Recognition Of Emotional Facial Expressions Research Articles

The role of emotional factors in face processing abilities in autism spectrum conditions

Facial emotion recognition is considered atypical in individuals with autism spectrum conditions (ASC), but emotion recognition abilities vary widely in autistic people, and there are inconsistent findings on the causes of these differences. Research indicates alexithymia may result in facial emotion recognition differences in ASC. Alternatively, mood disorders have been linked to atypical facial emotional expression recognition abilities in neurotypical adults. Investigating both the effects of alexithymia and mood disorders (depression and anxiety) is necessary to establish which of these factors may cause atypical facial emotion recognition in ASC. This study aimed to examine whether alexithymia or mood disorder symptomology is a predictor of atypical facial emotion recognition in individuals with ASC. Ninety-eight non-autistic adults and 80 autistic adults were recruited. Participants completed an online facial processing task to examine emotion and identity recognition abilities, the AQ-28, the TAS-20, and the HADS to measure autism severity, alexithymia symptoms, and depression and anxiety symptoms. Regression-based analyses found that autistic traits and autistic group membership did not predict facial emotion processing abilities after accounting for demographic variables, alexithymia and mood disorders: however, neither alexithymia nor mood disorder symptoms predicted variance in face processing abilities either. Our results concur with previous meta-analyses of facial emotion processing in autism spectrum disorder which report that studies do not always report deficits in face processing in autism: our findings are also not supportive of the model that argues that alexithymia explains facial emotion processing difficulties in autism.

Visual Field Restriction in the Recognition of Basic Facial Expressions: A Combined Eye Tracking and Gaze Contingency Study.

Uncertainties and discrepant results in identifying crucial areas for emotional facial expression recognition may stem from the eye tracking data analysis methods used. Many studies employ parameters of analysis that predominantly prioritize the examination of the foveal vision angle, ignoring the potential influences of simultaneous parafoveal and peripheral information. To explore the possible underlying causes of these discrepancies, we investigated the role of the visual field aperture in emotional facial expression recognition with 163 volunteers randomly assigned to three groups: no visual restriction (NVR), parafoveal and foveal vision (PFFV), and foveal vision (FV). Employing eye tracking and gaze contingency, we collected visual inspection and judgment data over 30 frontal face images, equally distributed among five emotions. Raw eye tracking data underwent Eye Movements Metrics and Visualizations (EyeMMV) processing. Accordingly, the visual inspection time, number of fixations, and fixation duration increased with the visual field restriction. Nevertheless, the accuracy showed significant differences among the NVR/FV and PFFV/FV groups, despite there being no difference in NVR/PFFV. The findings underscore the impact of specific visual field areas on facial expression recognition, highlighting the importance of parafoveal vision. The results suggest that eye tracking data analysis methods should incorporate projection angles extending to at least the parafoveal level.

이미지 메타 정보 기반 한국인 표정 감정 인식

Due to the recent pandemic and the development of ICT technology, the use of non-face-to-face and unmanned systems is expanding, and it is very important to understand emotions in communication in non-face-to-face situations. As emotion recognition methods for various facial expressions are required to understand emotions, artificial intelligence-based research is being conducted to improve facial expression emotion recognition in image data. However, existing research on facial expression emotion recognition requires high computing power and a lot of learning time because it utilizes a large amount of data to improve accuracy. To improve these limitations, this paper proposes a method of recognizing facial expressions using age and gender, which are image meta information, as a method of recognizing facial expressions with even a small amount of data. For facial expression emotion recognition, a face was detected using the Yolo Face model from the original image data, and age and gender were classified through the VGG model based on image meta information, and then seven emotions were recognized using the EfficientNet model. The accuracy of the proposed data classification learning model was higher as a result of comparing the meta-information-based data classification model with the model trained with all data.

