OBJECTIVE: Rodents acquire food information from their conspecifics and display a preference for the conspecifics\' consumed food. This social learning of food information from others promotes the survival of a species, and it is introduced as the socially transmitted food preference (STFP) task. The cholinergic system in the basal forebrain plays a role in the acquisition of STFP. Cannabidiol (CBD), one of the most abundant phytocannabinoids, exerts its therapeutic potential for cognitive deficits through versatile mechanisms of action, including its interaction with the cholinergic system. We hypothesize a positive relationship between CBD and STFP because acetylcholine (ACh) is involved in STFP, and CBD increases the ACh levels in the basal forebrain.
METHODS: Male C57BL/6J mice were trained to acquire the STFP task. We examined whether CBD affects STFP memory by administering CBD (20 mg/kg, i.p.) before the STFP social training. The involvement of cholinergic system in CBD\'s effect on STFP was examined by knockdown of brain acetylcholinesterase (AChE), applying a nonselective muscarinic antagonist SCO (3 mg/kg, i.p.) before CBD treatment, and measuring the basal forebrain ACh levels in the CBD-treated mice.
RESULTS: We first showed that CBD enhanced STFP memory. Knockdown of brain AChE also enhanced STFP memory, which mimicked CBD\'s effect on STFP. SCO blocked CBD\'s memory-enhancing effect on STFP. Our most significant finding is that the basal forebrain ACh levels in the CBD-treated mice, but not their control counterparts, were positively correlated with mice\'s STFP memory performance.
CONCLUSIONS: This study indicates that CBD enhances STFP memory in mice. Specifically, those which respond to CBD by increasing the muscarinic-mediated ACh signaling perform better in their STFP memory.

Shyness is typically associated with avoidant social behavior and restricted affect in new social situations. However, we know considerably less about how one child\'s shyness influences another child\'s behavior and affect in new social situations. Children\'s shyness was parent-reported when children were age 3 (N = 105, 52 girls, Mage = 3.50 years), and children were tested approximately 1 year later (Mage = 4.76 years) in same-gender dyads where they were asked to give an impromptu speech about their most recent birthday in front of an experimenter and the other member of the dyad. We examined whether children\'s shyness and speech order influenced their own and their social partner\'s observed behavior and affect during the speech. Regardless of speech order, children\'s own shyness was positively associated with their own avoidant social behavior and gaze aversion. Regardless of shyness, children who gave their speech second averted their gaze more than children who gave their speech first. We also found that children who gave their speech second displayed less positive affect if their social partner who they watched give the speech first was shyer. We speculate that some 4-year-old children may be sensitive to the avoidant behaviors of their shy peers and, in turn, respond with less animation when it is their turn to participate in the same activity. RESEARCH HIGHLIGHTS: We examined whether preschool children\'s shyness and speech order influenced their own and their social partner\'s observed behavior and affect during a dyadic speech task Children\'s own shyness was positively associated with their own avoidant social behavior and gaze aversion Children who gave their speech second averted their gaze more than children who gave their speech first. Children who gave their speech second displayed less positive affect if their social partner who they watched give a speech first was shyer These findings suggest that preschool-aged children are sensitive to learning about their environment indirectly through social observation.

