The neural and computational systems of social learning

Wanting to matter and learning to care: A neurodevelopmental window of opportunity for (Pro) social learning?

Wanting to matter-to feel socially recognized, appreciated, and capable of actions that benefit others-represents a fundamental motivation in human development. The motivational salience of mattering appears to increase in adolescence. Evidence suggests this is related to pubertal increases in the incentive salience for gaining social value and personal agency. This can provide a useful heuristic for understanding motivational proclivities (i.e. wanting to matter) that influence action-outcome learning as young adolescents are exploring and learning how to navigate increasingly complex social and relational environments. Adolescence also brings new capacities, motives, and opportunities for learning to care about and contribute to the benefit of others. Together, these create a window of opportunity: a sensitive period for learning to gain salient feelings of mattering through caring prosocial actions and valued societal contributions. Successfully discovering ways of mattering by doing things that matter to others may contribute to formative socio-emotional learning about self/other. Advances in understanding these social and relational learning processes and their neurodevelopmental underpinnings can inform strategies to improve developmental trajectories of social competence and wellbeing among adolescents growing up in a rapidly changing and increasingly techno-centric world.

The neuroscience of active learning and direct instruction

Throughout the educational system, students experiencing active learning pedagogy perform better and fail less than those taught through direct instruction. Can this be ascribed to differences in learning from a neuroscientific perspective? This review examines mechanistic, neuroscientific evidence that might explain differences in cognitive engagement contributing to learning outcomes between these instructional approaches. In classrooms, direct instruction comprehensively describes academic content, while active learning provides structured opportunities for learners to explore, apply, and manipulate content. Synaptic plasticity and its modulation by arousal or novelty are central to all learning and both approaches. As a form of social learning, direct instruction relies upon working memory. The reinforcement learning circuit, associated agency, curiosity, and peer-to-peer social interactions combine to enhance motivation, improve retention, and build higher-order-thinking skills in active learning environments. When working memory becomes overwhelmed, additionally engaging the reinforcement learning circuit improves retention, providing an explanation for the benefits of active learning. This analysis provides a mechanistic examination of how emerging neuroscience principles might inform pedagogical choices at all educational levels.

The convergence between defence and care in mammals

The motivations to protect oneself and others have often been seen as conflicting. Here, we discuss recent evidence that self-defensive mechanisms may in fact be recruited to enable the helping of others. In some instances, the defensive response to a threat may even be more decisive in promoting helping than the response to a conspecific's distress (as predicted by empathy-altruism models). In light of this evidence, we propose that neural mechanisms implicated in self-defence may have been repurposed through evolution to enable the protection of others, and that defence and care may be convergent rather than conflicting functions. Finally, we present and discuss a working model of the shared brain mechanisms implicated in defence of both self and others.

How adolescents learn to build social bonds: A developmental computational account of social explore-exploit decision-making

Building social bonds is a critical task of adolescence that affords opportunities for learning, identity formation, and social support. Failing to develop close relationships in adolescence hinders adult interpersonal functioning and contributes to problems such as loneliness and depression. During adolescence, increased reward sensitivity and greater social flexibility both contribute to healthy social development, yet we lack a clear theory of how these processes interact to support social functioning. Here, we propose synthesizing these two literatures using a computational reinforcement learning framework that recasts how adolescents pursue and learn from social rewards as a social explore-exploit problem. To become socially skilled, adolescents must balance both their efforts to form individual bonds within specific groups and manage memberships across multiple groups to maximize access to social resources. We draw on insights from sociological studies on social capital in collective networks and neurocognitive research on foraging and cooperation to describe the social explore-exploit dilemma faced by adolescents navigating a modern world with increasing access to diverse resources and group memberships. Our account provides important new directions for examining the dynamics of adolescent behavior in social groups and understanding how social value computations can support positive relationships into adulthood.

Brain structure correlates of social information use: an exploratory machine learning approach

Introduction

Individual differences in social learning impact many important decisions, from voting behavior to polarization. Prior research has found that there are consistent and stable individual differences in social information use. However, the underlying mechanisms of these individual differences are still poorly understood.

Methods

We used two complementary exploratory machine learning approaches to identify brain volumes related to individual differences in social information use.

Results and discussion

Using lasso regression and random forest regression we were able to capture linear and non-linear brain-behavior relationships. Consistent with previous studies, our results suggest there is a robust positive relationship between the volume of the left pars triangularis and social information use. Moreover, our results largely overlap with common social brain network regions, such as the medial prefrontal cortex, superior temporal sulcus, temporal parietal junction, and anterior cingulate cortex. Besides, our analyses also revealed several novel regions related to individual differences in social information use, such as the postcentral gyrus, the left caudal middle frontal gyrus, the left pallidum, and the entorhinal cortex. Together, these results provide novel insights into the neural mechanisms that underly individual differences in social learning and provide important new leads for future research.

