The dorsomedial prefrontal cortex computes task-invariant relative subjective value for self and other

The neural representation of metacognition in preferential decision-making

Humans regularly assess the quality of their judgements, which helps them adjust their behaviours. Metacognition is the ability to accurately evaluate one's own judgements, and it is assessed by comparing objective task performance with subjective confidence report in perceptual decisions. However, for preferential decisions, assessing metacognition in preference-based decisions is difficult because it depends on subjective goals rather than the objective criterion. Here, we develop a new index that integrates choice, reaction time, and confidence report to quantify trial-by-trial metacognitive sensitivity in preference judgements. We found that the dorsomedial prefrontal cortex (dmPFC) and the right anterior insular were more activated when participants made bad metacognitive evaluations. Our study suggests a crucial role of the dmPFC-insula network in representing online metacognitive sensitivity in preferential decisions.

On some statistical and cerebral aspects of the limits of working memory capacity in anthropoid primates, with particular reference to Pan and Homo, and their significance for human evolution

Some comparative ontogenetic data imply that effective working-memory capacity develops in ways that are independent of brain size in humans. These are interpreted better from neuroscientific considerations about the continuing development of neuronal architecture in adolescents and young adults, than from one about gross brain mass which already is reached in childhood. By contrast, working-memory capacity in Pan never develops beyond that of three- or four-year-old children. The phylogenetic divergence begs the question of whether it is any longer plausible to infer from the fossil record, that over the past two million years, an ostensibly gradual increase in endocranial volumes, assigned to the genus Homo, can be correlated in a scientifically-meaningful manner with the gradual evolution of our effective executive working memory. It is argued that whereas Pan's effective working-memory capacity is relatively similar to that of its storage working-memory, our working memory is relatively larger with deeper executive control.

A distinct cortical code for socially learned threat

Animals can learn about sources of danger while minimizing their own risk by observing how others respond to threats. However, the distinct neural mechanisms by which threats are learned through social observation (known as observational fear learning1-4 (OFL)) to generate behavioural responses specific to such threats remain poorly understood. The dorsomedial prefrontal cortex (dmPFC) performs several key functions that may underlie OFL, including processing of social information and disambiguation of threat cues5-11. Here we show that dmPFC is recruited and required for OFL in mice. Using cellular-resolution microendoscopic calcium imaging, we demonstrate that dmPFC neurons code for observational fear and do so in a manner that is distinct from direct experience. We find that dmPFC neuronal activity predicts upcoming switches between freezing and moving state elicited by threat. By combining neuronal circuit mapping, calcium imaging, electrophysiological recordings and optogenetics, we show that dmPFC projections to the midbrain periaqueductal grey (PAG) constrain observer freezing, and that amygdalar and hippocampal inputs to dmPFC opposingly modulate observer freezing. Together our findings reveal that dmPFC neurons compute a distinct code for observational fear and coordinate long-range neural circuits to select behavioural responses.

The effect of psychological distance on intertemporal choice of the reward processing: an eye-tracking investigation

This study employed eye-tracking technology to investigate how varying dimensions of psychological distance-temporal, probability, and social-affect intertemporal choice. Across three experiments, participants were asked to select between two intertemporal options while their eye movements were monitored. Findings revealed inconsistent impacts of different psychological distances on intertemporal decision-making. Increased temporal and social distances led to a preference for larger delayed rewards (Studies 1 and 3), whereas an increase in probability distance did not significantly alter choice preferences (Study 2). The research also highlighted a general pattern in information processing; as psychological distance widened, participants showed a tendency toward dimension-specific processing in making intertemporal decisions.

Functional division of the dorsal striatum based on a graph neural network

The dorsal striatum, an essential nucleus in subcortical areas, has a crucial role in controlling a variety of complex cognitive behaviors; however, few studies have been conducted in recent years to explore the functional subregions of the dorsal striatum that are significantly activated when performing multiple tasks. To explore the differences and connections between the functional subregions of the dorsal striatum that are significantly activated when performing different tasks, we propose a framework for functional division of the dorsal striatum based on a graph neural network model. First, time series information for each voxel in the dorsal striatum is extracted from acquired functional magnetic resonance imaging data and used to calculate the connection strength between voxels. Then, a graph is constructed using the voxels as nodes and the connection strengths between voxels as edges. Finally, the graph data are analyzed using the graph neural network model to functionally divide the dorsal striatum. The framework was used to divide functional subregions related to the four tasks including olfactory reward, "0-back" working memory, emotional picture stimulation, and capital investment decision-making. The results were further subjected to conjunction analysis to obtain 15 functional subregions in the dorsal striatum. The 15 different functional subregions divided based on the graph neural network model indicate that there is functional differentiation in the dorsal striatum when the brain performs different cognitive tasks. The spatial localization of the functional subregions contributes to a clear understanding of the differences and connections between functional subregions.

