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Facial occlusion alters social processes that rely on face visibility, including spontaneous mimicry of emotions. Given that facial mimicry of emotions is theorized to play an important role in how we empathize or share emotions with others, here we investigated if empathy was reduced for faces wearing masks because masks may reduce the ability to mimic facial expressions. In two preregistered experiments, participants rated their empathy for faces displaying happy or neutral emotions and wearing masks or no masks. We manipulated mimicry by either blocking mimicry with observers holding a pen in between their teeth (Experiment 1) or by producing a state of constant congruent mimicry by instructing observers to smile (Experiment 2). Results showed reduced empathy ratings for masked faces. Mimicry overall facilitated empathy, with reduced empathy ratings when mimicry was blocked and higher empathy ratings when it was instructed. However, this effect of mimicry did not vary with mask condition. Thus, while observers were impaired in sharing emotions with masked faces, this impairment did not seem to be explained by a reduction in facial mimicry. These results show that mimicry is an important process for sharing emotions, but that occluding faces with masks reduces emotion sharing via a different mechanism. [ABSTRACT FROM AUTHOR]

Facial expression recognition(FER) is a hot topic in computer vision, especially as deep learning based methods are gaining traction in this field. However, traditional convolutional neural networks (CNN) ignore the relative position relationship of key facial features (mouth, eyebrows, eyes, etc.) due to changes of facial expressions in real-world environments such as rotation, displacement or partial occlusion. In addition, most of the works in the literature do not take visual tempos into account when recognizing facial expressions that possess higher similarities. To address these issues, we propose a visual tempos 3D-CapsNet framework(VT-3DCapsNet). First, we propose 3D-CapsNet model for emotion recognition, in which we introduced improved 3D-ResNet architecture that integrated with AU-perceived attention module to enhance the ability of feature representation of capsule network, through expressing deeper hierarchical spatiotemporal features and extracting latent information (position, size, orientation) in key facial areas. Furthermore, we propose the temporal pyramid network(TPN)-based expression recognition module(TPN-ERM), which can learn high-level facial motion features from video frames to model differences in visual tempos, further improving the recognition accuracy of 3D-CapsNet. Extensive experiments are conducted on extended Kohn-Kanada (CK+) database and Acted Facial Expression in Wild (AFEW) database. The results demonstrate competitive performance of our approach compared with other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The study of facial expressions in mammals provided great advances in the identification of their emotions and then in the comprehension of their sentience. So far, this area of research has excluded birds. With a naturalist approach, we analysed facial blushing and feather displays in domestic fowl. Hens were filmed in situations contrasting in emotional valence and arousal level: situations known to indicate calm states (positive valence / low arousal), have rewarding effects (positive valence / high arousal) or induce fear-related behaviour (negative valence / high arousal). Head feather position as well as skin redness of comb, wattles, ear lobes and cheeks varied across these situations. Skin of all four areas was less red in situations with low arousal compared to situations with higher arousal. Furthermore, skin redness of the cheeks and ear lobes also varied depending on the valence of the situation: redness was higher in situations with negative valence compared to situations with positive valence. Feather position also varied with the situations. Feather fluffing was mostly observed in positively valenced situations, except when hens were eating. We conclude that hens have facial displays that reveal their emotions and that blushing is not exclusive to humans. This opens a promising way to explore the emotional lives of birds, which is a critical step when trying to improve poultry welfare. [ABSTRACT FROM AUTHOR]

With the continuous progress of technology, facial recognition technology is widely used in various scenarios as a mature biometric technology. However, the accuracy of facial feature recognition has become a major challenge. This study proposes a face length feature and angle feature recognition method for digital libraries, targeting the recognition of different facial features. Firstly, an in-depth study is conducted on the architecture of facial action networks based on attention mechanisms to provide more accurate and comprehensive facial features. Secondly, a network architecture based on length and angle features of facial expressions, the expression recognition network is explored to improve the recognition rate of different expressions. Finally, an end-to-end network framework based on attention mechanism for facial feature points is constructed to improve the accuracy and stability of facial feature recognition network. To verify the effectiveness of the proposed method, experiments were conducted using the facial expression dataset FER-2013. The experimental results showed that the average recognition rate for the seven common expressions was 97.28% to 99.97%. The highest recognition rate for happiness and surprise was 99.97%, while the relatively low recognition rate for anger, fear, and neutrality was 97.18%. The data has verified that the research method can effectively recognize and distinguish different facial expressions, with high accuracy and robustness. The recognition method based on attention mechanism for facial feature points has effectively optimized the recognition process of facial length and angle features, significantly improving the stability of facial expression recognition, especially in complex environments, providing reliable technical support for digital libraries and other fields. This study aims to promote the development of facial recognition technology in digital libraries, improve the service quality and user experience of digital libraries. [ABSTRACT FROM AUTHOR]

Insula damage results in substantial impairments in facial emotion recognition. In particular, left hemispheric damage appears to be associated with poorer recognition of aversively rated facial expressions. Functional imaging can provide information on differences in the processing of these stimuli in patients with insula lesions when compared to healthy matched controls (HCs). We therefore investigated 17 patients with insula lesions in the chronic stage following stroke and 13 HCs using a passive-viewing task with pictures of facial expressions testing the blood oxygenation dependent (BOLD) effect in predefined regions of interest (ROIs). We expected a decrease in functional activation in an area modulating emotional response (left ventral striatum) but not in the facial recognition areas in the left inferior fusiform gyrus. Quantification of BOLD-response in ROIs but also voxel-based statistics confirmed this hypothesis. The voxel-based analysis demonstrated that the decrease in BOLD in the left ventral striatum was driven by left hemispheric damaged patients (n = 10). In our patient group, insula activation was strongly associated with the intensity rating of facial expressions. In conclusion, the combination of performance testing and functional imaging in patients following circumscribed brain damage is a challenging method for understanding emotion processing in the human brain. [ABSTRACT FROM AUTHOR]

Animal affective computing is an emerging new field, which has so far mainly focused on pain, while other emotional states remain uncharted territories, especially in horses. This study is the first to develop AI models to automatically recognize horse emotional states from facial expressions using data collected in a controlled experiment. We explore two types of pipelines: a deep learning one which takes as input video footage, and a machine learning one which takes as input EquiFACS annotations. The former outperforms the latter, with 76% accuracy in separating between four emotional states: baseline, positive anticipation, disappointment and frustration. Anticipation and frustration were difficult to separate, with only 61% accuracy. [ABSTRACT FROM AUTHOR]

Facial mimicry, the tendency to imitate facial expressions of other individuals, has been shown to play a critical role in the processing of emotion expressions. At the same time, there is evidence suggesting that its role might change when the cognitive demands of the situation increase. In such situations, understanding another person is dependent on working memory. However, whether facial mimicry influences working memory representations for facial emotion expressions is not fully understood. In the present study, we experimentally interfered with facial mimicry by using established behavioral procedures, and investigated how this interference influenced working memory recall for facial emotion expressions. Healthy, young adults (N = 36) performed an emotion expression n-back paradigm with two levels of working memory load, low (1-back) and high (2-back), and three levels of mimicry interference: high, low, and no interference. Results showed that, after controlling for block order and individual differences in the perceived valence and arousal of the stimuli, the high level of mimicry interference impaired accuracy when working memory load was low (1-back) but, unexpectedly, not when load was high (2-back). Working memory load had a detrimental effect on performance in all three mimicry conditions. We conclude that facial mimicry might support working memory for emotion expressions when task load is low, but that the supporting effect possibly is reduced when the task becomes more cognitively challenging. [ABSTRACT FROM AUTHOR]

