Anger superiority effect: The importance of dynamic emotional facial expressions

Age-dependent changes in the anger superiority effect: Evidence from a visual search task

The perception of threatening facial expressions is a critical skill necessary for detecting the emotional states of others and responding appropriately. The anger superiority effect hypothesis suggests that individuals are better at processing and identifying angry faces compared with other nonthreatening facial expressions. In adults, the anger superiority effect is present even after controlling for the bottom-up visual saliency, and when ecologically valid stimuli are used. However, it is as yet unclear whether this effect is present in children. To fill this gap, we tested the anger superiority effect in children ages 6-14 years in a visual search task by using emotional dynamic stimuli and equating the visual salience of target and distractors. The results suggest that in childhood, the angry superiority effect consists of improved accuracy in detecting angry faces, while in adolescence, the ability to discriminate angry faces undergoes further development, enabling faster and more accurate threat detection.

Can we dissociate hypervigilance to social threats from altered perceptual decision-making processes in lonely individuals? An exploration with Drift Diffusion Modeling and event-related potentials

It has been hypothesized that lonely individuals demonstrate hypervigilance toward social threats. However, recent studies have raised doubts about the reliability of tasks commonly used to measure attentional biases toward threats. Two alternative approaches have been suggested to overcome the limitations of traditional analysis of attentional bias. First, the neurophysiological indicators of orienting to threats were shown to have superior psychometric characteristics compared to overt measures of behavioral performance. The second approach involves utilizing computational modeling to isolate latent components corresponding to specific cognitive mechanisms from observable data. To test the usefulness of these approaches in loneliness research, we analyzed behavioral and electroencephalographic (EEG) data from 26 lonely and 26 non-lonely participants who performed a dot-probe task using a computational modeling approach. We applied the Drift Diffusion Model (DDM) and extracted N2pc-an event-related potential that serves as an indicator of spatial attention. No evidence for social threat hypervigilance has been found in DDM parameters nor in N2pc characteristics in the current study. However, we did observe decreased drift rate and increased variability in drift rate between trials within the lonely group, indicating reduced efficiency in perceptual decision-making among lonely individuals. These effects were not detected using standard behavioral measures used in the dot-probe paradigm. Given that DDM indicators were sensitive to differences in perceptual discrimination between the two groups, even when no overt differences were found in standard behavioral measures, it may be postulated that computational approaches offer a more comprehensive understanding of cognitive processes.

Influence of stimulus manipulation on conscious awareness of emotional facial expressions in the match-to-sample paradigm

The conscious perception of emotional facial expressions plays an indispensable role in social interaction. However, previous psychological studies have reported inconsistent findings regarding whether conscious awareness is greater for emotional expressions than for neutral expressions. Furthermore, whether this phenomenon is attributable to emotional or visual factors remains unknown. To investigate these issues, we conducted five psychological experiments to test the conscious perception of emotional and neutral facial expressions using the match-to-sample paradigm. Facial stimuli were momentarily presented in the peripheral visual fields while participants read simultaneously presented letters in the central visual fields. The participants selected a perceived face from nine samples. The results of all experiments demonstrated that emotional expressions were more accurately identified than neutral expressions. Furthermore, Experiment 4 showed that angry expressions were identified more accurately than anti-angry expressions, which expressed neutral emotions with comparable physical changes to angry expressions. Experiment 5, testing the interaction between emotional expression and face direction, showed that angry expressions looking toward participants were more accurately identified than those looking away from participants, even though they were physically identical. These results suggest that the conscious awareness of emotional facial expressions is enhanced by their emotional significance.

EEG alpha band functional connectivity reveals distinct cortical dynamics for overt and covert emotional face processing

Current knowledge regarding how the focus of our attention during face processing influences neural responses largely comes from neuroimaging studies reporting on regional brain activations. The present study was designed to add novel insights to this research by studying how attention can differentially impact the way cortical regions interact during emotional face processing. High-density electroencephalogram was recorded in a sample of fifty-two healthy participants during an emotional face processing task. The task required participants to either attend to the expressions (i.e., overt processing) or attend to a perceptual distractor, which rendered the expressions task-irrelevant (i.e., covert processing). Functional connectivity in the alpha band was estimated in source space and modeled using graph theory to quantify whole-brain integration and segregation. Results revealed that overt processing of facial expressions is linked to reduced cortical segregation and increased cortical integration, this latter specifically for negative expressions of fear and sadness. Furthermore, we observed increased communication efficiency during overt processing of negative expressions between the core and the extended face processing systems. Overall, these findings reveal that attention makes the interaction among the nodes involved in face processing more efficient, also uncovering a connectivity signature of the prioritized processing mechanism of negative expressions, that is an increased cross-communication within the nodes of the face processing network.