Familial transmission of mental illnesses and health behaviors is well established. However, little research has examined familial transmission of mental health help-seeking behaviors despite social science theoretical traditions that support its occurrence including social learning theory and the network episode model. Among parent-adolescent dyads, extant literature supports consideration of adolescent-autonomy versus parent-gatekeeping according to whether or not parents recognize a mental health problem in their adolescent. Given this, we examined familial transmission of self-reported mental health help-seeking among parent-adolescent dyads over an 18-month period from a school-based study (N = 422; Texas, USA). Generalized estimating equations tested the effect of multiple forms of parent help-seeking on similar forms of adolescent help-seeking, controlling for personal/family characteristics. We also examined interaction by parent recognition of a mental health problem in their adolescent to discern unique intergenerational processes across these subgroups of parent-adolescent dyads. Owing to effect modification by parent problem recognition (p<0.01), two unique familial transmission of help-seeking pathways emerged. When parent problem recognition was present, parent self help-seeking history reduced adolescent help-seeking net of controls. In contrast, when parent problem recognition was absent, parent self help-seeking history increased adolescent help-seeking net of controls. Our findings provide evidence of familial transmission of mental health help-seeking behaviors, but the direction of influence fundamentally depends on parent recognition of a mental health problem in their adolescent in order to reveal intergenerationally transmitted processes. The findings support our hypotheses that familial transmission of help-seeking starts early in adolescence and is likely influenced by parent modeling and gatekeeping, though explanations for the patterns observed, such as short- and long-term positive and negative mixed impacts of past help-seeking experiences of parents, require further study to ascertain.

Social learning is learning from the observation of how others interact with the environment. However, in nature, individuals often need to process serial social information and may favour either the most recent information (recency bias), constantly updating knowledge to match the environment, or the information that appeared first in the series (primacy bias), which may slow down adjustment to environmental change. Mate-copying is a widespread form of social learning in a mate choice context related to conformity in mate choice, and where a naive individual develops a preference for a given mate (or mate phenotype) seen being chosen by conspecifics. Mate-copying is documented in most vertebrate taxa and in the fruit fly Drosophila melanogaster. Here, we tested experimentally whether female fruit flies show a primacy or a recency bias by presenting pictures of a female copulating with one of two contrastingly coloured male phenotypes. We found that after two sequential contradictory demonstrations, females show a tendency to prefer males of the phenotype preferred in the first demonstration, suggesting that mate-copying in D. melanogaster is not based on the most recently observed mating and may be influenced by a form of primacy bias.

Understanding the interplay between social activities and disease dynamics is crucial for effective public health interventions. Recent studies using coupled behavior-disease models assumed homogeneous populations. However, heterogeneity in population, such as different social groups, cannot be ignored. In this study, we divided the population into social media users and non-users, and investigated the impact of homophily (the tendency for individuals to associate with others similar to themselves) and online events on disease dynamics. Our results reveal that homophily hinders the adoption of vaccinating strategies, hastening the approach to a tipping point after which the population converges to an endemic equilibrium with no vaccine uptake. Furthermore, we find that online events can significantly influence disease dynamics, with early discussions on social media platforms serving as an early warning signal of potential disease outbreaks. Our model provides insights into the mechanisms underlying these phenomena and underscores the importance of considering homophily in disease modeling and public health strategies.

BACKGROUND: Human learning unfolds under uncertainty. Uncertainty is heterogeneous with different forms exerting distinct influences on learning. While one can be uncertain about what to do to maximize rewarding outcomes, known as policy uncertainty, one can also be uncertain about general world knowledge, known as epistemic uncertainty. In complex and naturalistic environments such as the social world, adaptive learning may hinge on striking a balance between attending to and resolving each type of uncertainty. Prior work illustrates that people with anxiety-those with increased threat and uncertainty sensitivity-learn less from aversive outcomes, particularly as outcomes become more uncertain. How does a learner adaptively trade-off between attending to these distinct sources of uncertainty to successfully learn about their social environment?
METHODS: We developed a novel eye-tracking method to capture highly granular estimates of policy and epistemic uncertainty based on gaze patterns and pupil diameter (a physiological estimate of arousal) RESULTS: These empirically derived uncertainty measures reveal that humans (N = 94) flexibly switch between resolving policy and epistemic uncertainty to adaptively learn about which individuals can be trusted and which should be avoided. However, those with increased anxiety (N = 49) do not flexibly switch between resolving policy and epistemic uncertainty, and instead express less uncertainty overall CONCLUSIONS: Combining modeling and eye-tracking techniques, we show that altered learning in people with anxiety emerges from an insensitivity to policy uncertainty and rigid choice policies, leading to maladaptive behaviors with untrustworthy people.