Fearful facial expressions are nonverbal and biologically salient signals of potential threat that automatically hold, capture, and direct observers' attention. They are characterized by enlarged eye whites and dilated pupils, and fearful eyes alone are sufficient to capture attention. The morphological properties of the eye region, such as sclera exposure, are thought to play an important role in nonverbal communication. Specifically, increased sclera exposure associated with fearful expressions has been shown to moderate how observers' shift their attention toward the direction of another's gaze. Yet, the extent to which variability in sclera exposure possibly impacts the capture and hold of attention by fearful faces is untested. To address this, a sample of 249 adults completed a dot-probe task of selective attention with fearful and neutral faces. The results suggested that (1) fearful faces were prioritized over neutral faces (i.e., they captured and held attention), (2) greater sclera exposure at target locations facilitated reaction times, and (3) attention was held by greater sclera exposure of fearful faces at task irrelevant locations resulting in delayed disengagement. Collectively, the results indicate that fearful facial expressions and sclera exposure modulate spatial attention through independent and interactive mechanisms. Sclera exposure appears to be an important facilitator of nonverbal communication and perhaps represents an understudied variable in social cognition more broadly.

Neuropsychological research aims to unravel how diverse individuals' brains exhibit similar functionality when exposed to the same stimuli. The evocation of consistent responses when different subjects watch the same emotionally evocative stimulus has been observed through modalities like fMRI, EEG, physiological signals and facial expressions. We refer to the quantification of these shared consistent signals across subjects at each time instant across the temporal dimension as Consistent Response Measurement (CRM). CRM is widely explored through fMRI, occasionally with EEG, physiological signals and facial expressions using metrics like Inter-Subject Correlation (ISC). However, fMRI tools are expensive and constrained, while EEG and physiological signals are prone to facial artifacts and environmental conditions (such as temperature, humidity, and health condition of subjects). In this research, facial expression videos are used as a cost-effective and flexible alternative for CRM, minimally affected by external conditions. By employing computer vision-based automated facial keypoint tracking, a new metric similar to ISC, called the Average t-statistic, is introduced. Unlike existing facial expression-based methodologies that measure CRM of secondary indicators like inferred emotions, keypoint, and ICA-based features, the Average t-statistic is closely associated with the direct measurement of consistent facial muscle movement using the Facial Action Coding System (FACS). This is evidenced in DISFA dataset where the time-series of Average t-statistic has a high correlation (R2 = 0.78) with a metric called AU consistency, which directly measures facial muscle movement through FACS coding of video frames. The simplicity of recording facial expressions with the automated Average t-statistic expands the applications of CRM such as measuring engagement in online learning, customer interactions, etc., and diagnosing outliers in healthcare conditions like stroke, autism, depression, etc. To promote further research, we have made the code repository publicly available. [ABSTRACT FROM AUTHOR]

Parents with a history of childhood maltreatment may be more likely to respond inadequately to their child's emotional cues, such as crying or screaming, due to previous exposure to prolonged stress. While studies have investigated parents' physiological reactions to their children's vocal expressions of emotions, less attention has been given to their responses when perceiving children's facial expressions of emotions. The present study aimed to determine if viewing facial expressions of emotions in children induces cardiovascular changes in mothers (hypo- or hyper-arousal) and whether these differ as a function of childhood maltreatment. A total of 104 mothers took part in this study. Their experiences of childhood maltreatment were measured using the Childhood Trauma Questionnaire (CTQ). Participants' electrocardiogram signals were recorded during a task in which they viewed a landscape video (baseline) and images of children's faces expressing different intensities of emotion. Heart rate variability (HRV) was extracted from the recordings as an indicator of parasympathetic reactivity. Participants presented two profiles: one group of mothers had a decreased HRV when presented with images of children's facial expressions of emotions, while the other group's HRV increased. However, HRV change was not significantly different between the two groups. The interaction between HRV groups and the severity of maltreatment experienced was marginal. Results suggested that experiences of childhood emotional abuse were more common in mothers whose HRV increased during the task. Therefore, more severe childhood experiences of emotional abuse could be associated with mothers' cardiovascular hyperreactivity. Maladaptive cardiovascular responses could have a ripple effect, influencing how mothers react to their children's facial expressions of emotions. That reaction could affect the quality of their interaction with their child. Providing interventions that help parents regulate their physiological and behavioral responses to stress might be helpful, especially if they have experienced childhood maltreatment. [ABSTRACT FROM AUTHOR]

Emoji are an important substitute for non-verbal cues (such as facial expressions) in online written communication. So far, however, little is known about individual differences regarding how they are perceived. In the current study, we examined the influence of gender, age, and culture on emoji comprehension. Specifically, a sample of 523 participants across the UK and China completed an emoji classification task. In this task, they were presented with a series of emoji, each representing one of six facial emotional expressions, across four commonly used platforms (Apple, Android, WeChat, and Windows). Their task was to choose from one of six labels (happy, sad, angry, surprised, fearful, disgusted) which emotion was represented by each emoji. Results showed that all factors (age, gender, and culture) had a significant impact on how emojis were classified by participants. This has important implications when considering emoji use, for example, conversation with partners from different cultures. [ABSTRACT FROM AUTHOR]

Deficits in social cognition in attention deficit hyperactivity disorder (ADHD) have been associated with difficulties in functioning. Since recognizing emotional facial expressions is essential for developing the perceptual components of the theory of mind (ToM), it is important to assess this relationship in children with ADHD. This study therefore compared the recognition of emotional stimuli and gaze patterns between children with ADHD and healthy children using eye-tracking with dynamic facial images. It also examined the relationship between facial emotion recognition accuracy, gaze patterns, ToM scores, and ADHD symptoms. Children with ADHD aged 8–13 (n = 47) and a control group (n = 38) completed a facial emotion recognition test, ToM tests, and the Conners' Parent Rating Scale. Participants' gaze patterns in response to dynamic facial emotion expressions were recorded using eye-tracking technology. Children with ADHD exhibited significantly lower accuracy in the recognition of the facial expressions of disgust and anger. The percentage fixation in the eye region was also significantly lower for happy, angry, sad, disgusted, and neutral emotions in the children with ADHD compared to the control group. No relationship was determined between the percentage of fixations on facial areas of interests and ADHD symptoms or ToM tests. This study provides evidence that children with ADHD experience deficits in visual attention to emotional cues. In addition, it suggests that facial emotion recognition deficits in children with ADHD represent a separate domain of social cognition that develops independently of ToM skills and core symptoms. Understanding and treating the social difficulties of individuals with ADHD may help improve their social functioning. [ABSTRACT FROM AUTHOR]

