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Previous research has examined the real-time cognitive processes underlying perceivers' ability to resolve racial ambiguity into monoracial categorizations, but such processes for multiracial categorizations are less clear. Using a novel, three-choice mouse-tracking paradigm, we found that when perceivers categorized faces as multiracial their hand movements revealed an initial attraction to a monoracial category (study 1). Moreover, exposure to multiracial individuals moderated these effects. When measured (Study 2) or manipulated (Study 3), multiracial exposure reduced monoracial category activation and activation occurred for both morphed and real multiracial faces (Study 4). Together, the findings suggest that multiracial categorizations emerge from dynamic competition between relatively more accessible monoracial categories and a less-accessible multiracial category, which is attenuated through greater exposure to multiracial targets. This research is the first to chart out the real-time dynamics underlying multiracial categorizations and offers a new theoretical account of this increasingly common form of social categorization.

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From a glimpse of a face, people form trait impressions that operate as "facial stereotypes", which are largely inaccurate yet nevertheless drive social behavior. Behavioral studies have long pointed to dimensions of trustworthiness and dominance that are thought to underlie face impressions due to their evolutionarily adaptive nature. Using human neuroimaging (N=26, 19 female, 7 male), we identify a two-dimensional representation of faces' inferred traits in the middle temporal gyrus (MTG), a region involved in domain-general conceptual processing including the activation of social concepts. The similarity of neural-response patterns for any given pair of faces in the bilateral MTG was predicted by their proximity in trustworthiness-dominance space, an effect that could not be explained by mere visual similarity. This MTG trait-space representation occurred automatically, was relatively invariant across participants, and did not depend on the explicit endorsement of face impressions (i.e., beliefs that face impressions are valid and accurate). In contrast, regions involved in high-level social reasoning (the bilateral temporoparietal junction and posterior superior temporal sulcus; TPJ-pSTS) and entity-specific social knowledge (the left anterior temporal lobe; ATL), also exhibited this trait-space representation, but only among participants who explicitly endorsed forming these impressions. Together, the findings identify a two-dimensional neural representation of face impressions and suggest that multiple implicit and explicit mechanisms give rise to biases based on facial appearance. While the MTG implicitly represents a multidimensional trait space for faces, the TPJ-pSTS and ATL are involved in the explicit application of this trait space for social evaluation and behavior.Significance Statement People form trait impressions based on facial features, which operate like facial stereotypes that bias social decision-making and shape real-world outcomes in career, legal, and political domains. We show that the brain represents others' faces as points in a two-dimensional space tracking trustworthiness and dominance. One brain region, involved in the activation of conceptual attributes, automatically represented this trait space in response to faces, even if participants did not explicitly endorse the use of facial stereotyping. Other regions, involved in the social reasoning of others' internal qualities, also represented this trait space, but only among participants who endorsed facial stereotyping. The findings reveal how harmful biases based on facial appearance arise in the brain through multiple implicit and explicit mechanisms.

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Initial impressions of others based on facial appearances are often inaccurate yet can lead to dire outcomes. Across four studies, adult participants underwent a counterstereotype training to reduce their reliance on facial appearance in consequential social judgments of White male faces. In Studies 1 and 2, trustworthiness and sentencing judgments among control participants predicted whether real-world inmates were sentenced to death versus life in prison, but these relationships were diminished among trained participants. In Study 3, a sequential priming paradigm demonstrated that the training was able to abolish the relationship between even automatically and implicitly perceived trustworthiness and the inmates' life-or-death sentences. Study 4 extended these results to realistic decision-making, showing that training reduced the impact of facial trustworthiness on sentencing decisions even in the presence of decision-relevant information. Overall, our findings suggest that a counterstereotype intervention can mitigate the potentially harmful effects of relying on facial appearance in consequential social judgments.

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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.

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Cesario claims that all bias research tells us is that people "end up using the information they have come to learn as being probabilistically accurate in their daily lives" (sect. 5, para. 4). We expose Cesario's flawed assumptions about the relationship between accuracy and bias. Through statistical simulations and empirical work, we show that even probabilistically accurate responses are regularly accompanied by bias.