Face-Selective Patches in Marmosets Are Involved in Dynamic and Static Facial Expression Processing

The correct identification of facial expressions is critical for understanding the intention of others during social communication in the daily life of all primates. Here we used ultra-high-field fMRI at 9.4 T to investigate the neural network activated by facial expressions in awake New World common marmosets from both male and female sex, and to determine the effect of facial motions on this network. We further explored how the face-patch network is involved in the processing of facial expressions. Our results show that dynamic and static facial expressions activate face patches in temporal and frontal areas (O, PV, PD, MD, AD, and PL) as well as in the amygdala, with stronger responses for negative faces, also associated with an increase of the respiration rates of the monkey. Processing of dynamic facial expressions involves an extended network recruiting additional regions not known to be part of the face-processing network, suggesting that face motions may facilitate the recognition of facial expressions. We report for the first time in New World marmosets that the perception and identification of changeable facial expressions, vital for social communication, recruit face-selective brain patches also involved in face detection processing and are associated with an increase of arousal.SIGNIFICANCE STATEMENT Recent research in humans and nonhuman primates has highlighted the importance to correctly recognize and process facial expressions to understand others' emotions in social interactions. The current study focuses on the fMRI responses of emotional facial expressions in the common marmoset (Callithrix jacchus), a New World primate species sharing several similarities of social behavior with humans. Our results reveal that temporal and frontal face patches are involved in both basic face detection and facial expression processing. The specific recruitment of these patches for negative faces associated with an increase of the arousal level show that marmosets process facial expressions of their congener, vital for social communication.

What is missing in the study of emotion expression?

While approaching celebrations for the 150 years of "The Expression of the Emotions in Man and Animals", scientists' conclusions on emotion expression are still debated. Emotion expression has been traditionally anchored to prototypical and mutually exclusive facial expressions (e.g., anger, disgust, fear, happiness, sadness, and surprise). However, people express emotions in nuanced patterns and - crucially - not everything is in the face. In recent decades considerable work has critiqued this classical view, calling for a more fluid and flexible approach that considers how humans dynamically perform genuine expressions with their bodies in context. A growing body of evidence suggests that each emotional display is a complex, multi-component, motoric event. The human face is never static, but continuously acts and reacts to internal and environmental stimuli, with the coordinated action of muscles throughout the body. Moreover, two anatomically and functionally different neural pathways sub-serve voluntary and involuntary expressions. An interesting implication is that we have distinct and independent pathways for genuine and posed facial expressions, and different combinations may occur across the vertical facial axis. Investigating the time course of these facial blends, which can be controlled consciously only in part, is recently providing a useful operational test for comparing the different predictions of various models on the lateralization of emotions. This concise review will identify shortcomings and new challenges regarding the study of emotion expressions at face, body, and contextual levels, eventually resulting in a theoretical and methodological shift in the study of emotions. We contend that the most feasible solution to address the complex world of emotion expression is defining a completely new and more complete approach to emotional investigation. This approach can potentially lead us to the roots of emotional display, and to the individual mechanisms underlying their expression (i.e., individual emotional signatures).

Negative and Positive Bias for Emotional Faces: Evidence from the Attention and Working Memory Paradigms

Visual attention and visual working memory (VWM) are two major cognitive functions in humans, and they have much in common. A growing body of research has investigated the effect of emotional information on visual attention and VWM. Interestingly, contradictory findings have supported both a negative bias and a positive bias toward emotional faces (e.g., angry faces or happy faces) in the attention and VWM fields. We found that the classical paradigms-that is, the visual search paradigm in attention and the change detection paradigm in VWM-are considerably similar. The settings of these paradigms could therefore be responsible for the contradictory results. In this paper, we compare previous controversial results from behavioral and neuroscience studies using these two paradigms. We suggest three possible contributing factors that have significant impacts on the contradictory conclusions regarding different emotional bias effects; these factors are stimulus choice, experimental setting, and cognitive process. We also propose new research directions and guidelines for future studies.

