Stimulus generalization as a mechanism for learning to trust

Early life adversity is associated with greater similarity in neural representations of ambiguous and threatening stimuli

Exposure to early life adversity (ELA) is hypothesized to sensitize threat-responsive neural circuitry. This may lead individuals to overestimate threat in the face of ambiguity, a cognitive-behavioral phenotype linked to poor mental health. The tendency to process ambiguity as threatening may stem from difficulty distinguishing between ambiguous and threatening stimuli. However, it is unknown how exposure to ELA relates to neural representations of ambiguous and threatening stimuli, or how processing of ambiguity following ELA relates to psychosocial functioning. The current fMRI study examined multivariate representations of threatening and ambiguous social cues in 41 emerging adults (aged 18 to 19 years). Using representational similarity analysis, we assessed neural representations of ambiguous and threatening images within affective neural circuitry and tested whether similarity in these representations varied by ELA exposure. Greater exposure to ELA was associated with greater similarity in neural representations of ambiguous and threatening images. Moreover, individual differences in processing ambiguity related to global functioning, an association that varied as a function of ELA. By evidencing reduced neural differentiation between ambiguous and threatening cues in ELA-exposed emerging adults and linking behavioral responses to ambiguity to psychosocial wellbeing, these findings have important implications for future intervention work in at-risk, ELA-exposed populations.

Far from the threatening crowd: Generalisation of conditioned threat expectancy and fear in COVID-19 lockdown

Fear and anxiety are rarely confined to specific stimuli or situations. In fear generalisation, there is a spread of fear responses elicited by physically dissimilar generalisation stimuli (GS) along a continuum between danger and safety. The current study investigated fear generalisation with a novel online task using COVID-19-relevant stimuli (i.e., busy or quiet shopping street/mall scenes) during pandemic lockdown restrictions in the United Kingdom. Participants (N = 50) first completed clinically relevant trait measures before commencing a habituation phase, where two conditioned stimuli (CSs; i.e., a busy or quiet high street/mall scene) were presented. Participants then underwent fear conditioning where one conditioned stimulus (CS+) was followed by an aversive unconditioned stimulus (US; a loud female scream accompanied by a facial photograph of a female displaying a fearful emotion) and another (CS-) was not. In a test phase, six generalisation stimuli were presented where the US was withheld, and participants provided threat expectancy and fear ratings for all stimuli. Following successful conditioning, fear generalization was observed for both threat expectancy and fear ratings. Trait worry partially predicted generalised threat expectancy and COVID-19 fear strongly predicted generalised fear. In conclusion, a generalisation gradient was evident using an online remote generalisation task with images of busy/quiet streets during the pandemic. Worry and fear of COVID-19 predicted fear generalisation.

Automating weighing of faces and voices based on cue saliency in trustworthiness impressions

When encountering people, their faces are usually paired with their voices. We know that if the face looks familiar, and the voice is high-pitched, the first impression will be positive and trustworthy. But, how do we integrate these two multisensory physical attributes? Here, we explore 1) the automaticity of audiovisual integration in shaping first impressions of trustworthiness, and 2) the relative contribution of each modality in the final judgment. We find that, even though participants can focus their attention on one modality to judge trustworthiness, they fail to completely filter out the other modality for both faces (Experiment 1a) and voices (Experiment 1b). When asked to judge the person as a whole, people rely more on voices (Experiment 2) or faces (Experiment 3). We link this change to the distinctiveness of each cue in the stimulus set rather than a general property of the modality. Overall, we find that people weigh faces and voices automatically based on cue saliency when forming trustworthiness impressions.

Perceptual Generalization of Alcohol-Related Value Characterizes Risky Drinkers

Generalizing from past experiences to novel situations is critical for adaptive behavior, whereas overgeneralization can promote maladaptive responses (e.g., context-inappropriate fear in anxiety). Here, we propose that overgeneralizing alcohol-related associations characterizes risky drinking. We conducted two online experiments assessing generalization of alcohol-related gains (Study 1) and losses (Study 2) among individuals who engaged in light or risky patterns of drinking (Study 1: N = 88, 24-44 years old; Study 2: N = 87, 21-44 years old). After learning to associate cards with alcohol and non-alcohol-related outcomes, participants chose whether to play with cards varying in perceptual similarity to those shown during conditioning. Finally, participants completed a surprise recognition memory test for all outcomes. Although both groups showed comparable conditioning, we found that risky drinkers overgeneralized alcohol-related gains and losses. Risky drinkers also showed a bias toward recognizing alcohol-related images. These results indicate a novel role for overgeneralization of alcohol-related gains and losses as a mechanism associated with risky drinking.

Neural representations of ambiguous affective stimuli and resilience to anxiety in emerging adults

The tendency to interpret ambiguous stimuli as threatening has been associated with a range of anxiety disorders. Responses to ambiguity may be particularly relevant to mental health during the transition from adolescence to adulthood ("emerging adulthood"), when individuals encounter unfamiliar challenges and navigate novel social situations. However, it remains unclear whether neural representations of ambiguity relate to risk for anxiety. The present study sought to examine whether multivariate representations of ambiguity - and their similarity to representations of threat - relate to appraisals of ambiguity or anxiety in a sample of emerging adults. Participants (N = 41) viewed threatening (angry), nonthreatening (happy), and ambiguous (surprised) facial stimuli while undergoing fMRI. Outside of the scanner, participants were presented with the same stimuli and categorized the ambiguous faces as positive or negative. Using representational similarity analyses (RSA), we investigated whether the degree of pattern similarity in responses to ambiguous, nonthreatening, and threatening faces within the amygdala related to appraisals of ambiguous stimuli and anxiety symptomatology. We found that individuals who evidenced greater similarity (i.e., less differentiation) in neural representations of ambiguous and nonthreatening faces within the left amygdala reported lower concurrent anxiety. Additionally, trial-level pattern similarity predicted subsequent appraisals of ambiguous stimuli. These findings provide insight into how neural representations of ambiguity relate to risk or resilience for the development of anxiety.