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Reducing negative impacts of stress, for example through mindfulness training, benefits physical and psychological well-being and is becoming ever more crucial owing to large-scale societal uncertainties (e.g., COVID-19). Whereas extensive research has focused on mindfulness-related reductions in self-reported negativity, essentially no research has targeted task-based behavioral outcomes throughout long-term mindfulness trainings. Responses to emotionally ambiguous signals (e.g., surprised expressions), which might be appraised as either positive or negative, provide a nuanced assessment of one's emotional bias across diverse contexts, offering unique leverage for assessing the effects of mindfulness. Here, we compared the effects of short- and long-term training via Mindfulness-Based Stress Reduction on ratings of faces with a relatively clear (angry, happy) and ambiguous (surprised) valence. Ratings became more positive for ambiguity from the start (Week 1) to end of training (Week 8; p < .001), but there were no short-term effects (from a single class session). This shift toward positivity continued through an additional 8-week follow-up (Week 16; p < .001). Notably, posttraining valence bias (Week 8) was uniquely predicted by the nonreactivity facet of mindfulness (p = .01). Together, mindfulness promotes a relatively long-lasting shift toward positivity bias, which is uniquely supported by reduced emotional reactivity. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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Impressions of other people's faces (e.g., trustworthiness) have long been thought to be evoked by morphological variation (e.g., upturned mouth) in a universal, fixed manner. However, recent research suggests that these impressions vary considerably across perceivers and targets' social-group memberships. Across 4,247 U.S. adults recruited online, we investigated whether racial and gender stereotypes may be a critical factor underlying this variability in facial impressions. In Study 1, we found that not only did facial impressions vary by targets' gender and race, but also the structure of these impressions was associated with the structure of stereotype knowledge. Study 2 extended these findings by demonstrating that individual differences in perceivers' own unique stereotype associations predicted the structure of their own facial impressions. Together, the findings suggest that the structure of people's impressions of others' faces is driven not only by the morphological variation of the face but also by learned stereotypes about social groups.

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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.

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Across multiple domains of social perception-including social categorization, emotion perception, impression formation and mentalizing-multivariate pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data has permitted a more detailed understanding of how social information is processed and represented in the brain. As in other neuroimaging fields, the neuroscientific study of social perception initially relied on broad structure-function associations derived from univariate fMRI analysis to map neural regions involved in these processes. In this review, we trace the ways that social neuroscience studies using MVPA have built on these neuroanatomical associations to better characterize the computational relevance of different brain regions, and discuss how MVPA allows explicit tests of the correspondence between psychological models and the neural representation of social information. We also describe current and future advances in methodological approaches to multivariate fMRI data and their theoretical value for the neuroscience of social perception.

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Previous research has shown that social-conceptual associations, such as stereotypes, can influence the visual representation of faces and neural pattern responses in ventral temporal cortex (VTC) regions, such as the fusiform gyrus (FG). Current models suggest that this social-conceptual impact requires medial orbitofrontal cortex (mOFC) feedback signals during perception. Backward masking can disrupt such signals, as it is a technique known to reduce functional connectivity between VTC regions and regions outside VTC. During functional magnetic resonance imaging (fMRI), subjects passively viewed masked and unmasked faces, and following the scan, perceptual biases and stereotypical associations were assessed. Multi-voxel representations of faces across the VTC, and in the FG and mOFC, reflected stereotypically biased perceptions when faces were unmasked, but this effect was abolished when faces were masked. However, the VTC still retained the ability to process masked faces and was sensitive to their categorical distinctions. Functional connectivity analyses confirmed that masking disrupted mOFC-FG connectivity, which predicted a reduced impact of stereotypical associations in the FG. Taken together, our findings suggest that the biasing of face representations in line with stereotypical associations does not arise from intrinsic processing within the VTC and FG alone, but instead it depends in part on top-down feedback from the mOFC during perception.

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Everyday social interactions hinge on our ability to resolve uncertainty in nonverbal cues. For example, although some facial expressions (e.g. happy, angry) convey a clear affective meaning, others (e.g. surprise) are ambiguous, in that their meaning is determined by the context. Here, we used mouse-tracking to examine the underlying process of resolving uncertainty. Previous work has suggested an initial negativity, in part via faster response times for negative than positive ratings of surprise. We examined valence categorizations of filtered images in order to compare faster (low spatial frequencies; LSF) versus more deliberate processing (high spatial frequencies; HSF). When participants categorised faces as "positive", they first exhibited a partial attraction toward the competing ("negative") response option, and this effect was exacerbated for HSF than LSF faces. Thus, the effect of response conflict due to an initial negativity bias was exaggerated for HSF faces, likely because these images allow for greater deliberation than the LSFs. These results are consistent with the notion that more positive categorizations are characterised by an initial attraction to a default, negative response.

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Researchers have noted the resemblance across core models of social cognition, in which trait inferences centre on others' intentions and abilities (for example, warmth, competence). Current views posit that this common 'trait space' originates from the adaptive utility of the dimensions, predicting a relatively fixed and universal architecture. In contrast, we hypothesize that perceivers learn conceptual knowledge of how traits correlate, which shapes trait inferences similarly across domains (for example, faces, person knowledge, stereotypes), from which a common trait space emerges. Here we show substantial overlap between the structures of perceivers' conceptual and social perceptual trait spaces, across perceptual domains (studies 1-4) and that conceptual associations directly shape trait space (study 5). Furthermore, we find evidence that conceptual trait space is learned from social perception and actual personality structure (studies 6 and 7). Our findings suggest conceptual trait associations serve as a cornerstone in social perception, providing broad implications for the study of social behaviour.