A threat from within: Learning to fear by observing aversive bodily symptoms in others

Although observational fear learning has been implicated in the development of phobic-related fears, studies investigating observational learning of fear of bodily symptoms remain scarce. Therefore, the aim of the present study was to investigate whether fear in response to bodily symptoms can be acquired simply by observing a fearful reaction to provocation of aversive bodily symptoms in others. Forty healthy participants underwent an observational fear conditioning paradigm consisting of two phases. In the first phase, participants observed a demonstrator reacting to an aversive bodily symptom provocation (unconditioned stimulus or US, i.e., labored breathing) paired with one conditioned stimulus (CS+) but not with the other one (CS-, both CSs were geometric symbols presented on a screen the demonstrator was watching). In the second phase, participants were directly presented with the same conditioned stimuli, but in the absence of the US. Our results revealed enhanced conditioned fear responses in the beginning of the second phase to the CS + as compared to CS-, as indexed by greater skin conductance and subjective fear responses, as well as greater potentiation of startle eyeblink responses to the CS + as compared to the ITI. Taken together, these findings implicate that fear of bodily symptoms can be learned through observation of others, that is, without first-hand experience of bodily threat.

Transmission of social bias through observational learning

People often rely on social learning-learning by observing others' actions and outcomes-to form preferences in advance of their own direct experiences. Although typically adaptive, we investigated whether social learning may also contribute to the formation and spread of prejudice. In six experiments (n = 1550), we demonstrate that by merely observing interactions between a prejudiced actor and social group members, observers acquired the prejudices of the actor. Moreover, observers were unaware of the actors' bias, misattributing their acquired group preferences to the behavior of group members, despite identical behavior between groups. Computational modeling revealed that this effect was due to value shaping, whereby one's preferences are shaped by another's actions toward a target, in addition to the target's reward feedback. These findings identify social learning as a potent mechanism of prejudice formation that operates implicitly and supports the transmission of intergroup bias.

Cheerful tails: Delving into positive emotional contagion

This review delves into the phenomenon of positive emotional contagion (PEC) in rodents, an area that remains relatively understudied compared to the well-explored realm of negative emotions such as fear or pain. Rodents exhibit clear preferences for individuals expressing positive emotions over neutral counterparts, underscoring the importance of detecting and responding to positive emotional signals from others. We thoroughly examine the adaptive function of PEC, highlighting its pivotal role in social learning and environmental adaptation. The developmental aspect of the ability to interpret positive emotions is explored, intricately linked to maternal care and social interactions, with oxytocin playing a central role in these processes. We discuss the potential involvement of the reward system and draw attention to persisting gaps in our understanding of the neural mechanisms governing PEC. Presenting a comprehensive overview of the existing literature, we focus on food-related protocols such as the Social Transmission of Food Preferences paradigm and tickling behaviour. Our review emphasizes the pressing need for further research to address lingering questions and advance our comprehension of positive emotional contagion.

The influence of social feedback on reward learning in the Iowa gambling task

Learning, an important activity for both human and animals, has long been a focal point of research. During the learning process, subjects assimilate not only their own information but also information from others, a phenomenon known as social learning. While numerous studies have explored the impact of social feedback as a reward/punishment during learning, few studies have investigated whether social feedback facilitates or inhibits the learning of environmental rewards/punishments. This study aims to test the effects of social feedback on economic feedback and its cognitive processes by using the Iowa Gambling Task (IGT). One hundred ninety-two participants were recruited and categorized into one non-social feedback group and four social feedback groups. Participants in the social feedback groups were informed that after the outcome of each choice, they would also receive feedback from an online peer. This peer was a fictitious entity, with variations in identity (novice or expert) and feedback type (random or effective). The Outcome-Representation Learning model (ORL model) was used to quantify the cognitive components of learning. Behavioral results showed that both the identity of the peer and the type of feedback provided significantly influenced the deck selection, with effective social feedback increasing the ratio of chosen good decks. Results in the ORL model showed that the four social feedback groups exhibited lower learning rates for gain and loss compared to the nonsocial feedback group, which suggested, in the social feedback groups, the impact of the recent outcome on the update of value decreased. Parameters such as forgetfulness, win frequency, and deck perseverance in the expert-effective feedback group were significantly higher than those in the non-social feedback and expert-random feedback groups. These findings suggest that individuals proactively evaluate feedback providers and selectively adopt effective feedback to enhance learning.

Advances in Social Cognitive and Affective Neuroscience: Ten Highly Cited Articles Published in Brain Sciences in 2022-2023

In the realm of Social Cognitive and Affective Neuroscience, researchers employ a variety of methods to address theoretical and practical questions that focus on the intricate interplay between social perception, cognition, and emotion across diverse populations and contexts [...].

Doubling down on dual systems: A cerebellum-amygdala route towards action- and outcome-based social and affective behavior

The amygdala and cerebellum are both evolutionary preserved brain structures containing cortical as well as subcortical properties. For decades, the amygdala has been considered the fear-center of the brain, but recent advances have shown that the amygdala acts as a critical hub between cortical and subcortical systems and shapes social and affective behaviors beyond fear. Likewise, the cerebellum is a dedicated control unit that fine-tunes motor behavior to fit contextual requirements. There is however increasing evidence that the cerebellum strongly influences subcortical as well as cortical processes beyond the motor domain. These insights broadened the view on the cerebellum's functions to also include social and affective behavior. Here we explore how the amygdala and cerebellum might interact in shaping social and affective behaviors based on their roles in threat reactivity and reinforcement learning. A novel mechanistic neural framework of cerebellum-amygdala interactions will be presented which provides testable hypotheses for future social and affective neuroscientific research in humans.

