Teaching robots the art of human social synchrony.

Humanoid robots can now learn the art of social synchrony using neural networks.

Social class perception is driven by stereotype-related facial features.

Social class is a powerful hierarchy that determines many privileges and disadvantages. People form impressions of others' social class (like other important social attributes) from facial appearance, and these impressions correlate with stereotype judgments. However, what drives these related subjective judgments remains unknown.

Cultural facial expressions dynamically convey emotion category and intensity information.

Communicating emotional intensity plays a vital ecological role because it provides valuable information about the nature and likelihood of the sender's behavior. For example, attack often follows signals of intense aggression if receivers fail to retreat. Humans regularly use facial expressions to communicate such information.

Testing, explaining, and exploring models of facial expressions of emotions.

Models are the hallmark of mature scientific inquiry. In psychology, this maturity has been reached in a pervasive question-what models best represent facial expressions of emotion? Several hypotheses propose different combinations of facial movements [action units (AUs)] as best representing the six basic emotions and four conversational signals across cultures. We developed a new framework to formalize such hypotheses as predictive models, compare their ability to predict human emotion categorizations in Western and East Asian cultures, explain the causal role of individual AUs, and explore updated, culture-accented models that improve performance by reducing a prevalent Western bias.

Face mediated human-robot interaction for remote medical examination.

Realtime visual feedback from consequences of actions is useful for future safety-critical human-robot interaction applications such as remote physical examination of patients. Given multiple formats to present visual feedback, using face as feedback for mediating human-robot interaction in remote examination remains understudied. Here we describe a face mediated human-robot interaction approach for remote palpation.

Simulating dynamic facial expressions of pain from visuo-haptic interactions with a robotic patient.

Medical training simulators can provide a safe and controlled environment for medical students to practice their physical examination skills. An important source of information for physicians is the visual feedback of involuntary pain facial expressions in response to physical palpation on an affected area of a patient. However, most existing robotic medical training simulators that can capture physical examination behaviours in real-time cannot display facial expressions and comprise a limited range of patient identities in terms of ethnicity and gender.

Facial expressions elicit multiplexed perceptions of emotion categories and dimensions.

Human facial expressions are complex, multi-component signals that can communicate rich information about emotions, including specific categories, such as "anger," and broader dimensions, such as "negative valence, high arousal." An enduring question is how this complex signaling is achieved. Communication theory predicts that multi-component signals could transmit each type of emotion information-i.

Modeling individual preferences reveals that face beauty is not universally perceived across cultures.

Facial attractiveness confers considerable advantages in social interactions, with preferences likely reflecting psychobiological mechanisms shaped by natural selection. Theories of universal beauty propose that attractive faces comprise features that are closer to the population average while optimizing sexual dimorphism. However, emerging evidence questions this model as an accurate representation of facial attractiveness, including representing the diversity of beauty preferences within and across cultures.

Revealing the information contents of memory within the stimulus information representation framework.

The information contents of memory are the cornerstone of the most influential models in cognition. To illustrate, consider that in predictive coding, a prediction implies that specific information is propagated down from memory through the visual hierarchy. Likewise, recognizing the input implies that sequentially accrued sensory evidence is successfully matched with memorized information (categorical knowledge).

The use of contextual information in forensic toxicology: An international survey of toxicologists' experiences.

Cognitive bias is a well-documented automatic process that can have serious negative consequences in a variety of settings. For example, cognitive bias within a forensic science setting can lead to examiners' judgements being swayed by details that they have learned while working on the case, and which go beyond the physical evidence being examined. Although cognitive bias has been studied in many forensic disciplines, such as fingerprints, bullet comparison, and document examination, knowledge of cognitive bias within forensic toxicology is lacking.

Data-Driven Methods to Diversify Knowledge of Human Psychology.

Psychology aims to understand real human behavior. However, cultural biases in the scientific process can constrain knowledge. We describe here how data-driven methods can relax these constraints to reveal new insights that theories can overlook.

Discovering cultural differences (and similarities) in facial expressions of emotion.

Understanding the cultural commonalities and specificities of facial expressions of emotion remains a central goal of Psychology. However, recent progress has been stayed by dichotomous debates (e.g.

Functional Smiles: Tools for Love, Sympathy, and War.

