Recognition Of Anger Research Articles

Multimodal Dataset Construction and Validation for Driving-Related Anger: A Wearable Physiological Conduction and Vehicle Driving Data Approach

Anger impairs a driver’s control and risk assessment abilities, heightening traffic accident risks. Constructing a multimodal dataset during driving tasks is crucial for accurate anger recognition. This study developed a multimodal physiological -vehicle driving dataset (DPV-MFD) based on drivers’ self-reported anger during simulated driving tasks. In Experiment 1, responses from 624 participants to anger-inducing videos and driving scenarios were collected via questionnaires to select appropriate materials. In Experiments 2 and 3, multimodal dynamic data and self-reported SAM emotion ratings were collected during simulated and real-vehicle tasks, capturing physiological and vehicle responses in neutral and anger states. Spearman’s correlation coefficient analysis validated the DPV-MFD’s effectiveness and explored the relationships between multimodal data and emotional dimensions. The CNN-LSTM deep learning network was used to assess the emotion recognition performance of the DPV-MFD across different time windows, and its applicability in real-world driving scenarios was validated. Compared to using EEG data alone, integrating multimodal data significantly improved anger recognition accuracy, with accuracy and F1 scores rising by 4.49% and 9.14%, respectively. Additionally, real-vehicle data closely matched simulated data, confirming the dataset’s effectiveness for real-world applications. This research is pivotal for advancing emotion-aware human–machine- interaction and intelligent transportation systems.

Social Cognition in Parkinson's Disease after Focused Ultrasound Subthalamotomy: A Controlled Study.

Social cognition (SC) encompasses a set of cognitive functions that enable individuals to understand and respond appropriately to social interactions. Although focused ultrasound subthalamotomy (FUS-STN) effectively treats Parkinson's disease (PD) clinical motor features, its impact and safety on cognitive-behavioral interactions/interpersonal awareness are unknown. This study investigated the effects of unilateral FUS-STN on facial emotion recognition (FER) and affective and cognitive theory of mind (ToM) in PD patients from a randomized sham-controlled trial (NCT03454425). Subjects performed SC evaluation before and 4 months after the procedure while still under blind assessment conditions. The SC assessment included the Karolinska Directed Emotional Faces task for FER, the Reading the Mind in the Eyes (RME) test for affective ToM, and The Theory of Mind Picture Stories Task (ToM PST) (order, questions, and total score) for cognitive ToM. The active treatment group showed anecdotal-to-moderate evidence of no worsening in SC after FUS-STN. Anecdotal evidence for an improvement was recognized in the SC score changes, from baseline to post-treatment, for the active treatment group compared with sham for the RME, ToM PST order, ToM PST total, FER total, and recognition of fear, disgust, and anger. This study provides the first evidence that unilateral FUS-STN does not impair social cognitive abilities, indicating that it can be considered a safe treatment approach for this domain in PD patients. Furthermore, the results suggest FUS-STN may even lead to some improvement in social cognitive outcomes, which should be considered as a preliminary finding requiring further investigation with larger samples sizes. © 2024 International Parkinson and Movement Disorder Society.

Differential Social Cognitive Performance in Older Adults With Mild Cognitive Impairment and Dementia

To study general and subdomain performance in measures of social cognition in individuals with mild cognitive impairment (MCI), and dementia, and to explore associations between social cognitive and neuropsychological subdomains. Cross-sectional study of participants from the Sydney Memory and Ageing Study (MAS). Current data was collected in 2016-2018. Community-dwelling older adults (n=321) aged 80 years and above, with no history of neurological or psychiatric conditions. Participants had dementia, MCI, or no cognitive impairment (NCI). Social cognition was indexed using the Reading the Mind in the Eyes Test (RMET), the Interpersonal Reactivity Index - Perspective Taking (IRI-PT) and Empathic Concern (IRI-EC) subscales, and the Emotion Recognition Task (ERT). These subdomain scores were used to make a composite social cognition score. Apathy was measured via the Apathy Evaluation Scale (AES). Neurocognitive function was indexed using the Addenbrooke Cognitive Examination v3 (ACE-3). Dementia was associated with poorer overall social cognitive composite performance. MCI and dementia participants performed poorer on RMET and recognition of anger, disgust and happiness on ERT. RMET and ERT disgust remained significant after controlling for relevant covariates. Dementia participants performed poorer than MCI and NCI on the IRI-PT, IRI-EC, and AES. AES remained significant after regression. RMET was correlated with ACE-3 Fluency and/or Language in all study groups. MCI is associated with poorer scores in specific social cognitive assessments. Dementia is somewhat associated with poorer scores in informant-rated social cognition scales, though this is no longer significant after accounting for apathy.