Prefrontal cortex state representations shape human credit assignment

People learn adaptively from feedback, but the rate of such learning differs drastically across individuals and contexts. Here, we examine whether this variability reflects differences in what is learned. Leveraging a neurocomputational approach that merges fMRI and an iterative reward learning task, we link the specificity of credit assignment-how well people are able to appropriately attribute outcomes to their causes-to the precision of neural codes in the prefrontal cortex (PFC). Participants credit task-relevant cues more precisely in social compared vto nonsocial contexts, a process that is mediated by high-fidelity (i.e., distinct and consistent) state representations in the PFC. Specifically, the medial PFC and orbitofrontal cortex work in concert to match the neural codes from feedback to those at choice, and the strength of these common neural codes predicts credit assignment precision. Together this work provides a window into how neural representations drive adaptive learning.

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.

Uncertainty aversion predicts the neural expansion of semantic representations

Correctly identifying the meaning of a stimulus requires activating the appropriate semantic representation among many alternatives. One way to reduce this uncertainty is to differentiate semantic representations from each other, thereby expanding the semantic space. Here, in four experiments, we test this semantic-expansion hypothesis, finding that uncertainty-averse individuals exhibit increasingly differentiated and separated semantic representations. This effect is mirrored at the neural level, where uncertainty aversion predicts greater distances between activity patterns in the left inferior frontal gyrus when reading words, and enhanced sensitivity to the semantic ambiguity of these words in the ventromedial prefrontal cortex. Two direct tests of the behavioural consequences of semantic expansion further reveal that uncertainty-averse individuals exhibit reduced semantic interference and poorer generalization. Together, these findings show that the internal structure of our semantic representations acts as an organizing principle to make the world more identifiable.

Age-related differences in the social associative learning of trust information

Trust is a key component of social interaction. Older adults, however, often exhibit excessive trust relative to younger adults. One explanation is that older adults may learn to trust differently than younger adults. Here, we examine how younger (N = 33) and older adults (N = 30) learn to trust over time. Participants completed a classic iterative trust game with 3 partners. Younger and older adults shared similar amounts but differed in how they shared money. Compared to younger adults, older adults invested more with untrustworthy partners and less with trustworthy partners. As a group, older adults displayed less learning than younger adults. However, computational modeling suggests that this is not because older adults learn differently from positive and negative feedback than younger adults. Model-based fMRI analyses revealed several age- and learning-related differences in neural processing. Specifically, we found that older learners (N = 19), relative to older non-learners (N = 11), had greater reputation-related activity in metalizing/memory areas while making their decisions. Collectively, these findings suggest that older adult learners use social cues differently from non-learners.

A Study of Factors Influencing the Volume of Responses to Posts in Physician Online Community

Today's diverse health needs place greater demands on physicians. However, individual doctors have limited capabilities and may encounter many unsolvable medical problems. The physician online community provides a platform for physicians to communicate with each other and help each other. Physicians can post for help about problems they encounter at work. The number of responses to physicians' posts is critical to whether or not the problem is resolved. This study collected information on 13,226 posts from a well-known physician online community in China to analyze the factors that influence the number of post replies. In the analysis of the post content of the physician online community, this study innovatively introduces word usage features in the medical field. TextMind was used to extract the rate of several types of words in posts that frequently appear when describing medical information. Ultimately, we found that the rate of time words, visual words, auditory words, and physiological process words used in posts had a positive and significant effect on the number of post responses. A series of new post features has been found to have an impact on the number of post replies in physician online communities. This finding is beneficial for physicians to quickly obtain peer assistance through online platforms, increasing the likelihood of solving workplace challenges and improving physician care, as well as the success of physician online communities.

The influence of fake news on face-trait learning

Humans spontaneously attribute a wide range of traits to conspecifics based on their facial appearance. Unsurprisingly, previous findings indicate that this 'person evaluation' is affected by information provided about the target's past actions and behaviours. Strikingly, many news items shared on social media sites (e.g., Twitter) describe the actions of individuals who are often shown in accompanying images. This kind of material closely resembles that encountered by participants in previous studies of face-trait learning. We therefore sought to determine whether Twitter posts that pair facial images with favourable and unfavourable biographical information also modulate subsequent trait evaluation of the people depicted. We also assessed whether the effects of this information-valence manipulation were attenuated by the presence of the "disputed tag", introduced by Twitter as a means to combat the influence of fake-news. Across two preregistered experiments, we found that fictional tweets that paired facial images with details of the person's positive or negative actions affected the extent to which readers subsequently judged the faces depicted to be trustworthy. When the rating phase followed immediately after the study phase, the presence of the disputed tag attenuated the effect of the behavioural information (Experiment 1: N = 128; Mage = 34.06; 89 female, 36 male, 3 non-binary; 116 White British). However, when the rating phase was conducted after a 10-minute delay, the presence of the disputed tag had no significant effect (Experiment 2: N = 128; Mage = 29.12; 78 female, 44 male, 4 non-binary, 2 prefer not to say; 110 White British). Our findings suggest that disputed tags may have relatively little impact on the long-term face-trait learning that occurs via social media. As such, fake news stories may have considerable potential to shape users' person evaluation.