Processing faces accurately and efficiently is a key capability of humans and other animals that engage in sophisticated social tasks. Recent studies reported a decoupled coding for faces in the primate inferotemporal cortex, with two separate neural populations coding for the geometric position of (texture-free) facial landmarks and for the image texture at fixed landmark positions, respectively. Here, we formally assess the efficiency of this decoupled coding by appealing to the information-theoretic notion of description length, which quantifies the amount of information that is saved when encoding novel facial images, with a given precision. We show that despite decoupled coding describes the facial images in terms of two sets of principal components (of landmark shape and image texture), it is more efficient (i.e., yields more information compression) than the encoding in terms of the image principal components only, which corresponds to the widely used eigenface method. The advantage of decoupled coding over eigenface coding increases with image resolution and is especially prominent when coding variants of training set images that only differ in facial expressions. Moreover, we demonstrate that decoupled coding entails better performance in three different tasks: the representation of facial images, the (daydream) sampling of novel facial images, and the recognition of facial identities and gender. In summary, our study provides a first principle perspective on the efficiency and accuracy of the decoupled coding of facial stimuli reported in the primate inferotemporal cortex. [ABSTRACT FROM AUTHOR]

A close relationship between emotional contagion and spontaneous facial mimicry has been theoretically proposed and is supported by empirical data. Facial expressions are essential in terms of both emotional and motor synchrony. Previous studies have demonstrated that trait emotional empathy enhanced spontaneous facial mimicry, but the relationship between autistic traits and spontaneous mimicry remained controversial. Moreover, previous studies presented faces that were static or videotaped, which may lack the "liveliness" of real-life social interactions. We addressed this limitation by using an image relay system to present live performances and pre-recorded videos of smiling or frowning dynamic facial expressions to 94 healthy female participants. We assessed their subjective experiential valence and arousal ratings to infer the amplitude of emotional contagion. We measured the electromyographic activities of the zygomaticus major and corrugator supercilii muscles to estimate spontaneous facial mimicry. Individual differences measures included trait emotional empathy (empathic concern) and the autism-spectrum quotient. We did not find that live performances enhanced the modulatory effect of trait differences on emotional contagion or spontaneous facial mimicry. However, we found that a high trait empathic concern was associated with stronger emotional contagion and corrugator mimicry. We found no two-way interaction between the autism spectrum quotient and emotional condition, suggesting that autistic traits did not modulate emotional contagion or spontaneous facial mimicry. Our findings imply that previous findings regarding the relationship between emotional empathy and emotional contagion/spontaneous facial mimicry using videos and photos could be generalized to real-life interactions. [ABSTRACT FROM AUTHOR]

Facial mimicry is the automatic imitation of the facial affect expressions of others. It serves as an important component of interpersonal communication and affective co-experience. Facial mimicry has so far been measured by Electromyography (EMG), which requires a complex measuring apparatus. Recently, software for measuring facial expressions have become available, but it is still unclear how well it is suited for measuring facial mimicry. This study investigates the comparability of the automated facial coding software Affdex with EMG for measuring facial mimicry. For this purpose, facial mimicry was induced in 33 subjects by presenting naturalistic affect-expressive video sequences (anger, joy). The response of the subjects is measured simultaneously by facial EMG (corrugator supercilii muscle, zygomaticus major muscle) and by Affdex (action units lip corner puller and brow lowerer and affects joy and anger). Subsequently, the correlations between the measurement results of EMG and Affdex were calculated. After the presentation of the joy stimulus, there was an increase in zygomaticus muscle activity (EMG) about 400 ms after stimulus onset and an increase in joy and lip corner puller activity (Affdex) about 1200 ms after stimulus onset. The joy and the lip corner puller activity detected by Affdex correlate significantly with the EMG activity. After presentation of the anger stimulus, corrugator muscle activity (EMG) also increased approximately 400 ms after stimulus onset, whereas anger and brow lowerer activity (Affdex) showed no response. During the entire measurement interval, anger activity and brow lowerer activity (Affdex) did not correlate with corrugator muscle activity (EMG). Using Affdex, the facial mimicry response to a joy stimulus can be measured, but it is detected approximately 800 ms later compared to the EMG. Thus, electromyography remains the tool of choice for studying subtle mimic processes like facial mimicry. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine how the depressor supercilii (DS) connects to the levator labii superioris alaeque nasi (LLSAN) and inferior fibers of the orbicularis oculi (OOc INF) in the human midface. While grimacing, contraction of the DS with fibers connecting to the LLSAN and OOc INF can assist in pulling the medial eyebrow downward more than when these connecting fibers are not present. Contraction of these distinct connecting fibers between the DS and the LLSAN can also slightly elevate the nasal ala and upper lip. The DS was examined in 44 specimens of embalmed adult Korean cadavers. We found that the DS connected to the LLSAN or the OOc INF by muscle fibers or thin aponeuroses in 33 (75.0%) of the 44 specimens. The DS was connected to both the LLSAN and OOc INF by muscle fibers or aponeuroses and had no connection to either in 5 (11.4%) and 11 (25.0%) specimens, respectively. The DS was connected to the LLSAN by the muscle fibers and thin aponeuroses in 6 (13.6%) and 4 (9.1%) specimens, respectively. The DS was connected to the OOc INF by the muscle fibers and thin aponeuroses in 5 (11.4%) and 23 (52.3%) specimens, respectively. Our findings regarding the anatomical connections of the glabellar region DS to the midface LLSAN and OOc INF provide insights on the dynamic balance between the brow depressors such as the DS and brow-elevating muscle and contribute to understanding the anatomical origins of individual variation in facial expressions. These results can also improve the safety, predictability, and aesthetics of treatments for the glabellar region with botulinum toxin type A and can be helpful when performing electromyography.

This document is a correction notice for an article titled "Creative problem solving and facial expressions: A stage based comparison" published in the journal PLoS ONE. The correction states that the images for Figures 6 and 7 in the article were incorrectly switched and provides the correct versions of the figures and their captions. Additionally, there is a misspelling in the second sentence of the second paragraph of the Facial expression analysis subdivision of Data analysis. The correct sentence compares the performance of automatic facial expression recognition tools, stating that OpenFace has been shown to be superior to high-paid commercial software such as Noldus FaceReader and Affectiva in detecting automatic facials. The authors of the article are Mritunjay Kumar, Satyaki Roy, Braj Bhushan, and Ahmed Sameer. [Extracted from the article]

Evidence is discordant regarding how emotional processing and cognitive control interact to shape behavior. This observational study sought to examine this interaction by looking at the distinction between proactive and reactive modes of control and how they relate to emotional processing. Seventy-four healthy participants performed an emotional priming Stroop task. On each trial, target stimuli of a spatial Stroop task were preceded by sad or neutral facial expressions, providing two emotional conditions. To manipulate the requirement of both proactive and reactive control, the proportion of congruent trials (PC) was varied at the list-wide (LWPC) and item-specific (ISPC) levels, respectively. We found that sad priming led to behavioral costs only in trials with low proactive and reactive cognitive control demands. Our findings suggest that emotional processing affects cognitive processes other than cognitive control in the Stroop task. Moreover, both proactive and reactive control modes seem effective in overcoming emotional interference of priming stimuli. [ABSTRACT FROM AUTHOR]

Disentanglement research is a critical and important issue in the field of image editing. In order to perform disentangled editing on images generated by generative models, this paper presents an unsupervised, model-agnostic, two-stage trained editing framework. This work addresses the problem of discovering interpretable, disentangled directions of edited image attributes in the latent space of generative models. This effort's primary objective was to address the limitations discovered in previous research, mainly (a) the discovered editing directions are interpretable but significantly entangled, i.e., changes to one attribute affect the others and (b) Prior research has utilized direction discovery and direction disentanglement separately, and they can't work synergistically. More specifically, this paper proposes a two-stage training method that discovers the editing direction with semantics, perturbs the dimension of the direction vector, adjusts it with a penalty mechanism, and makes the editing direction more disentangled. This allows easy distinguishable image editing, such as age and facial expressions in facial images. Experimentally compared to other methods, the proposed method outperforms them both qualitatively and quantitatively in terms of interpretability, disentanglement, and distinguishability of the generated images. The implementation of our method is available at https://github.com/ydniuyongjie/twoStageForFaceEdit. [ABSTRACT FROM AUTHOR]

