of neural signals beyond what is possible with single-scale causality. Approach. We design a multiscale model-based Granger-like causality method based on directed information and evaluate its success both in realistic biophysical spike-field simulations and in motor cortical datasets from two non-human primates (NHP) performing a motor behavior. To compute multiscale causality, we learn point-process generalized linear models that predict the spike events at a given time based on the history of both spike trains and field potential signals. We also learn linear Gaussian models that predict the field potential signals at a given time based on their own history as well as either the history of binary spike events or that of latent firing rates. Main results. We find that our method reveals the true multiscale causality network structure in biophysical simulations despite the presence of model mismatch. Further, models with the identified multiscale causalities in the NHP neural datasets lead to better prediction of both spike trains and field potential signals compared to just modeling single-scale causalities. Finally, we find that latent firing rates are better predictors of field potential signals compared with the binary spike events in the NHP datasets. Significance. This multiscale causality method can reveal the directed functional interactions across spatiotemporal scales of brain activity to inform basic science investigations and neurotechnologies.

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.

Dissecting functional contributions of the social brain to strategic behavior

Social interactions routinely lead to neural activity in a "social brain network" comprising, among other regions, the temporoparietal junction (TPJ) and the dorsomedial prefrontal cortex (dmPFC). But what is the function of these areas? Are they specialized for behavior in social contexts or do they implement computations required for dealing with any reactive process, even non-living entities? Here, we use fMRI and a game paradigm separating the need for these two aspects of cognition. We find that most social-brain areas respond to both social and non-social reactivity rather than just to human opponents. However, the TPJ shows a dissociation from the dmPFC: its activity and connectivity primarily reflect context-dependent outcome processing and reactivity detection, while dmPFC engagement is linked to implementation of a behavioral strategy. Our results characterize an overarching computational property of the social brain but also suggest specialized roles for subregions of this network.

Neuronal Circuits for Social Decision-Making and Their Clinical Implications

Social living facilitates individual access to rewards, cognitive resources, and objects that would not be otherwise accessible. There are, however, some drawbacks to social living, particularly when competing for scarce resources. Furthermore, variability in our ability to make social decisions can be associated with neuropsychiatric disorders. The neuronal mechanisms underlying social decision-making are beginning to be understood. The momentum to study this phenomenon has been partially carried over by the study of economic decision-making. Yet, because of the similarities between these different types of decision-making, it is unclear what is a social decision. Here, we propose a definition of social decision-making as choices taken in a context where one or more conspecifics are involved in the decision or the consequences of it. Social decisions can be conceptualized as complex economic decisions since they are based on the subjective preferences between different goods. During social decisions, individuals choose based on their internal value estimate of the different alternatives. These are complex decisions given that conspecifics beliefs or actions could modify the subject's internal valuations at every choice. Here, we first review recent developments in our collective understanding of the neuronal mechanisms and circuits of social decision-making in primates. We then review literature characterizing populations with neuropsychiatric disorders showing deficits in social decision-making and the underlying neuronal circuitries associated with these deficits.

Social Relationship Strength Modulates the Similarity of Brain-to-Brain Representations of Group Members

Within our societies, humans form co-operative groups with diverse levels of relationship quality among individual group members. In establishing relationships with others, we use attitudes and beliefs about group members and the group as a whole to establish relationships with particular members of our social networks. However, we have yet to understand how brain responses to group members facilitate relationship quality between pairs of individuals. We address this here using a round-robin interpersonal perception paradigm in which each participant was both a perceiver and target for every other member of their group in a set of 20 unique groups of between 5 and 6 members in each (total N = 111). Using functional magnetic resonance imaging, we show that measures of social relationship strength modulate the brain-to-brain multivoxel similarity patterns between pairs of participants' responses when perceiving other members of their group in regions of the brain implicated in social cognition. These results provide evidence for a brain mechanism of social cognitive processes serving interpersonal relationship strength among group members.

Dedicated Representation of Others in the Macaque Frontal Cortex: From Action Monitoring and Prediction to Outcome Evaluation

Social neurophysiology has increasingly addressed how several aspects of self and other are distinctly represented in the brain. In social interactions, the self–other distinction is fundamental for discriminating one’s own actions, intentions, and outcomes from those that originate in the external world. In this paper, we review neurophysiological experiments using nonhuman primates that shed light on the importance of the self–other distinction, focusing mainly on the frontal cortex. We start by examining how the findings are impacted by the experimental paradigms that are used, such as the type of social partner or whether a passive or active interaction is required. Next, we describe the 2 sociocognitive systems: mirror and mentalizing. Finally, we discuss how the self–other distinction can occur in different domains to process different aspects of social information: the observation and prediction of others’ actions and the monitoring of others’ rewards.

Coevolution of actions, personal norms and beliefs about others in social dilemmas

Human decision-making is affected by a diversity of factors including material cost-benefit considerations, normative and cultural influences, learning and conformity with peers and external authorities (e.g. cultural, religious, political, organisational). Also important are dynamically changing personal perceptions of the situation and beliefs about actions and expectations of others as well as psychological phenomena such as cognitive dissonance and social projection. To better understand these processes, I develop a unifying modelling framework describing the joint dynamics of actions and attitudes of individuals and their beliefs about the actions and attitudes of their groupmates. I consider which norms get internalised and which factors control beliefs about others. I predict that the long-term average characteristics of groups are largely determined by a balance between material payoffs and the values promoted by the external authority. Variation around these averages largely reflects variation in individual costs and benefits mediated by individual psychological characteristics. The efforts of an external authority to change the group behaviour in a certain direction can, counter-intuitively, have an opposite effect on individual behaviour. I consider how various factors can affect differences between groups and societies in the tightness/looseness of their social norms. I show that the most important factors are social heterogeneity, societal threat, effects of authority, cultural variation in the degree of collectivism/individualism, the population size and the subsistence style. My results can be useful for achieving a better understanding of human social behaviour and historical and current social processes, and in developing more efficient policies aiming to modify social behaviour.

The Role of the Medial Prefrontal Cortex in Moderating Neural Representations of Self and Other in Primates

As a frontal node in the primate social brain, the medial prefrontal cortex (MPFC) plays a critical role in coordinating one's own behavior with respect to that of others. Current literature demonstrates that single neurons in the MPFC encode behavior-related variables such as intentions, actions, and rewards, specifically for self and other, and that the MPFC comes into play when reflecting upon oneself and others. The social moderator account of MPFC function can explain maladaptive social cognition in people with autism spectrum disorder, which tips the balance in favor of self-centered perspectives rather than taking into consideration the perspective of others. Several strands of evidence suggest a hypothesis that the MPFC represents different other mental models, depending on the context at hand, to better predict others' emotions and behaviors. This hypothesis also accounts for aberrant MPFC activity in autistic individuals while they are mentalizing others.