Differences In Emotion Recognition Research Articles

Genetic algorithms reveal identity independent representation of emotional expressions.

People readily and automatically process facial emotion and identity, and it has been reported that these cues are processed both dependently and independently. However, this question of identity independent encoding of emotions has only been examined using posed, often exaggerated expressions of emotion, that do not account for the substantial individual differences in emotion recognition. In this study, we ask whether people's unique beliefs of how emotions should be reflected in facial expressions depend on the identity of the face. To do this, we employed a genetic algorithm where participants created facial expressions to represent different emotions. Participants generated facial expressions of anger, fear, happiness, and sadness, on two different identities. Facial features were controlled by manipulating a set of weights, allowing us to probe the exact positions of faces in high-dimensional expression space. We found that participants created facial expressions belonging to each identity in a similar space that was unique to the participant, for angry, fearful, and happy expressions, but not sad. However, using a machine learning algorithm that examined the positions of faces in expression space, we also found systematic differences between the two identities' expressions across participants. This suggests that participants' beliefs of how an emotion should be reflected in a facial expression are unique to them and identity independent, although there are also some systematic differences in the facial expressions between two identities that are common across all individuals. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Emotional Context Effects on the Rating of Ambiguous Facial Expressions in Depression and Schizophrenia Spectrum Disorders

Objective To investigate the influence of visual contextual information on emotion recognition of ambiguous facial expressions in depression and schizophrenia spectrum disorders. Method: Ambiguous facial expressions and emotional contexts representing anger, disgust, fear, joy, sadness and surprise were validated in a pre-test with healthy independent raters. Afterwards, 20 healthy participants (8 women, 12 men; mean age 24.35 ± 2.85 years), 20 participants with schizophrenia spectrum disorders (9 women, 11 men; mean age 40.25 ± 11.68 years) and 19 participants with depression (11 women, 8 men; mean age 43.74 ± 12.65 years) rated the emotional content of nine different faces in seven different emotion-suggesting contexts. The proportions of context-congruent answers and differences between emotion ratings in each context were analysed using non-parametric Kruskal-Wallis and explorative, paired Wilcoxon tests. Correlational analyses explored the influence of clinical symptoms assessed by clinician-administered scales. Results: The overall proportion of context-congruent answers did not differ between participants with depression and schizophrenia spectrum disorders compared to healthy participants. Participants with schizophrenia spectrum disorders were more susceptible to anger-suggesting contexts and participants with depression were more susceptible to fear-suggesting contexts. Differences in emotion recognition were associated with the severity of depressive, but not psychotic, symptoms. Conclusion: Despite increased susceptibility to anger-suggesting cues in schizophrenia and to fear-suggesting cues in depression, visual contextual influence remains largely consistent with healthy participants. Preserved emotional responsiveness suggests an efficacy of emotion training but emphasizes the need for additional research focusing on other factors contributing to social interaction deficits.

Gender Differences in Facial Emotion Recognition Among Adolescents Depression with Non-Suicidal Self-Injury.

Despite the perception that healthy female are superior at emotional identification, it remains unclear whether gender-specific differences exist in adolescent depression and whether such specific differences in emotional recognition are associated with the most salient feature of adolescent depression---non-suicidal self-injury (NSSI). In this study, 1428 adolescents (1136 females and 292 males) with depression and NSSI were examined using the Facial Emotion Recognition Task, Patient Health Questionnaire-9 (PHQ-9), and Functional Assessment of Self-mutilation questionnaire (FASM). This study was grouped by gender. Data were analyzed using the descriptive statistics, independent sample t-test, chi-square test, non-parametric test (Mann-Whitney U-test), Spearman correlation and Multiple linear regression analysis. Depressed females reported a significantly greater frequency of self-injurious behaviour and more severe depressive symptoms than males. Face emotion recognition was also significantly more accurate in females and was positively correlated with levels of self-injury and depression, whereas no such correlations were found in males. Among depressed adolescents, face emotion recognition is better in females and is associated with self-injurious behaviour. This study found that the greater susceptibility to depression and NSSI among adolescent females may stem in part from superior recognition and sensitivity to the negative emotions of others.