Facial expressions and identities recognition in Parkinson disease

Parkinson's Disease (PD) is associated with motor and non-motor symptoms. Among the latter are deficits in matching, identification, and recognition of emotional facial expressions. On one hand, this deficit has been attributed to a dysfunction in emotion processing. Another explanation (which does not exclude the former) links this deficit with reduced facial expressiveness in these patients, which prevents them from properly understanding or embodying emotions. To disentangle the specific contribution of emotion comprehension and that of facial expression processing in PD's observed deficit with emotions we performed two experiments on non-emotional facial expressions. In Experiment 1, a group of PD patients and a group of Healthy Controls (HC) underwent a task of non-emotional expression recognition in faces of different identity and a task of identity recognition in faces with different expression. No differences were observed between the two groups in accuracies. In Experiment 2, PD patients and Healthy Controls underwent a task where they had to recognize the identity of faces encoded through a non-emotional facial expression, through a rigid head movement, or as neutral. Again, no group differences were observed. In none of the two experiments hypomimia scores had a specific effect on expression processing. We conclude that in PD patients the observed impairment with emotional expressions is likely due to a specific deficit for emotions to a greater extent than for facial expressivity processing.

Comparative analysis of emotional facial expression recognition and empathy in children with prader-willi syndrome and autism spectrum disorder

BackgroundPrader-Willi Syndrome (PWS) is a rare neurodevelopmental disorder that is often comorbid with Autism Spectrum Disorder (ASD). Due to the close association between these two conditions, and recognizing that Theory of Mind (ToM) is related to social behaviors in ASD, there is a growing interest in studying the reciprocity of social communication between these two groups.MethodThe primary objective of this study was to compare how children (n = 45) with PWS (n = 15), ASD (n = 15), and a control group (n = 15) respond to emotion recognition of facial expressions and empathy, which are both concepts related to ToM. The study utilized two tools named FEEL and Deusto-e-Motion 1.0. We also evaluated the Working Memory index of the WISC-IV scale, the Social Perception domain of the NEPSY-II battery, and the SCQ in both clinical groups.ResultsOur findings suggest that individuals with PWS exhibit lower accuracy in recognizing facial expressions and empathy compared to the control group. Both clinical groups exhibited a delayed reaction time compared to the control group. Children with PWS display difficulties in recognizing emotions of disgust and surprise. In terms of cognitive empathy, children with PWS showed a greater inclination to respond to disgust as compared to children with ASD.ConclusionsThis study represents the initial stage in comprehending the emotional and empathetic abilities of children with PWS and ASD. The findings can provide valuable insights for developing future interventions.

3DEmo: For Portrait Emotion Recognition with New Dataset

Emotional Expression Recognition (EER) and Facial Expression Recognition (FER) are active research areas in the affective computing field, which involves studying human emotion, recognition, and sentiment analysis. The main objective of this research is to develop algorithms that can accurately interpret and estimate human emotions from portrait images. The emotions depicted in a portrait can reflect various factors such as psychological and physiological states, the artist’s emotional responses, social and environmental aspects, and the period in which the painting was created. This task is challenging because (i) the portraits are often depicted in an artistic or stylized manner rather than realistically or naturally, (ii) the texture and color features obtained from natural faces and paintings differ, affecting the success rate of emotion recognition algorithms, and (iii) it is a new research area, where practically we do not have visual arts portrait facial emotion estimation models or datasets. To address these challenges, we need a new class of tools and a database specifically tailored to analyze portrait images. This study aims to develop art portrait emotion recognition methods and create a new digital portrait dataset containing 927 images. The proposed model is based on (i) a 3-dimensional estimation of emotions learned by a deep neural network and (ii) a novel deep learning module (3DEmo) that could be easily integrated into existing FER models. To evaluate the effectiveness of the developed models, we also tested their robustness on a facial emotion recognition dataset. The extensive simulation results show that the presented approach outperforms established methods. We expect that this dataset and the developed new tools will encourage further research in recognizing emotions in portrait paintings and predicting artists’ emotions in the painting period based on their artwork.

The role of the differential outcomes procedure and schizotypy in the recognition of dynamic facial expressions of emotions

Emotional facial expression recognition is a key ability for adequate social functioning. The current study aims to test if the differential outcomes procedure (DOP) may improve the recognition of dynamic facial expressions of emotions and to further explore whether schizotypal personality traits may have any effect on performance. 183 undergraduate students completed a task where a face morphed from a neutral expression to one of the six basic emotions at full intensity over 10 s. Participants had to press spacebar as soon as they identified the emotion and choose which had appeared. In the first block, participants received no outcomes. In the second block, a group received specific outcomes associated to each emotion (DOP group), while another group received non-differential outcomes after correctly responding (NOP group). Employing generalized linear models (GLMs) and Bayesian inference we estimated different parameters to answer our research goals. Schizotypal personality traits did not seem to affect dynamic emotional facial expression recognition. Participants of the DOP group were less likely to respond incorrectly to faces showing Fear and Surprise at fewer intensity levels. This may suggest that the DOP could lead to better identification of the main features that differentiate each facial expression of emotion.