White matter-based brain network topological properties associated with individual impulsivity

Delay discounting (DD), a parameter derived from the intertemporal choice task, is a representative behavioral indicator of choice impulsivity. Previous research reported not only an association between DD and impulsive control disorders and negative health outcomes but also the neural correlates of DD. However, to date, there are few studies investigating the structural brain network topologies associated with individual differences in DD and whether self-reported measures (BIS-11) of impulsivity associated with DD share the same or distinct neural mechanisms is still unclear. To address these issues, here, we combined graph theoretical analysis with diffusion tensor imaging to investigate the associations between DD and the topological properties of the structural connectivity network and BIS-11 scores. Results revealed that people with a steep DD (greater impatience) had decreased small-worldness (a shift toward weaker small-worldnization) and increased degree centrality in the medial superior prefrontal cortex, associated with subjective value in the task. Though DD was associated with the BIS-11 motor impulsiveness subscale, this subscale was linked to topological properties different from DD; that is, high motor impulsiveness was associated with decreased local efficiency (less segregation) and decreased degree centrality in the precentral gyrus, involved in motor control. These findings provide insights into the systemic brain characteristics underlying individual differences in impulsivity and potential neural markers which could predict susceptibility to impulsive behaviors.

The dorsomedial prefrontal cortex represents subjective value across effort-based and risky decision-making

Decisions that require taking effort costs into account are ubiquitous in real life. The neural common currency theory hypothesizes that a particular neural network integrates different costs (e.g., risk) and rewards into a common scale to facilitate value comparison. Although there has been a surge of interest in the computational and neural basis of effort-related value integration, it is still under debate if effort-based decision-making relies on a domain-general valuation network as implicated in the neural common currency theory. Therefore, we comprehensively compared effort-based and risky decision-making using a combination of computational modeling, univariate and multivariate fMRI analyses, and data from two independent studies. We found that effort-based decision-making can be best described by a power discounting model that accounts for both the discounting rate and effort sensitivity. At the neural level, multivariate decoding analyses indicated that the neural patterns of the dorsomedial prefrontal cortex (dmPFC) represented subjective value across different decision-making tasks including either effort or risk costs, although univariate signals were more diverse. These findings suggest that multivariate dmPFC patterns play a critical role in computing subjective value in a task-independent manner and thus extend the scope of the neural common currency theory.

Development of the Paternal Brain in Humans throughout Pregnancy

Previous studies have demonstrated that paternal caregiving behaviors are reliant on neural pathways similar to those supporting maternal care. Interestingly, a greater variability exists in parental phenotypes in men than in women among individuals and mammalian species. However, less is known about when or how such variability emerges in men. We investigated the longitudinal changes in the neural, hormonal, and psychological bases of expression of paternal caregiving in humans throughout pregnancy and the first 4 months of the postnatal period. We measured oxytocin and testosterone, paternity-related psychological traits, and neural response to infant-interaction videos using fMRI in first-time fathers and childless men at three time points (early to mid-pregnancy, late pregnancy, and postnatal). We found that paternal-specific brain activity in prefrontal areas distinctly develops during middle-to-late pregnancy and is enhanced in the postnatal period. In addition, among fathers, the timing of the development of prefrontal brain activity was associated with specific parenting phenotypes.

The brain stimulation of DLPFC regulates choice preference in intertemporal choice self-other differences

Intertemporal choice requires to make decision by evaluating the value of two options consisting of different times and benefits. The dorsolateral prefrontal cortex (DLPFC) is a key brain region for modulating intertemporal choice. The aim of this study is to investigate the effect of non-invasive brain stimulation over DLPFC on intertemporal choice behavior for self and others. We used transcranial direct current stimulation (tDCS) and continuous theta burst stimulation (cTBS) to stimulate bilateral DLPFC in two experiments respectively. After stimulation, subjects made a choice between a Smaller-Sooner (SS) reward and a Larger-Later (LL) reward in intertemporal choice task. The results showed that cTBS stimulation on the left DLPFC reduced the choice preference for SS reward when individuals made choices for themselves. The cTBS stimulation caused preference difference between choosing for self and parents. But tDCS stimulation had no effect on regulating choice preference. In addition, subjects preferred SS reward for self than strangers. Time-types and monetary difference of rewards affected the choice preference. The presence of immediate time increased the choice preference of SS reward. As the monetary difference increased, the choice proportion of SS reward decreased. Our study demonstrates that brain stimulation on the left DLPFC can regulate choice preference behavior in intertemporal choice.

Neural activity tracking identity and confidence in social information

Humans learn about the environment either directly by interacting with it or indirectly by seeking information about it from social sources such as conspecifics. The degree of confidence in the information obtained through either route should determine the impact that it has on adapting and changing behaviour. We examined whether and how behavioural and neural computations differ during non-social learning as opposed to learning from social sources. Trial-wise confidence judgements about non-social and social information sources offered a window into this learning process. Despite matching exactly the statistical features of social and non-social conditions, confidence judgements were more accurate and less changeable when they were made about social as opposed to non-social information sources. In addition to subjective reports of confidence, differences were also apparent in the Bayesian estimates of participants' subjective beliefs. Univariate activity in dorsomedial prefrontal cortex and posterior temporoparietal junction more closely tracked confidence about social as opposed to non-social information sources. In addition, the multivariate patterns of activity in the same areas encoded identities of social information sources compared to non-social information sources.