Observational reinforcement learning in children and young adults

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

Political reinforcement learners

Politics can seem home to the most calculating and yet least rational elements of humanity. How might we systematically characterize this spectrum of political cognition? Here, we propose reinforcement learning (RL) as a unified framework to dissect the political mind. RL describes how agents algorithmically navigate complex and uncertain domains like politics. Through this computational lens, we outline three routes to political differences, stemming from variability in agents' conceptions of a problem, the cognitive operations applied to solve the problem, or the backdrop of information available from the environment. A computational vantage on maladies of the political mind offers enhanced precision in assessing their causes, consequences, and cures.

Kurvers RHJ. A Cognitive Computational Approach to Social and Collective Decision-Making

Collective dynamics play a key role in everyday decision-making. Whether social influence promotes the spread of accurate information and ultimately results in adaptive behavior or leads to false information cascades and maladaptive social contagion strongly depends on the cognitive mechanisms underlying social interactions. Here we argue that cognitive modeling, in tandem with experiments that allow collective dynamics to emerge, can mechanistically link cognitive processes at the individual and collective levels. We illustrate the strength of this cognitive computational approach with two highly successful cognitive models that have been applied to interactive group experiments: evidence-accumulation and reinforcement-learning models. We show how these approaches make it possible to simultaneously study (a) how individual cognition drives social systems, (b) how social systems drive individual cognition, and (c) the dynamic feedback processes between the two layers.

A prefrontal-thalamic circuit encodes social information for social recognition

Social recognition encompasses encoding social information and distinguishing unfamiliar from familiar individuals to form social relationships. Although the medial prefrontal cortex (mPFC) is known to play a role in social behavior, how identity information is processed and by which route it is communicated in the brain remains unclear. Here we report that a ventral midline thalamic area, nucleus reuniens (Re) that has reciprocal connections with the mPFC, is critical for social recognition in male mice. In vivo single-unit recordings and decoding analysis reveal that neural populations in both mPFC and Re represent different social stimuli, however, mPFC coding capacity is stronger. We demonstrate that chemogenetic inhibitions of Re impair the mPFC-Re neural synchronization and the mPFC social coding. Projection pathway-specific inhibitions by optogenetics reveal that the reciprocal connectivity between the mPFC and the Re is necessary for social recognition. These results reveal an mPFC-thalamic circuit for social information processing.

Dynamic mutual predictions during social learning: A computational and interbrain model

During social interactions, we constantly learn about the thoughts, feelings, and personality traits of our interaction partners. Learning in social interactions is critical for bond formation and acquiring knowledge. Importantly, this type of learning is typically bi-directional, as both partners learn about each other simultaneously. Here we review the literature on social learning and propose a new computational and neural model characterizing mutual predictions that take place within and between interactions. According to our model, each partner in the interaction attempts to minimize the prediction error of the self and the interaction partner. In most cases, these inferential models become similar over time, thus enabling mutual understanding to develop. At the neural level, this type of social learning may be supported by interbrain plasticity, defined as a change in interbrain coupling over time in neural networks associated with social learning, among them the mentalizing network, the observation-execution system, and the hippocampus. The mutual prediction model constitutes a promising means of providing empirically verifiable accounts of how relationships develop over time.

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.

Flexible Cultural Learning Through Action Coordination

The cultural transmission of technical know-how has proven vital to the success of our species. The broad diversity of learning contexts and social configurations, as well as the various kinds of coordinated interactions they involve, speaks to our capacity to flexibly adapt to and succeed in transmitting vital knowledge in various learning contexts. Although often recognized by ethnographers, the flexibility of cultural learning has so far received little attention in terms of cognitive mechanisms. We argue that a key feature of the flexibility of cultural learning is that both the models and learners recruit cognitive mechanisms of action coordination to modulate their behavior contingently on the behavior of their partner, generating a process of mutual adaptation supporting the successful transmission of technical skills in diverse and fluctuating learning environments. We propose that the study of cultural learning would benefit from the experimental methods, results, and insights of joint-action research and, complementarily, that the field of joint-action research could expand its scope by integrating a learning and cultural dimension. Bringing these two fields of research together promises to enrich our understanding of cultural learning, its contextual flexibility, and joint action coordination.

Normative Processing Needs Multiple Levels of Explanation: From Algorithm to Implementation

Norms are the rules about what is allowed or forbidden by social groups. A key debate for norm psychology is whether these rules arise from mechanisms that are domain-specific and genetically inherited or domain-general and deployed for many other nonnorm processes. Here we argue for the importance of assessing and testing domain-specific and domain-general processes at multiple levels of explanation, from algorithmic (psychological) to implementational (neural). We also critically discuss findings from cognitive neuroscience supporting that social and nonsocial learning processes, essential for accounts of cultural evolution, can be dissociated at these two levels. This multilevel framework can generate new hypotheses and empirical tests of cultural evolution accounts of norm processing against purely domain-specific nativist alternatives.