Cultural differences in recognizing emotions of masked faces.

In the wake of the global pandemic, interacting with others while wearing masks has emerged as a global challenge. A growing body of literature has reported that face masks hinder emotion recognition in Western populations. Given that diagnostic facial features for recognizing specific emotions (e.g., happiness) differ between Western and Eastern cultures, there may be cultural differences in the effects of face masks on emotion recognition. Relying on the previous findings showing cultural differences in emotion recognition, we conducted a preregistered study where 203 American and 209 Japanese participants judged the emotional expressions of faces (happy, fearful, angry, sad, disgust, and neutral) with and without masks. The results showed cultural differences in emotion recognition of faces with and without masks. Specifically, face masks decreased the accuracy of happy emotion recognition in the Americans but not in the Japanese. The results suggest that the effect of wearing masks on emotion recognition depends on the types of emotions and culture and supports previous findings indicating cultural differences in the decoding strategy for facial expressions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A systematic literature review of emotion recognition using EEG signals

In this study, we conducted a systematic literature review of 107 primary studies conducted between 2017 and 2023 to discern trends in datasets, classifiers, and contributions to human emotion recognition using EEG signals. We identified DEAP (43%), SEED (29%), DREAMER (8%), and SEED-IV (5%) as the most commonly used EEG signal datasets. Deep learning techniques, especially transformer neural architecture search (TNAS), global-to-local feature aggregation network (GLFANet), attention-based convolutional transformer neural network (ACTNN) and efficient CNN-contrastive learning (ECNN-C), demonstrate superior performance across different datasets. Our comparative analysis of the validation scenarios revealed that subject-dependent validations outperformed subject-independent validations, highlighting the challenge of individual differences. This finding underscores the need for future research to address these individual differences in emotion recognition and enhance the generalizability of the models. The research contributions spanned seven categories: data augmentation, domain adaptation, channel selection, preprocessing, feature selection, classifiers, and feature extraction, with a major emphasis on feature extraction and classification (34%). This trend suggests a growing recognition of the importance of these contributions in the development of effective emotion-recognition systems. Our study contributes to the field by providing a comprehensive overview of recent trends, illuminating the performance of various classifiers, and highlighting key areas for future research on EEG-based emotion recognition. This work has significant implications for various applications, including mental health, human–computer interaction, and affective brain–computer interfaces.

How do native and non-native speakers recognize emotions in the instructor’s voice in educational videos? Exploring the first step of the cognitive-affective model of e-learning for international learners

The emotional stance of the instructor in an educational video can influence the learning process. For this reason, we checked the first link of the cognitive-affective model of e-learning, namely, whether learners can recognize emotions that an instructor expresses only with their voice. Since English is not the native language for many learners and most instructional videos are produced in English, we tested for possible differences in emotion recognition between native and non-native speakers. We focused on positive emotions typically conveyed in such videos — enthusiasm and calmness. Native and non-native English speakers watched 12 short video clips about wood as a building material spoken by an instructor in different emotional tones — five videos expressed enthusiasm, five calmness, one boredom and one frustration. Participants rated the extent to which they thought the narrator expressed a specific emotion, the valence and activation level of the narration and solved an English vocabulary test. Both native and non-native speakers recognized the correct emotions (except for frustration), demonstrating the power of voice prosody to convey emotion in a multimedia learning scenario. Native speakers rated the enthusiastic videos more positively than non-native speakers, indicating a subtle difference in the way the two groups perceive emotions expressed through voice.