The image features of emotional faces that predict the initial eye movement to a face

Emotional facial expressions are important visual communication signals that indicate a sender's intent and emotional state to an observer. As such, it is not surprising that reactions to different expressions are thought to be automatic and independent of awareness. What is surprising, is that studies show inconsistent results concerning such automatic reactions, particularly when using different face stimuli. We argue that automatic reactions to facial expressions can be better explained, and better understood, in terms of quantitative descriptions of their low-level image features rather than in terms of the emotional content (e.g. angry) of the expressions. Here, we focused on overall spatial frequency (SF) and localized Histograms of Oriented Gradients (HOG) features. We used machine learning classification to reveal the SF and HOG features that are sufficient for classification of the initial eye movement towards one out of two simultaneously presented faces. Interestingly, the identified features serve as better predictors than the emotional content of the expressions. We therefore propose that our modelling approach can further specify which visual features drive these and other behavioural effects related to emotional expressions, which can help solve the inconsistencies found in this line of research.

Attentional control moderates the relationship between pain catastrophizing and selective attention to pain faces on the antisaccade task

Cognitive models of chronic pain emphasize the critical role of pain catastrophizing in attentional bias to pain-related stimuli. The aim of this study was (a) to investigate the relationship between pain catastrophizing and the ability to inhibit selective attention to pain-related faces (attentional bias); and (b) to determine whether attentional control moderated this relationship. One hundred and ten pain-free participants completed the anti-saccade task with dynamic facial expressions, specifically painful, angry, happy, and neutral facial expressions and questionnaires including a measure of pain catastrophizing. As predicted, participants with high pain catastrophizing had significantly higher error rates for antisaccade trials with pain faces relative to other facial expressions, indicating a difficulty disinhibiting attention towards painful faces. In moderation analyses, data showed that attentional control moderated the relationship between attentional bias to pain faces and pain catastrophizing. Post-hoc analyses demonstrated that it was shifting attention (not focusing) that accounted for this effect. Only for those with high self-reported ability to shift attention was there a significant relationship between catastrophizing and attentional bias to pain. These findings confirm that attentional control is necessary for an association between attentional bias and catastrophizing to be observed, which may explain the lack of relationships between attentional bias and individual characteristics, such as catastrophizing, in prior research.

Widespread and lateralized social brain activity for processing dynamic facial expressions

Dynamic facial expressions of emotions constitute natural and powerful means of social communication in daily life. A number of previous neuroimaging studies have explored the neural mechanisms underlying the processing of dynamic facial expressions, and indicated the activation of certain social brain regions (e.g., the amygdala) during such tasks. However, the activated brain regions were inconsistent across studies, and their laterality was rarely evaluated. To investigate these issues, we measured brain activity using functional magnetic resonance imaging in a relatively large sample (n = 51) during the observation of dynamic facial expressions of anger and happiness and their corresponding dynamic mosaic images. The observation of dynamic facial expressions, compared with dynamic mosaics, elicited stronger activity in the bilateral posterior cortices, including the inferior occipital gyri, fusiform gyri, and superior temporal sulci. The dynamic facial expressions also activated bilateral limbic regions, including the amygdalae and ventromedial prefrontal cortices, more strongly versus mosaics. In the same manner, activation was found in the right inferior frontal gyrus (IFG) and left cerebellum. Laterality analyses comparing original and flipped images revealed right hemispheric dominance in the superior temporal sulcus and IFG and left hemispheric dominance in the cerebellum. These results indicated that the neural mechanisms underlying processing of dynamic facial expressions include widespread social brain regions associated with perceptual, emotional, and motor functions, and include a clearly lateralized (right cortical and left cerebellar) network like that involved in language processing.