Nucleus accumbens core single cell ensembles bidirectionally respond to experienced versus observed aversive events

Fear learning is a critical feature of survival skills among mammals. In rodents, fear learning manifests itself through direct experience of the aversive event or social transmission of aversive stimuli such as observing and acting on conspecifics' distress. The neuronal network underlying the social transmission of information largely overlaps with the brain regions that mediate behavioral responses to aversive and rewarding stimuli. In this study, we recorded single cell activity patterns of nucleus accumbens (NAc) core neurons using in vivo optical imaging of calcium transients via miniature scopes. This cutting-edge imaging methodology not only allows us to record activity patterns of individual neurons but also lets us longitudinally follow these individual neurons across time and different behavioral states. Using this approach, we identified NAc core single cell ensembles that respond to experienced and/or observed aversive stimuli. Our results showed that experienced and observed aversive stimuli evoke NAc core ensemble activity that is largely positive, with a smaller subset of negative responses. The size of the NAc single cell ensemble response was greater for experienced aversive stimuli compared to observed aversive events. Our results also revealed sex differences in the NAc core single cell ensembles responses to experience aversive stimuli, where females showed a greater accumbal response. Importantly, we found a subpopulation within the NAc core single cell ensembles that show a bidirectional response to experienced aversive stimuli versus observed aversive stimuli (i.e., negative response to experienced and positive response to observed). Our results suggest that the NAc plays a role in differentiating somatosensory experience from social observation of aversion at a single cell level. These results have important implications for psychopathologies where social information processing is maladaptive, such as autism spectrum disorders.

Disentangling sensory precision and prior expectation of change in autism during tactile discrimination

Predictive coding theories suggest that core symptoms in autism spectrum disorders (ASD) may stem from atypical mechanisms of perceptual inference (i.e., inferring the hidden causes of sensations). Specifically, there would be an imbalance in the precision or weight ascribed to sensory inputs relative to prior expectations. Using three tactile behavioral tasks and computational modeling, we specifically targeted the implicit dynamics of sensory adaptation and perceptual learning in ASD. Participants were neurotypical and autistic adults without intellectual disability. In Experiment I, tactile detection thresholds and adaptation effects were measured to assess sensory precision. Experiments II and III relied on two-alternative forced choice tasks designed to elicit a time-order effect, where prior knowledge biases perceptual decisions. Our results suggest a subtler explanation than a simple imbalance in the prior/sensory weights, having to do with the dynamic nature of perception, that is the adjustment of precision weights to context. Compared to neurotypicals, autistic adults showed no difference in average performance and sensory sensitivity. Both groups managed to implicitly learn and adjust a prior that biased their perception. However, depending on the context, autistic participants showed no, normal or slower adaptation, a phenomenon that computational modeling of trial-to-trial responses helped us to associate with a higher expectation for sameness in ASD, and to dissociate from another observed robust difference in terms of response bias. These results point to atypical perceptual learning rather than altered perceptual inference per se, calling for further empirical and computational studies to refine the current predictive coding theories of ASD.

Resampling reduces bias amplification in experimental social networks

Large-scale social networks are thought to contribute to polarization by amplifying people's biases. However, the complexity of these technologies makes it difficult to identify the mechanisms responsible and evaluate mitigation strategies. Here we show under controlled laboratory conditions that transmission through social networks amplifies motivational biases on a simple artificial decision-making task. Participants in a large behavioural experiment showed increased rates of biased decision-making when part of a social network relative to asocial participants in 40 independently evolving populations. Drawing on ideas from Bayesian statistics, we identify a simple adjustment to content-selection algorithms that is predicted to mitigate bias amplification by generating samples of perspectives from within an individual's network that are more representative of the wider population. In two large experiments, this strategy was effective at reducing bias amplification while maintaining the benefits of information sharing. Simulations show that this algorithm can also be effective in more complex networks.

Rats respond to aversive emotional arousal of human handlers with the activation of the basolateral and central amygdala

Reading danger signals may save an animal's life, and learning about threats from others allows avoiding first-hand aversive and often fatal experiences. Fear expressed by other individuals, including those belonging to other species, may indicate the presence of a threat in the environment and is an important social cue. Humans and other animals respond to conspecifics' fear with increased activity of the amygdala, the brain structure crucial for detecting threats and mounting an appropriate response to them. It is unclear, however, whether the cross-species transmission of threat information involves similar mechanisms, e.g., whether animals respond to the aversively induced emotional arousal of humans with activation of fear-processing circuits in the brain. Here, we report that when rats interact with a human caregiver who had recently undergone fear conditioning, they show risk assessment behavior and enhanced amygdala activation. The amygdala response involves its two major parts, the basolateral and central, which detect a threat and orchestrate defensive responses. Further, we show that humans who learn about a threat by observing another aversively aroused human, similar to rats, activate the basolateral and centromedial parts of the amygdala. Our results demonstrate that rats detect the emotional arousal of recently aversively stimulated caregivers and suggest that cross-species social transmission of threat information may involve similar neural circuits in the amygdala as the within-species transmission.

Is neuroimaging ready for the classroom? A systematic review of hyperscanning studies in learning

Whether education research can be informed by findings from neuroscience studies has been hotly debated since Bruer's (1997) famous claim that neuroscience and education are "a bridge too far". However, this claim came before recent advancements in portable electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) technologies, and second-person neuroscience techniques that brought about significant headway in understanding instructor-learner interactions in the classroom. To explore whether neuroscience and education are still two very separate fields, we systematically review 15 hyperscanning studies that were conducted in real-world classrooms or that implemented a teaching-learning task to investigate instructor-learner dynamics. Findings from this investigation illustrate that inter-brain synchrony between instructor and learner is an additional and valuable dimension to understand the complex web of instructor- and learner-related variables that influence learning. Importantly, these findings demonstrate the possibility of conducting real-world classroom studies with portable neuroimaging techniques and highlight the potential of such studies in providing translatable real-world implications. Once thought of as incompatible, a successful coupling between neuroscience and education is now within sight.