Reading language of the eyes in female depression.

Aberrations in non-verbal social cognition have been reported to coincide with major depressive disorder. Yet little is known about the role of the eyes. To fill this gap, the present study explores whether and, if so, how reading language of the eyes is altered in depression. For this purpose, patients and person-by-person matched typically developing individuals were administered the Emotions in Masked Faces task and Reading the Mind in the Eyes Test, modified, both of which contained a comparable amount of visual information available. For achieving group homogeneity, we set a focus on females as major depressive disorder displays a gender-specific profile. The findings show that facial masks selectively affect inferring emotions: recognition of sadness and anger are more heavily compromised in major depressive disorder as compared with typically developing controls, whereas the recognition of fear, happiness, and neutral expressions remains unhindered. Disgust, the forgotten emotion of psychiatry, is the least recognizable emotion in both groups. On the Reading the Mind in the Eyes Test patients exhibit lower accuracy on positive expressions than their typically developing peers, but do not differ on negative items. In both depressive and typically developing individuals, the ability to recognize emotions behind a mask and performance on the Reading the Mind in the Eyes Test are linked to each other in processing speed, but not recognition accuracy. The outcome provides a blueprint for understanding the complexities of reading language of the eyes within and beyond the COVID-19 pandemic.

Decomposing the variance in early maladaptive schemas: the major role of one general factor, the minor role of domains, and their differential relations to facial emotion recognition.

Despite the growing interest in the early maladaptive schemas, the progress in understanding their impacts is decelerated by a lack of clear understanding of their structure. Different composite scores are calculated without a solid ground or a clarified meaning. Here we explain that the schema variance can be theoretically decomposed into three components: schema-specific, domain-specific due to the unmet core needs, and the common variance we call general susceptibility; each can differentially correlate with other substantive variables. Using this framework, we empirically examine the structure of schemas and their relationships to facial emotion recognition, a crucial ability that can widely affect our social interactions. A sample of adults completed an emotion recognition task and the Young Schema Questionnaire. Using different factor models, the specific and shared variance across schemas was analyzed. Then, the relation of these variance components to facial emotion recognition was explored. A general factor explained 27%, 40%, and 64% of the total variance in items, schemas, and domains, respectively. Partialling out the common variance, there was little domain-specific variance remained. Regarding facial emotion recognition, they were not correlated with specific schemas; however, the general susceptibility factor was correlated with anger recognition. The variance decomposition approach to schemas, which uses the bifactor model, may offer a clearer way to explore the impacts of schemas. While domain scores are widely used, their reliability, validity, and meaning are questionable. The generic factor, which is consistently extractable from empirical data, requires further attention.

Machiavellian behavior and social-emotional functioning in middle childhood and early adolescence.

Machiavellianism is an antisocial interpersonal style involving the use of manipulative, deceptive, and coercive behaviors in the pursuit of self-interest. Although widely studied as a "dark" personality trait in adults, relatively little is known about the developmental correlates of Machiavellian tendencies earlier in life. The present study addressed this knowledge gap by examining associations between Machiavellian behavior and three theoretically relevant social-emotional domains-prosocial emotions, emotion recognition skills, and self-control-in a community sample of 7- and 11-year-old Canadian children (N = 300, 50% female). Of particular interest was the extent to which individual differences in social-emotional capacities were uniquely associated with Machiavellian behavior after controlling for aggression, a relatively well-studied antisocial behavior in childhood. Parents reported on children's Machiavellian behavior and aggression. Social-emotional correlates were assessed via parent and child reports, behavioral tasks, and physiological assessments. Machiavellian behavior and aggression were similarly associated with lower parent-reported prosocial emotions and self-control. Machiavellian (but not aggressive) behavior was associated with lower child-reported guilt (a prosocial emotion), higher resting skin conductance levels (reflecting a general tendency for higher arousal), and better anger recognition. Semipartial correlational analyses indicated that these patterns of association with Machiavellian behaviors held independent of aggression. These findings indicate that, by middle childhood, Machiavellian behavior constitutes a distinct form of antisocial conduct that is associated with a unique social-emotional risk profile. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Facial emotion-recognition deficits in patients with schizophrenia and unaffected first-degree relatives.

