Dynamic Facial Expressions Of Emotion Research Articles

The role of visual spatial frequencies in newborns' processing of dynamic facial expressions of emotion.

Evidence on newborns' discrimination of emotional facial expressions is scarce, and the question of what is the nature of the visual information that newborns rely on to perform such discrimination remains open. Here, we manipulated the spatial frequency (SF) content of the stimuli by selectively removing low spatial frequency (LSF) and high spatial frequency bands using newborn-appropriate cutoffs to investigate what information newborns use when preferring and discriminating between dynamic displays showing happy and fearful expressions unfolding over time. Using a preferential looking paradigm, in Study 1 (N = 63, 59% females, 92% White), we showed that newborns looked longer to happy over fearful expressions in unfiltered (broad spatial frequency) and high-pass (high spatial frequency > 0.6 cycles per degree [cpd]) faces but not in low-pass (LSF < 0.5 cpd) faces. In Study 2 (N = 22, 59% females, 91% White), newborns tested in a visual habituation paradigm showed successful discrimination of the two LSF emotions. Results show that newborns can discriminate between dynamic images of happy and fearful facial expressions containing either extreme low SF (< 0.5 cpd) information or higher SF (> 0.6 cpd) bandwidth. Their preference for the happy expression was present for intact and high-pass filtered faces but not for low-pass faces. This SF effect is tentatively driven by an enhancement of attentional response to the LSF fearful face, whereas the response to the happy face is unaffected by the SF manipulation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A neurophysiological signature of dynamic emotion recognition associated with social communication skills and cortical gamma-aminobutyric acid levels in children.

Emotion recognition is a core feature of social perception. In particular, perception of dynamic facial emotional expressions is a major feature of the third visual pathway. However, the classical N170 visual evoked signal does not provide a pure correlate of such processing. Indeed, independent component analysis has demonstrated that the N170 component is already active at the time of the P100, and is therefore distorted by early components. Here we implemented, a dynamic face emotional paradigm to isolate a more pure face expression selective N170. We searched for a neural correlate of perception of dynamic facial emotional expressions, by starting with a face baseline from which a facial expression evolved. This allowed for a specific facial expression contrast signal which we aimed to relate with social communication abilities and cortical gamma-aminobutyric acid (GABA) levels. We recorded event-related potentials (ERPs) and Magnetic Resonance (MRS) measures in 35 typically developing (TD) children, (10-16 years) sex-matched, during emotion recognition of an avatar morphing/unmorphing from neutral to happy/sad expressions. This task allowed for the elimination of the contribution low-level visual components, in particular the P100, by morphing baseline isoluminant neutral faces into specific expressions, isolating dynamic emotion recognition. Therefore, it was possible to isolate a dynamic face sensitive N170 devoid of interactions with earlier components. We found delayed N170 and P300, with a hysteresis type of dependence on stimulus trajectory (morphing/unmorphing), with hemispheric lateralization. The delayed N170 is generated by an extrastriate source, which can be related to the third visual pathway specialized in biological motion processing. GABA levels in visual cortex were related with N170 amplitude and latency and predictive of worse social communication performance (SCQ scores). N170 latencies reflected delayed processing speed of emotional expressions and related to worse social communication scores. In sum, we found a specific N170 electrophysiological signature of dynamic face processing related to social communication abilities and cortical GABA levels. These findings have potential clinical significance supporting the hypothesis of a spectrum of social communication abilities and the identification of a specific face-expression sensitive N170 which can potentially be used in the development of diagnostic and intervention tools.

The Interplay between Chronotype and Emotion Regulation in the Recognition of Facial Expressions of Emotion.