Preterm human infants often show periodic breathing (PB) or apnea of prematurity (AOP), breathing patterns which are accompanied by intermittent hypoxia (IH). We examined cause-effect relationships between transient IH and reduced facial bone growth using a rat model. Neonatal pups from 14 timed pregnant Sprague-Dawley rats were randomly assigned to an IH condition, with oxygen altering between 10% and 21% every 4 min for 1 h immediately after birth, or to a litter-matched control group. The IH pups were compared with their age- and sex-matched control groups in body weight (WT), size of facial bones and nor-epinephrine (NE) levels in blood at 3, 4, and 5-weeks. Markedly increased activity of osteoclasts in sub-condylar regions of 3-week-old IH-treated animals appeared, as well as increased numbers of sympathetic nerve endings in the same region of tissue sections. Male IH-pups showed significantly higher levels of NE levels in sera at 3, 4 as well as 5-week-old time points. NE levels in 4- and-5-week-old female pups did not differ significantly. Intercondylar Width, Mandible Length and Intermolar Width measures consistently declined after IH insults in 3- and 4-week-old male as well as female animals. Three-week-old male IH-pups only showed a significantly reduced (p < 0.05) body weight compared to those of 3-week controls. However, female IH-pups were heavier than age-matched controls at all 3 time-points. Trabecular bone configuration, size of facial bones, and metabolism are disturbed after an IH challenge 1 h immediately after birth. The findings raise the possibility that IH, introduced by breathing patterns such as PB or AOP, induce significantly impaired bone development and metabolic changes in human newborns. The enhanced NE outflow from IH exposure may serve a major role in deficient bone growth, and may affect bone and other tissue influenced by that elevation. [ABSTRACT FROM AUTHOR]

The present study investigated (1) how well humans can recognize facial expressions represented by a small set of landmarks, a commonly used technique in facial recognition in machine learning and (2) differences in conscious observational behaviors to recognized different types of expressions. Our video stimuli consisted of facial expression represented by 68 landmark points. Conscious observational behaviors were measured by movements of the mouse cursor where a small area around it was only visible to participants. We constructed Bayesian models to analyze how personality traits and observational behaviors influenced how participants recognized different facial expressions. We found that humans could recognize positive expressions with high accuracy, similar to machine learning, even when faces were represented by a small set of landmarks. Although humans fared better than machine learning, recognition of negative expressions was not as high as positives. Our results also showed that personality traits and conscious observational behaviors significantly influenced recognizing facial expressions. For example, people with high agreeableness could correctly recognize faces expressing happiness by observing several areas among faces without focusing on any specific part for very long. These results suggest a mechanism whereby personality traits lead to different conscious observational behaviors and recognitions of facial expressions are based on information obtained through those observational behaviors. [ABSTRACT FROM AUTHOR]

It is well-known that lighting conditions have an important influence on the automatic recognition of human expressions. Although the impact of lighting on the perception of emotions has been studied in different works, databases of facial expressions do not consider intentional lighting. In this work, a new database of facial expressions performed by virtual characters with four different lighting configurations is presented. This database, named UIBVFEDPlus-Light, is an extension of the previously published UIBVFED virtual facial expression dataset. It includes 100 characters, four lighting configurations and a software application that allows one to interactively visualize the expressions, and manage their intensity and lighting condition. Also, an experience of use is described to show how this work can raise new challenges to facial expression and emotion recognition techniques under usual lighting environments. Thus, opening new study perspectives in this area. [ABSTRACT FROM AUTHOR]

Trait inferences from first impressions are drawn rapidly and spontaneously. However, the Covid-19 pandemic forced interactions online introducing differential influential factors on first impressions. As such, there is an absence of research investigating video background on videoconferencing impression formation. This study explored the influence of video background, facial expression, and gender on first impressions of trustworthiness and competence. Video background affected trustworthy and competence perceptions with Plants and Book backgrounds scoring highly on both dimensions while the Home and Novelty backgrounds consistently received the lowest ratings. Happy faces were perceived as more trustworthy and more competent while female faces were also rated as more trustworthy and more competent, regardless of the background they were using. The explanations for these findings are discussed, along with future directions for research and the implications for videoconferencing use. [ABSTRACT FROM AUTHOR]

Recent deep-learning techniques have made it possible to manipulate facial expressions in digital photographs or videos, however, these techniques still lack fine and personalized ways to control their creation. Moreover, current technologies are highly dependent on large labeled databases, which limits the range and complexity of expressions that can be modeled. Thus, these technologies cannot deal with non-basic emotions. In this paper, we propose a novel interdisciplinary approach combining the Generative Adversarial Network (GAN) with a technique inspired by cognitive sciences, psychophysical reverse correlation. Reverse correlation is a data-driven method able to extract an observer's 'mental representation' of what a given facial expression should look like. Our approach can generate 1) personalized facial expression prototypes, 2) of basic emotions, and non-basic emotions that are not available in existing databases, and 3) without the need for expertise. Personalized prototypes obtained with reverse correlation can then be applied to manipulate facial expressions. In addition, our system challenges the universality of facial expression prototypes by proposing the concepts of dominant and complementary action units to describe facial expression prototypes. The evaluations we conducted on a limited number of emotions validate the effectiveness of our proposed method. The code is available at https://github.com/yansen0508/Mental-Deep-Reverse-Engineering. [ABSTRACT FROM AUTHOR]

Communication within online platforms supported by chatbots requires algorithms, language processing methods, and an effective visual representation. These are crucial elements for increasing user engagement and making communication more akin to natural conversation. Chatbots compete with other graphic elements within websites or applications, and thus attracting a user's attention is a challenge even before the actual conversation begins. A chatbot may remain unnoticed even with sophisticated techniques at play. Drawing attention to the chatbot area localized within the periphery area can be carried out with the use of various visual characteristics. The presented study analyzed the impact of changes in a chatbot's emotional expressions on user reaction. The aim of this study was to observe, based on user reaction times, whether changes in a chatbot's emotional expressions make it more noticeable. The results showed that users are more sensitive to positive emotions within chatbots, as positive facial expressions were noticed more quickly than negative ones. [ABSTRACT FROM AUTHOR]

Emotional facial expressions are an important part of across species social communication, yet the factors affecting human recognition of dog emotions have received limited attention. Here, we characterize the recognition and evaluation of dog and human emotional facial expressions by 4-and 6-year-old children and adult participants, as well as the effect of dog experience in emotion recognition. Participants rated the happiness, anger, valence, and arousal from happy, aggressive, and neutral facial images of dogs and humans. Both respondent age and experience influenced the dog emotion recognition and ratings. Aggressive dog faces were rated more often correctly by adults than 4-year-olds regardless of dog experience, whereas the 6-year-olds' and adults' performances did not differ. Happy human and dog expressions were recognized equally by all groups. Children rated aggressive dogs as more positive and lower in arousal than adults, and participants without dog experience rated aggressive dogs as more positive than those with dog experience. Children also rated aggressive dogs as more positive and lower in arousal than aggressive humans. The results confirm that recognition of dog emotions, especially aggression, increases with age, which can be related to general dog experience and brain structure maturation involved in facial emotion recognition. [ABSTRACT FROM AUTHOR]