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The perception of social categories, emotions, and personality traits from others' faces each have been studied extensively but in relative isolation. We synthesize emerging findings suggesting that, in each of these domains of social perception, both a variety of bottom-up facial features and top-down social cognitive processes play a part in driving initial perceptions. Among such top-down processes, social-conceptual knowledge in particular can have a fundamental structuring role in how we perceive others' faces. Extending the Dynamic Interactive framework (Freeman & Ambady, 2011), we outline a perspective whereby the perception of social categories, emotions, and traits from faces can all be conceived as emerging from an integrated system relying on domain-general cognitive properties. Such an account of social perception would envision perceptions to be a rapid, but gradual, process of negotiation between the variety of visual cues inherent to a person and the social cognitive knowledge an individual perceiver brings to the perceptual process. We describe growing evidence in support of this perspective as well as its theoretical implications for social psychology.

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Humans reliably categorize configurations of facial actions into specific emotion categories, leading some to argue that this process is invariant between individuals and cultures. However, growing behavioral evidence suggests that factors such as emotion-concept knowledge may shape the way emotions are visually perceived, leading to variability-rather than universality-in facial-emotion perception. Understanding variability in emotion perception is only emerging, and the neural basis of any impact from the structure of emotion-concept knowledge remains unknown. In a neuroimaging study, we used a representational similarity analysis (RSA) approach to measure the correspondence between the conceptual, perceptual, and neural representational structures of the six emotion categories Anger, Disgust, Fear, Happiness, Sadness, and Surprise. We found that subjects exhibited individual differences in their conceptual structure of emotions, which predicted their own unique perceptual structure. When viewing faces, the representational structure of multivoxel patterns in the right fusiform gyrus was significantly predicted by a subject's unique conceptual structure, even when controlling for potential physical similarity in the faces themselves. Finally, cross-cultural differences in emotion perception were also observed, which could be explained by individual differences in conceptual structure. Our results suggest that the representational structure of emotion expressions in visual face-processing regions may be shaped by idiosyncratic conceptual understanding of emotion categories.

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The visual system is able to extract an enormous amount of socially relevant information from the face, including social categories, personality traits, and emotion. While facial features may be directly tied to certain perceptions, emerging research suggests that top-down social cognitive factors (e.g., stereotypes, social-conceptual knowledge, prejudice) considerably influence and shape the perceptual process. The rapid integration of higher-order social cognitive processes into visual perception can give rise to systematic biases in face perception and may potentially act as a mediating factor for intergroup behavioral and evaluative biases. Drawing on neuroimaging evidence, we review the ways that top-down social cognitive factors shape visual perception of facial features. This emerging work in social and affective neuroscience builds upon work on predictive coding and perceptual priors in cognitive neuroscience and visual cognition, suggesting domain-general mechanisms that underlie a social-visual interface through which social cognition affects visual perception.

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BACKGROUND: Although mental health stigmatization has myriad pernicious consequences, it remains unknown whether mental disorders are stigmatized for the same reasons. AIMS: This study identified the stigma-related beliefs that were associated with several common mental illnesses (Study 1), and the extent to which those beliefs predicted stigmatization (Study 2). METHODS: In Study 1, we used multidimensional scaling to identify the stigma-related beliefs attributed to nine common mental disorders (e.g. depression, schizophrenia). Study 2 explored whether beliefs commonly associated with depression predicted its stigmatization. RESULTS: In Study 1, we found that the nine mental illnesses differed from each other on two dimensions: social desirability and controllability. In Study 2, we found that regardless of participants' own depression status, their perceptions that depression is controllable predicted depression-related stigmatization. CONCLUSIONS: Our results suggest that stigmatization toward different mental illnesses stem from combinations of different stigmatized beliefs.

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Over the past decade, mouse-tracking in choice tasks has become a popular method across psychological science. This method exploits hand movements as a measure of multiple response activations that can be tracked continuously over hundreds of milliseconds. Whereas early mouse-tracking research focused on specific debates, researchers have realized the methodology has far broader theoretical value. This more recent work demonstrates that mouse-tracking is a widely applicable measure across the field, capable of exposing the micro-structure of real-time decisions including their component processes and millisecond-resolution time-course in ways that inform theory. In the article, recent advances in the mouse-tracking approach are described, and comparisons with the gold standard measure of reaction time and other temporally-sensitive methodologies are provided. Future directions, including mapping to neural representations with brain-imaging and ways to improve our theoretical understanding of mouse-tracking methodology, are discussed.

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An emerging focus on the geometry of representational structures is advancing a variety of areas in social perception, including social categorization, emotion perception, and trait impressions. Here, we review recent studies adopting a representational geometry approach, and argue that important advances in social perception can be gained by triangulating on the structure of representations via three levels of analysis: neuroimaging, behavioral measures, and computational modeling. Among other uses, this approach permits broad and comprehensive tests of how bottom-up facial features and visual processes as well as top-down social cognitive factors and conceptual processes shape perceptions of social categories, emotion, and personality traits. Although such work is only in its infancy, a focus on corroborating representational geometry across modalities is allowing researchers to use multiple levels of analysis to constrain theoretical models in social perception. This approach holds promise to further our understanding of the multiply determined nature of social perception and its neural basis.

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