Emotion regulation strategies affect the experience and processing of emotions and emotional stimuli. Chronotype has also been shown to influence the processing of emotional stimuli, with late chronotypes showing a bias towards better processing of negative stimuli. Additionally, greater eveningness has been associated with increased difficulties in emotion regulation and preferential use of expressive suppression strategies. Therefore, the present study aimed to understand the interplay between chronotype and emotion regulation on the recognition of dynamic facial expressions of emotion. To that end, 287 participants answered self-report measures and performed an online facial emotion recognition task from short video clips where a neutral face gradually morphed into a full-emotion expression (one of the six basic emotions). Participants should press the spacebar to stop each video as soon as they could recognize the emotional expression, and then identify it from six provided labels/emotions. Greater eveningness was associated with shorter response times (RT) in the identification of sadness, disgust and happiness. Higher scores of expressive suppression were associated with longer RT in identifying sadness, disgust, anger and surprise. Expressive suppression significantly moderated the relationship between chronotype and the recognition of sadness and anger, with chronotype being a significant predictor of emotion recognition times only at higher levels of expressive suppression. No significant effects were observed for cognitive reappraisal. These results are consistent with a negative bias in emotion processing in late chronotypes and increased difficulty in anger and sadness recognition for expressive suppressor morning-types.

Differential beta desynchronisation responses to dynamic emotional facial expressions are attenuated in higher trait anxiety and autism

Daily life demands that we differentiate between a multitude of emotional facial expressions (EFEs). The mirror neuron system (MNS) is becoming increasingly implicated as a neural network involved with understanding emotional body expressions. However, the specificity of the MNS’s involvement in emotion recognition has remained largely unexplored. This study investigated whether six basic dynamic EFEs (anger, disgust, fear, happiness, sadness, and surprise) would be differentiated through event-related desynchronisation (ERD) of sensorimotor alpha and beta oscillatory activity, which indexes sensorimotor MNS activity. We found that beta ERD differentiated happy, fearful, and sad dynamic EFEs at the central region of interest, but not at occipital regions. Happy EFEs elicited significantly greater central beta ERD relative to fearful and sad EFEs within 800 - 2,000 ms after EFE onset. These differences were source-localised to the primary somatosensory cortex, which suggests they are likely to reflect differential sensorimotor simulation rather than differential attentional engagement. Furthermore, individuals with higher trait anxiety showed less beta ERD differentiation between happy and sad faces. Similarly, individuals with higher trait autism showed less beta ERD differentiation between happy and fearful faces. These findings suggest that the differential simulation of specific affective states is attenuated in individuals with higher trait anxiety and autism. In summary, the MNS appears to support the skills needed for emotion processing in daily life, which may be influenced by certain individual differences. This provides novel evidence for the notion that simulation-based emotional skills may underlie the emotional difficulties that accompany affective disorders, such as anxiety.

Subnormal short-latency facial mimicry responses to dynamic emotional facial expressions in male adolescents with disruptive behavior disorders and callous-unemotional traits.

Using still pictures of emotional facial expressions as experimental stimuli, reduced amygdala responses or impaired recognition of basic emotions were repeatedly found in people with psychopathic traits. The amygdala also plays an important role in short‐latency facial mimicry responses. Since dynamic emotional facial expressions may have higher ecological validity than still pictures, we compared short‐latency facial mimicry responses to dynamic and static emotional expressions between adolescents with psychopathic traits and normal controls. Facial EMG responses to videos or still pictures of emotional expressions (happiness, anger, sadness, fear) were measured. Responses to 500‐ms dynamic expressions in videos, as well as the subsequent 1500‐ms phase of maximal (i.e., static) expression, were compared between male adolescents with disruptive behavior disorders and high (n = 14) or low (n = 17) callous‐unemotional (CU) traits, and normal control subjects (n = 32). Responses to still pictures were also compared between groups. EMG responses to dynamic expressions were generally significantly smaller in the high‐CU group than in the other two groups, which generally did not differ. These group differences gradually emerged during the 500‐ms stimulus presentation period but in general they were already seen a few hundred milliseconds after stimulus onset. Group differences were absent during the 1500‐ms phase of maximal expression and during exposure to still pictures. Subnormal short‐latency mimicry responses to dynamic emotional facial expressions in the high‐CU group might have negative consequences for understanding emotional facial expressions of others during daily life when human facial interactions are primarily dynamic.