Optogenetic and chemogenetic approaches reveal differences in neuronal circuits that mediate initiation and maintenance of social interaction

For social interaction to be successful, two conditions must be met: the motivation to initiate it and the ability to maintain it. This study uses both optogenetic and chemogenetic approaches to reveal the specific neural pathways that selectively influence those two social interaction components.

Reward learning improves social signal processing in autism model mice

Social and reward signal processing and their association are critical elements of social motivation. Despite the use of reward learning to improve the social interactions of patients with autism spectrum disorder (ASD), the underlying neural mechanisms are unknown. Here, we found different yet conjunct neuronal representations of social and reward signals in the mouse medial prefrontal cortex (mPFC). We also found that social signal processing is selectively disrupted, whereas reward signal processing is intact in the mPFC of Shank2-knockout mice, a mouse model of ASD. Furthermore, reward learning not only allows Shank2-knockout mice to associate social stimuli with reward availability, but it also rescues the impaired social signal processing. These findings provide insights into the neural basis for the therapeutic use of reward learning in ASD.

Algorithm-mediated social learning in online social networks

Human social learning is increasingly occurring on online social platforms, such as Twitter, Facebook, and TikTok. On these platforms, algorithms exploit existing social-learning biases (i.e., towards prestigious, ingroup, moral, and emotional information, or 'PRIME' information) to sustain users' attention and maximize engagement. Here, we synthesize emerging insights into 'algorithm-mediated social learning' and propose a framework that examines its consequences in terms of functional misalignment. We suggest that, when social-learning biases are exploited by algorithms, PRIME information becomes amplified via human-algorithm interactions in the digital social environment in ways that cause social misperceptions and conflict, and spread misinformation. We discuss solutions for reducing functional misalignment, including algorithms promoting bounded diversification and increasing transparency of algorithmic amplification.

Decoding social rewards via inter-areal coordination frequency in the brain

Vicarious reward plays a pivotal role in shaping altruism and prosociality. However, neural circuit mechanisms underlying the distinction between vicarious reward and experienced reward are poorly understood. Putnam et al. recently demonstrated that the two types of reward are represented by distinct coordination frequencies within the same cingulate-amygdala pathway.

A Brain-To-Brain Mechanism for Social Transmission of Threat Learning

Survival and adaptation in environments require swift and efficacious learning about what is dangerous. Across species, much of such threat learning is acquired socially, e.g., through the observation of others' ("demonstrators'") defensive behaviors. However, the specific neural mechanisms responsible for the integration of information shared between demonstrators and observers remain largely unknown. This dearth of knowledge is addressed by performing magnetoencephalography (MEG) neuroimaging in demonstrator-observer dyads. A set of stimuli are first shown to a demonstrator whose defensive responses are filmed and later presented to an observer, while neuronal activity is recorded sequentially from both individuals who never interacted directly. These results show that brain-to-brain coupling (BtBC) in the fronto-limbic circuit (including insula, ventromedial, and dorsolateral prefrontal cortex) within demonstrator-observer dyads predict subsequent expressions of learning in the observer. Importantly, the predictive power of BtBC magnifies when a threat is imminent to the demonstrator. Furthermore, BtBC depends on how observers perceive their social status relative to the demonstrator, likely driven by shared attention and emotion, as bolstered by dyadic pupillary coupling. Taken together, this study describes a brain-to-brain mechanism for social threat learning, involving BtBC, which reflects social relationships and predicts adaptive, learned behaviors.

Impaired social learning in patients with major depressive disorder revealed by a reinforcement learning model

Background/objective

Patients with major depressive disorder (MDD) have altered learning rates for rewards and losses in non-social learning paradigms. However, it is not well understood whether the ability to learn from social interactions is altered in MDD patients. Using reinforcement learning during the repeated Trust Game (rTG), we investigated how MDD patients learn to trust newly-met partners in MDD patients.

Method

Sixty-eight MDD patients and fifty-four controls each played as 'investor' and interacted with ten different partners. We manipulated both the level of trustworthiness by varying the chance of reciprocity (10, 30, 50, 70 and 90%) and reputation disclosure, where partners' reputation was either pre-disclosed or hidden.

Results

Our reinforcement learning model revealed that MDD patients had significantly higher learning rates for losses than the controls in both the reputation disclosure and non-disclosure condition. The difference was larger when reputation was not disclosed than disclosed. We observed no difference in learning rates for gains in either condition.

Conclusions

Our findings highlight that abnormal learning for losses underlies the social learning process in MDD patients. This abnormality is higher when situational unpredictability is high versus low. Our findings provide novel insights into social rehabilitation of MDD.