Rational and Continuous Measurement of the Emotional Decision Making in Visual Recognition of Facial Emotional Expressions with M.A.R.I.E.: First Half

Rational and Continuous Measurement of the Emotional Decision Making in Visual Recognition of Facial Emotional Expressions with M.A.R.I.E.: First Half

Altered attentional processing of facial expression features in severe alcohol use disorder: An eye-tracking study.

Social cognition impairments, and notably emotional facial expression (EFE) recognition difficulties, as well as their functional and clinical correlates, are increasingly documented in severe alcohol use disorder (SAUD). However, insights into their underlying mechanisms are lacking. Here, we tested if SAUD was associated with alterations in the attentional processing of EFEs. In a preregistered study, 40 patients with SAUD and 40 healthy controls (HCs) had to identify the emotional expression conveyed by faces while having their gaze recorded by an eye-tracker. We assessed indices of initial (first fixation locations) and later (number of fixations and dwell-time) attention with reference to regions of interest corresponding to the eyes, mouth, and nose, which carry key information for EFE recognition. We centrally found that patients had less first fixations to key facial features in general, as well as less fixations and dwell time to the eyes specifically, relative to the rest of the face, compared to controls. These effects were invariant across emotional expressions. Additional exploratory analyses revealed that patients with SAUD had a less structured viewing pattern than controls. These results offer novel, direct, evidence that patients with SAUD's socioaffective difficulties already emerge at the facial attentional processing stage, along with precisions regarding the nature and generalizability of the effects. Potential implications for the mechanistic conceptualization and treatment of social cognition difficulties in SAUD are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

To see or not to see: the parallel processing of self-relevance and facial expressions

The self, like the concept of central "gravity", facilitates the processing of information that is directly relevant to the self. This phenomenon is known as the self-prioritization effect. However, it remains unclear whether the self-prioritization effect extends to the processing of emotional facial expressions. To fill this gap, we used a self-association paradigm to investigate the impact of self-relevance on the recognition of emotional facial expressions while controlling for confounding factors such as familiarity and overlearning. Using a large and diverse sample, we replicated the effect of self-relevance on face processing but found no evidence for a modulation of self-relevance on facial emotion recognition. We propose two potential theoretical explanations to account for these findings and emphasize that further research with different experimental designs and a multitasks measurement approach is needed to understand this mechanism fully. Overall, our study contributes to the literature on the parallel cognitive processing of self-relevance and facial emotion recognition, with implications for both social and cognitive psychology.

Face perception and facial emotional expression recognition ability: Both unique predictors of the broader autism phenotype.

Autism spectrum disorder (ASD) and the broader autistic phenotype (BAP) have been suggested to be associated with perceptual-cognitive difficulties processing human faces. However, the empirical results are mixed, arguably, in part due to inadequate samples and analyses. Consequently, we administered the Cambridge Face Perception Test (CFPT), the Reading the Mind in the Eyes Test (RMET), a vocabulary test, and the Autism Quotient (AQ) to a sample of 318 adults in the general community. Based on a disattenuated path analytic modelling strategy, we found that both face perception ability (β = -.21) and facial emotional expression recognition ability (β = -.27) predicted uniquely and significantly the Communication dimension of AQ. Vocabulary failed to yield a significant, direct effect onto the Communication dimension of the AQ. We conclude that difficulties perceiving information from the faces of others may contribute to difficulties in nonverbal communication, as conceptualised and measured within the context of BAP.

Facing Change: Using Automated Facial Expression Analysis to Examine Emotional Flexibility in the Treatment of Depression.