Sex differences in emotion recognition: investigating the moderating effects of stimulus features

ABSTRACT Emotion recognition – a prerequisite for social interactions – varies among individuals. Sex differences have been proposed as a central source of individual differences, although the existing evidence is rather heterogeneous. In the current study (N = 426), we investigated the potential moderating effects of stimulus features, including modality, emotion specificity, and the sex of the encoder (referring to the sex of the actor) on the magnitude of sex differences in emotion recognition. Our findings replicated women’s overall better emotion recognition, particularly evident for negative expressions (fear and anger) compared to men. This outperformance was observed across all modalities, with the largest differences for audiovisually expressed emotions, while the sex of the encoder had no impact. Given our findings, future studies should consider these and other potential moderator variables to better estimate sex differences.

Exploring Emotion Recognition Patterns Among Iranian People Using CANTAB as an Approved Neuro-Psychological Assessment.

Emotion recognition is the main component of social cognition and has various patterns in different cultures and nationalities. The present study aimed to investigate emotion recognition patterns among Iranians using the Cambridge neuro-psychological test automated battery (CANTAB) as a valid neuropsychological test. In this descriptive-analytical study, 117 males and females (Mean±SD of age 32.1±6.4) were initially assessed by computerized intelligence and progressive matrices of RAVEN-2. Furthermore, the excitement recognition subtest taken from the Cambridge neuro-psychological test automated battery (CANTAB) was performed. The correct response of participants to each of the six basic emotions as well as the recognition time was used for analysis. The maximum correct response rate was 75.83% related to happy emotion. The correct responses for sadness, surprise, disgust, anger, and fear were 70%, 68.48%, 47.84%, 42.54%, and 38.26%, respectively. Moreover, the shortest recognition time was related to disgust at 322 ms, while sadness with a mean response time of 1800 ms and fear response time at 1529 ms indicated the longest recognition time. In addition, participants recognized happiness with a mean response time of 1264 ms better than other emotions; however, post-hoc t-test analyses showed that only the correct responses for sadness and surprised emotions did not differ significantly, (t(112)=-0.59, P=0.55, d=0.05). These results suggested that different emotions have various correct responses. However, sadness and surprise did not differ. The findings of this study could be beneficial for evaluating cognitive elements, as well as cognitive abilities and inabilities among the Iranian population. Moreover, the findings could be used for investigating social cognition in this population. Emotion recognition patterns among Iranians were investigated using a valid neuropsychological test.Iranians showed higher accuracy in recognizing happiness and lower accuracy in recognizing fear.Disgust was recognized with the shortest response time, while sadness and fear had the longest recognition time.The findings highlight cultural differences in emotion recognition and can aid in evaluating cognitive abilities and social cognition in the Iranian population.The study emphasizes the importance of considering cultural factors in assessing and understanding emotion recognition. Understanding how people recognize emotions is crucial for effective communication and building social connections. However, the ability to recognize emotions can vary across cultures. This study aimed to investigate how Iranians recognize emotions using a reliable test. The researchers assessed 117 Iranian adults, both males and females, using a computer-based test. Participants were asked to identify six basic emotions (happiness, sadness, anger, disgust, fear, and surprise) displayed on a screen. The researchers measured the participants' accuracy in identifying each emotion and the time it took them to recognize it. The findings revealed that Iranians were most accurate in recognizing happiness and least accurate in recognizing fear. They were better at identifying positive emotions like happiness and surprise compared to negative emotions like disgust and anger. Participants took the least time to recognize disgust and the longest time to recognize sadness and fear. These results show that Iranians have specific patterns in recognizing emotions, which can be influenced by cultural factors. Understanding these patterns is important for assessing cognitive abilities and social cognition in the Iranian population. Moreover, these findings have broader implications. They highlight the need to consider cultural differences in emotion recognition, as it can impact communication and social interactions. The study's outcomes can be valuable for various applications. For instance, they can aid in developing tests to assess emotion recognition difficulties in individuals with conditions such as autism or schizophrenia. Furthermore, these findings can be useful for professionals, such as employees in customer service or mental health providers, who need to accurately interpret others' emotions. By shedding light on cultural variations in emotion recognition, this research contributes to our understanding of human emotions and their role in interpersonal relationships.