Facial expressions are widely recognized as universal indicators of underlying internal states in most species of animals, thereby presenting as a non-invasive measure for assessing physical and mental conditions. Despite the advancement of artificial intelligence-assisted tools for automated analysis of voluminous facial expression data in human subjects, the corresponding tools for mice still remain limited so far. Considering that mice are the most prevalent model animals for studying human health and diseases, a comprehensive characterization of emotion-dependent patterns of facial expressions in mice could extend our knowledge on the basis of emotions and the related disorders. Here, we present a framework for the development of a deep learning-powered tool for classifying facial expressions in head-fixed mouse. We demonstrate that our machine vision was capable of accurately classifying three different emotional states from lateral facial images in head-fixed mouse. Moreover, we objectively determined how our classifier characterized the differences among the facial images through the use of an interpretation technique called Gradient-weighted Class Activation Mapping. Importantly, our machine vision presumably discerned the data by leveraging multiple facial features. Our approach is likely to facilitate the non-invasive decoding of a variety of emotions from facial images in head-fixed mice. [ABSTRACT FROM AUTHOR]

Emotion research commonly uses either controlled and standardised pictures or natural video stimuli to measure participants' reactions to emotional content. Natural stimulus materials can be beneficial; however, certain measures such as neuroscientific methods, require temporally and visually controlled stimulus material. The current study aimed to create and validate video stimuli in which a model displays positive, neutral and negative expressions. These stimuli were kept as natural as possible while editing timing and visual features to make them suitable for neuroscientific research (e.g. EEG). The stimuli were successfully controlled regarding their features and the validation studies show that participants reliably classify the displayed expression correctly and perceive it as genuine. In conclusion, we present a motion stimulus set that is perceived as natural and that is suitable for neuroscientific research, as well as a pipeline describing successful editing methods for controlling natural stimuli. [ABSTRACT FROM AUTHOR]

Ostracism has been shown to induce considerable physiological, behavioral and cognitive changes in adults. Previous research demonstrated its effects on children's cognitive and behavioral abilities, but less is known about its impact on their capacity to recognize subtle variations in social cues. The present study aimed at investigating whether social manipulations of inclusion and ostracism modulate emotion recognition abilities in children, and whether this modulation varies across childhood. To do so, 5- and 10-year-old children participated in a computer-based ball tossing game called Cyberball during which they were either included or ostracized. Then, they completed a facial emotion recognition task in which they were required to identify neutral facial expressions, or varying levels of intensity of angry and fearful facial expressions. Results indicated lower misidentification rates for children who were previously ostracized as compared to children who were previously included, both at 5 and 10 years of age. Moreover, when looking at children's accuracy and sensitivity to facial expressions, 5-year-olds' decoding abilities were affected by the social manipulation, while no difference between included and ostracized participants was observed for 10-year-olds. In particular, included and ostracized 10-year-old children as well as ostracized 5-year-olds showed higher accuracy and sensitivity for expressions of fear as compared to anger, while no such difference was observed for included 5-year-olds. Overall, the current study presents evidence that Cyberball-induced inclusion and ostracism modulate children's recognition of emotional faces. [ABSTRACT FROM AUTHOR]

Food rewards are believed to have a positive valence in horses. The aim of this study was to assess the effect of food rewards on horse behavior before entering a horse chute, and behavior and facial movements while restrained in it. Thirteen female adult horses were brought once daily to an animal handling facility for three weeks. In week 1, baseline period, no reinforcement was applied. In weeks 2 and 3, experimental phase, half of the horses received positive reinforcement treatment after entering and remaining in the chute; the remaining horses were considered as controls (no positive reinforcement applied). There was a cross-over between the groups during the experimental phase. Horses were individually brought to the restraining chute and videos recorded during 60-sec. The duration and number of entries into the area close to the gate leading to the chute were measured before restraining and body posture, neck position, and tail swinging were recorded in the chute. Facial movements were also recorded and scored using EquiFACS methodology. Multilevel linear and logistic models were built to assess behavioral changes from baseline to the treatment phase and between phases (control and positively reinforced). Horses did not change their body posture or tail swings across the different phases (P > 0.1) and were less likely to show lowered neck during the positively reinforced phase (OR: 0.05; CI95%: 0.00–0.56; P = 0.05) compared to baseline. The likelihood of a lowered neck did not differ between the positive reinforcement and control phases (P = 0.11). In the positively reinforced phase, horses seemed to be more attentive (ears forward) and active (less eye closures, more nose movements) than in the control phase. A three-day positive reinforcement phase did not elicit major changes in body behavior in the chute but affected the facial movements of group-housed mares. [ABSTRACT FROM AUTHOR]

The automatic detection of facial expressions of pain is needed to ensure accurate pain assessment of patients who are unable to self-report pain. To overcome the challenges of automatic systems for determining pain levels based on facial expressions in clinical patient monitoring, a surface electromyography method was tested for feasibility in healthy volunteers. In the current study, two types of experimental gradually increasing pain stimuli were induced in thirty-one healthy volunteers who attended the study. We used a surface electromyography method to measure the activity of five facial muscles to detect facial expressions during pain induction. Statistical tests were used to analyze the continuous electromyography data, and a supervised machine learning was applied for pain intensity prediction model. Muscle activation of corrugator supercilii was most strongly associated with self-reported pain, and the levator labii superioris and orbicularis oculi showed a statistically significant increase in muscle activation when the pain stimulus reached subjects' self -reported pain thresholds. The two strongest features associated with pain, the waveform length of the corrugator supercilii and levator labii superioris, were selected for a prediction model. The performance of the pain prediction model resulted in a c-index of 0.64. In the study results, the most detectable difference in muscle activity during the pain experience was connected to eyebrow lowering, nose wrinkling and upper lip raising. As the performance of the prediction model remains modest, yet with a statistically significant ordinal classification, we suggest testing with a larger sample size to further explore the variables that affect variation in expressiveness and subjective pain experience.

This study examined whether self-reports or ratings of experienced affect, often used as manipulation checks on the efficacy of affect induction procedures (AIPs), reflect genuine changes in affective states rather than response biases arising from demand characteristics or social desirability effects. In a between-participants design, participants were exposed to positive, negative and neutral images with valence-congruent music or sound to induce happy, sad and neutral mood. Half of the participants had to actively appraise each image whereas the other half viewed images passively. We hypothesised that if ratings of affective valence are subject to response biases then they should reflect the target mood in the same way for active appraisal and passive exposure as participants encountered the same affective stimuli in both conditions. We also tested whether the AIP resulted in mood-congruent changes in facial expressions analysed by FaceReader to see whether behavioural indicators corroborate the self-reports. The results showed that while participants' ratings reflected the induced target valence, the difference between positive and negative AIP was significantly attenuated in the active appraisal condition, suggesting that self-reports of mood experienced after the AIP are not entirely a reflection of response biases. However, there were no effects of the AIP on FaceReader valence scores, in line with theories questioning the existence of cross-culturally and inter-individually universal behavioural indicators of affective states. Efficacy of AIPs is therefore best checked using self-reports. [ABSTRACT FROM AUTHOR]