This study aimed to determine trait- and state-dependent markers of schizophrenia by investigating facial emotion-recognition (FER) deficits in remitted patients with schizophrenia and their first-degree relatives (FR). Three groups were included: the Schizophrenia group (n=66), their unaffected FR group (n=40), and healthy controls (n=50) who were matched for age, sex, and years of education. A facial-labeling task was used to examine FER deficits using the following eight standardized expressions: happy, fearful, disgusted, angry, sad, contemptuous, surprised, and neutral. There was a poorer accuracy in the recognition of sadness and anger in the Schizophrenia group as well as in contempt in both the Schizophrenia and FR groups compared with healthy controls. The response times for the recognition of contempt, sadness, and neutral emotion were delayed in the Schizophrenia group and those for fear were delayed in the Schizophrenia and FR groups compared with healthy controls. Concerning the accuracy in FER, sadness and anger can be considered state-dependent markers of remitted schizophrenia, and contempt is a trait-dependent marker of schizophrenia. Similarly, for response times in FER, contempt, sadness, and neutral emotion can be considered state-dependent markers of remitted schizophrenia, while fear is considered a trait-dependent marker of schizophrenia. These findings may contribute to the early diagnosis of schizophrenia and the development of relevant therapeutic interventions.

Pregnancy enhances facial recognition of anger: Transition from early to late pregnancy

IntroductionPregnancy and the postpartum period involve several physiological adaptations crucial for offspring care. Recent research has highlighted reproduction-related brain plasticity in human mothers. Associations with aspects of maternal caregiving suggest adaptive changes that facilitate a woman’s transition to motherhood. However, the dynamic changes that affect a woman’s brain are not merely adaptive, and they likely confer a vulnerability for the mental disorders. To elucidate the pathophysiology of psychiatric problems that occur during the perinatal period, gaining insights into the physiological changes in brain function due to pregnancy is crucial.ObjectivesAlthough it has been hypothesized that pregnancy enhances social cognitive functions in mothers to adapt to the offspring care, there are few reports to support this hypothesis. This study aims to investigate whether social cognitive functions change during the first pregnancy, with a focus on maternal adaptation to offspring care.MethodsThe study included a first pregnancy group and a never-pregnant control group. We conducted a prospective study comparing pregnant women between two-time points (T1, T2); at less than 21 weeks of gestation [T1] and those after 30 weeks of gestation [T2]. To assess the effects of pregnancy and gestational age (< 21 weeks or 30 weeks or more), both the control (never-pregnant) group and pregnant group were evaluated at two time points with similar intervals. The Emotion Recognition Task [ERT] of the Cambridge Neuropsychological Test Automated Battery (CANTAB) was performed to examine the emotion recognition of six basic emotions in facial expressions. We analyzed a cohort of 26 participants in the pregnant group and 25 in the control group. We performed a two-way repeated measures analysis of variance with pregnancy status and gestational period (T1, T2) as independent variables.Results Significant interactions between group and time points (T1, T2) were observed only for Unbiased Hit Rate Anger (p<0.01); facial recognition accuracy for anger increased with the progression of pregnancy. There were no significant interactions for Unbiased Hit Rate Sadness, Happiness, Fear, Disgust, or Surprise.Conclusions This is the first study to demonstrate that facial recognition of anger enhances with the progression of pregnancy, utilizing never-pregnant women as a never-pregnant control group. The results of this study contribute to the physiological effects of pregnancy on the brain and cognitive function and have potential for further study of perinatal mental health problems.Disclosure of InterestNone Declared

The association between psychopathology, childhood trauma, and emotion processing.