Multivariate analysis differentiates intertemporal choices in both value and cognitive control network

Choices between immediate smaller reward and long-term larger reward are referred to as intertemporal choice. Numerous functional magnetic resonance imaging (fMRI) studies have investigated the neural substrates of intertemporal choice via conventional univariate analytical approaches, revealing dissociable activations of decisions involving immediately available rewards and decisions involving delayed rewards in value network. With the help of multivariate analyses, which is more sensitive for evaluating information encoded in spatially distributed patterns, we showed that fMRI activity patterns represent viable signatures of intertemporal choice, as well as individual differences while controlling for age. Notably, in addition to value network, regions from cognitive control network play prominent roles in differentiating between different intertemporal choices as well as individuals with distinct discount rates. These findings provide clear evidence that substantiates the important role of value and cognitive control networks in the neural representation of one's intertemporal decisions.

A Common Neural Account for Social and Nonsocial Decisions

To date, social and nonsocial decisions have been studied largely in isolation. Consequently, the extent to which social and nonsocial forms of decision uncertainty are integrated using shared neurocomputational resources remains elusive. Here, we address this question using simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) in healthy human participants (young adults of both sexes) and a task in which decision evidence in social and nonsocial contexts varies along comparable scales. First, we identify time-resolved build-up of activity in the EEG, akin to a process of evidence accumulation (EA), across both contexts. We then use the endogenous trial-by-trial variability in the slopes of these accumulating signals to construct parametric fMRI predictors. We show that a region of the posterior-medial frontal cortex (pMFC) uniquely explains trial-wise variability in the process of evidence accumulation in both social and nonsocial contexts. We further demonstrate a task-dependent coupling between the pMFC and regions of the human valuation system in dorso-medial and ventro-medial prefrontal cortex across both contexts. Finally, we report domain-specific representations in regions known to encode the early decision evidence for each context. These results are suggestive of a domain-general decision-making architecture, whereupon domain-specific information is likely converted into a "common currency" in medial prefrontal cortex and accumulated for the decision in the pMFC.SIGNIFICANCE STATEMENT Little work has directly compared social-versus-nonsocial decisions to investigate whether they share common neurocomputational origins. Here, using combined electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) and computational modeling, we offer a detailed spatiotemporal account of the neural underpinnings of social and nonsocial decisions. Specifically, we identify a comparable mechanism of temporal evidence integration driving both decisions and localize this integration process in posterior-medial frontal cortex (pMFC). We further demonstrate task-dependent coupling between the pMFC and regions of the human valuation system across both contexts. Finally, we report domain-specific representations in regions encoding the early, domain-specific, decision evidence. These results suggest a domain-general decision-making architecture, whereupon domain-specific information is converted into a common representation in the valuation system and integrated for the decision in the pMFC.

Neural implementation of computational mechanisms underlying the continuous trade-off between cooperation and competition

Social interactions evolve continuously. Sometimes we cooperate, sometimes we compete, while at other times we strategically position ourselves somewhere in between to account for the ever-changing social contexts around us. Research on social interactions often focuses on a binary dichotomy between competition and cooperation, ignoring people's evolving shifts along a continuum. Here, we develop an economic game - the Space Dilemma - where two players change their degree of cooperativeness over time in cooperative and competitive contexts. Using computational modelling we show how social contexts bias choices and characterise how inferences about others' intentions modulate cooperativeness. Consistent with the modelling predictions, brain regions previously linked to social cognition, including the temporo-parietal junction, dorso-medial prefrontal cortex and the anterior cingulate gyrus, encode social prediction errors and context-dependent signals, correlating with shifts along a cooperation-competition continuum. These results provide a comprehensive account of the computational and neural mechanisms underlying the continuous trade-off between cooperation and competition.

Localized task-invariant emotional valence encoding revealed by intracranial recordings

The ability to distinguish between negative, positive and neutral valence is a key part of emotion perception. Emotional valence has conceptual meaning that supersedes any particular type of stimulus, although it is typically captured experimentally in association with particular tasks. We sought to identify neural encoding for task-invariant emotional valence. We evaluated whether high-gamma responses (HGRs) to visually displayed words conveying emotions could be used to decode emotional valence from HGRs to facial expressions. Intracranial electroencephalography was recorded from 14 individuals while they participated in two tasks, one involving reading words with positive, negative, and neutral valence, and the other involving viewing faces with positive, negative, and neutral facial expressions. Quadratic discriminant analysis was used to identify information in the HGR that differentiates the three emotion conditions. A classifier was trained on the emotional valence labels from one task and was cross-validated on data from the same task (within-task classifier) as well as the other task (between-task classifier). Emotional valence could be decoded in the left medial orbitofrontal cortex and middle temporal gyrus, both using within-task classifiers and between-task classifiers. These observations suggest the presence of task-independent emotional valence information in the signals from these regions.

