Better social reversal learning is associated with a more social approach across time.

Flexibly updating behaviors towards others is crucial for adaptive social functioning. Previous studies have found that difficulties in flexibly updating behaviors are associated with social anxiety (SA). However, it is unclear whether such difficulties relate to actual social behaviors. The current study investigated the relationships between negative-to-positive social reversal learning, social approach behavior, and SA across time. Participants (MTurk, Time 1 = 275, Time 2 = 126, 16 weeks later) completed a performance-based social reversal-learning task. In the initial phase, participants learned that interactions with certain individuals are associated with negative outcomes, whereas interactions with other individuals are associated with positive outcomes. In the reversal phase, these associations were reversed, requiring participants to update their behaviors. The relationships between the performance in the task, SA severity, and social approach behavior reported by participants were assessed cross-sectionally and longitudinally. We found that negative-to-positive updating was negatively associated with SA severity. Furthermore, negative-to-positive updating was positively correlated with social approach behavior, both cross-sectionally and prospectively. Hence, individuals with better negative-to-positive updating at Time 1 reported significantly more social approach behaviors across time. The results support the role of negative-to-positive updating as a mechanism associated with SA and social approach, advancing and refining interpersonal and cognitive theories of SA.

Oxytocin and social learning in socially anxious men and women.

OBJECTIVE: This study extended a classic self-referential learning paradigm by investigating the effects of intranasally-administered oxytocin in high and low socially anxious participants during social learning, as a function of social anxiety levels and sex. METHODS: In a randomized double-blinded design, 160 participants were either given intranasal oxytocin (24 I.U.) or placebo. Subsequently, while lying in an MR scanner, participants were shown neutral faces that were paired with positively, neutrally, or negatively valenced self-referential sentences, during which we measured self-reported arousal and sympathy of the facial stimuli, pupil dilation, and changes in the brain-oxygen-level dependent signal. Four-factor mixed analyses of variance with the between-subjects factors group (high socially anxious vs. low socially anxious), substance (oxytocin vs. placebo), and sex (male vs. female) and the within-subjects factor sentence valence (positive vs. neutral vs. negative) were conducted for each measure, respectively. RESULTS: Administration of intranasal oxytocin yielded an increase in sympathy ratings in high socially anxious compared to low socially anxious individuals and decreased arousal ratings for positively-conditioned faces in low socially anxious participants. As an objective physiological measure of arousal, pupil dilation mirrored the behavioral results. Oxytocin effects on neural activation in the insula interacted with anxiety levels and sex: low socially anxious individuals yielded lower activation under oxytocin than placebo; the converse was observed in high socially anxious individuals. This interaction also differed between sexes, as men yielded higher activation levels than women. These findings were more prominent for positively- and negatively-conditioned faces. Within the amygdala, high socially anxious men yielded higher activation than high socially anxious women in the left hemisphere, and low socially anxious men yielded higher activation than low socially anxious women from positively- and negatively-conditioned faces, though no influence of oxytocin was detected. CONCLUSION: These results suggest oxytocin-induced behavioral, physiological, and neural changes as a function of social learning in socially low and high anxious individuals. These findings challenge the amygdalocentric view of the role of emotions in social learning, instead contributing to the growing body of findings implicating the insula therein, revealing an interaction between oxytocin, sex, and emotional valence. Such discoveries raise an interesting set of questions regarding the computational goals of regions such as the insula in emotional learning and how neural activity can play a diagnostic or prognostic role in social anxiety, potentially leading to new treatment opportunities that may combine oxytocin and neurofeedback differentially for men and women.

Disentangling genetic, plastic and social learning drivers of sex-specific foraging behaviour in Trinidadian guppies (Poecilia reticulata).