Orbital and nasal parameters among modern humans show considerable variation, which affects facial shape, and these characteristics vary according to race, region, and period in evolution. The aim of the study was to ascertain whether there are sex differences in the orbital and/or nasal indexes and/or the single measurements used to calculate these in a Kosovar population. The following parameters were taken into consideration: orbital height (OH), orbital width (OW), nasal height (NH), and nasal width (NW). The ratios between orbital index/nasal index (RONI) were calculated. All measurements were obtained from a population sample comprising 408 individuals. The accuracy in sex prediction was 52.86% (CI95% = 45.05%–60.67%) for NW and 64.96% for NH (CI95% = 57.50%– 72.42%). The difference between male and female indexes was statistically significant (P < 0.05). The anthropometric study revealed that only NW and NH are configured as predictors of sexual dimorphism. It could be useful to increase the number of samples to test the discriminant function in other population groups. [ABSTRACT FROM AUTHOR]

Throughout pregnancy, fetuses are exposed to a range of chemosensory inputs influencing their postnatal behaviors. Such prenatal exposure provides the fetus with continuous sensory information to adapt to the environment they face once born. This study aimed to assess the chemosensory continuity through a systematic review and meta-analysis of existing evidence on chemosensory continuity from prenatal to first postnatal year. Web of Science Core. Collections, MEDLINE, PsycINFO, EBSCOhost ebook collection was searched from 1900 to 2021. Studies identified from the search were grouped according to type of stimuli the fetuses were exposed to prenatally that the neonatal infants' responses to were being evaluated, namely flavors transferred from the maternal diet, and the odor of their own amniotic fluid. Of the 12 studies that met the eligibility criteria for inclusion (k = 6, k = 6, respectively in the first and the second group of studies), and eight studies (k = 4, k = 4, respectively) provided sufficient data suitable for meta-analysis. Infants, during their first year of life, oriented their heads for significantly longer durations in the direction of the prenatally experienced stimuli with large pooled effect sizes (flavor stimuli, d = 1.24, 95% CI [0.56, 1.91]; amniotic fluid odor, d = 0.853; 95% CI [.632, 1.073]). The pooled effect size for the duration of mouthing behavior was significant in response to prenatal flavor exposure through maternal diet (d = 0.72; 95% CI [0.306, 1.136]), but not for the frequency of negative facial expressions (d = -0.87, 95% CI [-2.39, 0.66]). Postnatal evidence suggests that there is a chemosensory continuity from fetal to the first year of postnatal life. [ABSTRACT FROM AUTHOR]

In social contexts, the dynamic nature of others' emotions places unique demands on attention and emotion regulation. Mindfulness, characterized by heightened and receptive moment-to-moment attending, may be well-suited to meet these demands. In particular, mindfulness may support more effective cognitive control in social situations via efficient deployment of top-down attention. To test this, a randomized controlled study examined effects of mindfulness training (MT) on behavioral and neural (event-related potentials [ERPs]) responses during an emotional go/no-go task that tested cognitive control in the context of emotional facial expressions that tend to elicit approach or avoidance behavior. Participants (N = 66) were randomly assigned to four brief (20 min) MT sessions or to structurally equivalent book learning control sessions. Relative to the control group, MT led to improved discrimination of facial expressions, as indexed by d-prime, as well as more efficient cognitive control, as indexed by response time and accuracy, and particularly for those evidencing poorer discrimination and cognitive control at baseline. MT also produced better conflict monitoring of behavioral goal-prepotent response tendencies, as indexed by larger No-Go N200 ERP amplitudes, and particularly so for those with smaller No-Go amplitude at baseline. Overall, findings are consistent with MT's potential to enhance deployment of early top-down attention to better meet the unique cognitive and emotional demands of socioemotional contexts, particularly for those with greater opportunity for change. Findings also suggest that early top-down attention deployment could be a cognitive mechanism correspondent to the present-oriented attention commonly used to explain regulatory benefits of mindfulness more broadly.

Using a public goods laboratory experiment, this paper analyzes the extent to which face-to-face communication keeps its efficiency gains even after its removal. This is important as communication in real world is costly (e.g. time). If the effect of communication is long-lasting, the number of communication periods could be minimized. This paper provides evidence that there is a lasting positive effect on contributions even after communication was removed. Yet, after the removal, the contributions are lower and abate over time to the previous magnitude. This is referred to as the reverberation effect of communication. As we do not observe an effect of endogenizing communication, the strongest driver of the size of the contributions is the existence of communication or its reverberation. Eventually, the experiment provides evidence for a strong end-game effect after communication was removed, insinuating communication does not protect from the end-game behavior. In total, the results of the paper imply, that the effects of communication are not permanent but communication should be repeated. Simultaneously, results indicate no need for permanent communication. Since communication is conducted using video-conference tools, we present results from a machine learning based analysis of facial expressions to predict contribution behavior on group level. [ABSTRACT FROM AUTHOR]

Human facial attractiveness is related to physical features, such as clear complexion and symmetry. However, it is also known that facial attractiveness judgments are influenced by a wide range of non-physical factors. Here, we examined the effect of the personality information of a target person on facial attractiveness judgments. In Experiment 1, participants read a verbal description of a target person (high or low honesty), followed by the presentation of the target face and facial attractiveness rating. The honest personality increased the rated facial attractiveness, replicating a previous report. This "honesty premium" effect was independent of pre-rated facial attractiveness (Experiment 1), target gender, participant gender, and target clothing (Experiment 2). Experiment 3 found that creative personality did not affect facial attractiveness ratings, while an aggressive personality was suggested to decrease the rated facial attractiveness of male targets. We did not find evidence that participants' moods caused these effects. The results suggest that the "what is good is beautiful" stereotype is robust and that facial attractiveness is malleable and dependent on various physical and non-physical information. [ABSTRACT FROM AUTHOR]

Automatic facial coding (AFC) is a promising new research tool to efficiently analyze emotional facial expressions. AFC is based on machine learning procedures to infer emotion categorization from facial movements (i.e., Action Units). State-of-the-art AFC accurately classifies intense and prototypical facial expressions, whereas it is less accurate for non-prototypical and less intense facial expressions. A potential reason might be that AFC is typically trained with standardized and prototypical facial expression inventories. Because AFC would be useful to analyze less prototypical research material as well, we set out to determine the role of prototypicality in the training material. We trained established machine learning algorithms either with standardized expressions from widely used research inventories or with unstandardized emotional facial expressions obtained in a typical laboratory setting and tested them on identical or cross-over material. All machine learning models' accuracies were comparable when trained and tested with held-out dataset from the same dataset (acc. = [83.4% to 92.5%]). Strikingly, we found a substantial drop in accuracies for models trained with the highly prototypical standardized dataset when tested in the unstandardized dataset (acc. = [52.8%; 69.8%]). However, when they were trained with unstandardized expressions and tested with standardized datasets, accuracies held up (acc. = [82.7%; 92.5%]). These findings demonstrate a strong impact of the training material's prototypicality on AFC's ability to classify emotional faces. Because AFC would be useful for analyzing emotional facial expressions in research or even naturalistic scenarios, future developments should include more naturalistic facial expressions for training. This approach will improve the generalizability of AFC to encode more naturalistic facial expressions and increase robustness for future applications of this promising technology. [ABSTRACT FROM AUTHOR]