Brain Regions Activity During a Deceitful Monetary Game: An fMRI Study

: Finding neural correlates underlying deception may have implementations in judicial, security, and financial settings. Telling a successful lie may activate different brain regions associated with risk evaluation, subsequent reward/punishment possibility, decision-making, and theory of mind (ToM). Many other protocols have been developed to study individuals who proceed with deception under instructed laboratory conditions. However, no protocol has practiced lying in a real-life environment. We performed a functional MRI using a 3Tesla machine on 31 healthy individuals to detect the participants who successfully lie in a previously-designed game to earn or lose the monetary reward. The results revealed that lying results in an augmented activity in the right dorsolateral and right dorsomedial prefrontal cortices, the right inferior parietal lobule, bilateral inferior frontal gyri, and right anterior cingulate cortex. The findings would contribute to forensic practices regarding the detection of a deliberate lie. They may also have implications for guilt detection, social cognition, and the societal notions of responsibility.

The orbitofrontal cortex represents advantageous choice in the Iowa gambling task

A good‐based model, the central neurobiological model of economic decision‐making, proposes that the orbitofrontal cortex (OFC) represents binary choice outcome, that is, the chosen good. A good is defined by a group of determinants characterizing the conditions in which the commodity is offered, including commodity type, cost, risk, time delay, and ambiguity. Previous studies have found that the OFC represents the binary choice outcome in decision‐making tasks involving commodity type, cost, risk, and delay. Real‐life decisions are often complex and involve uncertainty, rewards, and penalties; however, whether the OFC represents binary choice outcomes in a complex decision‐making situation, for example, Iowa gambling task (IGT), remains unclear. Here, we propose that the OFC represents binary choice outcome, that is, advantageous choice versus disadvantageous choice, in the IGT. We propose two hypotheses: first, the activity pattern in the human OFC represents an advantageous choice; and second, choice induces an OFC‐related functional network. Using functional magnetic resonance imaging and advanced machine‐learning tools, we found that the OFC represented an advantageous choice in the IGT. The OFC representation of advantageous choice was related to decision‐making performance. Choice modulated the functional connectivity between the OFC and the superior medial gyrus. In conclusion, the OFC represents an advantageous choice during the IGT. In the framework of a good‐based model, the results extend the role of the OFC to complex decision‐making situation when making a binary choice.

Stimulation of the dorsolateral prefrontal cortex modulates muscle sympathetic nerve activity and blood pressure in humans

Introduction

Muscle sympathetic nerve activity (MSNA) controls the diameter of arterioles in skeletalmuscle, contributing importantly to the beat-to-beat regulation of blood pressure (BP). Although brain imaging studies have shown that bursts of MSNA originate in the rostral ventrolateral medulla, other subcortical and cortical structures-including the dorsolateral prefrontal cortex (dlPFC)-contribute.

Hypothesis

We tested the hypothesis that MSNA and BP could be modulated by stimulating the dlPFC.

Method

dlPFC. In 22 individuals MSNA was recorded via microelectrodes inserted into the common peroneal nerve, together with continuous BP, electrocardiographic, and respiration.Stimulation of the right (n=22) or left dlPFC (n=10) was achieved using transcranial alternating current (tcACS; +2 to -2mA, 0.08 Hz,100 cycles), applied between the nasion and electrodes over the F3 or F4 EEG sites on the scalp.

Results

Sinusoidal stimulation of either dlPFC caused cyclicmodulation of MSNA, BP and heart rate, and a significant increase in BP.

Conclusion

We have shown, for the first time, that tcACS of the dlPFC in awake humans causes partial entrainment of MSNA, heart rate and BP, arguing for an important role of this higher-level cortical area in the control of cardiovascular function.

Cortical ensembles orchestrate social competition through hypothalamic outputs

Most social species self-organize into dominance hierarchies^1,2, which decreases aggression and conserves energy^3,4, but it is not clear how individuals know their social rank. We have only begun to learn how the brain represents social rank^5-9 and guides behaviour on the basis of this representation. The medial prefrontal cortex (mPFC) is involved in social dominance in rodents^7,8 and humans^10,11. Yet, precisely how the mPFC encodes relative social rank and which circuits mediate this computation is not known. We developed a social competition assay in which mice compete for rewards, as well as a computer vision tool (AlphaTracker) to track multiple, unmarked animals. A hidden Markov model combined with generalized linear models was able to decode social competition behaviour from mPFC ensemble activity. Population dynamics in the mPFC predicted social rank and competitive success. Finally, we demonstrate that mPFC cells that project to the lateral hypothalamus promote dominance behaviour during reward competition. Thus, we reveal a cortico-hypothalamic circuit by which the mPFC exerts top-down modulation of social dominance.

Prefrontal theta phase-dependent rTMS-induced plasticity of cortical and behavioral responses in human cortex

BACKGROUND

Prefrontal theta oscillations are involved in neuronal information transfer and retention. Phases along the theta cycle represent varied excitability states, whereby high-excitability states correspond to high-frequency neuronal activity and heightened capacity for plasticity induction, as demonstrated in animal studies. Human studies corroborate this model and suggest a core role of prefrontal theta activity in working memory (WM).