Reduced effects of social feedback on learning in Turner syndrome

Turner syndrome is a genetic condition caused by a complete or partial loss of one of the X chromosomes. Previous studies indicate that Turner syndrome is associated with challenges in social skills, but the underlying mechanisms remain largely unexplored. A possible mechanism is a reduced social influence on learning. The current study examined the impact of social and non-social feedback on learning in women with Turner syndrome (n = 35) and a sex- and age-matched control group (n = 37). Participants were instructed to earn points by repeatedly choosing between two stimuli with unequal probabilities of resulting in a reward. Mastering the task therefore required participants to learn through feedback which of the two stimuli was more likely to be rewarded. Data were analyzed using computational modeling and analyses of choice behavior. Social feedback led to a more explorative choice behavior in the control group, resulting in reduced learning compared to non-social feedback. No effects of social feedback on learning were found in Turner syndrome. The current study thus indicates that women with Turner syndrome may be less sensitive to social influences on reinforcement learning, than the general population.

Sensory cortex plasticity supports auditory social learning

Social learning (SL) through experience with conspecifics can facilitate the acquisition of many behaviors. Thus, when Mongolian gerbils are exposed to a demonstrator performing an auditory discrimination task, their subsequent task acquisition is facilitated, even in the absence of visual cues. Here, we show that transient inactivation of auditory cortex (AC) during exposure caused a significant delay in task acquisition during the subsequent practice phase, suggesting that AC activity is necessary for SL. Moreover, social exposure induced an improvement in AC neuron sensitivity to auditory task cues. The magnitude of neural change during exposure correlated with task acquisition during practice. In contrast, exposure to only auditory task cues led to poorer neurometric and behavioral outcomes. Finally, social information during exposure was encoded in the AC of observer animals. Together, our results suggest that auditory SL is supported by AC neuron plasticity occurring during social exposure and prior to behavioral performance.

Individual differences in gaze-cuing effect are associated with facial emotion recognition and social conformity

Spontaneous gaze following and the concomitant joint attention enable us to share representations of the world with others, which forms a foundation of a broad range of social cognitive processes. Although this form of social orienting has long been suggested as a critical starting point for the development of social and communicative behavior, there is limited evidence directly linking it to higher-level social cognitive processes among healthy adults. Here, using a gaze-cuing paradigm, we examined whether individual differences in gaze following tendency predict higher-order social cognition and behavior among healthy adults. We found that individuals who showed greater gaze-cuing effect performed better in recognizing others' emotion and had greater tendency to conform with group opinion. These findings provide empirical evidence supporting the fundamental role of low-level socio-attentional processes in human sociality.

Dissociation of vicarious and experienced rewards by coupling frequency within the same neural pathway

Vicarious reward, essential to social learning and decision making, is theorized to engage select brain regions similarly to experienced reward to generate a shared experience. However, it is just as important for neural systems to also differentiate vicarious from experienced rewards for social interaction. Here, we investigated the neuronal interaction between the primate anterior cingulate cortex gyrus (ACCg) and the basolateral amygdala (BLA) when social choices made by monkeys led to either vicarious or experienced reward. Coherence between ACCg spikes and BLA local field potential (LFP) selectively increased in gamma frequencies for vicarious reward, whereas it selectively increased in alpha/beta frequencies for experienced reward. These respectively enhanced couplings for vicarious and experienced rewards were uniquely observed following voluntary choices. Moreover, reward outcomes had consistently strong directional influences from ACCg to BLA. Our findings support a mechanism of vicarious reward where social agency is tagged by interareal coordination frequency within the same shared pathway.

Aggressive and psychopathic traits are linked to the acquisition of stable but imprecise hostile expectations

Individuals with hostile expectations (HEX) anticipate harm from seemingly neutral or ambiguous stimuli. However, it is unclear how HEX are acquired, and whether specific components of HEX learning can predict antisocial thought, conduct, and personality. In an online sample of healthy young individuals (n = 256, 69% women), we administered a virtual shooting task and applied computational modelling of behaviour to investigate HEX learning and its constellation of correlates. HEX acquisition was best explained by a hierarchical reinforcement learning mechanism. Crucially, we found that individuals with relatively higher self-reported aggressiveness and psychopathy developed stronger and less accurate hostile beliefs as well as larger prediction errors. Moreover, aggressive and psychopathic traits were associated with more temporally stable hostility representations. Our study thus shows that aggressiveness and psychopathy are linked with the acquisition of robust yet imprecise hostile beliefs through reinforcement learning.

How we learn social norms: a three-stage model for social norm learning

As social animals, humans are unique to make the world function well by developing, maintaining, and enforcing social norms. As a prerequisite among these norm-related processes, learning social norms can act as a basis that helps us quickly coordinate with others, which is beneficial to social inclusion when people enter into a new environment or experience certain sociocultural changes. Given the positive effects of learning social norms on social order and sociocultural adaptability in daily life, there is an urgent need to understand the underlying mechanisms of social norm learning. In this article, we review a set of works regarding social norms and highlight the specificity of social norm learning. We then propose an integrated model of social norm learning containing three stages, i.e., pre-learning, reinforcement learning, and internalization, map a potential brain network in processing social norm learning, and further discuss the potential influencing factors that modulate social norm learning. Finally, we outline a couple of future directions along this line, including theoretical (i.e., societal and individual differences in social norm learning), methodological (i.e., longitudinal research, experimental methods, neuroimaging studies), and practical issues.

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

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

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.