Background and objective: Patients suffering from Parkinson's disease (PD) present a reduction in facial movements called hypomimia. In this work, we propose to use machine learning facial expression analysis from face images based on action unit domains to improve PD detection. We propose different domain adaptation techniques to exploit the latest advances in automatic face analysis and face action unit detection. Methods: Three different approaches are explored to model facial expressions of PD patients: (i) face analysis using single frame images and also using sequences of images, (ii) transfer learning from face analysis to action units recognition, and (iii) triplet-loss functions to improve the automatic classification between patients and healthy subjects. Results: Real face images from PD patients show that it is possible to properly model elicited facial expressions using image sequences (neutral, onset-transition, apex, offset-transition, and neutral) with accuracy improvements of up to 5.5% (from 72.9% to 78.4%) with respect to single-image PD detection. We also show that our proposed action unit domain adaptation provides improvements of up to 8.9% (from 78.4% to 87.3%) with respect to face analysis. Finally, we also show that triplet-loss functions provide improvements of up to 3.6% (from 78.8% to 82.4%) with respect to action unit domain adaptation applied upon models created from scratch. The code of the experiments is available at https://github.com/luisf-gomez/Explorer-FE-AU-in-PD. Conclusions: Domain adaptation via transfer learning methods seem to be a promising strategy to model hypomimia in PD patients. Considering the good results and also the fact that only up to five images per participant are considered in each sequence, we believe that this work is a step forward in the development of inexpensive computational systems suitable to model and quantify problems of PD patients in their facial expressions. [ABSTRACT FROM AUTHOR]

Evidence suggests that incidental modulation of affective states affects the ability to keep track of time. Alexithymia represents an ideal condition to further address the emotion-time processing link, as it refers to a trait characterized by a deficit of affective processing. 31 healthy participants completed an online version of the TAS-20 scale, which measures alexithymia, and a time reproduction task of visual stimuli related to positive (i.e., happiness) and negative (i.e., anger) facial expressions. Results documented a positive correlation between TAS-20 score and the variability in reproducing sub-second durations of the anger expression stimuli We also found an overestimation of sub-second durations of non-affective expressions in borderline/alexithymic participants. Finally, in line with the literature, we confirmed the overall tendency to overestimate the duration of anger expression stimuli. These findings, which can be interpreted in terms of abnormal scalar timing property in alexithymia, expand previous investigations linking this personality trait with abnormal processing of negative emotions. The evidence that alexithymia predicts the reproduction variability of sub-second durations of negative affective stimuli corroborates previous neuroimaging studies documenting cerebellar deficits in these individuals. [ABSTRACT FROM AUTHOR]

Emotion reasoning, including labeling of facial expressions, is an important building block for a child's social development. This study investigated age biases in labeling facial expressions in children and adults, focusing on the influence of intensity and expression on age bias. Children (5 to 14 years old; N = 152) and adults (19 to 25 years old; N = 30) labeled happiness, disgust or sadness at five intensity levels (0%; 25%; 50%; 75%; and 100%) in facial images of children and adults. Sensitivity was computed for each of the expression-intensity combinations, separately for the child and adult faces. Results show that children and adults have an age bias at low levels of intensity (25%). In the case of sadness, children have an age bias for all intensities. Thus, the impact of the age of the face seems largest for expressions which might be most difficult to recognise. Moreover, both adults and children label most expressions best in adult rather than child faces, leading to an other-age bias in children and an own-age bias in adults. Overall, these findings reveal that both children and adults exhibit an age bias in labeling subtle facial expressions of emotions. [ABSTRACT FROM AUTHOR]

The current research explored toddlers' gaze fixation during a scene showing a person expressing sadness after a ball is stolen from her. The relation between the duration of gaze fixation on different parts of the person's sad face (e.g., eyes, mouth) and theory of mind skills was examined. Eye tracking data indicated that before the actor experienced the negative event, toddlers divided their fixation equally between the actor's happy face and other distracting objects, but looked longer at the face after the ball was stolen and she expressed sadness. The strongest predictor of increased focus on the sad face versus other elements of the scene was toddlers' ability to predict others' emotional reactions when outcomes fulfilled (happiness) or failed to fulfill (sadness) desires, whereas toddlers' visual perspective-taking skills predicted their more specific focusing on the actor's eyes and, for boys only, mouth. Furthermore, gender differences emerged in toddlers' fixation on parts of the scene. Taken together, these findings suggest that top-down processes are involved in the scanning of emotional facial expressions in toddlers.

Background: Facial injuries affect one-third of severely injured patients. These injuries have devastating long-term negative impacts on quality of life. We aimed to study the epidemiology of facial injuries and factors affecting the mortality of hospitalized facial trauma patients in Al-Ain City, United Arab Emirates. Methodology: This is a retrospective analysis of prospectively collected data from Al-Ain Hospital Trauma Registry. All patients with facial injury who were hospitalized for more than 24 hours or who died after arrival at the hospital during the period from January 2014 to December 2017 were studied. Two sample data analysis was used to compare patients who died and those who survived. Significant factors were then entered into a backward logistic regression model to define factors affecting mortality. Results: 408 patients having a mean age of 31.9 years were studied, 87.3% were males. The main mechanisms of injury were road traffic collisions (52.2%) and fall from height (11.3%). 289 (70.8%) patients had associated injuries which were mainly in the head and chest. The backward logistic regression model showed that the Glasgow Coma Scale (GCS) was the only factor that predicted mortality, p<0.0001 with the best cut-off point of 7.5, having a sensitivity of 0.972 and a specificity of 0.8. The ROC had an area under the curve of 0.924. Conclusion: The majority of facial injury patients in our setting are young males who were involved in road traffic collisions or falls from height. The most important factor predicting the mortality of these patients was the low GCS. Those having a GCS of 8 and more had a better chance of survival. This information is very important when counseling patients or their relatives for facial surgery. [ABSTRACT FROM AUTHOR]

Cultural context shapes the way that emotions are expressed and socially interpreted. Building on previous research looking at cultural differences in judgements of facial expressions, we examined how listeners recognize speech-embedded emotional expressions and make inferences about a speaker's feelings in relation to their vocal display. Canadian and Chinese participants categorized vocal expressions of emotions (anger, fear, happiness, sadness) expressed at different intensity levels in three languages (English, Mandarin, Hindi). In two additional tasks, participants rated the intensity of each emotional expression and the intensity of the speaker's feelings from the same stimuli. Each group was more accurate at recognizing emotions produced in their native language (in-group advantage). However, Canadian and Chinese participants both judged the speaker's feelings to be equivalent or more intense than their actual display (especially for highly aroused, negative emotions), suggesting that similar inference rules were applied to vocal expressions by the two cultures in this task. Our results provide new insights on how people categorize and interpret speech-embedded vocal expressions versus facial expressions and what cultural factors are at play. [ABSTRACT FROM AUTHOR]