Evolutionary biologists have long been interested in parsing out the roles of genetics, plasticity and their interaction on adaptive trait divergence. Since males and females often have different ecological and reproductive roles, separating how their traits are shaped by interactions between their genes and environment is necessary and important. Here, we disentangle the sex-specific effects of genetic divergence, developmental plasticity, social learning and contextual plasticity on foraging behaviour in Trinidadian guppies (Poecilia reticulata) adapted to high- or low-predation habitats. We reared second-generation siblings from both predation regimes with or without predator chemical cues, and with adult conspecifics from either high- or low-predation habitats. We then quantified their foraging behaviour in water with and without predator chemical cues. We found that high-predation guppies forage more efficiently than low-predation guppies, but this behavioural difference is context-dependent and shaped by different mechanisms in males and females. Higher foraging efficiency in high-predation females is largely genetically determined, and to a smaller extent socially learned from conspecifics. However, in high-predation males, higher foraging efficiency is plastically induced by predator cues during development. Our study demonstrates sex-specific differences in genetic versus plastic responses in foraging behaviour, a trait of significance in organismal fitness and ecosystem dynamics.

The dorsomedial prefrontal cortex prioritizes social learning during rest.

Sociality is a defining feature of the human experience: We rely on others to ensure survival and cooperate in complex social networks to thrive. Are there brain mechanisms that help ensure we quickly learn about our social world to optimally navigate it? We tested whether portions of the brain's default network engage "by default" to quickly prioritize social learning during the memory consolidation process. To test this possibility, participants underwent functional MRI (fMRI) while viewing scenes from the documentary film, Samsara. This film shows footage of real people and places from around the world. We normed the footage to select scenes that differed along the dimension of sociality, while matched on valence, arousal, interestingness, and familiarity. During fMRI, participants watched the "social" and "nonsocial" scenes, completed a rest scan, and a surprise recognition memory test. Participants showed superior social (vs. nonsocial) memory performance, and the social memory advantage was associated with neural pattern reinstatement during rest in the dorsomedial prefrontal cortex (DMPFC), a key node of the default network. Moreover, it was during early rest that DMPFC social pattern reinstatement was greatest and predicted subsequent social memory performance most strongly, consistent with the "prioritization" account. Results simultaneously update 1) theories of memory consolidation, which have not addressed how social information may be prioritized in the learning process, and 2) understanding of default network function, which remains to be fully characterized. More broadly, the results underscore the inherent human drive to understand our vastly social world.

Auditory risk recognition is socially transmitted across territory borders in wild birds.

Prey species commonly assess predation risk based on acoustic signals, such as predator vocalizations or heterospecific alarm calls. The resulting risk-sensitive decision-making affects not only the behavior and life-history of individual prey, but also has far-reaching ecological consequences for population, community, and ecosystem dynamics. Although auditory risk recognition is ubiquitous in animals, it remains unclear how individuals gain the ability to recognize specific sounds as cues of a threat. Here, it has been shown that free-living birds (Wood Warblers Phylloscopus sibilatrix) can learn to recognize unfamiliar, complex sounds (samples of punk rock songs) as cues of a threat from conspecifics holding adjacent territories during the spring breeding season. In a playback experiment, Wood Warblers initially ignored the unfamiliar sounds, but after repeatedly hearing that these sounds trigger alarm calling reaction of neighbors, most individuals showed an anti-predator response to them. Moreover, once learned soon after nestlings hatching, the anti-predator response of parents toward previously unfamiliar sounds was then retained over the entire nestlings rearing period. These results demonstrate that social learning via the association of unfamiliar sounds with known alarm signals enables the spread of anti-predator behavior across territory borders and provides a mechanism explaining the widespread abilities of animals to assess predation risk based on acoustic cues.