Does emotion recognition change across phases of the ovulatory cycle?

Recognizing emotions is an essential ability for successful interpersonal interaction. Prior research indicates some links between the endocrine system and emotion recognition ability, but only a few studies focused on within-subject differences across distinct ovulatory cycle phases and this ability. These studies have demonstrated mixed results that might be potentially due to heterogeneity in experimental tasks, methodologies, and lacking ecological validity. In the current study, we investigated associations between within-subject differences in ovarian hormones levels and emotion recognition from auditory, visual, and audiovisual modalities in N = 131 naturally cycling participants across the late follicular and mid-luteal phase of the ovulatory cycle. We applied a within-subject design with sessions in the late follicular and mid-luteal cycle phase, and also assessed salivary progesterone and estradiol in these sessions. Our findings did not reveal any significant difference in emotion recognition ability across two cycle phases. Thus, they emphasize the necessity of employing large-scale replication studies with well-established study designs along with proper statistical analyses. Moreover, our findings indicate that the potential link between ovulatory cycle phases (late follicular and mid-luteal) and emotion recognition ability might have been overestimated in previous studies, and may contribute to theoretical and practical implications of socio-cognitive neuroendocrinology.

Genetic algorithms reveal profound individual differences in emotion recognition

Emotional communication relies on a mutual understanding, between expresser and viewer, of facial configurations that broadcast specific emotions. However, we do not know whether people share a common understanding of how emotional states map onto facial expressions. This is because expressions exist in a high-dimensional space too large to explore in conventional experimental paradigms. Here, we address this by adapting genetic algorithms and combining them with photorealistic three-dimensional avatars to efficiently explore the high-dimensional expression space. A total of 336 people used these tools to generate facial expressions that represent happiness, fear, sadness, and anger. We found substantial variability in the expressions generated via our procedure, suggesting that different people associate different facial expressions to the same emotional state. We then examined whether variability in the facial expressions created could account for differences in performance on standard emotion recognition tasks by asking people to categorize different test expressions. We found that emotion categorization performance was explained by the extent to which test expressions matched the expressions generated by each individual. Our findings reveal the breadth of variability in people's representations of facial emotions, even among typical adult populations. This has profound implications for the interpretation of responses to emotional stimuli, which may reflect individual differences in the emotional category people attribute to a particular facial expression, rather than differences in the brain mechanisms that produce emotional responses.

Exploring Sex Differences in Key Frequency Bands and Channel Connections for EEG-based Emotion Recognition.

Previous studies have demonstrated the existence of sex differences in emotion recognition by comparing the performance of same-sex and cross-sex training strategies. However, the EEG properties behind the sex differences have not been fully explored. To fill this research gap, we aim to investigate the sex differences in key frequency bands and channel connections of EEG signals. The single-modality attentive simple graph convolutional network (ASGC) is applied to three datasets SEED, SEED-IV and SEED-V under subject-dependence conditions. The classification rates are 90.86 ±4.84%, 83.14 ± 8.84% and 78.33±7.83%, respectively. The adjacency matrices learned by ASGC indicate that females and males have similar channel-connection patterns, but the degree of importance of channel connections varies by sex. Additionally, by comparing the classification results of 5 frequency bands, we find that males and females represent similar frequency band characteristics, i.e., high-frequency bands achieve better performance, indicating that these frequency bands are more related to emotion processing. Finally, we conduct the cross-subject experiment using ASGC and find that the same-sex strategy outperforms the cross-sex strategy, which is consistent with previous studies. The results also imply that males may be more suitable for sex generalization. However, this finding needs the support of more samples and advanced algorithms.