Trait impressions from faces depend on the goals of the perceiver

Trait impressions from faces formed in the real world likely depend on the circumstances in which a face is seen, in particular, on the goal of the perceiver in that circumstance. This goal dependency is typically not incorporated into laboratory studies, an omission that has limited our understanding of trait impressions from faces.

Reward Uncertainty and Expected Value Enhance Generalization of Episodic Memory

Previous research has revealed some mechanisms underlying the generalization of reward expectation of generalization stimuli, but little is known about the generalization of episodic memory for rewarding events, its consolidation, and how reward components such as expected value and reward uncertainty affect it. Participants underwent a Pavlovian reward-conditioning task to test whether reward conditioning would enhance episodic memory generalization and which reward components would directly affect it. Counterbalanced across participants, one semantic category was paired with a reward, while the other was never paired. Following a delay of either 5 min or 24 h, participants took a memory test consisting of old, highly similar, and new items. We found that participants were more likely to falsely recognize lure items as old in the reward-paired category after 5 min and 24 h delays. These results indicate that reward conditioning enhanced the generalization of episodic memory, but this effect was not necessarily dependent on consolidation. The composite score and raw data of generalization further showed that the uncertainty and expected value enhanced generalization. Together, these findings revealed an effect of reward conditioning on episodic memory generalization and supported the enhancement effects of expected value and uncertainty.

Personality Across World Regions Predicts Variability in the Structure of Face Impressions

Research on face impressions has often focused on a fixed, universal architecture, treating regional variability as noise. Here, we demonstrated a crucial yet neglected role of cultural learning processes in forming face impressions. In Study 1, we found that variability in the structure of adult perceivers' face impressions across 42 world regions (N = 287,178) could be explained by variability in the actual personality structure of people living in those regions. In Study 2, data from 232 world regions (N = 307,136) revealed that adult perceivers use the actual personality structure learned from their local environment to form lay beliefs about personality, and these beliefs in turn support the structure of perceivers' face impressions. Together, these results suggest that people form face impressions on the basis of a conceptual understanding of personality structure that they have come to learn from their regional environment. The findings suggest a need for greater attention to the regional and cultural specificity of face impressions.

The cultural learning account of first impressions

Humans spontaneously attribute character traits to strangers based on their facial appearance. Although these 'first impressions' typically have no basis in reality, some authors have assumed that they have an innate origin. By contrast, the Trait Inference Mapping (TIM) account proposes that first impressions are products of culturally acquired associative mappings that allow activation to spread from representations of facial appearance to representations of trait profiles. According to TIM, cultural instruments, including propaganda, illustrated storybooks, art and iconography, ritual, film, and TV, expose many individuals within a community to common sources of correlated face-trait experience, yielding first impressions that are shared by many, but typically inaccurate. Here, we review emerging empirical findings, many of which accord with TIM, and argue that future work must distinguish first impressions based on invariant facial features (e.g., shape) from those based on facial behaviours (e.g., expressions).

Decision neuroscience and neuroeconomics: Recent progress and ongoing challenges

In the past decade, decision neuroscience and neuroeconomics have developed many new insights in the study of decision making. This review provides an overarching update on how the field has advanced in this time period. Although our initial review a decade ago outlined several theoretical, conceptual, methodological, empirical, and practical challenges, there has only been limited progress in resolving these challenges. We summarize significant trends in decision neuroscience through the lens of the challenges outlined for the field and review examples where the field has had significant, direct, and applicable impacts across economics and psychology. First, we review progress on topics including reward learning, explore-exploit decisions, risk and ambiguity, intertemporal choice, and valuation. Next, we assess the impacts of emotion, social rewards, and social context on decision making. Then, we follow up with how individual differences impact choices and new exciting developments in the prediction and neuroforecasting of future decisions. Finally, we consider how trends in decision-neuroscience research reflect progress toward resolving past challenges, discuss new and exciting applications of recent research, and identify new challenges for the field. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Emotion and Motivation.

The computational challenge of social learning

The complex reward structure of the social world and the uncertainty endemic to social contexts poses a challenge for modeling. For example, during social interactions, the actions of one person influence the internal states of another. These social dependencies make it difficult to formalize social learning problems in a mathematically tractable way. While it is tempting to dispense with these complexities, they are a defining feature of social life. Because the structure of social interactions challenges the simplifying assumptions often made in models, they make an ideal testbed for computational models of cognition. By adopting a framework that embeds existing social knowledge into the model, we can go beyond explaining behaviors in laboratory tasks to explaining those observed in the wild.

Neurocomputational mechanisms engaged in moral choices and moral learning

The neural circuitry involved in moral decisions has been studied since the early days of cognitive neuroscience, mainly using moral dilemma. However, the neurocomputational mechanisms describing how the human brain makes moral decisions and learns in various moral contexts are only starting to be established. Here we review recent results from an emerging field using model-based fMRI, which describes moral choices at a mechanistic level. These findings unify the field of moral decision making, extend a conceptual framework previously developed for value-based decision making and characterize how moral processes are computed in the brain. Moral dilemma can be modeled as value-based decisions that weigh self-interests against moral costs/harm to others and different types of prediction errors can be distinguished in different aspects of moral learning. These key computational signals help to describe moral choices and moral learning at an algorithmic level and to reveal how these cognitive operations are implemented in the brain. This researches provide a foundation to account for the neurocomputational mechanisms underlying moral decision making.