Alfabetización en salud: proceso de aprendizaje significativo personal y comunitario / Health literacy: meaningful personal and community learning process

El aprendizaje y la salud son dos elementos vinculados entre sí. El hecho de cuidar de la salud requiere del aprendizaje de conocimientos, habilidades, comportamientos y actitudes que se desarrollan a lo largo de nuestra vida. Los aprendizajes relacionados con la salud comportan estilos de vida más saludables, la mejora del bienestar, la calidad de vida y la salud de la comunidad. El aprendizaje significativo transforma las vidas, abriendo nuevas oportunidades, posibilitando nuevas competencias y formando nuevas redes sociales. Este artículo pretende reflexionar sobre la relación entre elementos de la alfabetización en salud y el proceso de aprendizaje significativo. (AU)

Learning and health are both interrelated aspects. The act of looking after health requires learning knowledge, skills, behaviors, and attitudes that develop throughout our lives. Health-related learning leads to healthier lifestyles, improved well-being, better quality of life and community health. Significant learning transforms lives, paving the way towards new opportunities, enabling new skills and forming new social networks. This paper aims to reflect on the relationship between aspects of health literacy and the meaningful learning process. (AU)

Environmental harshness does not affect the propensity for social learning in great tits, Parus major.

According to the harsh environment hypothesis, natural selection should favour cognitive mechanisms to overcome environmental challenges. Tests of this hypothesis to date have largely focused on asocial learning and memory, thus failing to account for the spread of information via social means. Tests in specialized food-hoarding birds have shown strong support for the effects of environmental harshness on both asocial and social learning. Whether the hypothesis applies to non-specialist foraging species remains largely unexplored. We evaluated the relative importance of social learning across a known harshness gradient by testing generalist great tits, Parus major, from high (harsh)- and low (mild)-elevation populations in two social learning tasks. We showed that individuals use social learning to find food in both colour-associative and spatial foraging tasks and that individuals differed consistently in their use of social learning. However, we did not detect a difference in the use or speed of implementing socially observed information across the elevational gradient. Our results do not support predictions of the harsh environment hypothesis suggesting that context-dependent costs and benefits as well as plasticity in the use of social information may play an important role in the use of social learning across environments. Finally, this study adds to the accumulating evidence that the harsh environment hypothesis appears to have more pronounced effects on specialists compared to generalist species.

Visuo-frontal interactions during social learning in freely moving macaques.

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

Co-producing knowledge on the use of urban natural space: Participatory system dynamics modelling to understand a complex urban system.

Decision-makers are increasingly asked to act differently in how they respond to complex urban challenges, recognising the value in bringing together and integrating cross-disciplinary, cross-sectoral knowledge to generate effective solutions. Participatory modelling allows to bring stakeholders together, enhance knowledge and understanding of a system, and identify the impacts of interventions to a given problem. This paper uses an interdisciplinary and systems approach to investigate a complex urban problem, using a participatory System Dynamics modelling process as an approach to facilitate learning and co-produce knowledge on the factors influencing the use of urban natural space. Stakeholders used a Systems Dynamics model and interface, as a tool to collectively identify pathways for improving the use of space and simulating their impacts. Under the lens of knowledge co-production, the paper reflects how such mechanisms can lead to the co-production of knowledge and social learning. The findings also contribute to identify ways of increasing the value of urban natural space focusing on urban areas undergoing physical and social transformation, such as the Thamesmead case study, London, UK.

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.

Discovering social learning ecosystems during clinical clerkship from United States medical students' feedback encounters: a content analysis.

PURPOSE: We examined United States medical students' self-reported feedback encounters during clerkship training to better understand in situ feedback practices. Specifically, we asked: Who do students receive feedback from, about what, when, where, and how do they use it? We explored whether curricular expectations for preceptors' written commentary aligned with feedback as it occurs naturalistically in the workplace. METHODS: This study occurred from July 2021 to February 2022 at Southern Illinois University School of Medicine. We used qualitative survey-based experience sampling to gather students' accounts of their feedback encounters in 8 core specialties. We analyzed the who, what, when, where, and why of 267 feedback encounters reported by 11 clerkship students over 30 weeks. Code frequencies were mapped qualitatively to explore patterns in feedback encounters. RESULTS: Clerkship feedback occurs in patterns apparently related to the nature of clinical work in each specialty. These patterns may be attributable to each specialty's "social learning ecosystem"­the distinctive learning environment shaped by the social and material aspects of a given specialty's work, which determine who preceptors are, what students do with preceptors, and what skills or attributes matter enough to preceptors to comment on. CONCLUSION: Comprehensive, standardized expectations for written feedback across specialties conflict with the reality of workplace-based learning. Preceptors may be better able­and more motivated­to document student performance that occurs as a natural part of everyday work. Nurturing social learning ecosystems could facilitate workplace-based learning such that, across specialties, students acquire a comprehensive clinical skillset appropriate for graduation.