OBJECTIVE/HYPOTHESIS

We aimed at modulating prefrontal neuronal excitability and WM performance in healthy humans, using real-time EEG analysis for triggering repetitive transcranial magnetic stimulation (rTMS) theta-phase synchronized to the left dorsomedial prefrontal cortex.

METHODS

16 subjects underwent 3 different rTMS interventions on separate days, with pulses triggered according to the individual's real-time EEG activity: 400 rTMS gamma-frequency (100 Hz) triplet bursts applied during either the negative peak of the prefrontal theta oscillation, the positive peak, or at random phase. Changes in cortical excitability were assessed with EEG responses following single-pulse TMS, and behavioral effects by using a WM task.

RESULTS

Negative-peak rTMS increased single-pulse TMS-induced prefrontal theta power and theta-gamma phase-amplitude coupling, and decreased WM response time. In contrast, positive-peak rTMS decreased prefrontal theta power, while no changes were observed after random-phase rTMS.

CONCLUSION

Findings point to the feasibility of EEG-TMS technology in a theta-gamma phase-amplitude coupling mode for effectively modifying WM networks in human prefrontal cortex, with potential for therapeutic applications.

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.

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.

Posterior medial frontal cortex regulates sympathy: A TMS study

Harm to some elicits greater sympathy than harm to others. Here, we examine the role of posterior medial frontal cortex (PMFC) in regulating sympathy, and explore the potential role of PMFC in the related phenomena of mentalizing and representing others as connected with oneself. We down-regulated either PMFC or a control region (middle temporal visual area), then assessed feelings of sympathy for and self-other overlap with two characters described as having suffered physical harm, and who were framed as adversarial or affiliative, respectively. We also measured mentalizing performance with regard to inferring the cognitive and affective states of the adversarial character. As hypothesized, down-regulating PMFC increased sympathy for both characters. Whereas we had predicted that down-regulating PMFC would decrease mentalizing ability given the postulated role of PMFC in the mentalizing network, participants in the PMFC down-regulation condition evinced greater second-order cognitive inference ability relative to controls. We observed no effect of the TMS manipulation on self-other overlap, although sympathy and self-other overlap were positively correlated. These findings are discussed as they may inform understanding of the functional role(s) of PMFC in regulating responses broadly linked with empathy.

Inferences on a multidimensional social hierarchy use a grid-like code

Generalizing experiences to guide decision-making in novel situations is a hallmark of flexible behavior. Cognitive maps of an environment or task can theoretically afford such flexibility, but direct evidence has proven elusive. In this study, we found that discretely sampled abstract relationships between entities in an unseen two-dimensional social hierarchy are reconstructed into a unitary two-dimensional cognitive map in the hippocampus and entorhinal cortex. We further show that humans use a grid-like code in entorhinal cortex and medial prefrontal cortex for inferred direct trajectories between entities in the reconstructed abstract space during discrete decisions. These grid-like representations in the entorhinal cortex are associated with decision value computations in the medial prefrontal cortex and temporoparietal junction. Collectively, these findings show that grid-like representations are used by the human brain to infer novel solutions, even in abstract and discrete problems, and suggest a general mechanism underpinning flexible decision-making and generalization.

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.

Seven computations of the social brain

The social environment presents the human brain with the most complex information processing demands. The computations that the brain must perform occur in parallel, combine social and nonsocial cues, produce verbal and nonverbal signals and involve multiple cognitive systems, including memory, attention, emotion and learning. This occurs dynamically and at timescales ranging from milliseconds to years. Here, we propose that during social interactions, seven core operations interact to underwrite coherent social functioning; these operations accumulate evidence efficiently-from multiple modalities-when inferring what to do next. We deconstruct the social brain and outline the key components entailed for successful human-social interaction. These include (i) social perception; (ii) social inferences, such as mentalizing; (iii) social learning; (iv) social signaling through verbal and nonverbal cues; (v) social drives (e.g. how to increase one's status); (vi) determining the social identity of agents, including oneself and (vii) minimizing uncertainty within the current social context by integrating sensory signals and inferences. We argue that while it is important to examine these distinct aspects of social inference, to understand the true nature of the human social brain, we must also explain how the brain integrates information from the social world.

Human dorsomedial prefrontal cortex delineates the self and other against the tendency to form interdependent social representations

In this issue of Neuron, using non-invasive brain stimulation, Wittmann et al. (2021) highlight a causal role of the dorsomedial prefrontal cortex in keeping separate estimations for the self and others, protecting against a default human tendency to form interdependent social representations.

Causal manipulation of self-other mergence in the dorsomedial prefrontal cortex

To navigate social environments, people must simultaneously hold representations about their own and others’ abilities. During self-other mergence, people estimate others’ abilities not only on the basis of the others’ past performance, but the estimates are also influenced by their own performance. For example, if we perform well, we overestimate the abilities of those with whom we are co-operating and underestimate competitors. Self-other mergence is associated with specific activity patterns in the dorsomedial prefrontal cortex (dmPFC). Using a combination of non-invasive brain stimulation, functional magnetic resonance imaging, and computational modeling, we show that dmPFC neurostimulation silences these neural signatures of self-other mergence in relation to estimation of others’ abilities. In consequence, self-other mergence behavior increases, and our assessments of our own performance are projected increasingly onto other people. This suggests an inherent tendency to form interdependent social representations and a causal role of the dmPFC in separating self and other representations.