The Recognition of Facial Expressions Under Surgical Masks: The Primacy of Anger

BackgroundThe need to wear surgical masks in everyday life has drawn the attention of psychologists to the negative effects of face covering on social processing. A recent but not homogeneous literature has highlighted large costs in the ability to recognize emotions.MethodsHere it was investigated how mask covering impaired the recognition of facial mimicry in a large group of 220 undergraduate students. Sex differences in emotion recognition were also analyzed in two subgroups of 94 age-matched participants. Subjects were presented with 112 pictures displaying the faces of eight actors (4 women and 4 men) wearing or not wearing real facemasks, and expressing seven emotional states (neutrality, surprise, happiness, sadness, disgust, anger and fear). The task consisted in categorizing facial expressions while indicating the emotion recognizability with a 3-point Likert scale. Scores underwent repeated measures ANOVAs.ResultsOverall, face masking reduced emotion recognition by 31%. All emotions were affected by mask covering except for anger. Face covering was most detrimental to sadness and disgust, both relying on mouth and nose expressiveness. Women showed a better performance for subtle expressions such as surprise and sadness, both in masked and natural conditions, and men for fear recognition (in natural but especially masked conditions).ConclusionAnger display was unaffected by masking, also because corrugated forehead and frowning eyebrows were clearly exposed. Overall, facial masking seems to polarize non-verbal communication toward the happiness/anger dimension, while minimizing emotions that stimulate an empathic response in the observer.

Social Inference from Middle to Older Adulthood.

Inferring the emotional state or the true meaning of another person's utterance is a key aspect of social cognition and critical for successful social interactions. In this study, we assess age-related differences in emotion recognition and sincere and sarcastic social exchanges in the context of cognitive and demographic factors. One hundred and eighty-seven adults ranging from middle to older adulthood completed the Mini-SEA Emotion Recognition test and Part B of The Awareness of Social Inference Test - Short Form (TASIT-S). Fluid intelligence and executive abilities were also assessed. Sex differences and the relationship with education level were also investigated. Regression models were used to assess age-related differences controlling for baseline cognitive and demographic factors. Age was negatively associated with accuracy for inferring sincere social exchanges. No differences were identified for accuracy for inferring sarcastic exchanges. Likewise, no age differences were identified for emotion recognition (Mini-SEA). Fluid intelligence was associated with accuracy for inferring sincere exchanges, but this was independent of age-related effects. A female advantage was identified for emotion recognition. Age is associated with difficulty in inferring sincere exchanges, which is not explained by fluid intelligence, verbal abstract reasoning, or auditory verbal attention. A female advantage in emotion recognition is consistent with findings reported in younger adults. Both age and sex should be considered in clinical assessments using the Mini-SEA and the TASIT-S.

Do women with Premenstrual Dysphonic Disorder experience differences in emotion recognition during the menstrual cycle?

IntroductionThe relationship between behavioral changes and the menstrual cycle in women at a reproductive age has been investigated in several studies; women during every menstrual cycle experience noticeable changes in levels of sex hormones which are consequently reflected on their mood and behavior. The relationship between the menstrual cycle and the emotion recognition processing has been also studied.ObjectivesThe aim of this study was to examine if differences exist between women with Premenstrual Dysphonic Disorder (PMDD) and women without PMDD in Emotion recognition processing across menstrual cycle.MethodsWe examined 26 women with a PMDD and 30 women without PMDD, who have both visited the Mental Health Centre (aged 18-35 y.o., right handed, educational level >9 y., regular cycle duration). Women were clinically interviewed (DSM-V); also the Emotion Recognition Task (ERT) was administered in the luteal and the follicular phase.ResultsWomen with PMDD showed significant differences in emotion recognition depending on the the luteal and the follicular phase (according to estradiol and progesterone level) whereas women without PMDD did not present significantly different responses to the emotional stimuli.ConclusionsOur findings suggest that there is an effect of PMDD on emotional facial recognition across the two phases of the menstrual cycle. Thus, the importance of incorporating ERT in the formal clinical examination of PMDD is highlighted.DisclosureNo significant relationships.