Childhood trauma is highly prevalent and can have a negative impact on the development of socioemotional processes resulting in a higher vulnerability for mental disorders in adulthood. Previous studies have associated the severity of childhood trauma with deficits in social functioning, such as a negative attention bias, suggesting altered social information processing as a mechanism underlying the association between childhood trauma and transdiagnostic psychopathologies. In a cross-sectional setup with a total of 103 participants (26 with major depressive disorder, MDD; 24 with posttraumatic stress disorder, PTSD; 22 with somatic symptom disorder, SDD; and 31 healthy volunteers, HV), this study applied eye tracking in an emotion recognition paradigm. Reaction times, accuracy, and gaze behavior were analyzed for 4 different facial expressions as a function of self-reported childhood trauma and diagnosis. The aim was to investigate to what extent emotion processing is associated with (a) childhood trauma, (b) psychopathology, and (c) respective interacting effects. Patients showed higher reaction times and error rates overall in classifying emotions than HVs, especially for the recognition of anger and fear. Individuals with a diagnosis of PTSD and MDD were particularly slow in their response to these emotions. Higher scores of reported childhood trauma were associated with faster responses for classifying anger and fear and slower initiation of eye movements for SSD, MDD, and HVs for anger. These findings indicate that childhood trauma may contribute to attentional and information-processing biases relevant for social interaction. Identifying individual social deficits offers implications for tailored therapeutic interventions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Deficits in emotion recognition and processing in children with high callous-unemotional traits: the role of the MAOA gene.

Children with high Callous-Unemotional (CU) traits show deficits in recognizing and processing facial expressions. Alterations in emotion recognition have been linked to a higher synaptic concentration of monoaminergic neurotransmitters. The current study investigated the relationship between the MAOA-Low-activity alleles and the ability to recognize and process facial expressions in 97 male children (8-12years old) diagnosed with disruptive behavior disorder. Participants completed a computerized emotion-recognition task while an eye-tracking system recorded the number (Fixation Count, FC) and length (Fixation Duration, FD) of fixations to the eye region of the emotional stimuli. Children with high CU traits exhibited lower scores in recognition of sadness and anger, and lower FC and FD for sadness and fear than children with low CU traits. Children carrying the MAOA-Low-activity alleles displayed lower FD for sadness, and FD and FC for fear than those carrying the MAOA-High-activity alleles. These genetic effects appeared even stronger in children with CU traits. Moderation analysis revealed that CU traits were associated with lower FC and FD for fear, and lower FD for sadness, probably due to the MAOA-Low-activity alleles. Our findings, although to be replicated, suggest MAOA-Low-activity alleles as potential genetic biomarkers to identify CU children in need of training focused on emotion processing.

Inducing sad recognition bias: A novel emotional probabilistic reward task and its affective consequences.

Recognition of sadness from facial expressions is associated with empathic responses. In this study, we devised an emotional probabilistic reward task (PRT) to facilitate sadness recognition and tested its effects on attentional and empathic responses to others in distress. During the emotional PRT, healthy participants were asked to discriminate between facial expressions subtly expressing sadness or anger. Reward feedback for correct sadness and anger recognition was provided, with different probabilities between the training (70% vs. 30%) and control groups (50% vs. 50%). Subsequently, participants performed a visual dot-probe task involving facial expressions of sadness, anger, fear, and happiness. They also completed an empathy rating task while viewing short video clips depicting people experiencing distressing or neutral events. The results showed that the training group developed greater recognition bias for sadness than the control group. Within the training group, sad recognition bias was positively associated with subsequent attentional orienting to sad faces and empathic concern towards distressed others. These findings suggest that the emotional PRT holds promise for modifying cognitive and emotional processes that are associated with empathy for others.