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During self-other mergence (SOM), people confuse one’s own with another’s performance

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Brain stimulation over dorsomedial prefrontal cortex (dmPFC) alters neural SOM

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Brain stimulation over dmPFC simultaneously alters behavioral SOM

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This suggests a causal role of dmPFC in separating self and other representations

Prefrontal Theta-Phase Synchronized Brain Stimulation With Real-Time EEG-Triggered TMS

Background

Theta-band neuronal oscillations in the prefrontal cortex are associated with several cognitive functions. Oscillatory phase is an important correlate of excitability and phase synchrony mediates information transfer between neuronal populations oscillating at that frequency. The ability to extract and exploit the prefrontal theta rhythm in real time in humans would facilitate insight into neurophysiological mechanisms of cognitive processes involving the prefrontal cortex, and development of brain-state-dependent stimulation for therapeutic applications.

Objectives

We investigate individual source-space beamforming-based estimation of the prefrontal theta oscillation as a method to target specific phases of the ongoing theta oscillations in the human dorsomedial prefrontal cortex (DMPFC) with real-time EEG-triggered transcranial magnetic stimulation (TMS). Different spatial filters for extracting the prefrontal theta oscillation from EEG signals are compared and additional signal quality criteria are assessed to take into account the dynamics of this cortical oscillation.

Methods

Twenty two healthy participants were recruited for anatomical MRI scans and EEG recordings with 18 composing the final analysis. We calculated individual spatial filters based on EEG beamforming in source space. The extracted EEG signal was then used to simulate real-time phase-detection and quantify the accuracy as compared to post-hoc phase estimates. Different spatial filters and triggering parameters were compared. Finally, we validated the feasibility of this approach by actual real-time triggering of TMS pulses at different phases of the prefrontal theta oscillation.

Results

Higher phase-detection accuracy was achieved using individualized source-based spatial filters, as compared to an average or standard Laplacian filter, and also by detecting and avoiding periods of low theta amplitude and periods containing a phase reset. Using optimized parameters, prefrontal theta-phase synchronized TMS of DMPFC was achieved with an accuracy of ±55°.

Conclusion

This study demonstrates the feasibility of triggering TMS pulses during different phases of the ongoing prefrontal theta oscillation in real time. This method is relevant for brain state-dependent stimulation in human studies of cognition. It will also enable new personalized therapeutic repetitive TMS protocols for more effective treatment of neuropsychiatric disorders.

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.

Multivariable pattern classification differentiates relational self-esteem from personal self-esteem

Relational self-esteem (RSE) refers to one’s sense of self-worth based on the relationship with significant others, such as family and best friends. Although previous neuroimaging research has investigated the neural processes of RSE, it is less clear how RSE is represented in multivariable neural patterns. Being able to identify a stable RSE signature could contribute to knowledge about relational self-worth. Here, using multivariate pattern classification to differentiate RSE from personal self-esteem (PSE), which pertains to self-worth derived from personal attributes, we obtained a stable diagnostic signature of RSE relative to PSE. We found that multivariable neural activities in the superior/middle temporal gyrus, precuneus, posterior cingulate cortex, dorsal medial Prefrontal Cortex (dmPFC) and temporo-parietal junction were responsible for diagnosis of RSE, suggesting that the evaluation of RSE involves the retrieval of relational episodic memory, perspective-taking and value calculation. Further, these diagnostic neural signatures were able to sensitively decode neural activities related to RSE in another independent test sample, indicating the reliability of the brain state represented. By providing a reliable multivariate brain pattern for RSE relative to PSE, our results informed more cognitively prominent processing of RSE than that of PSE and enriched our knowledge about how relational self-worth is generated in the brain.

Self-reference Network-Related Interactions During the Process of Cognitive Impairment in the Early Stages of Alzheimer's Disease

Background: Normal establishment of cognition occurs after forming a sensation to stimuli from internal or external cues, in which self-reference processing may be partially involved. However, self-reference processing has been less studied in the Alzheimer’s disease (AD) field within the self-reference network (SRN) and has instead been investigated within the default-mode network (DMN). Differences between these networks have been proven in the last decade, while ultra-early diagnoses have increased. Therefore, investigation of the altered pattern of SRN is significantly important, especially in the early stages of AD.

Methods: A total of 65 individuals, including 43 with mild cognitive impairment (MCI) and 22 cognitively normal individuals, participated in this study. The SRN, dorsal attention network (DAN), and salience network (SN) were constructed with resting-state functional magnetic resonance imaging (fMRI), and voxel-based analysis of variance (ANOVA) was used to explore significant regions of network interactions. Finally, the correlation between the network interactions and clinical characteristics was analyzed.