A smile is the most frequent facial expression, but not all smiles are equal. A social-functional account holds that smiles of reward, affiliation, and dominance serve basic social functions, including rewarding behavior, bonding socially, and negotiating hierarchy. Here, we characterize the facial-expression patterns associated with these three types of smiles.

Toward a Social Psychophysics of Face Communication.

As a highly social species, humans are equipped with a powerful tool for social communication-the face. Although seemingly simple, the human face can elicit multiple social perceptions due to the rich variations of its movements, morphology, and complexion. Consequently, identifying precisely what face information elicits different social perceptions is a complex empirical challenge that has largely remained beyond the reach of traditional methods.

Space-by-time manifold representation of dynamic facial expressions for emotion categorization.

Visual categorization is the brain computation that reduces high-dimensional information in the visual environment into a smaller set of meaningful categories. An important problem in visual neuroscience is to identify the visual information that the brain must represent and then use to categorize visual inputs. Here we introduce a new mathematical formalism-termed space-by-time manifold decomposition-that describes this information as a low-dimensional manifold separable in space and time.

Four not six: Revealing culturally common facial expressions of emotion.

As a highly social species, humans generate complex facial expressions to communicate a diverse range of emotions. Since Darwin's work, identifying among these complex patterns which are common across cultures and which are culture-specific has remained a central question in psychology, anthropology, philosophy, and more recently machine vision and social robotics. Classic approaches to addressing this question typically tested the cross-cultural recognition of theoretically motivated facial expressions representing 6 emotions, and reported universality.

The Human Face as a Dynamic Tool for Social Communication.

As a highly social species, humans frequently exchange social information to support almost all facets of life. One of the richest and most powerful tools in social communication is the face, from which observers can quickly and easily make a number of inferences - about identity, gender, sex, age, race, ethnicity, sexual orientation, physical health, attractiveness, emotional state, personality traits, pain or physical pleasure, deception, and even social status. With the advent of the digital economy, increasing globalization and cultural integration, understanding precisely which face information supports social communication and which produces misunderstanding is central to the evolving needs of modern society (for example, in the design of socially interactive digital avatars and companion robots).

Reconstructing dynamic mental models of facial expressions in prosopagnosia reveals distinct representations for identity and expression.

The human face transmits a wealth of signals that readily provide crucial information for social interactions, such as facial identity and emotional expression. Yet, a fundamental question remains unresolved: does the face information for identity and emotional expression categorization tap into common or distinct representational systems? To address this question we tested PS, a pure case of acquired prosopagnosia with bilateral occipitotemporal lesions anatomically sparing the regions that are assumed to contribute to facial expression (de)coding (i.e.

Facial movements strategically camouflage involuntary social signals of face morphology.

Animals use social camouflage as a tool of deceit to increase the likelihood of survival and reproduction. We tested whether humans can also strategically deploy transient facial movements to camouflage the default social traits conveyed by the phenotypic morphology of their faces. We used the responses of 12 observers to create models of the dynamic facial signals of dominance, trustworthiness, and attractiveness.

Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over time.

Designed by biological and social evolutionary pressures, facial expressions of emotion comprise specific facial movements to support a near-optimal system of signaling and decoding. Although highly dynamical, little is known about the form and function of facial expression temporal dynamics. Do facial expressions transmit diagnostic signals simultaneously to optimize categorization of the six classic emotions, or sequentially to support a more complex communication system of successive categorizations over time? Our data support the latter.

Facial expressions of emotion are not culturally universal.

Since Darwin's seminal works, the universality of facial expressions of emotion has remained one of the longest standing debates in the biological and social sciences. Briefly stated, the universality hypothesis claims that all humans communicate six basic internal emotional states (happy, surprise, fear, disgust, anger, and sad) using the same facial movements by virtue of their biological and evolutionary origins [Susskind JM, et al. (2008) Nat Neurosci 11:843-850].

Social experience does not abolish cultural diversity in eye movements.

Adults from Eastern (e.g., China) and Western (e.

Internal representations reveal cultural diversity in expectations of facial expressions of emotion.

Facial expressions have long been considered the "universal language of emotion." Yet consistent cultural differences in the recognition of facial expressions contradict such notions (e.g.