Tolerance to spatial-relational transformations in unfamiliar faces: A further challenge to a configural processing account of identity recognition

One of the most important questions in face perception research is to understand what information is extracted from a face in order to recognize its identity. Recognition of facial identity has been attributed to a special sensitivity to "configural" information. However, recent studies have challenged the configural account by showing that participants are poor in discriminating variations of metric distances among facial features, especially for familiar as opposed to unfamiliar faces, whereas a configural account predicts the opposite. We aimed to extend these previous results by examining classes of unfamiliar faces with which we have different levels of expertise. We hypothesized an inverse relation between sensitivity to configural information and expertise with a given class of faces, but only for neutral expressions. By first matching perceptual discriminability, we measured tolerance to subtle configural transformations with same-race (SR) versus other-race (OR) faces, and with upright versus upside-down faces. Consistently with our predictions, we found a lower sensitivity to at-threshold configural changes for SR compared to OR faces. We also found that, for our stimuli, the face inversion effect disappeared for neutral but not for emotional faces - a result that can also be attributed to a lower sensitivity to configural transformations for faces presented in a more familiar orientation. The present findings question a purely configural account of face processing and suggest that the role of spatial-relational information in face processing varies according to the functional demands of the task and to the characteristics of the stimuli.

Brain Responses to Dynamic Facial Expressions: A Normative Meta-Analysis

Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI) studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos) are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.

Dynamic Displays Enhance the Ability to Discriminate Genuine and Posed Facial Expressions of Emotion

Accurately gauging the emotional experience of another person is important for navigating interpersonal interactions. This study investigated whether perceivers are capable of distinguishing between unintentionally expressed (genuine) and intentionally manipulated (posed) facial expressions attributed to four major emotions: amusement, disgust, sadness, and surprise. Sensitivity to this discrimination was explored by comparing unstaged dynamic and static facial stimuli and analyzing the results with signal detection theory. Participants indicated whether facial stimuli presented on a screen depicted a person showing a given emotion and whether that person was feeling a given emotion. The results showed that genuine displays were evaluated more as felt expressions than posed displays for all target emotions presented. In addition, sensitivity to the perception of emotional experience, or discriminability, was enhanced in dynamic facial displays, but was less pronounced in the case of static displays. This finding indicates that dynamic information in facial displays contributes to the ability to accurately infer the emotional experiences of another person.

Facial expression movement enhances the measurement of temporal dynamics of attentional bias in the dot-probe task

The facial dot-probe task is one of the most common experimental paradigms used to assess attentional bias toward emotional information. In recent years, however, the psychometric properties of this paradigm have been questioned. In the present study, attentional bias to emotional face stimuli was measured with dynamic and static images of realistic human faces in 97 college students (63 women) who underwent either a positive or a negative mood-induction prior to the experiment. We controlled the bottom-up salience of the stimuli in order to dissociate the top-down orienting of attention from the effects of the bottom-up physical properties of the stimuli. A Bayesian analysis of our results indicates that 1) the traditional global attentional bias index shows a low reliability, 2) reliability increases dramatically when biased attention is analyzed by extracting a series of bias estimations from trial-to-trial (Zvielli, Bernstein, & Koster, 2015), 3) dynamic expression of emotions strengthens biased attention to emotional information, and 4) mood-congruency facilitates the measurement of biased attention to emotional stimuli. These results highlight the importance of using ecologically valid stimuli in attentional bias research, together with the importance of estimating biased attention at the trial level.

Facilitating Effects of Emotion on the Perception of Biological Motion: Evidence for a Happiness Superiority Effect

It has been reported that visual perception can be influenced not only by the physical features of a stimulus but also by the emotional valence of the stimulus, even without explicit emotion recognition. Some previous studies reported an anger superiority effect while others found a happiness superiority effect during visual perception. It thus remains unclear as to which emotion is more influential. In the present study, we conducted two experiments using biological motion (BM) stimuli to examine whether emotional valence of the stimuli would affect BM perception; and if so, whether a specific type of emotion is associated with a superiority effect. Point-light walkers with three emotion types (anger, happiness, and neutral) were used, and the threshold to detect BM within noise was measured in Experiment 1. Participants showed higher performance in detecting happy walkers compared with the angry and neutral walkers. Follow-up motion velocity analysis revealed that physical difference among the stimuli was not the main factor causing the effect. The results of the emotion recognition task in Experiment 2 also showed a happiness superiority effect, as in Experiment 1. These results show that emotional valence (happiness) of the stimuli can facilitate the processing of BM.