Results: We discovered four interactions among the three networks, with the SRN showing different distributions in the left and right hemispheres from the DAN and SN and modulated interactions between them. Group differences in the interactions that were impaired in MCI patients indicated that the degree of damage was most severe in the SRN, least severe in the SN, and intermediate in the DAN. The two SRN-related interactions showed positive effects on the executive and memory performances of MCI patients with no overlap with the clinical assessments performed in this study.

Conclusion: This study is the first and primary evidence of SRN interactions related to MCI patients’ functional performance. The influence of the SRN in the ultra-early stages of AD is nonnegligible. There are still many unknowns regarding the contribution of the SRN in AD progression, and we strongly recommend future research in this area.

The relationship between apathy and impulsivity in large population samples

Apathy and impulsivity are debilitating conditions associated with many neuropsychiatric conditions, and expressed to variable degrees in healthy people. While some theories suggest that they lie at different ends of a continuum, others suggest their possible co-existence. Surprisingly little is known, however, about their empirical association in the general population. Here, gathering data from six large studies (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$n = 3755$$\end{document}n=3755), we investigated the relationship between measures of apathy and impulsivity in young adults. The questionnaires included commonly used self-assessment tools—Apathy Evaluation Scale, Barratt Impulsiveness Scale (BIS-11) and UPPS-P Scale—as well as a more recent addition, the Apathy Motivation Index (AMI). Remarkably, across datasets and assessment tools, global measures of apathy and impulsivity correlated positively. However, analysis of sub-scale scores revealed a more complex relationship. Although most dimensions correlated positively with one another, there were two important exceptions revealed using the AMI scale. Social apathy was mostly negatively correlated with impulsive behaviour, and emotional apathy was orthogonal to all other sub-domains. These results suggest that at a global level, apathy and impulsivity do not exist at distinct ends of a continuum. Instead, paradoxically, they most often co-exist in young adults. Processes underlying social and emotional apathy, however, appear to be different and dissociable from behavioural apathy and impulsivity.

Expectation and dyspnea: The neurobiological basis of respiratory nocebo effects

Cues such as odours that do not per se evoke bronchoconstriction can become triggers of asthma exacerbations. Despite its clinical significance, the neural basis of this respiratory nocebo effect is unknown. We investigated this effect in a functional magnetic resonance imaging (fMRI) study involving 36 healthy volunteers. The experiment consisted of an Experience phase in which volunteers experienced dyspnea while being exposed to an odorous gas ("Histarinol"). Volunteers were told that "Histarinol" induces dyspnea by bronchoconstriction. This was compared to another odorous gas which did not evoke dyspnea. Actually, dyspnea was induced by a concealed, resistive load inserted into the breathing system. In a second, Expectation phase, Histarinol and the control gas were both followed by an identical, very mild load. Respiration parameters were continuously recorded and after each trial participants rated dyspnea intensity. Dyspnea ratings were significantly higher in Histarinol compared to control conditions, both in the Experience and in the Expectation phase, despite identical physical resistance in the Expectation phase. Insula fMRI signal matched the actual load, i.e. a significant difference between Histarinol and Control in the Experience phase, but no difference in the Expectation phase. The periaqueductal gray showed a significantly higher fMRI signal during the expectation of dyspnea. Finally, Histarinol related deactivations during the Expectation phase in the rostral anterior cingulate cortex mirror similar responses for nocebo effects in pain. These findings highlight the neural basis of expectation effects associated with dyspnea, which has important consequences for our understanding of the perception of respiratory symptoms.

Neural Computations of Threat

A host of learning, memory, and decision-making processes form the individual's response to threat and may be disrupted in anxiety and post-trauma psychopathology. Here we review the neural computations of threat, from the first encounter with a dangerous situation, through learning, storing, and updating cues that predict it, to making decisions about the optimal course of action. The overview highlights the interconnected nature of these processes and their reliance on shared neural and computational mechanisms. We propose an integrative approach to the study of threat-related processes, in which specific computations are studied across the various stages of threat experience rather than in isolation. This approach can generate new insights about the evolution, diagnosis, and treatment of threat-related psychopathology.

Social processing by the primate medial frontal cortex

The primate medial frontal cortex is comprised of several brain regions that are consistently implicated in regulating complex social behaviors. The medial frontal cortex is also critically involved in many non-social behaviors, such as those involved in reward, affective, and decision-making processes, broadly implicating the fundamental role of the medial frontal cortex in internally guided cognition. An essential question therefore is what unique contributions, if any, does the medial frontal cortex make to social behaviors? In this chapter, we outline several neural algorithms necessary for mediating adaptive social interactions and discuss selected evidence from behavioral neurophysiology experiments supporting the role of the medial frontal cortex in implementing these algorithms. By doing so, we primarily focus on research in nonhuman primates and examine several key attributes of the medial frontal cortex. Specifically, we review neuronal substrates in the medial frontal cortex uniquely suitable for enabling social monitoring, observational and vicarious learning, as well as predicting the behaviors of social partners. Moreover, by utilizing the three levels of organization in information processing systems proposed by Marr (1982) and recently adapted by Lockwood, Apps, and Chang (2020) for social information processing, we survey selected social functions of the medial frontal cortex through the lens of socially relevant algorithms and implementations. Overall, this chapter provides a broad overview of the behavioral neurophysiology literature endorsing the importance of socially relevant neural algorithms implemented by the primate medial frontal cortex for regulating social interactions.