Altruism as an Explanation for Human Consanguinity

BACKGROUND

Human inbreeding is a sociobiological puzzle. Despite widespread knowledge of its potential for genetic disorders, human consanguinity remains surprisingly common. The current reasons explaining its continued persistence in today's modern world have major shortcomings.

SUMMARY

We propose that the Neolithic Agrarian revolution modified the structure of populations. It increased competition for the limited resources in which a larger group had better chances of survival. As a result, small, drifting, socially open bands of hunter-gatherers were transformed into bigger, less mobile, and more powerful kinship groups (tribes). In this transformation, a central role was played by human trust - an aspect of human altruism which is a universal sociobiological principle of behavior. Altruism (and trust) is an essential premise of social contracts such as economic cooperation, marriage arrangement, and creation of alliances between people. In kinship groups, human trust is limited to kin, so tribes remain small, economically poor, and consanguineous due to lack of nonkin mates. The expanding of trust from kin to that of nonbiological relatives increases the size of human groups, fosters economic wealth, and decreases the rate of consanguinity. Key Messages: The lack of nonkin altruism leads to: (a) poverty (due to poor economic cooperation with nonkin), (b) maintaining small group size, and (c) inbreeding.

Why is the literature on first impressions so focused on White faces?

We spontaneously attribute to strangers a wide variety of character traits based on their facial appearance. While these first impressions have little or no basis in reality, they exert a strong influence over our behaviour. Cognitive scientists have revealed a great deal about first impressions from faces including their factor structure, the cues on which they are based, the neurocognitive mechanisms responsible, and their developmental trajectory. In this field, authors frequently strive to remove as much ethnic variability from stimulus sets as possible. Typically, this convention means that participants are asked to judge the likely traits of White faces only. In the present article, we consider four possible reasons for the lack of facial diversity in this literature and find that it is unjustified. Next, we illustrate how the focus on White faces has undermined scientific efforts to understand first impressions from faces and argue that it reinforces socially regressive ideas about 'race' and status. We go on to articulate our concern that opportunities may be lost to leverage the knowledge derived from the study of first impressions against the dire consequences of prejudice and discrimination. Finally, we highlight some promising developments in the field.

Person knowledge shapes face identity perception

Recognition of others' identity through facial features is essential in life. Using both correlational and experimental approaches, we examined how person knowledge biases the perception of others' facial identity. When a participant believed any two individuals were more similar in personality, their faces were perceived to be correspondingly more similar (assessed via mousetracking, Study 1). Further, participants' facial representations of target individuals that were believed to have a more similar personality were found to have a greater physical resemblance (assessed via reverse-correlation, Studies 2 and 3). Finally, when participants learned about novel individuals who had a more similar personality, their faces were visually represented more similarly (Study 4). Together, the findings show that the perception of facial identity is driven not only by facial features but also the person knowledge we have learned about others, biasing it toward alternate identities despite the fact that those identities lack any physical resemblance.

Spontaneous first impressions emerge from brief training

People have a strong and reliable tendency to infer the character traits of strangers based solely on facial appearance. In five highly powered and pre-registered experiments, we investigate the relative merits of learning and nativist accounts of the origins of these first impressions. First, we test whether brief periods of training can establish consistent first impressions de novo. Using a novel paradigm with Greebles-a class of synthetic object with inter-exemplar variation that approximates that seen between individual faces-we show that participants quickly learn to associate appearance cues with trustworthiness (Experiments 1 and 2). In a further experiment, we show that participants easily learn a two-dimensional structure in which individuals are presented as simultaneously varying in both trustworthiness and competence (Experiment 3). Crucially, in the final two experiments (Experiments 4 and 5) we show that, once learned, these first impressions occur following very brief exposure (100 ms). These results demonstrate that first impressions can be rapidly learned and, once learned, take on features previously thought to hold only for innate first impressions (rapid availability). Taken together, these results highlight the plausibility of learning accounts of first impressions.

Young children learn first impressions of faces through social referencing

Previous research has demonstrated that the tendency to form first impressions from facial appearance emerges early in development. We examined whether social referencing is one route through which these consistent first impressions are acquired. In Study 1, we show that 5- to 7-year-old children are more likely to choose a target face previously associated with positive non-verbal signals as more trustworthy than a face previously associated with negative non-verbal signals. In Study 2, we show that children generalise this learning to novel faces who resemble those who have previously been the recipients of positive non-verbal behaviour. Taken together, these data show one means through which individuals within a community could acquire consistent, and potentially inaccurate, first impressions of others faces. In doing so, they highlight a route through which cultural transmission of first impressions can occur.

Enhancing models of social and strategic decision making with process tracing and neural data

Every decision we take is accompanied by a characteristic pattern of response delay, gaze position, pupil dilation, and neural activity. Nevertheless, many models of social decision making neglect the corresponding process tracing data and focus exclusively on the final choice outcome. Here, we argue that this is a mistake, as the use of process data can help to build better models of human behavior, create better experiments, and improve policy interventions. Specifically, such data allow us to unlock the "black box" of the decision process and evaluate the mechanisms underlying our social choices. Using these data, we can directly validate latent model variables, arbitrate between competing personal motives, and capture information processing strategies. These benefits are especially valuable in social science, where models must predict multi-faceted decisions that are taken in varying contexts and are based on many different types of information. This article is categorized under: Economics > Interactive Decision-Making Neuroscience > Cognition Psychology > Reasoning and Decision Making.