EEG Decoding of Dynamic Facial Expressions of Emotion: Evidence from SSVEP and Causal Cortical Network Dynamics

The neural cognitive mechanism in processing static facial expressions (FEs) has been well documented, whereas the one underlying perceiving dynamic faces remains unclear. In this study, Fourier transformation and time–frequency analysis of Electroencephalography (EEG) data were carried out to detect the brain activation underlying dynamic or static FEs while twenty-one participants were viewing dynamic or static faces flicking at 10 Hz. In particular, steady-state visual evoked potentials (SSVEPs) were quantified through spectral power analysis of EEG recordings. Besides, Granger causality (GC) analysis (GCA) was also performed to capture the causal cortical network dynamics during dynamic or static FEs of emotion. It was discovered that the dynamic (from neural to happy (N2H) or vice versa (H2N)) FEs elicited larger SSVEPs than the static ones. Additionally, GCA demonstrated that the H2N case, in which happy FEs were being gradually changed into neutral ones, exhibited larger GC measure during the late processing stage than that from the early stage. Consequently, enhanced SSVEPs and effective brain connectivity for dynamic FEs illustrated that participants might need consume more attentional resources to process the dynamic faces, particularly for the change from happy to neutral faces. The new neural index might facilitate us to better understand the cognitive processing of dynamic and static FEs.

Oxytocin and emotion recognition: Investigating the possible roles of facial synchrony and eye gaze

The neuropeptide oxytocin (OT) has been shown to influence social cognition, including better recognition of emotion in faces. One potential way in which OT improves emotion recognition is by increasing the correspondence between a perceiver's own facial activity and observed facial expressions. Here we investigate whether increased facial synchrony while viewing facial expressions increases emotion recognition, and whether this effect is moderated by OT. Change in visual attention as captured by eye-gaze is another way in which OT might improve emotion recognition. We also examine visual attention to observed expressions, and whether this is influenced by OT. One hundred and four male undergraduates took part in a double-blind, randomized, between-subjects study in which they self-administered either a placebo (PL) or 24 IU of OT before viewing dynamic facial expressions of emotion, during which their facial activity and eye-gaze were measured, before answering questions on emotion recognition and affiliation. It was hypothesized that participants in the OT condition would exhibit more facial synchrony than would those in the PL condition, and that OT would influence time spent looking at the eye region of target faces. Consistent with previous research, participants in the OT condition were marginally but significantly better at emotion recognition than those in the PL condition. However, participants in the OT condition displayed less facial synchrony for fearful expressions, and there was no effect of OT on measures of eye-gaze. These results suggest that OT does not improve emotion recognition through increased facial synchrony or changing visual attention.

The effect of oxytocin on pupil response to naturalistic dynamic facial expressions

The neuropeptide oxytocin (OT) has been found to play an important role in a variety of social behaviours and social cognition in particular. The social salience hypothesis of OT suggests that OT shifts attention towards socially relevant stimuli, which offers an explanation for improvements on social cognition measures following OT administration. Pupil dilation occurs with increasing attentional resource allocation and previous research has found that OT administration led to an increase in pupil diameter in response to social stimuli relative to placebo (PL), thereby suggesting increased social attention. The current study aimed to investigate the effects of OT on pupillary responses to more naturalistic social stimuli in a larger sample. Ninety-four male participants took part in the double-blind, placebo controlled, mixed-design study, in which they self-administered either an OT or PL nasal spray before viewing naturalistic dynamic facial expressions of emotion (happy, sad, fear and anger). Contrary to prediction, there was no effect of OT administration on pupil diameter. The results are discussed in light of the social salience hypothesis and with reference to the methodological differences between studies.