Socially relative reward valuation in the primate brain

Reward valuation in social contexts is by nature relative rather than absolute; it is made in reference to others. This socially relative reward valuation is based on our propensity to conduct comparisons and competitions between self and other. Exploring its neural substrate has been an active area of research in human neuroimaging. More recently, electrophysiological investigation of the macaque brain has enabled us to understand neural mechanisms underlying this valuation process at single-neuron and network levels. Here I show that shared neural networks centered at the medial prefrontal cortex and dopamine-related subcortical regions are involved in this process in humans and nonhuman primates. Thus, socially relative reward valuation is mediated by cortico-subcortically coordinated activity linking social and reward brain networks.

Prefrontal-amygdala circuits in social decision-making

An increasing amount of research effort is being directed toward investigating the neural bases of social cognition from a systems neuroscience perspective. Evidence from multiple animal species is beginning to provide a mechanistic understanding of the substrates of social behaviors at multiple levels of neurobiology, ranging from those underlying high-level social constructs in humans and their more rudimentary underpinnings in monkeys to circuit-level and cell-type-specific instantiations of social behaviors in rodents. Here we review literature examining the neural mechanisms of social decision-making in humans, non-human primates and rodents, focusing on the amygdala and the medial and orbital prefrontal cortical regions and their functional interactions. We also discuss how the neuropeptide oxytocin impacts these circuits and their downstream effects on social behaviors. Overall, we conclude that regulated interactions of neuronal activity in the prefrontal-amygdala pathways critically contribute to social decision-making in the brains of primates and rodents.

Neural tracking of subjective value under riskand ambiguity in adolescence

Although many neuroimaging studies on adolescent risk taking have focused on brain activation during outcome valuation, less attention has been paid to the neural correlates of choice valuation. Subjective choice valuation may be particularly influenced by whether a choice presents risk (known probabilities) or ambiguity (unknown probabilities), which has rarely been studied in developmental samples. Therefore, we examined the neural tracking of subjective value during choice under risk and ambiguity in a large sample of adolescents (N = 188, 12–22 years). Specifically, we investigated which brain regions tracked subjective value coding under risk and ambiguity. A model-based approach to estimate individuals’ risk and ambiguity attitudes showed prominent variation in individuals’ aversions to risk and ambiguity. Furthermore, participants subjectively experienced the ambiguous options as being riskier than the risky options. Subjective value tracking under risk was coded by activation in ventral striatum and superior parietal cortex. Subjective value tracking under ambiguity was coded by dorsolateral prefrontal cortex (PFC) and superior temporal gyrus activation. Finally, overlapping activation in the dorsomedial PFC was observed for subjective value under both conditions. Overall, this is the first study to chart brain activation patterns for subjective choice valuation under risk and ambiguity in an adolescent sample, which shows that the building blocks for risk and ambiguity processing are already present in early adolescence. Finally, we highlight the potential of combining behavioral modeling with fMRI for investigating choice valuation in adolescence, which may ultimately aid in understanding who takes risks and why.

A Multi-Brain Framework for Social Interaction

Social interaction can be seen as a dynamic feedback loop that couples action, reaction, and internal cognitive processes across individual agents. A fuller understanding of the social brain requires a description of how the neural dynamics across coupled brains are linked and how they coevolve over time. We elaborate a multi-brain framework that considers social interaction as an integrated network of neural systems that dynamically shape behavior, shared cognitive states, and social relationships. We describe key findings from multi-brain experiments in humans and animal models that shed new light on the function of social circuits in health and disease. Finally, we discuss recent progress in elucidating the cellular-level mechanisms underlying inter-brain neural dynamics and outline key areas for future research.

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.

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.

Foraging optimally in social neuroscience: computations and methodological considerations

Research in social neuroscience has increasingly begun to use the tools of computational neuroscience to better understand behaviour. Such approaches have proven fruitful for probing underlying neural mechanisms. However, little attention has been paid to how the structure of experimental tasks relates to real-world decisions, and the problems that brains have evolved to solve. To go significantly beyond current understanding, we must begin to use paradigms and mathematical models from behavioural ecology, which offer insights into the decisions animals must make successfully in order to survive. One highly influential theory-marginal value theorem (MVT)-precisely characterises and provides an optimal solution to a vital foraging decision that most species must make: the patch-leaving problem. Animals must decide when to leave collecting rewards in a current patch (location) and travel somewhere else. We propose that many questions posed in social neuroscience can be approached as patch-leaving problems. A richer understanding of the neural mechanisms underlying social behaviour will be obtained by using MVT. In this 'tools of the trade' article, we outline the patch-leaving problem, the computations of MVT and discuss the application to social neuroscience. Furthermore, we consider the practical challenges and offer solutions for designing paradigms probing patch leaving, both behaviourally and when using neuroimaging techniques.