Research on driver’s anger recognition method based on multimodal data fusion

Objectives This paper aims to address the challenge of low accuracy in single-modal driver anger recognition by introducing a multimodal driver anger recognition model. The primary objective is to develop a multimodal fusion recognition method for identifying driver anger, focusing on electrocardiographic (ECG) signals and driving behavior signals. Methods Emotion-inducing experiments were performed employing a driving simulator to capture both ECG signals and driving behavioral signals from drivers experiencing both angry and calm moods. An analysis of characteristic relationships and feature extraction was conducted on ECG signals and driving behavior signals related to driving anger. Seventeen effective feature indicators for recognizing driving anger were chosen to construct a dataset for driver anger. A binary classification model for recognizing driving anger was developed utilizing the Support Vector Machine (SVM) algorithm. Results Multimodal fusion demonstrated significant advantages over single-modal approaches in emotion recognition. The SVM-DS model using decision-level fusion had the highest accuracy of 84.75%. Compared with the driver anger emotion recognition model based on unimodal ECG features, unimodal driving behavior features, and multimodal feature layer fusion, the accuracy increased by 9.10%, 4.15%, and 0.8%, respectively. Conclusions The proposed multimodal recognition model, incorporating ECG and driving behavior signals, effectively identifies driving anger. The research results provide theoretical and technical support for the establishment of a driver anger system.

Negative Emotion Recognition Algorithm of Network Catchwords Based on Language Feature Dimension

The traditional negative emotion recognition algorithm has a limited language feature dimension, which leads to the inaccuracy of negative emotion recognition. In order to improve the identification and analysis of emotion in network buzzwords, the back propagation of error (BP) and the restricted Boltzmann machine (RBM) algorithms are adopted to effectively solve the problem of insufficient data for emotion analysis in different contexts. First, a method is proposed to identify negative emotions, and a deep neural network (DNN) model is constructed. Then, experiments were carried out, which used manually labeled data sets and divided them into different emotion categories, and which compared the BP algorithm, Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM) for negative emotion recognition of online buzzwords. The experimental results show that the DNN model performs well in the recognition of anger, sadness, fear and disgust, with the accuracy reaching 93.56%, 93.58%, 89.84% and 88.53% respectively, which is obviously superior to the other three methods. The designed DNN model has a potential application prospect in the negative emotion recognition of online buzzwords, which can be further popularized in the future.

An intelligent wearable embedded architecture for stress detection and psychological behavior monitoring using heart rate variability

This study quantifies individual stress levels through real-time analysis of wearable sensor data. An embedded setup utilizes artificial neural networks to analyze R-R intervals and Heart Rate Variability (HRV). Emotion recognition of happiness, sadness, surprise, fear, and anger is explored using seven normalized HRV features. Statistical analysis and classification with a neural network model are performed on approximately 20,700 segments,with participants within the age ranged from 23 to 40, mixed gender, and normal health status, along with other pertinent demographics included. Findings show stress observation’s potential for mental well-being and early detection of stress-related disorders. Three classification algorithms (LVQ, BPN, CART) are evaluated, comparing ECG signal correlation features with traditional ones. BPN achieves the highest emotional recognition accuracy, surpassing LVQ by 5.9% – 8.5% and CART by 2% – 6.5%. Maximum accuracy is 82.35% for LVQ and 97.77% for BPN, but does not exceed 95%. Using only 72 feature sets yields the highest accuracy, surpassing S1 by 17.9% – 20.5% and combined S1/S2 by 11% – 12.7%. ECG signal correlation features outperform traditional features, potentially increasing emotion recognition accuracy by 25%. This study contributes to stress quantification and emotion recognition, promoting mental well-being and early stress disorder detection. The proposed embedded setup and analysis framework offer real-time monitoring and assessment of stress levels, enhancing health and wellness.