Depression involves deficits in emotional flexibility. To date, the varied and dynamic nature of emotional processes during therapy has mostly been measured at discrete time intervals using clients' subjective reports. Because emotions tend to fluctuate and change from moment to moment, the understanding of emotional processes in the treatment of depression depends to a great extent on the existence of sensitive, continuous, and objectively codified measures of emotional expression. In this observational study, we used computerized measures to analyze high-resolution time-series facial expression data as well as self-reports to examine the association between emotional flexibility and depressive symptoms at the client as well as at the session levels. Video recordings from 283 therapy sessions of 58 clients who underwent 16 sessions of manualized psychodynamic psychotherapy for depression were analyzed. Data was collected as part of routine practice in a university clinic that provides treatments to the community. Emotional flexibility was measured in each session using an automated facial expression emotion recognition system. The clients' depression level was assessed at the beginning of each session using the Beck Depression Inventory-II (Beck et al., 1996). Higher emotional flexibility was associated with lower depressive symptoms at the treatment as well as at the session levels. These findings highlight the centrality of emotional flexibility both as a trait-like as well as a state-like characteristic of depression. The results also demonstrate the usefulness of computerized measures to capture key emotional processes in the treatment of depression at a high scale and specificity.

P01.10.B EMOTION RECOGNITION IN PATIENTS WITH LOW-GRADE GLIOMA: THE RELATIONSHIP WITH TUMOR LOCATION AND TUMOR VOLUME

Abstract BACKGROUND Patients with low-grade gliomas (LGG), generally function well at the time of diagnosis and have a favourable prognosis. However, LGG can have impact on cognitive functioning of patients. To date, little is known about social cognition (SC) in patients with LGG. Social cognitive functions allow the processing of complex social information, with as important element the ability to recognize other people’s emotional expressions. Inaccurate recognition or misinterpretation of emotional facial expressions can lead to impairments in social functioning, which can have adverse effects on quality of life. Therefore, the aim of the present study was to investigate emotion recognition in patients with LGG and the relationship with tumor location and tumor volume. MATERIAL AND METHODS 125 patients with IDH mutated astrocytoma and oligodendroglioma grade 2 and 3, were matched with 169 healthy controls (HC). Tumor location and volume were evaluated pre-radiotherapy based on MRI scans. As a parameter for LGG volume the clinical radiotherapy target volume was used. SC was measured with a test for emotion recognition, i.e. the Facial Expressions of Emotion Stimuli and Tests (FEEST), after surgery. Descriptive statistics and between-group comparisons were performed. RESULTS On a group level, patients with LGG performed significantly lower on the FEEST total score compared to HC. Also, compared to norm data used in clinical practice, 32.8% of the patients showed an impaired performance. Larger LGG volume was significantly associated (p < 0.001) with poorer performance on emotion recognition. However, no direct association between LGG location (frontal, temporal, parietal) and emotion recognition was found. CONCLUSION In patients with LGG, impaired emotion recognition is often present before start of radiotherapy, and is related to larger LGG volume but not to location. Because of the relatively favourable prognosis of patients with LGG, maintaining quality of life is of high importance. Therefore, a thorough neuropsychological examination, including measurements for SC, is necessary to inform patients with LGG about possible changes in SC, and offer appropriate psychoeducation and care.

Modulation of emotion-enhanced recollection by gender and task instructions.

Previous work has shown recognition of emotional facial expressions may differentially relate to task demands, such as whether one indirectly or directly encodes the emotional information. Given gender differences in emotion processing and memory, we assessed whether participant gender might moderate these encoding task effects. Using a between-subjects design with a sample of 100 undergraduates, participants made judgments about the gender (indirect) or emotion (direct) of facial stimuli displaying fearful, angry, happy, and neutral expressions. Different task-related effects were observed by gender for faces accompanied by recollection, as measured with the Remember-Know paradigm. Namely, women demonstrated better memory discrimination for emotional facial expressions only for remember responses following indirect encoding, whereas this effect was not significant for men. These results highlight the importance of considering participant gender, type of encoding task, and level of recollection on emotional memory for faces. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Recognition of Facial and Vocal Emotional Expressions by SOAR Model