Facial expression recognition (FER) is significantly influenced by the cultural background (CB) of observers and the masking conditions of the target face. This study aimed to clarify these factors' impact on FER, particularly in machine-learning datasets, increasingly used in human-computer interaction and automated systems. We conducted an FER experiment with East Asian participants and compared the results with the FERPlus dataset, evaluated by Western raters. Our novel analysis approach focused on variability between images and participants within a "majority" category and the eye-opening rate of target faces, providing a deeper understanding of FER processes. Notable findings were differences in "fear" perception between East Asians and Westerners, with East Asians more likely to interpret "fear" as "surprise." Masking conditions significantly affected emotion categorization, with "fear" perceived by East Asians for non-masked faces interpreted as "surprise" for masked faces. Then, the emotion labels were perceived as different emotions across categories in the masking condition, rather than simply lower recognition rates or confusion as in existing studies. Additionally, "sadness" perceived by Westerners was often interpreted as "disgust" by East Asians. These results suggest that one-to-one network learning models, commonly trained using majority labels, might overlook important minority response information, potentially leading to biases in automated FER systems. In conclusion, FER dataset characteristics differ depending on the target face's masking condition and the diversity among evaluation groups. This study highlights the need to consider these factors in machine-learning-based FER that relies on human-judged labels, to contribute to the development of more nuanced and fair automated FER systems. Our findings emphasize the novelty of our approach compared to existing studies and the importance of incorporating a broader range of human variability in FER research, setting the stage for future evaluations of machine learning classifiers on similar data., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Nagata, Okajima. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: This study aimed to explore the influence of emotional feedback materials on attentional capture at different presentation times and to investigate the mechanisms of positive and negative attentional biases., Methods: Two experiments were conducted. Experiment 1 recruited 47 participants, and Experiment 2 recruited 46 participants. Emotional facial images and emotional words were used as feedback materials. A learning-testing paradigm was employed to explore the effect of emotional feedback materials on attentional capture at different presentation times (1000 ms/100 ms)., Results: We compared the accuracy and reaction times of participants under emotional and neutral conditions at both presentation times. Experiment 1 revealed that participants exhibited a stable positive attentional bias towards emotional facial images. Additionally, under the 100 ms feedback condition, emotional interference on judgment task accuracy was greater than under the 1000 ms feedback condition. Experiment 2 found that under the 100 ms feedback condition, emotional interference on reaction time was greater than under the 1000 ms feedback condition. Comparing the data from both experiments revealed that the processing time for emotional facial images was longer than for emotional words., Conclusions: (1) Emotional facial images are more effective than emotional words in capturing attention. (2) When positive and negative information with equal arousal levels alternates over a period of time, individuals exhibit a stable positive attentional bias. (3) When there is intense competition for attention and cognitive resources, emotional information is prioritized for processing., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Gao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Signed languages such as American Sign Language (ASL) rely on visuospatial information that combines hand and bodily movements, facial expressions, and fingerspelling. Signers communicate in a wide array of sub-optimal environments, such as in dim lighting or from a distance. While fingerspelling is a common and essential part of signed languages, the perception of fingerspelling in difficult visual environments is not well understood. The movement and spatial patterns of ASL are well-suited to representation by dynamic Point Light Display (PLD) stimuli in which human movement is shown as an array of moving dots affixed to joints on the body. We created PLD videos of fingerspelled location names. The location names were either Real (e.g., KUWAIT) or Pseudo-names (e.g., CLARTAND), and the PLDs showed either a High or a Low number of markers. In an online study, Deaf and Hearing ASL users (total N = 283) watched 27 PLD stimulus videos that varied by Word Type and Number of Markers. Participants watched the videos and typed the names they saw, along with how confident they were in their response. We predicted that when signers see ASL fingerspelling PLDs, language experience in ASL will be positively correlated with accuracy and self-rated confidence scores. We also predicted that Real location names would be understood better than Pseudo names. Our findings supported those predictions. We also discovered a significant interaction between Age and Word Type, which suggests that as people age, they use outside world knowledge to inform their fingerspelling success. Finally, we examined the accuracy and confidence in fingerspelling perception in early ASL users. Studying the relationship between language experience with PLD fingerspelling perception allows us to explore how hearing status, ASL fluency levels, and age of language acquisition affect the core abilities of understanding fingerspelling. [ABSTRACT FROM AUTHOR]

Reading the genuineness of facial expressions is important for increasing the credibility of information conveyed by faces. However, it remains unclear which spatio-temporal characteristics of facial movements serve as critical cues to the perceived genuineness of facial expressions. This study focused on observable spatio-temporal differences between perceived-as-genuine and deliberate expressions of happiness and anger expressions. In this experiment, 89 Japanese participants were asked to judge the perceived genuineness of faces in videos showing happiness or anger expressions. To identify diagnostic facial cues to the perceived genuineness of the facial expressions, we analyzed a total of 128 face videos using an automated facial action detection system; thereby, moment-to-moment activations in facial action units were annotated, and nonnegative matrix factorization extracted sparse and meaningful components from all action units data. The results showed that genuineness judgments reduced when more spatial patterns were observed in facial expressions. As for the temporal features, the perceived-as-deliberate expressions of happiness generally had faster onsets to the peak than the perceived-as-genuine expressions of happiness. Moreover, opening the mouth negatively contributed to the perceived-as-genuine expressions, irrespective of the type of facial expressions. These findings provide the first evidence for dynamic facial cues to the perceived genuineness of happiness and anger expressions. [ABSTRACT FROM AUTHOR]

Meta-analyses have found that people high in psychopathy categorize (or "recognize") others' prototypical facial emotion expressions with reduced accuracy. However, these have been contested with remaining questions regarding the strength, specificity, and mechanisms of this ability in psychopathy. In addition, few studies have tested holistically whether psychopathy is related to reduced facial mimicry or autonomic arousal in response to others' dynamic facial expressions. Therefore, the current study presented 6 s videos of a target person making prototypical emotion expressions (anger, fear, disgust, sadness, joy, and neutral) to N = 88 incarcerated adult males while recording facial electromyography, skin conductance response (SCR), and heart rate. Participants identified the emotion category and rated the valence and intensity of the target person's emotion. Psychopathy was assessed via the Psychopathy Checklist-Revised (PCL-R). We predicted that overall PCL-R scores and scores for the interpersonal/affective traits, in particular, would be related to reduced emotion categorization accuracy, valence ratings, intensity ratings, facial mimicry, SCR amplitude, and cardiac deceleration in response to the prototypical facial emotion expressions. In contrast to our hypotheses, PCL-R scores were unrelated to emotion categorization accuracy, valence ratings, and intensity ratings. Stimuli failed to elicit facial mimicry from the full sample, which does not allow drawing conclusions about the relationship between psychopathy and facial mimicry. However, participants displayed general autonomic arousal responses, but not to prototypical emotion expressions per se. PCL-R scores were also unrelated to SCR and cardiac deceleration. These findings failed to identify aberrant behavioral and physiological responses to prototypical facial emotion expressions in relation to psychopathy. [ABSTRACT FROM AUTHOR]

A wealth of research indicates that emotions play an instrumental role in creative problem-solving. However, most of these studies have relied primarily on diary studies and self-report scales when measuring emotions during the creative processes. There has been a need to capture in-the-moment emotional experiences of individuals during the creative process using an automated emotion recognition tool. The experiment in this study examined the process-related difference between the creative problem solving (CPS) and simple problem solving (SPS) processes using protocol analysis and Markov's chains. Further, this experiment introduced a novel method for measuring in-the-moment emotional experiences of individuals during the CPS and SPS processes using facial expressions and machine learning algorithms. The experiment described in this study employed 64 participants to solve different tasks while wearing camera-mounted headgear. Using retrospective analysis, the participants verbally reported their thoughts using video-stimulated recall. Our results indicate differences in the cognitive efforts spent at different stages during the CPS and SPS processes. We also found that most of the creative stages were associated with ambivalent emotions whereas the stage of block was associated with negative emotions. [ABSTRACT FROM AUTHOR]