Bees have been excellent model systems to study social learning - the ability of animals to change their behaviour based on observations of other individuals. Researchers have investigated several aspects of social learning in bees, including how it can lead to cultural traditions. A recent study also argues that bees have the capacity to socially learn behaviours that they could not innovate on their own. To understand these findings better, I review what we know about the mechanisms underlying social learning in bees and use these findings to compare social learning and culture in bees and humans. The findings suggest that the seemingly complex social behaviours of bees could arise from simple mechanisms underlying learning in general. I highlight the importance of investigating cognitive mechanisms and how they might differ across animals.

Social learning is a mechanism used by many species to efficiently gain information about their environment. Although many animals live in an environment where members of other species are present, little is known about interspecific social learning. Domesticated and urbanized species provide the opportunity to investigate whether nonhuman animals can learn from heterospecifics such as humans, who are integral parts of their social landscape. Although domestic dogs Canis familiaris have been intensively researched for their ability to learn from humans, most studies have focused on dogs living as pets. However, free-ranging dogs represent the majority of the world\'s dog population, they live alongside humans, scavenge on human refuse, and are subject to natural and sexual selection. Thus, free-ranging dogs with extensive exposure to humans and their artifacts provide the opportunity to investigate interspecific social learning in a naturalistic setting, where learning from humans might be a benefit for them. Here we tested individual free-ranging dogs in a between-subject design: Dogs in the control group could spontaneously choose between two novel and differently patterned food-delivering boxes. In the experimental group, instead, dogs could first observe an unfamiliar human approaching and eating from 1 of the 2 boxes. We provide the first evidence that free-ranging dogs match the choice of an unfamiliar human. These results show that at least simple forms of interspecific social learning might be involved in dogs\' success in living alongside humans in a complex urbanized environment.

For a reinforcement learning agent to finish trial-and-error in a realistic time duration, it is necessary to limit the scope of exploration during the learning process. However, limiting the exploration scope means limitation in optimality: the agent could fall into a suboptimal solution. This is the nature of local, bottom-up way of learning. An alternative way is to set a goal to be achieved, which is a more global, top-down way. The risk-sensitive satisficing (RS) value function incorporate, as a method of the latter way, the satisficing principle into reinforcement learning and enables agents to quickly converge to exploiting the optimal solution without falling into a suboptimal one, when an appropriate goal (aspiration level) is given. However, how best to determine the aspiration level is still an open problem. This study proposes social satisficing, a framework for multi-agent reinforcement learning which determines the aspiration level through information sharing among multiple agents. In order to verify the effectiveness of this novel method, we conducted simulations in a learning environment with many suboptimal goals (SuboptimaWorld). The results show that the proposed method, which converts the aspiration level at the episodic level into local (state-wise) aspiration levels, possesses a higher learning efficiency than any of the compared methods, and that the novel method has the ability to autonomously adjust exploration scope, while keeping the shared information minimal. This study provides a glimpse into an aspect of human and biological sociality which has been mentioned little in the context of artificial intelligence and machine learning.

Humans learn both directly, from own experience, and via social communication, from the experience of others. They also often integrate these two sources of knowledge to make predictions and choices. We hypothesized that when faced with the need to integrate communicated information into personal experience, people would represent the average of experienced exemplars with greater accuracy. In two experiments, Mturk users estimated the mean of consecutively and rapidly presented number sequences that represented bonuses ostensibly paid by different providers on a crowdsource platform. Participants who expected integrating these values with verbal information about possible change in bonuses were more accurate in extracting the means of the values compared to participants who did not have such expectation. While our study focused on socially communicated information, the observed effect may potentially extend to other forms of information integration. We suggest that expected integration of experience with additional information facilitates an abstract representation of personal experiences.