Prediction of Dynamic Facial Emotional Expressions Valences Based on Absolute Brainwaves Power in Adolescents: Using Quantitative Electroencephalogram

Prediction of Dynamic Facial Emotional Expressions Valences Based on Absolute Brainwaves Power in Adolescents: Using Quantitative Electroencephalogram

Perception of dynamic facial expressions of emotion between dogs and humans

Facial expressions are a core component of the emotional response of social mammals. In contrast to Darwin's original proposition, expressive facial cues of emotion appear to have evolved to be species-specific. Faces trigger an automatic perceptual process, and so, inter-specific emotion perception is potentially a challenge; since observers should not try to “read” heterospecific facial expressions in the same way that they do conspecific ones. Using dynamic spontaneous facial expression stimuli, we report the first inter-species eye-tracking study on fully unrestrained participants and without pre-experiment training to maintain attention to stimuli, to compare how two different species living in the same ecological niche, humans and dogs, perceive each other’s facial expressions of emotion. Humans and dogs showed different gaze distributions when viewing the same facial expressions of either humans or dogs. Humans modulated their gaze depending on the area of interest (AOI) being examined, emotion, and species observed, but dogs modulated their gaze depending on AOI only. We also analysed if the gaze distribution was random across AOIs in both species: in humans, eye movements were not correlated with the diagnostic facial movements occurring in the emotional expression, and in dogs, there was only a partial relationship. This suggests that the scanning of facial expressions is a relatively automatic process. Thus, to read other species’ facial emotions successfully, individuals must overcome these automatic perceptual processes and employ learning strategies to appreciate the inter-species emotional repertoire.

Human Observers and Automated Assessment of Dynamic Emotional Facial Expressions: KDEF-dyn Database Validation.

Most experimental studies of facial expression processing have used static stimuli (photographs), yet facial expressions in daily life are generally dynamic. In its original photographic format, the Karolinska Directed Emotional Faces (KDEF) has been frequently utilized. In the current study, we validate a dynamic version of this database, the KDEF-dyn. To this end, we applied animation between neutral and emotional expressions (happy, sad, angry, fearful, disgusted, and surprised; 1,033-ms unfolding) to 40 KDEF models, with morphing software. Ninety-six human observers categorized the expressions of the resulting 240 video-clip stimuli, and automated face analysis assessed the evidence for 6 expressions and 20 facial action units (AUs) at 31 intensities. Low-level image properties (luminance, signal-to-noise ratio, etc.) and other purely perceptual factors (e.g., size, unfolding speed) were controlled. Human recognition performance (accuracy, efficiency, and confusions) patterns were consistent with prior research using static and other dynamic expressions. Automated assessment of expressions and AUs was sensitive to intensity manipulations. Significant correlations emerged between human observers’ categorization and automated classification. The KDEF-dyn database aims to provide a balance between experimental control and ecological validity for research on emotional facial expression processing. The stimuli and the validation data are available to the scientific community.

Less differentiated facial responses to naturalistic films of another person's emotional expressions in adolescents and adults with High-Functioning Autism Spectrum Disorder

BackgroundReduced facial expressivity (flat affect) and deficits in nonverbal communicative behaviors are characteristic symptoms of autism spectrum disorder (ASD). Based on the important interpersonal functions of facial emotional responsiveness the present study aimed at a comprehensive and differentiated analysis of perceptible facial behavior in response to another person's naturalistic, dynamic facial expressions of emotion. MethodsIn a group of 21 adolescent and adult individuals with High-Funtioning autism spectrum disorder (HF-ASD) and in 21 matched healthy controls we examined perceptible facial responses using the whole range of action units of the Facial Action Coding System (FACS) while participants were watching films displaying continuous, dynamic real-life facial expressions of four universal emotions (cheerfulness, anger, sadness, anxiety). The duration of the 80 s films was in the typical range of casual face-to-face interactions. ResultsOverall, the number of congruent facial muscle movements while watching the emotion-laden stimulus films did not differ in the two groups. However, the comprehensive FACS analysis indicated that participants with HF-ASD displayed less differentiated facial responses to the watched emotional expressions. ConclusionsThe unusual or awkward patterns of facial emotional responses in ASD may hamper the recognition of affect in other people as well as the interaction partner's sense of interpersonal resonance, and thereby lead to social disadvantage in individuals with ASD.

Tracking the recognition of static and dynamic facial expressions of emotion across the life span.