Is Emotion recognition processing across menstrual cycle and a history of Postpartum Depression potential risk factors for Premenstrual Dysphonic Disorder?

IntroductionMany women during the different phases of the menstrual cycle experience significant emotional and cognitive changes; for some, these changes can affect their everyday living. Premenstrual Dysphonic Disorder (PMDD) is a health problem that affects up to 5% of women of childbearing age. The exact cause is unknown; still, hormonal changes throughout the menstrual cycle may play a role. Women with a family history of Postpartum Depression (PPD) may be at increased risk.ObjectivesThe purpose was to examine if Emotion recognition processing across menstrual cycle and a history of PPD are potential risk factors for PMDD.MethodsWe identified 34 women with a history of PPD and contacted their daughters to explain the purpose of our study. Of those meeting the criteria to participate, 38 volunteered (aged 18-30 y.o., right handed, educational level >9 y., regular cycle duration). The Emotion Recognition Task (ERT) was administered in the luteal and the follicular phase. Women found to present significant differences in emotion recognition depending on the estradiol and progesterone levels were clinically interviewed (DSM-V).ResultsOf the 16 women who have showed significant differences across the two phases of the menstrual cycle, 7 were diagnosed with PMDD (43,7%). Among the ones who have not presented differences (22), only 2 received a diagnosis of PMDD (9%).ConclusionsThis study shows that Emotion recognition processing across menstrual cycle and a history of PPD may predict which women could be at risk for PMDD, playing, therefore a key role in PMDD early diagnosis.DisclosureNo significant relationships.

Identifying similarities and differences in emotion recognition with EEG and eye movements among Chinese, German, and French People

Objective. Cultures have essential influences on emotions. However, most studies on cultural influences on emotions are in the areas of psychology and neuroscience, while the existing affective models are mostly built with data from the same culture. In this paper, we identify the similarities and differences among Chinese, German, and French individuals in emotion recognition with electroencephalogram (EEG) and eye movements from an affective computing perspective. Approach. Three experimental settings were designed: intraculture subject dependent, intraculture subject independent, and cross-culture subject independent. EEG and eye movements are acquired simultaneously from Chinese, German, and French subjects while watching positive, neutral, and negative movie clips. The affective models for Chinese, German, and French subjects are constructed by using machine learning algorithms. A systematic analysis is performed from four aspects: affective model performance, neural patterns, complementary information from different modalities, and cross-cultural emotion recognition. Main results. From emotion recognition accuracies, we find that EEG and eye movements can adapt to Chinese, German, and French cultural diversities and that a cultural in-group advantage phenomenon does exist in emotion recognition with EEG. From the topomaps of EEG, we find that the γ and β bands exhibit decreasing activities for Chinese, while for German and French, θ and α bands exhibit increasing activities. From confusion matrices and attentional weights, we find that EEG and eye movements have complementary characteristics. From a cross-cultural emotion recognition perspective, we observe that German and French people share more similarities in topographical patterns and attentional weight distributions than Chinese people while the data from Chinese are a good fit for test data but not suitable for training data for the other two cultures. Significance. Our experimental results provide concrete evidence of the in-group advantage phenomenon, cultural influences on emotion recognition, and different neural patterns among Chinese, German, and French individuals.

Measuring emotion recognition: Added value in diagnosing dementia of the Alzheimer's disease type.