Intervention study of visual communication design based on emotional interaction for emotional understanding in autism

BackgroundEmotional understanding deficit is one of the core symptoms in people with autism. In intervention studies of emotional understanding in people with autism, the visual communication design of emotional interactions can enable autistic people to better experience and understand the emotions of others and enhance their emotional comprehension ability.Subjects and Methods Three autistic children in a school in Shanghai were selected, and all three children were insensitive to identifying the emotions of others. The study used the single subject method in the variable passive design, with the visual communication design as the independent variable and the facial expression recognition ability as the dependent variable. In addition, round teaching for the subject intervention was used in this study.ResultsAfter 28 weeks of visual communication design based on emotional interaction, the three autistic children had different degrees of recognition of happiness, fear, anger, and sadness. The happy expressions in the image were learned by the three children first, followed by anger, and finally, two negative emotions: sadness and fear. This shows that visual design can improve the recognition ability of facial expressions by autism.ConclusionsThe visual communication design based on emotional interaction promotes the emotional comprehension ability of autism, making it easier for autistic children to understand and learn. This design also gives timely feedback to help autistic children understand and adjust their emotions. It can even migrate to psychological theory, social skills and other fields to improve the comprehensive development of autistic children.

Emotion Recognition in Multiple System Atrophy: An Exploratory Eye-Tracking Study.

Emotional processing is a core feature of social interactions and has been well studied in patients with idiopathic Parkinson's disease (PD), albeit with contradictory. . However, these studies excluded patients with atypical parkinsonism, such as multiple system atrophy (MSA). The objective of this exploratory study was to provide better insights into emotion processing in patients with MSA using eye tracking data. We included 21 MSA patients, 15 PD patients and 19 matched controls in this study. Participants performed a dynamic and a static emotion recognition task, and gaze fixations were analyzed in different areas of interest. Participants underwent neuropsychological testing and assessment of depression and alexithymia. MSA patients were less accurate in recognizing anger than controls (p = 0.02) and had overall fewer fixations than controls (p = 0.001). In the static task, MSA patients had fewer fixations (p < 0.001) and a longer time to first fixation (p = 0.026) on the eye region. Furthermore, MSA patients had a longer fixation duration overall than PD patients (p = 0.004) and longer fixations on the nose than controls (p = 0.005). Alexithymia scores were higher in MSA patients compared to controls (p = 0.038). This study demonstrated impaired recognition of anger in MSA patients compared to HCs. Fewer and later fixations on the eyes along with a center bias suggest avoidance of eye contact, which may be a characteristic gaze behavior in MSA patients.

Do masks cover more than just a face? A study on how facemasks affect the perception of emotional expressions according to their degree of intensity.

Emotional facial expressions convey crucial information in nonverbal communication and serve as a mediator in face-to-face relationships. Their recognition would rely on specific facial traits depending on the perceived emotion. During the COVID-19 pandemic, wearing a facemask has thus disrupted the human ability to read emotions from faces. Yet, these effects are usually assessed across studies from faces expressing stereotypical and exaggerated emotions, which is far removed from real-life conditions. The objective of the present study was to evaluate the impact of facemasks through an emotion categorization task using morphs ranging from a neutral face and an expressive face (anger, disgust, fear, happiness, and sadness) (from 0% neutral to 100% expressive in 20% steps). Our results revealed a strong impact of facemasks on the recognition of expressions of disgust, happiness, and sadness, resulting in a decrease in performance and an increase in misinterpretations, both for low and high levels of intensity. In contrast, the recognition of anger and fear, as well as neutral expression, was found to be less impacted by mask-wearing. Future studies should address this issue from a more ecological point of view with the aim of taking concrete adaptive measures in the context of daily interactions.

Facial expression recognition deficits in frontotemporal dementia and Alzheimer's disease: a meta-analytic investigation of effects of phenotypic variant, task modality, geographical region and symptomatic specificity.

Deficits in social cognition may be present in frontotemporal dementia (FTD) and Alzheimer's disease (AD). Here, we conduct a qualitative synthesis and meta-analysis of facial expression recognition studies in which we compare the deficits between both disorders. Furthermore, we investigate the specificity of the deficit regarding phenotypic variant, domain-specificity, emotion category, task modality, and geographical region. The results reveal that both FTD and AD are associated with facial expression recognition deficits, that this deficit is more pronounced in FTD compared to AD and that this applies for the behavioral as well as for language FTD-variants, with no difference between the latter two. In both disorders, overall emotion recognition was most frequently impaired, followed by recognition of anger in FTD and by fear in AD. Verbal categorization was the most frequently used task, although matching or intensity rating tasks may be more specific. Studies from Oceania revealed larger deficits. On the other hand, non-emotional control tasks were more impacted by AD than by FTD. The present findings sharpen the social cognitive phenotype of FTD and AD, and support the use of social cognition assessment in late-life neuropsychiatric disorders.