The effective transmission and decoding of dynamic facial expressions of emotion is omnipresent and critical for adapted social interactions in everyday life. Thus, common intuition would suggest an advantage for dynamic facial expression recognition (FER) over the static snapshots routinely used in most experiments. However, although many studies reported an advantage in the recognition of dynamic over static expressions in clinical populations, results obtained from healthy participants are contrasted. To clarify this issue, we conducted a large cross-sectional study to investigate FER across the life span in order to determine if age is a critical factor to account for such discrepancies. More than 400 observers (age range 5-96) performed recognition tasks of the six basic expressions in static, dynamic, and shuffled (temporally randomized frames) conditions, normalized for the amount of energy sampled over time. We applied a Bayesian hierarchical step-linear model to capture the nonlinear relationship between age and FER for the different viewing conditions. Although replicating the typical accuracy profiles of FER, we determined the age at which peak efficiency was reached for each expression and found greater accuracy for most dynamic expressions across the life span. This advantage in the elderly population was driven by a significant decrease in performance for static images, which was twice as large as for the young adults. Our data posit the use of dynamic stimuli as being critical in the assessment of FER in the elderly population, inviting caution when drawing conclusions from the sole use of static face images to this aim.

Investigating the recognition of static and dynamic facial expressions of emotion in MCI patients

Investigating the recognition of static and dynamic facial expressions of emotion in MCI patients

Cortical responses to dynamic emotional facial expressions generalize across stimuli, and are sensitive to task-relevance, in adults with and without Autism

Individuals with Autism Spectrum Disorders (ASD) report difficulties extracting meaningful information from dynamic and complex social cues, like facial expressions. The nature and mechanisms of these difficulties remain unclear. Here we tested whether that difficulty can be traced to the pattern of activity in “social brain” regions, when viewing dynamic facial expressions. In two studies, adult participants (male and female) watched brief videos of a range of positive and negative facial expressions, while undergoing functional magnetic resonance imaging (Study 1: ASD n = 16, control n = 21; Study 2: ASD n = 22, control n = 30). Patterns of hemodynamic activity differentiated among facial emotional expressions in left and right superior temporal sulcus, fusiform gyrus, and parts of medial prefrontal cortex. In both control participants and high-functioning individuals with ASD, we observed (i) similar responses to emotional valence that generalized across facial expressions and animated social events; (ii) similar flexibility of responses to emotional valence, when manipulating the task-relevance of perceived emotions; and (iii) similar responses to a range of emotions within valence. Altogether, the data indicate that there was little or no group difference in cortical responses to isolated dynamic emotional facial expressions, as measured with fMRI. Difficulties with real-world social communication and social interaction in ASD may instead reflect differences in initiating and maintaining contingent interactions, or in integrating social information over time or context.

Evidence of Rapid Modulation by Social Information of Subjective, Physiological, and Neural Responses to Emotional Expressions.

Recent research suggests that conceptual or emotional factors could influence the perceptual processing of stimuli. In this article, we aimed to evaluate the effect of social information (positive, negative, or no information related to the character of the target) on subjective (perceived and felt valence and arousal), physiological (facial mimicry) as well as on neural (P100 and N170) responses to dynamic emotional facial expressions (EFE) that varied from neutral to one of the six basic emotions. Across three studies, the results showed reduced ratings of valence and arousal of EFE associated with incongruent social information (Study 1), increased electromyographical responses (Study 2), and significant modulation of P100 and N170 components (Study 3) when EFE were associated with social (positive and negative) information (vs. no information). These studies revealed that positive or negative social information reduces subjective responses to incongruent EFE and produces a similar neural and physiological boost of the early perceptual processing of EFE irrespective of their congruency. In conclusion, the article suggests that the presence of positive or negative social context modulates early physiological and neural activity preceding subsequent behavior.