Neuropsychological tests, particularly for episodic memory, are used to classify patients in memory clinics. Still, the differential diagnosis between dementia of the Alzheimer’s disease type (Dementia‐AD), mild cognitive impairment (MCI), or major depressive disorder (MDD) is challenging. However, impairments in other domains, such as emotion recognition, an aspect of social cognition, might have additional value in distinguishing Dementia‐AD from MCI and MDD and hence signal progression of neurodegeneration. We evaluated this in patients visiting a memory clinic.Sixty healthy controls (HC) and 143 first time attendants of an academic hospital memory clinic who were eventually classified as Dementia‐AD (n = 45), MCI (n = 47), MDD (n = 27), or No Impairment (NI, n = 24) were included. We assessed group differences in Emotion Recognition (Ekman 60 Faces Test (EFT)) and episodic memory (Dutch Rey Auditory Verbal Learning Test (RAVLT)). With multinomial and binomial regression analysis, we assessed whether EFT was added to RAVLT in distinguishing patient groups.Dementia‐AD patients had significantly worse emotion recognition than HC, MCI, MDD, and NI groups, but no other between‐group differences were found. Episodic memory was impaired in Dementia‐AD and MCI patients. We found no memory impairments in the MDD and NI groups. Emotion recognition in addition to episodic memory was significantly better in predicting group membership than episodic memory alone.In conclusion, emotion recognition measurement had added value for differentiation between patients first visiting memory clinics, in particular in distinguishing Dementia‐AD from MCI. We recommend the standard inclusion of emotion recognition testing in neuropsychological assessment in memory clinics.

Does Music Training Improve Emotion Recognition Abilities? A Critical Review

There is widespread interest in the possibility that music training enhances nonmusical abilities. This possibility has been examined primarily for speech perception and domain-general abilities such as IQ. Although social and emotional processes are central to many musical activities, transfer from music training to socioemotional skills remains underexplored. Here we synthesize results from studies examining associations between music training and emotion recognition in voices and faces. Enhancements are typically observed for vocal emotions but not for faces, although most evidence is cross-sectional. These findings are discussed considering the design features of the studies. Future research could explore further the neurocognitive mechanisms underlying musician-related differences in emotion recognition, the role of predispositions, and the implications for broader aspects of socioemotional functioning.

Emotion Recognition of Facial Expressions Presented in Profile.

The literature on emotion recognition from facial expressions shows significant differences in recognition ability depending on the proposed stimulus. Indeed, affective information is not distributed uniformly in the face and recent studies showed the importance of the mouth and the eye regions for a correct recognition. However, previous studies used mainly facial expressions presented frontally and studies which used facial expressions in profile view used a between-subjects design or children faces as stimuli. The present research aims to investigate differences in emotion recognition between faces presented in frontal and in profile views by using a within subjects experimental design. The sample comprised 132 Italian university students (88 female, Mage = 24.27 years, SD = 5.89). Face stimuli displayed both frontally and in profile were selected from the KDEF set. Two emotion-specific recognition accuracy scores, viz., frontal and in profile, were computed from the average of correct responses for each emotional expression. In addition, viewing times and response times (RT) were registered. Frontally presented facial expressions of fear, anger, and sadness were significantly better recognized than facial expressions of the same emotions in profile while no differences were found in the recognition of the other emotions. Longer viewing times were also found when faces expressing fear and anger were presented in profile. In the present study, an impairment in recognition accuracy was observed only for those emotions which rely mostly on the eye regions.

Comparing symptoms and emotion recognition in African American and White samples with schizophrenia.

Racial status has an important role in schizophrenia, with African American samples being rated lower than White participants on a range of constructs. In many studies, however, demographic factors are not accounted for. In the present study, African American (n=106) and White participants (n=81) were compared on symptom severity and emotion recognition scales while controlling for other demographic factors. Contrary to our hypothesis, there were no differences in symptoms between racial groups. However, White participants performed better on an emotion recognition measure than African Americans. These differences were most prominent in response to negatively-valenced stimuli. This study replicated previous findings of racial differences in emotion recognition but not symptom severity. Future research should assess the role of racial identity on symptom severity. In addition, further research is needed to assess if utilising multi-ethnic stimuli improves performance by racial minorities on emotion recognition measures.