Instrumental learning in social interactions: Trait learning from faces and voices

Recent research suggests that reinforcement learning may underlie trait formation in social interactions with faces. The current study investigated whether the same learning mechanisms could be engaged for trait learning from voices. On each trial of a training phase, participants (N = 192) chose from pairs of human or slot machine targets that varied in the (1) reward value and (2) generosity of their payouts. Targets were either auditory (voices or tones; Experiment 1) or visual (faces or icons; Experiment 2) and were presented sequentially before payout feedback. A test phase measured participant choice behaviour, and a post-test recorded their target preference ratings. For auditory targets, we found a significant effect of reward only on target choices, but saw higher preference ratings for more generous humans and slot machines. For visual targets, findings from previous studies were replicated: participants learned about both generosity and reward, but generosity was prioritised in the human condition. These findings provide one of the first demonstrations of reinforcement learning of reward with auditory stimuli in a social learning task, but suggest that the use of auditory targets does alter learning in this paradigm. Conversely, reinforcement learning of reward and trait information with visual stimuli remains intact even when sequential presentation introduces a delay in feedback.

Generalization of conditioned fear along a dimension of increasing positive valence

The amount of fear evoked by potential threats is oftentimes proportional to the overlap in shared features with known threats. An adaptive learning system should therefore extract relevant features from threat stimuli to successfully detect other novel threats in the environment. But what if the most relevant feature of a threat stimulus is emotionally positive? Here, we used Pavlovian fear conditioning to ask whether people extract positive emotional features of a fear conditioned stimulus (CS) to selectively generalize to other stimuli that contain positive features. In a between subjects design, we first paired a picture of a face expressing either a slight amount of happiness or fear with an electrical shock to the wrist. We then tested fear generalization to modified face stimuli of the same identity expressing more or less happiness or fear. Both groups exhibited biased physiological arousal (a peak shift) to a face stimulus with the most exaggerated emotional expression, regardless of valence. Fear generalization diminished to unreinforced happy faces over the course of testing, whereas arousal was maintained to unreinforced fearful faces throughout testing. Finally, subjects fear conditioned to a slightly happy face were accurate at retrospectively identifying the correct CS, whereas subjects fear conditioned to a fearful face retrospectively misidentified a more fearful face as the threat CS. These findings suggest that positive emotional features extracted from a known threat can guide biased fear generalization, but that generalization is maintained by a dimension of increasing fear which also produces retrospective biases in threat intensity estimation.

Why do you attract me but not others? Retrieval of person knowledge and its generalization bring diverse judgments of facial attractiveness

Judgments of facial attractiveness play an important role in social interactions. However, it still remains unclear why these judgments are malleable. The present study aimed to understand whether the retrieval of person knowledge leads to different judgments of attractiveness of the same face. Event-related potentials and learning-recognition tasks were used to investigate the effects of person knowledge on facial attractiveness. The results showed that compared with familiar faces that were matched with negative person knowledge, those matched with positive person knowledge were evaluated as more attractive and evoked a larger early posterior negativity (EPN) and late positive complex (LPC). Additionally, positive similar faces had the same behavioral results and evoked large LPC, while unfamiliar faces did not have any significant effects. These results indicate that the effect of person knowledge on facial attractiveness occurs from early to late stage of facial attractiveness processing, and this effect could be generalized based on the similarity of the face structure, which occurred at the late stage. This mechanism may explain why individuals form different judgments of facial attractiveness.

Individual differences in trust evaluations are shaped mostly by environments, not genes

People evaluate a stranger's trustworthiness from their facial features in a fraction of a second, despite common advice "not to judge a book by its cover." Evaluations of trustworthiness have critical and widespread social impact, predicting financial lending, mate selection, and even criminal justice outcomes. Consequently, understanding how people perceive trustworthiness from faces has been a major focus of scientific inquiry, and detailed models explain how consensus impressions of trustworthiness are driven by facial attributes. However, facial impression models do not consider variation between observers. Here, we develop a sensitive test of trustworthiness evaluation and use it to document substantial, stable individual differences in trustworthiness impressions. Via a twin study, we show that these individual differences are largely shaped by variation in personal experience, rather than genes or shared environments. Finally, using multivariate twin modeling, we show that variation in trustworthiness evaluation is specific, dissociating from other key facial evaluations of dominance and attractiveness. Our finding that variation in facial trustworthiness evaluation is driven mostly by personal experience represents a rare example of a core social perceptual capacity being predominantly shaped by a person's unique environment. Notably, it stands in sharp contrast to variation in facial recognition ability, which is driven mostly by genes. Our study provides insights into the development of the social brain, offers a different perspective on disagreement in trust in wider society, and motivates new research into the origins and potential malleability of face evaluation, a critical aspect of human social cognition.

Living in a Disadvantaged Neighborhood Affects Neural Processing of Facial Trustworthiness

Neighborhood disorder (i.e., physical or social decay) is associated with decreased trust, which reinforces criminal behavior among some individuals in these communities. However, past research largely is descriptive and has not measured processes underlying trust. Using behavioral and neural indices [the late positive potential (LPP), a marker of salience elaboration] in a sample of adults (N = 55), we examined the association between perceived neighborhood disorder and facial trustworthiness perception as well as the potential moderating role of trustworthiness perception on the association between PND and criminal behavior. Individuals with higher perceived neighborhood disorder displayed less LPP differentiation between untrustworthy and trustworthy faces. Moreover, individuals with higher perceived neighborhood disorder and less LPP differentiation were less likely to commit a variety of crimes, whereas those with higher perceptions of neighborhood disorder and high LPP differentiation were more likely to commit a variety of crimes. Combined, these findings suggest that similarly processing trustworthy and untrustworthy faces, as indexed by less LPP differentiation, may reflect an adaptation among those with higher perceived neighborhood disorder that mitigates against deviant behavior and contacts with the law. Understanding the intersection between neighborhood characteristics and individual-level cognitive-affective processing may provide insight into what shapes beliefs and behaviors about important social information.

