Emotion Discrimination Research Articles

Attentional modulation as a mechanism for enhanced facial emotion discrimination: The case of action video game players

Action video game players (AVGPs) outperform nonvideo game players (NVGPs) on a wide variety of attentional tasks, mediating benefits to perceptual and cognitive decision processes. A key issue in the literature is the extent to which such benefits transfer beyond cognition. Using steady-state visual evoked potentials (SSVEP) as a neural measure of attentional resource allocation, we investigated whether the attentional benefit of AVGPs generalizes to the processing of rapidly presented facial emotions. AVGPs (n = 36) and NVGPs (n = 32) performed a novel, attention-demanding emotion discrimination task, requiring the identification of a target emotion in one of two laterally presented streams of emotional faces. The emotional faces flickered at either 2.0 Hz or 2.5 Hz. AVGPs outperformed NVGPs at detecting the target emotions regardless of the type of emotion. Correspondingly, attentional modulation of the SSVEP at parieto-occipital recording sites was larger in AVGPs compared with NVGPs. This difference appeared to be driven by a larger response to attended information, as opposed to a reduced response to irrelevant distractor information. Exploratory analyses confirmed that this novel paradigm elicited the expected pattern of event-related potentials associated with target detection and error processing. These components did not, however, differ between groups. Overall, the results indicate enhanced discrimination of facial emotions in AVGPs arising from enhanced attentional processing of emotional information. This presents evidence for the attentional advantage of AVGPs to extend beyond perceptual and cognitive processes.

The Sound of Emotion: Pinpointing Emotional Voice Processing Via Frequency Tagging EEG.

Successfully engaging in social communication requires efficient processing of subtle socio-communicative cues. Voices convey a wealth of social information, such as gender, identity, and the emotional state of the speaker. We tested whether our brain can systematically and automatically differentiate and track a periodic stream of emotional utterances among a series of neutral vocal utterances. We recorded frequency-tagged EEG responses of 20 neurotypical male adults while presenting streams of neutral utterances at a 4 Hz base rate, interleaved with emotional utterances every third stimulus, hence at a 1.333 Hz oddball frequency. Four emotions (happy, sad, angry, and fear) were presented as different conditions in different streams. To control the impact of low-level acoustic cues, we maximized variability among the stimuli and included a control condition with scrambled utterances. This scrambling preserves low-level acoustic characteristics but ensures that the emotional character is no longer recognizable. Results revealed significant oddball EEG responses for all conditions, indicating that every emotion category can be discriminated from the neutral stimuli, and every emotional oddball response was significantly higher than the response for the scrambled utterances. These findings demonstrate that emotion discrimination is fast, automatic, and is not merely driven by low-level perceptual features. Eventually, here, we present a new database for vocal emotion research with short emotional utterances (EVID) together with an innovative frequency-tagging EEG paradigm for implicit vocal emotion discrimination.

Development and validation of the first adaptive test of emotion perception in music

ABSTRACT The Musical Emotion Discrimination Task (MEDT) is a short, non-adaptive test of the ability to discriminate emotions in music. Test-takers hear two performances of the same melody, both played by the same performer but each trying to communicate a different basic emotion, and are asked to determine which one is “happier”, for example. The goal of the current study was to construct a new version of the MEDT using a larger set of shorter, more diverse music clips and an adaptive framework to expand the ability range for which the test can deliver measurements. The first study analysed responses from a large sample of participants (N = 624) to determine how musical features contributed to item difficulty, which resulted in a quantitative model of musical emotion discrimination ability rooted in Item Response Theory (IRT). This model informed the construction of the adaptive MEDT. A second study contributed preliminary evidence for the validity and reliability of the adaptive MEDT, and demonstrated that the new version of the test is suitable for a wider range of abilities. This paper therefore presents the first adaptive musical emotion discrimination test, a new resource for investigating emotion processing which is freely available for research use.