Learning rules of engagement for social exchange within and between groups

Globalizing economies and long-distance trade rely on individuals from different cultural groups to negotiate agreement on what to give and take. In such settings, individuals often lack insight into what interaction partners deem fair and appropriate, potentially seeding misunderstandings, frustration, and conflict. Here, we examine how individuals decipher distinct rules of engagement and adapt their behavior to reach agreements with partners from other cultural groups. Modeling individuals as Bayesian learners with inequality aversion reveals that individuals, in repeated ultimatum bargaining with responders sampled from different groups, can be more generous than needed. While this allows them to reach agreements, it also gives rise to biased beliefs about what is required to reach agreement with members from distinct groups. Preregistered behavioral (N = 420) and neuroimaging experiments (N = 49) support model predictions: Seeking equitable agreements can lead to overly generous behavior toward partners from different groups alongside incorrect beliefs about prevailing norms of what is appropriate in groups and cultures other than one's own.

Consensus design of a calibration experiment for human fear conditioning

Fear conditioning is a widely used laboratory model to investigate learning, memory, and psychopathology across species. The quantification of learning in this paradigm is heterogeneous in humans and psychometric properties of different quantification methods can be difficult to establish. To overcome this obstacle, calibration is a standard metrological procedure in which well-defined values of a latent variable are generated in an established experimental paradigm. These intended values then serve as validity criterion to rank methods. Here, we develop a calibration protocol for human fear conditioning. Based on a literature review, series of workshops, and survey of N = 96 experts, we propose a calibration experiment and settings for 25 design variables to calibrate the measurement of fear conditioning. Design variables were chosen to be as theory-free as possible and allow wide applicability in different experimental contexts. Besides establishing a specific calibration procedure, the general calibration process we outline may serve as a blueprint for calibration efforts in other subfields of behavioral neuroscience that need measurement refinement.

Inferring danger with minimal aversive experience

Learning about threats is crucial for survival and fundamentally rests upon Pavlovian conditioning. However, Pavlovian threat learning is largely limited to detecting known (or similar) threats and involves first-hand exposure to danger, which inevitably poses a risk of harm. We discuss how individuals leverage a rich repertoire of mnemonic processes that operate largely in safety and significantly expand our ability to recognize danger beyond Pavlovian threat associations. These processes result in complementary memories - acquired individually or through social interactions - that represent potential threats and the relational structure of our environment. The interplay between these memories allows danger to be inferred rather than directly learned, thereby flexibly protecting us from potential harm in novel situations despite minimal prior aversive experience.

Patterns of Arc mRNA expression in the rat brain following dual recall of fear- and reward-based socially acquired information

Learning can occur via direct experience or through observation of another individual (i.e., social learning). While research focused on understanding the neural mechanisms of direct learning is prevalent, less work has examined the brain circuitry mediating the acquisition and recall of socially acquired information. Here, we aimed to further elucidate the mechanisms underlying recall of socially acquired information by having male and female rats sequentially recall a socially transmitted food preference (STFP) and a fear association via fear conditioning by-proxy (FCbP). Brain tissue was processed for mRNA expression of the immediate early gene (IEG) Arc, which expresses in the nucleus following transcription before migrating to the cytoplasm over the next 25 min. Given this timeframe, we could identify whether Arc transcription was triggered by STFP recall, FCbP recall, or both. Contrary to past research, we found no differences in any Arc expression measures across a number of prefrontal regions and the ventral CA3 of the hippocampus between controls, demonstrators, and observers. We theorize that these results may indicate that relatively little Arc-dependent neural restructuring is taking place in the prefrontal cortices and ventral CA3 following recall of recently socially acquired information or directly acquired fear associations in these areas.

Learning from humans to build social cognition among robots

Self-organized groups of robots have generally coordinated their behaviors using quite simple social interactions. Although simple interactions are sufficient for some group behaviors, future research needs to investigate more elaborate forms of coordination, such as social cognition, to progress towards real deployments. In this perspective, we define social cognition among robots as the combination of social inference, social learning, social influence, and knowledge transfer, and propose that these abilities can be established in robots by building underlying mechanisms based on behaviors observed in humans. We review key social processes observed in humans that could inspire valuable capabilities in robots and propose that relevant insights from human social cognition can be obtained by studying human-controlled avatars in virtual environments that have the correct balance of embodiment and constraints. Such environments need to allow participants to engage in embodied social behaviors, for instance through situatedness and bodily involvement, but, at the same time, need to artificially constrain humans to the operational conditions of robots, for instance in terms of perception and communication. We illustrate our proposed experimental method with example setups in a multi-user virtual environment.

Social feedback enhances learning in Williams syndrome

Williams syndrome (WS) is a rare genetic condition characterized by high social interest and approach motivation as well as intellectual disability and anxiety. Despite the fact that social stimuli are believed to have an increased intrinsic reward value in WS, it is not known whether this translates to learning and decision making. Genes homozygously deleted in WS are linked to sociability in the general population, making it a potential model condition for understanding the social brain. Probabilistic reinforcement learning was studied with either social or non-social rewards for correct choices. Social feedback improved learning in individuals with Williams syndrome but not in typically developing controls or individuals with other intellectual disabilities. Computational modeling indicated that these effects on social feedback were mediated by a shift towards higher weight given to rewards relative to punishments and increased choice consistency. We conclude that reward learning in WS is characterized by high volatility and a tendency to learn how to avoid punishment rather than how to gain rewards. Social feedback can partly normalize this pattern and promote adaptive reward learning.