Green model to adapt classical conditioning learning in the hippocampus

Compared with the biological paradigms of classical conditioning, non-adaptive computational models are not capable of realistically simulating the biological behavioural functions of the hippocampal regions, because of their implausible requirement for a large number of learning trials, which can be on the order of hundreds. Additionally, these models did not attain a unified, final stable state even after hundreds of learning trials. Conversely, the output response has a different threshold for similar tasks in various models with prolonged transient response of unspecified status via the training or even testing phases. Accordingly, a green model is a combination of adaptive neuro-computational hippocampal and cortical models that is proposed by adaptively updating the whole weights in all layers for both intact networks and lesion networks using instar and outstar learning rules with adaptive resonance theory (ART). The green model sustains and expands the classical conditioning biological paradigms of the non-adaptive models. The model also overcomes the irregular output response behaviour by using the proposed feature of adaptivity. Further, the model successfully simulates the hippocampal regions without passing the final output response back to the whole network, which is considered to be biologically implausible. The results of the Green model showed a significant improvement confirmed by empirical studies of different tasks. In addition, the results indicated that the model outperforms the previously published models. All the obtained results successfully and quickly attained a stable, desired final state (with a unified concluding state of either "1" or "0") with a significantly shorter transient duration.

Behavioral and neural evidence of enhanced long-term memory for untrustworthy faces

In daily life, we automatically form impressions of other individuals on basis of subtle facial features that convey trustworthiness. Because these face-based judgements influence current and future social interactions, we investigated how perceived trustworthiness of faces affects long-term memory using event-related potentials (ERPs). In the current study, participants incidentally viewed 60 neutral faces differing in trustworthiness, and one week later, performed a surprise recognition memory task, in which the same old faces were presented intermixed with novel ones. We found that after one week untrustworthy faces were better recognized than trustworthy faces and that untrustworthy faces prompted early (350–550 ms) enhanced frontal ERP old/new differences (larger positivity for correctly remembered old faces, compared to novel ones) during recognition. Our findings point toward an enhanced long-lasting, likely familiarity-based, memory for untrustworthy faces. Even when trust judgments about a person do not necessarily need to be accurate, a fast access to memories predicting potential harm may be important to guide social behaviour in daily life.

Neural representations of honesty predict future trust behavior

Theoretical accounts propose honesty as a central determinant of trustworthiness impressions and trusting behavior. However, behavioral and neural evidence on the relationships between honesty and trust is missing. Here, combining a novel paradigm that successfully induces trustworthiness impressions with functional MRI and multivariate analyses, we demonstrate that honesty-based trustworthiness is represented in the posterior cingulate cortex, dorsolateral prefrontal cortex and intraparietal sulcus. Crucially, brain signals in these regions predict individual trust in a subsequent social interaction with the same partner. Honesty recruited the ventromedial prefrontal cortex (VMPFC), and stronger functional connectivity between the VMPFC and temporoparietal junction during honesty encoding was associated with higher trust in the subsequent interaction. These results suggest that honesty signals in the VMPFC are integrated into trustworthiness beliefs to inform present and future social behaviors. These findings improve our understanding of the neural representations of an individual’s social character that guide behaviors during interpersonal interactions.

We tend to be more trusting of people who we know to be honest. Here, the authors show using fMRI that honesty-based trustworthiness is represented in the posterior cingulate cortex, dorsolateral prefrontal cortex and intraparietal sulcus, and predicts subsequent trust decisions.

Effects of Male Defendants' Attractiveness and Trustworthiness on Simulated Judicial Decisions in Two Different Swindles

The present study aimed to examine the effects of male defendants' facial appearance (attractiveness and trustworthiness) on judicial decisions in two different swindles. We selected the following four categories of faces by manipulating facial attractiveness and trustworthiness simultaneously: the attractive and trustworthy face; the attractive but untrustworthy face; the unattractive but trustworthy face; and the unattractive and untrustworthy face. A total of six hundred and sixty-three participants across two studies were asked to make conviction-related judgments and penalty-related decisions for the defendants after they were randomly assigned to one of the four categories of faces. In Experiment 1, we used a blind-date swindle and found a "beauty penalty" for physically attractive defendants among females. Specifically, female participants were more likely to issue a guilty verdict to better-looking male defendants. Additionally, this "beauty-penalty effect" was merely observed in the untrustworthy condition. In Experiment 2, we used a telecommunication swindle, and the results showed that facial trustworthiness significantly predicted punishment magnitude and sentence decisions. Moreover, an exploratory analysis revealed that the disgust evoked by the faces partially mediated the relationship between facial trustworthiness and the assignment of criminal penalties. Taken together, these findings indicated that facial attractiveness and trustworthiness played different roles in judicial decisions. Importantly, the effect of facial attractiveness on judicial decisions differed as the detailed criminal circumstances of the offenses changed.