A dedicated hypothalamic oxytocin circuit controls aversive social learning.

To survive in a complex social group, one needs to know who to approach and, more importantly, who to avoid. In mice, a single defeat causes the losing mouse to stay away from the winner for weeks1. Here through a series of functional manipulation and recording experiments, we identify oxytocin neurons in the retrochiasmatic supraoptic nucleus (SOROXT) and oxytocin-receptor-expressing cells in the anterior subdivision of the ventromedial hypothalamus, ventrolateral part (aVMHvlOXTR) as a key circuit motif for defeat-induced social avoidance. Before defeat, aVMHvlOXTR cells minimally respond to aggressor cues. During defeat, aVMHvlOXTR cells are highly activated and, with the help of an exclusive oxytocin supply from the SOR, potentiate their responses to aggressor cues. After defeat, strong aggressor-induced aVMHvlOXTR cell activation drives the animal to avoid the aggressor and minimizes future defeat. Our study uncovers a neural process that supports rapid social learning caused by defeat and highlights the importance of the brain oxytocin system in social plasticity.

A Humane Social Learning-Informed Metaverse: Cultivating Positive Technology Experiences in Digital Learning Environments.

Online environments, such as metaverses, provide distinct social environments for people to engage in complex, cognitive, and multidirectional learning and meaning-making experiences. These engaging and influential environments highlight important factors associated with the Social Learning Theory (a process through which external settings influence behavior in specific environments). According to this theory, environments provide a space for youth to engage in reciprocal interactions of interpersonal, behavioral, and environmental cues. Online environments designed by social media companies have been scrutinized, given their dependence on algorithms (artificial intelligence systems). Research has revealed the effects of systems that use machine learning to subversively maintain engagement on their platforms for as long as possible. Given the constant changes in socializing environments, younger generational cohorts need to be adequately prepared for systems that determine what type of content they are exposed to, and shape the timing, frequency, and agentic influencers they engage with. Therefore, this article proposes a necessity to expand our understanding about social learning and current technology design principles. This article demonstrates the need for a paradigm shift toward exploring an innovative construct referred to as the digital learning environment. We examine existing issues in the design of digital spaces, provide a positive developmental psychology framework that informs further research, and propose solutions for researchers, educators, policymakers, and caregivers as they navigate healthy technology use and predominant mental health issues in the 21st century.

Effective Components of Social Emotional Learning Programs: A Meta-analysis.

Previous reviews have synthesized the impacts of universal school-based social emotional learning (SEL) programs. However, they have yet to attempt a meta-analytic approach with rigorous inclusion criteria to identify the key SEL components and explore what make these programs work. This study aims to fill that gap by examining the impacts of SEL programs and exploring the moderating effects of methodological characteristics, implementation features, and program components on SEL effectiveness. The final sample consisted of 12 high-quality SEL programs, 59 studies, and 83,233 participants, with an overall effect size of 0.15. Meta-regression results indicated that these SEL programs could significantly improve youth social emotional skills, reinforce affect and attitudes, promote academic performance, increase prosocial behaviors, and reduce antisocial behaviors. Training teachers' social emotional skills and reducing cognitive elements in SEL curricula were found to be effective components of SEL programs, whereas pedagogical activities, climate support, and family engagement were not. Large-scale studies of SEL programs tended to generate smaller effect sizes, and those with low program dosages were found to be less effective than those approaching the recommended dosage. Policy and practical implications on how to scale SEL programs are discussed.