The Effect of Observing High or Low Pain on the Development of Central Sensitization

It is unknown whether watching other people in high pain increases mechanical hypersensitivity induced by pain. We applied high-frequency electrical stimulation (HFS) on the skin of healthy volunteers to induce pinprick mechanical hypersensitivity. Before HFS participants were randomly allocated to 2 groups: in the low pain group, which was the control condition, they watched a model expressing and reporting lower pain scores, in the high pain group the model expressed and reported higher scores. The 2 videos were selected on the basis of a pilot/observational study that had been conducted before. We tested the differences in perceived intensity of the HFS procedure, in the development of hypersensitivity and the role of fear and empathy. The high pain group reported on average higher pain ratings during HFS. The perceived intensity of hypersensitivity, but not the unpleasantness or the length of the area was higher in the high pain group. Our results suggest that watching a person expressing more pain during HFS increases one's own pain ratings during HFS and may weakly facilitate the development of secondary mechanical hypersensitivity, although this latter result needs replication. PERSPECTIVE: Observing a person in high pain can influence the perceived pain intensity of a procedure leading to secondary mechanical hypersensitivity, and has a weak effect on hypersensitivity itself. The role of fear remains to be elucidated.

The association between acute stress & empathy: A systematic literature review

Empathy is a fundamental component of our social-emotional experience. Over the last decade, there has been increased interest in understanding the effects of acute stress on empathy. We provide a first comprehensive-and systematic-overview identifying emerging patterns and gaps in this literature. Regarding affective empathy, there is abundant evidence for stress contagion-the 'spillover' of stress from a stressed target to an unstressed perceiver. We highlight contextual factors that can facilitate and/or undermine these effects. Fewer studies have investigated the effects of acute stress on affective empathy, revealing a nuanced picture, some evidence suggests acute stress can block contagion of other's emotions; but again contextual differences need to be considered. Regarding cognitive empathy, most studies find no conclusive effects for simplistic measures of emotion recognition; however, studies using more complex empathy tasks find that acute stress might affect cognitive empathy differentially for men and women. This review provides an important first step towards understanding how acute stress can impact social-togetherness, and aims to aid future research by highlighting (in)congruencies and outstanding questions.

Modulation of social investigation by anterior hypothalamic nucleus rhythmic neural activity

Social interactions involve both approach and avoidance toward specific individuals. Currently, the brain regions subserving these behaviors are not fully recognized. The anterior hypothalamic nucleus (AHN) is a poorly defined brain area, and recent studies have yielded contradicting conclusions regarding its behavioral role. Here we explored the role of AHN neuronal activity in regulating approach and avoidance actions during social interactions. Using electrophysiological recordings from behaving mice, we revealed that theta rhythmicity in the AHN is enhanced during affiliative interactions, but decreases during aversive ones. Moreover, the spiking activity of AHN neurons increased during the investigation of social stimuli, as compared to objects, and was modulated by theta rhythmicity. Finally, AHN optogenetic stimulation during social interactions augmented the approach toward stimuli associated with the stimulation. These results suggest the role for AHN neural activity in regulating approach behavior during social interactions, and for theta rhythmicity in mediating the valence of social stimuli.

Subjective selection and the evolution of complex culture

Why is culture the way it is? Here I argue that a major force shaping culture is subjective (cultural) selection, or the selective retention of cultural variants that people subjectively perceive as satisfying their goals. I show that people evaluate behaviors and beliefs according to how useful they are, especially for achieving goals. As they adopt and pass on those variants that seem best, they iteratively craft culture into increasingly effective-seeming forms. I argue that this process drives the development of many cumulatively complex cultural products, including effective technology, magic and ritual, aesthetic traditions, and institutions. I show that it can explain cultural dependencies, such as how certain beliefs create corresponding new practices, and I outline how it interacts with other cultural evolutionary processes. Cultural practices everywhere, from spears to shamanism, develop because people subjectively evaluate them to be effective means of satisfying regular goals.

The causal role of affect sharing in driving vicarious fear learning

Vicarious learning, i.e. learning through observing others rather than through one's own experiences, is an integral skill of social species. The aim of this study was to assess the causal role of affect sharing, an important aspect of empathy, in vicarious fear learning. N = 39 participants completed a vicarious Pavlovian fear conditioning paradigm. In the learning stage, they watched another person-the demonstrator-responding with distress when receiving electric shocks to a color cue (conditioned stimulus; CS+; a different color served as CS-). In the subsequent test stage, an increased skin conductance response (SCR) to the CS+ presented in the absence of the demonstrator indexed vicarious fear learning. Each participant completed this paradigm under two different hypnotic suggestions, which were administered to induce high or low affect sharing with the demonstrator in the learning stage, following a counterbalanced within-subject design. In the learning stage, high affect sharing resulted in stronger unconditioned SCR, increased eye gaze toward the demonstrator's face, and higher self-reported unpleasantness while witnessing the demonstrator's distress. In the test stage, participants showed a stronger conditioned fear response (SCR) when they had learned under high, compared to low, affect sharing. In contrast, participants' declarative memory of how many shocks the demonstrator had received with each cue was not influenced by the affect sharing manipulation. These findings demonstrate that affect sharing is involved in enhancing vicarious fear learning, and thus advance our understanding of the role of empathy, and more generally emotion, in social observational learning.