Olfactory Generalization in Detector Dogs

Simple Summary

Dogs are valued for their odor detection capabilities in a vast range of fields. They help to find hidden and elusive targets, such as explosives, narcotics, missing persons, and invasive or endangered species, amongst an extensive list. In all these roles, dogs are required to find real target odors that vary somewhat from those with which they were trained. For example, dogs might be trained with an explosive mixture or certain explosive compounds, and then must be able to find homemade explosives of differing compositions or manufacturing processes. This ability, to respond to similar odors in the same way as they would respond to the originally trained odor, is known as generalization. A failure to generalize can result in dogs missing targets in working scenarios. Although generalization is usually desired to some extent, dogs must also discriminate against related odors that are not targets. Therefore, research that investigates factors that can influence dogs’ tendency to generalize, and conversely to discriminate, can inform training strategies to improve detection outcomes. However, this field requires further research with greater application to practical training.

Abstract

Generalizing to target odor variations while retaining specificity against non-targets is crucial to the success of detector dogs under working conditions. As such, the importance of generalization should be considered in the formulation of effective training strategies. Research investigating olfactory generalization from pure singular compounds to more complex odor mixtures helps to elucidate animals’ olfactory generalization tendencies and inform ways to alter the generalization gradient by broadening or narrowing the range of stimuli to which dogs will respond. Olfactory generalization depends upon both intrinsic factors of the odors, such as concentration, as well as behavioral and cognitive factors related to training and previous experience. Based on the current research, some training factors may influence generalization. For example, using multiple target exemplars appears to be the most effective way to promote elemental processing and broaden the generalization gradient, whereas increasing the number of training instances with fewer exemplars can narrow the gradient, thereby increasing discrimination. Overall, this research area requires further attention and study to increase our understanding of olfactory generalization in dogs, particularly detector dogs, to improve training and detection outcomes.

Multivoxel Pattern Analysis Reveals a Neural Phenotype for Trust Bias in Adolescents

The extent to which individuals are inclined to judge unfamiliar others as trustworthy can have important implications for social functioning. Using multivariate pattern analysis, a neural phenotype of trust bias was identified in 48 human adolescents (ages 14-18 years, 26 female). Adolescents who exhibited more similar brain response to faces at the extremes of a trustworthy gradient were more likely to rate neutral faces as trustworthy. This relation between neural pattern representation and trust bias was evinced in the amygdala. Amygdala-insula connectivity dissimilarity to faces at the extremes of the trustworthy gradient was associated with greater trust bias to neutral faces, serving as a distinct circuit-level contributor to decision-making over and above of amygdala pattern similarity. These findings aid understanding of neural mechanisms contributing to individual differences in social evaluations of ambiguity.

Anxious behaviour in a demonstrator affects observational learning

Humans can acquire fear through the observation of others’ (learning models’) threat responses. These responses can be direct responses to aversive stimuli, or anticipatory responses to threats. Most research focuses on learning from observation of direct responses only. Here, we investigated how observational fear conditioning is influenced by a learning model’s typically anxious anticipatory responses. High anxiety individuals often display typically anxious anticipatory behaviour, such as worsened discrimination between safe and unsafe stimuli, characterized by increased threat responses to safe stimuli. We hypothesized that observation of an anxiously behaving model would worsen discriminatory learning. To this end, we developed an observational conditioning paradigm where a learning model was exposed to one safe and one unsafe stimuli. The learning model displayed anticipatory aversion to either to the unsafe stimulus only (Non-Anxious Model group) or to both the safe and unsafe stimuli (Anxious Model group) in addition to reacting directly to an aversive stimulus paired with the unsafe stimulus. Contrary to expectations, discriminatory learning was not worsened in the Anxious Model group compared to the Non-Anxious Model group. Rather, we saw more robust discriminatory learning in the Anxious Model group. The study provides a first step towards understanding the effect of other’s anticipatory responses in general and typically anxious anticipatory responses in particular, on observational fear learning.

Generalization of fear in post-traumatic stress disorder

Overgeneralization (i.e., the transfer of fear to stimuli not related to an aversive event) is part of alterations in associative fear learning in mental disorders. In the present experimental study, we investigated whether this holds true for post-traumatic stress disorder (PTSD) related to childhood abuse. We expected that fear generalization under experimental conditions reflects generalization of aversive stimuli to different social domains in real life. Sixty-four women with PTSD after childhood abuse and 30 healthy participants (HC) underwent a differential fear conditioning and generalization paradigm. Online risk ratings, reaction time, and fear-potentiated startle served as dependent variables. Based on the subjectively assessed generalization of triggered intrusions across different domains of life, PTSD participants were split into two groups reporting low (low-GEN) and high (high-GEN) generalization. PTSD patients reported a higher expectation of an aversive event. During fear conditioning, they assessed the risk of danger related to a safety cue slower and showed a blunted fear-potentiated startle toward the danger cue. During generalization testing, reaction time increased in the high-GEN patients and decreased in the HC group with increasing similarity of a stimulus with the conditioned safety cue. Alterations of fear learning in PTSD suggest impaired defensive responses in case of a high threat probability. Moreover, our findings bridge the gap between the generalization of aversive cues during everyday life and laboratory-based experimental parameters: impairments in the processing of cues signaling safety generalize particularly in those patients who report a spreading of PTSD symptoms across different domains of everyday life.