Recognition of Facial and Vocal Emotional Expressions by SOAR Model

Facial trustworthiness dampens own-gender bias in emotion recognition

Previous research suggests that emotion recognition is influenced by social categories derived by invariant facial features such as gender and inferences of trustworthiness from facial appearance. The current study sought to replicate and extend these findings by examining the intersection of these social categories on recognition of emotional facial expressions. We used a dynamic emotion recognition task to assess accuracy and response times in the happiness and anger categorization displayed by female and male faces that differed in the degree of facial trustworthiness (i.e., trustworthy- vs. untrustworthy-looking faces). We found that facial trustworthiness was able to modulate the own-gender bias on emotion recognition, as responses to untrustworthy-looking faces revealed a bias towards ingroup members. Conversely, when faces look trustworthy, no differences on emotion recognition between female and male faces were found. In addition, positive inferences of trustworthiness lead to faster recognition of happiness in females and anger in males, showing that facial appearance was able to influence also the intersection between social categories and specific emotional expressions. Together, these results suggest that facial appearance, probably due to the activation of approach or avoidance motivational systems, is able to modulate the own-gender bias on emotion recognition.

Matters of development and experience: Evaluation of dog and human emotional expressions by children and adults.

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.

Emotion recognition and mood along the menstrual cycle

Previous studies have demonstrated menstrual cycle dependent changes in the recognition of facial emotional expressions, specifically the expression of fear, anger, sadness or disgust. While some studies demonstrate an improvement of emotion recognition performance during the peri-ovulatory phase, when estradiol levels peak, other studies demonstrate a deterioration of emotion recognition performance during the mid-luteal phase, when progesterone levels peak. It has been hypothesized, that these changes in emotion recognition performance mirror mood changes along the menstrual cycle. In the present study, we investigate, whether changes in emotion recognition performance along the menstrual cycle are mediated by mood changes along the menstrual cycle. In a combined cross-sectional and longitudinal study design, two large samples of women completed an emotion recognition task, as well as several mood questionnaires during their menses, peri-ovulatory or mid-luteal cycle phase. 65 women completed the task thrice, once during each cycle phase, order counterbalanced. In order to control for potential learning effects, a sample of 153 women completed the task only once in one of the three cycle phases. In both samples, results demonstrated no significant changes in emotion recognition performance along the menstrual cycle, irrespective of the performance measure investigated (accuracy, reaction time, frequency of emotion classifications) and irrespective of the emotion displayed. Bayesian statistics provided very strong evidence for the null hypothesis, that emotion recognition does not change along the menstrual cycle. There was also no moderation of emotion recognition changes along the menstrual cycle by mood changes along the menstrual cycle. Mood changes along the menstrual cycle followed the expected pattern with highest positive affect and least premenstrual symptoms around ovulation and lowest positive affect, but strongest premenstrual symptoms during menses. Interestingly, premenstrual symptoms were negatively related to estradiol, suggesting a protective effect of estrogen during the luteal cycle phase against mood worsening during the premenstrual phase.

Interactive Effects of Ayahuasca and Cannabidiol in Social Cognition in Healthy Volunteers: A Pilot, Proof-of-Concept, Feasibility, Randomized-Controlled Trial.

Serotonergic hallucinogens and cannabinoids may alter the recognition of emotions in facial expressions (REFE). Cannabidiol (CBD) attenuates the psychoactive effects of the cannabinoid-1 agonist tetrahydrocannabinol. Ayahuasca is a dimethyltryptamine-containing hallucinogenic decoction. It is unknown if CBD may moderate and attenuate the effects of ayahuasca on REFE. Seventeen healthy volunteers participated in a 1-week preliminary parallel-arm, randomized controlled trial for 18 months. Volunteers received a placebo or 600 mg of oral CBD followed by oral ayahuasca (1 mL/kg) 90 minutes later. Primary outcomes included REFE and empathy tasks (coprimary outcome). Tasks were performed at baseline and 6.5 hours, 1 and 7 days after the interventions. Secondary outcome measures included subjective effects, tolerability, and biochemical assessments. Significant reductions (all P values <0.05) only in reaction times were observed in the 2 tasks in both groups, without between-group differences. Furthermore, significant reductions in anxiety, sedation, cognitive deterioration, and discomfort were observed in both groups, without between-group differences. Ayahuasca, with or without CBD, was well tolerated, producing mainly nausea and gastrointestinal discomfort. No clinically significant effects were observed on cardiovascular measurements and liver enzymes. There was no evidence of interactive effects between ayahuasca and CBD. The safety of separate and concomitant drug intake suggests that both drugs could be applied to clinical populations with anxiety disorders and in further trials with larger samples to confirm findings.

Ostracism modulates children's recognition of emotional facial expressions.

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.