Tracking the recognition of static and dynamic facial expressions of emotion across life span

Tracking the recognition of static and dynamic facial expressions of emotion across life span

Brain synchronization during perception of facial emotional expressions with natural and unnatural dynamics

Research on the perception of facial emotional expressions (FEEs) often uses static images that do not capture the dynamic character of social coordination in natural settings. Recent behavioral and neuroimaging studies suggest that dynamic FEEs (videos or morphs) enhance emotion perception. To identify mechanisms associated with the perception of FEEs with natural dynamics, the present EEG (Electroencephalography)study compared (i) ecologically valid stimuli of angry and happy FEEs with natural dynamics to (ii) FEEs with unnatural dynamics, and to (iii) static FEEs. FEEs with unnatural dynamics showed faces moving in a biologically possible but unpredictable and atypical manner, generally resulting in ambivalent emotional content. Participants were asked to explicitly recognize FEEs. Using whole power (WP) and phase synchrony (Phase Locking Index, PLI), we found that brain responses discriminated between natural and unnatural FEEs (both static and dynamic). Differences were primarily observed in the timing and brain topographies of delta and theta PLI and WP, and in alpha and beta WP. Our results support the view that biologically plausible, albeit atypical, FEEs are processed by the brain by different mechanisms than natural FEEs. We conclude that natural movement dynamics are essential for the perception of FEEs and the associated brain processes.

Эффект перцептивной адаптации к динамическим экспрессиям лица

We present three experiments investigating the perceptual adaptation to dynamic facial emotional expressions. Dynamic expressions of six basic emotions were obtained by video recording of a poser’s face. In Experiment 1 participants (n=20) evaluated the intensity of 6 emotions, neutral state, genuineness and naturalness of dynamic expressions. The validated stimuli were further used as adaptors in Experiments 2 and 3 aimed at exploring the structure of facial expressions perceptual space by adaptation effects. In Experiment 2 participants (n=16) categorized neutral/emotion morphs after adaptation to dynamic expressions. In Experiment 3 (n=26) the task of the first stage was to categorize static frames derived from video records of the poser. Next individual psychometric functions were fitted for each participant and each emotion, to find the frame with emotion recognized correctly in 50% trials. These latter images were presented on the second stage in adaptation experiment, with dynamic video records as adaptors. Based on the three experiments, we found that facial expressions of happiness and sadness are perceived as opponent emotions and mutually facilitate the recognition of each other, whereas disgust and anger, and fear and surprise are perceptually similar and reduce the recognition accuracy of each other. We describe the categorical fields of dynamic facial expressions and of static images of initial phases of expression development. The obtained results suggest that dimensional and categorical approaches to perception of emotions are not mutually exclusive and probably describe different stages of face information processing. The study was supported by the Russian Foundation for Basic Research, project № 15-36-01281 “Structure of dynamic facial expressions perception”.

Priming Younger and Older Adults’ Sentence Comprehension: Insights from Dynamic Emotional Facial Expressions and Pupil Size Measures

Background: Prior visual-world research has demonstrated that emotional priming of spoken sentence processing is rapidly modulated by age. Older and younger participants saw two photographs of a positive and of a negative event side-by-side and listened to a spoken sentence about one of these events. Older adults’ fixations to the mentioned (positive) event were enhanced when the still photograph of a previously-inspected positive-valence speaker face was (vs. wasn’t) emotionally congruent with the event/sentence. By contrast, the younger adults exhibited such an enhancement with negative stimuli only. Objective: The first aim of the current study was to assess the replicability of these findings with dynamic face stimuli (unfolding from neutral to happy or sad). A second goal was to assess a key prediction made by socio-emotional selectivity theory, viz. that the positivity effect (a preference for positive information) displayed by older adults involves cognitive effort. Method: We conducted an eye-tracking visual-world experiment. Results: Most priming and age effects, including the positivity effects, replicated. However, against our expectations, the positive gaze preference in older adults did not co-vary with a standard measure of cognitive effort - increased pupil dilation. Instead, pupil size was significantly bigger when (both younger and older) adults processed negative than positive stimuli. Conclusion: These findings are in line with previous research on the relationship between positive gaze preferences and pupil dilation. We discuss both theoretical and methodological implications of these results.