Do You See What I See? Emotion Recognition Competencies in Sexually Abused School-Aged Children and Non-Abused Children

ABSTRACT Child sexual abuse (CSA) is a worldwide phenomenon that has been linked to deleterious consequences. Adverse life events, such as sexual abuse, can compromise the development of emotional competencies, an important dimension of children’s psychosocial development. This study aimed at evaluating emotion recognition competencies in sexually abused and non-abused children. The sample consisted of 97 sexually abused children (65 girls) and 78 non-abused children (56 girls) aged between 6 and 12 years. They were recruited in specialized intervention centers and elementary schools from the Montreal area. Recognition of joy, anger, fear, sadness, and neutral expressions was assessed using the Developmental Emotional Faces Stimulus Set (DEFSS; Meuwissen et al., 2017). Results of an ANCOVA revealed that the total scores of emotion recognition were significantly lower for victims of SA (M = 18.12, SE = 0.33) relative to non-abused children (M = 19.36, SE = 0.37), F(1,170) = 5.70, p < .05. Analyses performed on specific expressions yielded lower scores for the recognition of anger, F(1, 170) = 6.12, p = .014, partial η2 = .03, and joy, F(1, 170) = 8.04, p =.005, partial η2 = .04. Our findings highlight the importance of assessing emotion recognition competencies to improve intervention programs provided to sexually abused children and prevent the development of severe psychosocial problems.

Ocular emotion discrimination disorders in self-limited epilepsy patients with centrotemporal spikes complicated with electrical status epilepticus during sleep: A pediatric neuropsychological study.

We investigated the characteristics and factors influencing eye emotion recognition in self-limited epilepsy patients with centrotemporal spikes (SeLECTS) complicated with electrical status epilepticus during sleep (ESES). We selected SeLECTS (n=160) patients treated in the outpatient and inpatient departments of Anhui Children's Hospital from September 2020 to January 2022. According to the video electroencephalogram monitoring slow-wave index (SWI), SeLECTS patients with SWI<50% were assigned into the typical SeLECTS group (n=79), and patients with SWI ≥ 50% were assigned into the ESES group (n=81). Patients in the two groups were assessed by The Eye Basic Emotion Discrimination Task (EBEDT) and The Eye Complex Emotion Discrimination Task (ECEDT), respectively. Comparisons were made with age-, sex- and education level-matched healthy control participants. The correlation between the characteristics of emotional discrimination disorder in the eye area and the clinical influencing factors was analyzed in ESES group, and p ≤ .050 was the threshold for significance. Relative to the healthy control group, scores of sadness and fear in the typical SeLECTS group were markedly lower (p=.018, p=.023), while differences in scores of disgust, happiness, surprise, and anger were not significantly different between the groups (p=.072, p=.162, p=.395, p=.380, respectively). Compared with the healthy control group, the ESES group had significantly low scores in recognition of sadness, fear, disgust, and surprise (p=.006, p=.016, p=.043 and p=.038, respectively). However, differences in recognition of happiness and anger between the groups were not significant (p=.665 and p=.272). Univariate logistic analysis showed that the score of eye recognition for sadness in the ESES group was affected by age of onset, SWI, ESES duration and number of seizures. The score of eye recognition for fear was mainly affected by SWI, while the score of eye recognition for disgust was affected by SWI and number of seizures. The surprised eye emotion recognition score was mainly affected by the number of seizures. Variables with p<.1 were considered to be independent variables of multivariable ordered logistic regression. Multivariate logistic analysis showed that sadness emotion recognition was mainly affected by SWI and ESES duration, while disgust was mainly affected by SWI. The typical SeLECTS group showed impaired emotion (sadness and fear) recognition function in the eye area. The ESES group was associated with more intense emotional (sadness, fear, disgust, and surprise) recognition impairment in the eye region. The higher the SWI, the younger the onset age and the longer the duration of ESES, while the more the number of seizures, the more serious the impairment of emotional recognition function in the affected eye area.