Generalization of appetitive conditioned responses

A stimulus (conditioned stimulus, CS) associated with an appetitive unconditioned stimulus (US) acquires positive properties and elicits appetitive conditioned responses (CR). Such associative learning has been examined extensively in animals with food as the US, and results are used to explain psychopathologies (e.g., substance‐related disorders or obesity). Human studies on appetitive conditioning exist, too, but we still know little about generalization processes. Understanding these processes may explain why stimuli not associated with a drug, for instance, can elicit craving. Forty‐seven hungry participants underwent an appetitive conditioning protocol during which one of two circles with different diameters (CS+) became associated with an appetitive US (chocolate or salty pretzel, according to participants’ preference) but never the other circle (CS−). During generalization, US were delivered twice and the two CS were presented again plus four circles (generalization stimuli, GS) with gradually increasing diameters from CS− to CS+. We found successful appetitive conditioning as reflected in appetitive subjective ratings (positive valence, higher contingency) and physiological responses (startle attenuation and larger skin conductance responses) to CS+ versus CS−, and, importantly, both measures confirmed generalization as indicated by generalization gradients. Small changes in CS‐US contingency during generalization may have weakened generalization processes on the physiological level. Considering that appetitive conditioned responses can be generalized to non‐US‐associated stimuli, a next important step would be to investigate risk factors that mediate overgeneralization.

Numerous studies demonstrated overgeneralization of conditioned fear as a pathological marker for anxiety disorders as well as stress‐related disorders. Appetitive conditioning is crucially involved in mental disorders such as eating or substance‐related and addictive disorders. Thus far, the generalization processes of appetitive conditioned responses remain unexplored. In this study, we demonstrate for the first time a generalization gradient of appetitive conditioned responses. Our study contributes and extends the understanding of generalization processes by explaining, for instance, why craving can be elicited by stimuli that share physical properties with a stimulus signaling the drug.

Arbitrary signals of trustworthiness - social judgments may rely on facial expressions even with experimentally manipulated valence

Generalization has been suggested as a basic mechanism in forming impressions about unfamiliar people. In this study, we investigated how social evaluations will be transferred to individual faces across contexts and to expressions across individuals. A total of 93 people (33 men, age: M = 29.95; SD = 13.74) were exposed to facial images which they had to evaluate. In the Association phase, we presented one individual with (1) a trustworthy, (2) an untrustworthy, (3) or an ambiguous expression, with either positive or negative descriptive sentence pairs. In the Evaluation phase participants were shown (1) a new individual with the same emotional facial expression as seen before, and (2) a neutral image of the previously presented individual. They were asked to judge the trustworthiness of each person. We found that the valence of the social description is transferred to both individuals and expressions. That is, the social evaluations (positive or negative) transferred between the images of two different individuals if they both displayed the same facial expression. The consistency between the facial expression and the description, however, had no effect on the evaluation of the same expression appearing on an unfamiliar face. Results suggest that in social evaluation of unfamiliar people invariant and dynamically changing facial traits are used to a similar extent and influence these judgements through the same associative process.

Like what you see: Generalization of social learning determines art appreciation

We examine whether a stimulus generalization framework can provide insight in how experience shapes evaluative responses to artworks. Participants received positive information about one artwork and negative information about another artwork. Afterwards, we tested their evaluative responses not only to these artworks but also to similar artworks, which allowed us to assess generalization. Results showed that the artwork that was paired with positive information and the artwork that was similar to it were evaluated more positively than the other artworks. These findings confirm that theories that aim to explain art appreciation could benefit from taking learning and its generalization into account.

Viewing Adaptive Social Choice Through the Lens of Associative Learning

Because humans live in a dynamic and evolving social world, modeling the factors that guide social behavior has remained a challenge for psychology. In contrast, much progress has been made on understanding some of the more basic elements of human behavior, such as associative learning and memory, which has been successfully modeled in other species. Here we argue that applying an associative learning approach to social behavior can offer valuable insights into the human moral experience. We propose that the basic principles of associative learning-conserved across a range of species-can, in many situations, help to explain seemingly complex human behaviors, including altruistic, cooperative, and selfish acts. We describe examples from the social decision-making literature using Pavlovian learning phenomena (e.g., extinction, cue competition, stimulus generalization) to detail how a history of positive or negative social outcomes influences cognitive and affective mechanisms that shape moral choice. Examining how we might understand social behaviors and their likely reliance on domain-general mechanisms can help to generate testable hypotheses to further understand how social value is learned, represented, and expressed behaviorally.

The application of computational models to social neuroscience: promises and pitfalls

Interactions with conspecifics are key to any social species. In order to navigate this social world, it is crucial for individuals to learn from and about others. From learning new skills by observing parents perform them to making complex collective decisions, understanding the mechanisms underlying social cognitive processes has been of considerable interest to psychologists and neuroscientists. Here, we review studies that have used computational modelling techniques, combined with neuroimaging, to shed light on how people learn and make decisions in social contexts. As opposed to standard social neuroscience methods, the computational approach allows one to directly examine where in the brain particular computations, as estimated by models of behavior, are implemented. Findings suggest that people use several strategies to learn from others: vicarious reward learning, where one learns from observing the reward outcomes of another agent; action imitation, which relies on encoding a prediction error between the expected and actual actions of the other agent; and social inference, where one learns by inferring the goals and intentions of others. These computations are implemented in distinct neural networks, which may be recruited adaptively depending on task demands, the environment and other social factors.

Computational neuroscience approaches to social cognition

How do we form impressions of people and groups and use these representations to guide our actions? From its inception, social neuroscience has sought to illuminate such complex forms of social cognition, and recently these efforts have been invigorated by the use of computational modeling. Computational modeling provides a framework for delineating specific processes underlying social cognition and relating them to neural activity and behavior. We provide a primer on the computational modeling approach and describe how it has been used to elucidate psychological and neural mechanisms of impression formation, social learning, moral decision making, and intergroup bias.