Optimal dynamic pricing for public transportation considering consumer social learning.

Effective public transportation pricing strategies are critical to reducing traffic congestion and meeting consumer demand for sustainable urban development. In this study, we construct a dynamic game pricing model and a social learning network model for consumers of three modes of public transportation including metro, bus, and pa-transit. In the model, the metro, bus, and pa-transit operators maximize their profits through dynamic pricing optimization, and consumers maximize their utility by adjusting their travel habits through social learning in the social network. The reinforcement learning algorithm is applied to simulate the model, and the results show that: (1) as consumers' perceived sensitivity to different modes of travel increases, the market share and price of each mode of travel adjust accordingly. (2) When taking into account consumers' social learning behavior, the market share of metros remains high, while the market shares of buses and pa-transit are relatively low. (3) As consumers become more sensitive to their perception of each travel mode, operators invest more resources in improving service quality to gain market share, which in turn affects the price of each travel mode. Our results provide decision support for optimal pricing of urban public transportation.

Older infants' social learning behavior under uncertainty is modulated by the interaction of face and speech processing.

The origin of face or language influences infants' perceptual processing and social learning behavior. However, it remains unclear how infants' social learning behavior is affected when both information are provided simultaneously. Hence, the current study investigated whether and how infants' social learning in terms of gaze following is influenced by face race and language origin of an interaction partner in an uncertain situation. Our sample consisted of 91 Caucasian infants from German speaking families. They were divided into 2 age groups: Younger infants were 5- to 8-month-old (n = 46) and the older infants 11- to 20-month-old (n = 45). We used a modified online version of the gaze following paradigm by Xiao and colleagues by varying face race (Caucasian, and Asian faces) and language (German and French) of a female actor. We recorded infants looking behavior via webcam and coded it offline. Our results revealed that older but not younger infants were biased to follow the gaze of own-race adults speaking their native language. Our findings show that older infants are clearly influenced by adults' ethnicity and language in social learning situations of uncertainty.

Do children imitate even when it is costly? New insights from a novel task.

Children have a proclivity to learn through faithful imitation, but the extent to which this applies under significant cost remains unclear. To address this, we investigated whether 4- to 6-year-old children (N = 97) would stop imitating to forego a desirable food reward. We presented participants with a task involving arranging marshmallows and craft sticks, with the goal being either to collect marshmallows or build a tower. Children replicated the demonstrated actions with high fidelity regardless of the goal, but retrieved rewards differently. Children either copied the specific actions needed to build a tower, prioritizing tower completion over reward; or adopted a novel convention of stacking materials before collecting marshmallows, and developed their own method to achieve better outcomes. These results suggest children's social learning decisions are flexible and context-dependent, yet that when framed by an ostensive goal, children imitated in adherence to the goal despite incurring significant material costs.

Naïve information aggregation in human social learning.

To glean accurate information from social networks, people should distinguish evidence from hearsay. For example, when testimony depends on others' beliefs as much as on first-hand information, there is a danger of evidence becoming inflated or ignored as it passes from person to person. We compare human inferences with an idealized rational account that anticipates and adjusts for these dependencies by evaluating peers' communications with respect to the underlying communication pathways. We report on three multi-player experiments examining the dynamics of both mixed human-artificial and all-human social networks. Our analyses suggest that most human inferences are best described by a naïve learning account that is insensitive to known or inferred dependencies between network peers. Consequently, we find that simulated social learners that assume their peers behave rationally make systematic judgment errors when reasoning on the basis of actual human communications. We suggest human groups learn collectively through naïve signaling and aggregation that is computationally efficient and surprisingly robust. Overall, our results challenge the idea that everyday social inference is well captured by idealized rational accounts and provide insight into the conditions under which collective wisdom can emerge from social interactions.

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.

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. (AU)