Biased recognition of facial affect in patients with major depressive disorder reflects clinical state

Cognitive theories of depression posit that perception is negatively biased in depressive disorder. Previous studies have provided empirical evidence for this notion, but left open the question whether the negative perceptual bias reflects a stable trait or the current depressive state. Here we investigated the stability of negatively biased perception over time. Emotion perception was examined in patients with major depressive disorder (MDD) and healthy control participants in two experiments. In the first experiment subjective biases in the recognition of facial emotional expressions were assessed. Participants were presented with faces that were morphed between sad and neutral and happy expressions and had to decide whether the face was sad or happy. The second experiment assessed automatic emotion processing by measuring the potency of emotional faces to gain access to awareness using interocular suppression. A follow-up investigation using the same tests was performed three months later. In the emotion recognition task, patients with major depression showed a shift in the criterion for the differentiation between sad and happy faces: In comparison to healthy controls, patients with MDD required a greater intensity of the happy expression to recognize a face as happy. After three months, this negative perceptual bias was reduced in comparison to the control group. The reduction in negative perceptual bias correlated with the reduction of depressive symptoms. In contrast to previous work, we found no evidence for preferential access to awareness of sad vs. happy faces. Taken together, our results indicate that MDD-related perceptual biases in emotion recognition reflect the current clinical state rather than a stable depressive trait.

Independence of face identity and expression processing: exploring the role of motion

According to the classic Bruce and Young (1986) model of face recognition, identity and emotional expression information from the face are processed in parallel and independently. Since this functional model was published, a growing body of research has challenged this viewpoint and instead support an interdependence view. In addition, neural models of face processing emphasize differences in terms of the processing of changeable and invariant aspects of faces. This article provides a critical appraisal of this literature and discusses the role of motion in both expression and identity recognition and the intertwined nature of identity, expression and motion processing. We conclude by discussing recent advancements in this area and research questions that still need to be addressed.

Task-irrelevant emotion facilitates face discrimination learning

We understand poorly how the ability to discriminate faces from one another is shaped by visual experience. The purpose of the present study is to determine whether face discrimination learning can be facilitated by facial emotions. To answer this question, we used a task-irrelevant perceptual learning paradigm because it closely mimics the learning processes that, in daily life, occur without a conscious intention to learn and without an attentional focus on specific facial features. We measured face discrimination thresholds before and after training. During the training phase (4 days), participants performed a contrast discrimination task on face images. They were not informed that we introduced (task-irrelevant) subtle variations in the face images from trial to trial. For the Identity group, the task-irrelevant features were variations along a morphing continuum of facial identity. For the Emotion group, the task-irrelevant features were variations along an emotional expression morphing continuum. The Control group did not undergo contrast discrimination learning and only performed the pre-training and post-training tests, with the same temporal gap between them as the other two groups. Results indicate that face discrimination improved, but only for the Emotion group. Participants in the Emotion group, moreover, showed face discrimination improvements also for stimulus variations along the facial identity dimension, even if these (task-irrelevant) stimulus features had not been presented during training. The present results highlight the importance of emotions for face discrimination learning.

Eye tracking the face in the crowd task: why are angry faces found more quickly?

Among a crowd of distractor faces, threatening or angry target faces are identified more quickly and accurately than are nonthreatening or happy target faces, a finding known as the “face in the crowd effect.” Two perceptual explanations of the effect have been proposed: (1) the “target orienting” hypothesis (i.e., threatening targets orient attention more quickly than do nonthreatening targets and (2) the “distractor processing” hypothesis (i.e., nonthreatening distractors paired with a threatening target are processed more efficiently than vice versa, leading to quicker detection of threatening targets). Using a task, with real faces and multiple identities, the current study replicated the face in the crowd effect and then, via eye tracking, found greater support for the target orienting hypothesis. Across both the classical search asymmetry paradigm (i.e., one happy target in a crowd of angry distractors vs. one angry target in a crowd of happy distractors) and the constant distractor paradigm (i.e., one happy target in a crowd of neutral distractors vs. one angry target in a crowd of neutral distractors), fewer distractors were fixated before first fixating angry targets relative to happy targets, with no difference in the processing efficiency of distractors. These results suggest that the face in the crowd effect on this task is supported to a greater degree by attentional patterns associated with properties of target rather those of the crowd.