Predictive Effect of Social Cognitive Skills on Social Anxiety

The main purpose of this study is to examine the relationship between social anxiety and social cognition skills (emotion identification/discrimination, theory of mind, attribution bias, social functioning) and to investigate the predictive power of social cognition skills on social anxiety. In the study, it was also investigated whether social anxiety, social cognition skills and depression scores differed according to gender, age, reported diagnosis status and anxiety level. The sample of the study consisted of a total of 385 participants between the ages of 18-60. The research data were collected from the participants online using the Liebowitz Social Anxiety Scale, the Facial Emotion Identification and Facial Emotion Discrimination Tests, Reading the Mind in the Eyes Test, the Internal, Personal and Situational Attributes Scale, the Social Functioning Scale, the Beck Depression Inventory, and the Sociodemographic Information Form. It was determined that there was a negative relationship between social anxiety and emotion recognition, emotion discrimination and mind reading, and a positive relationship with externalization bias and depression. It was found that depression, emotion recognition and discrimination, mind reading, and antecedent social activities scale scores significantly predicted social anxiety. These variables explain 52% of the total variance related to social anxiety. In addition, when the depression effect was controlled, it was seen that social cognition skills explained 32% of the variance related to social anxiety. It was determined that the deterioration in social cognition skills and depression scores were associated with an increase in social anxiety. According to the results obtained from the research, suggestions were made to prevent social anxiety. It is suggested that it would be beneficial to include activities to develop social cognition skills, which are important for individuals' interpersonal communication, within intervention programs.

Neuropsychological performance facilitates emotion recognition in bipolar disorder

Aim of the studyIn bipolar disorder (BD), evidence for both cognitive impairment and deficit in emotion recognition has been found. Several investigations indicate that cognition and face processing can be interrelated. In this study, we assessed the correlations between cognitive functioning and emotion recognition (face expression) in patients with BD during an acute manic and depressive episode as well as in remission using a large battery of neurocognitive tests.Subject or material and methodsTwenty-four manic subjects, 21 with bipolar depression, and 22 euthymics, age-, sex-, and education-matched were included. Cognitive functions were assessed by the Wisconsin Card Sorting Test (WCST), Trail Making Test (TMT, Stroop Color-Word Interference Test (SCWT), California Verbal Learning Test (CVLT), Benton Visual Memory Test (BVRT), Rey-Osterreich Complex Figure Test (ROFT), d2 test and Verbal Fluency Test (VFT). For emotion recognition, the Penn Emotion Recognition Test and Penn Emotion Discrimination Test were employed.ResultsIn mania, performances on selected measures of the WCST, TMT, SCWT, CVLT, ROFT, d2 test, and VFT, achieved 19 positive correlations with better recognition of happiness. In depression, conducting these tests obtained 20 correlations with finer recognition of sadness. In remission, such performances acquired 18 correlations with greater identification of sadness (10 replicated those obtained in depression).DiscussionBetter emotion recognition in manic patients concerns mostly happiness, while in depression and remission, mainly sadness.ConclusionsBetter neuropsychological performance can facilitate emotion recognition. We hypothesize that the identification of sadness could be considered a biological marker of mood disorders.

Dissecting social decision-making: A spotlight on oxytocinergic transmission.

Social decision-making requires the ability to balance both the interests of the self and the interests of others to survive in social environments. Empathy is essential to the regulation of this type of interaction, and it often sustains relevant prosocial behaviors such as altruism and helping behavior. In the last decade, our capacity to assess affective and empathy-like behaviors in rodents has expanded our understanding of the neurobiological substrates that underly social decision-making processes such as prosocial behaviors. Within this context, oxytocinergic transmission is profoundly implicated in modulating some of the major components of social decision-making. Thus, this review will present evidence of the association between oxytocin and empathy-like and prosocial behaviors in nonhuman animals. Then, we will dissect the involvement of oxytocinergic transmission-across different brain regions and pathways-in some of the key elements of social decision-making such as emotional discrimination, social recognition, emotional contagion, social dominance, and social memory. Evidence of the modulatory role of oxytocin on social decision-making has raised considerable interest in its clinical relevance, therefore we will also discuss the controversial findings on intranasal oxytocin administration.

The Impact of Deafness on the Use of Information During Facial Emotion Discrimination

The Impact of Deafness on the Use of Information During Facial Emotion Discrimination

Emotional Valence in the Eye Region Modulates the Attentional Blink in a Task-Dependent Manner: Evidence from Event-Related Potentials.

Although emotional expressions conveyed by the eye regions are processed efficiently, little is known regarding the relationship between emotional processing of isolated eye regions and temporal attention. In this study, we conducted three rapid serial visual presentation (RSVP) experiments with varying task demands (emotion discrimination, eye detection, eyes ignored) related to the first target (T1) to investigate how the perception of emotional valence in the eye region (T1: happy, neutral, fearful) impacts the identification of a second target (T2: neutral houses). Event-related potential (ERP) findings indicated that fearful stimuli reliably increased N170 amplitude regardless of the emotional relevance of task demands. The P3 component exhibited enhanced responses to happy and fearful stimuli in the emotion discrimination task and to happy eye regions in the eye detection task. Analysis of T2-related ERPs within the attentional blink period revealed that T2 houses preceded by fearful and happy stimuli elicited larger N2 and P3 amplitudes than those preceded by neutral stimuli only in the emotion discrimination task. Together, these findings indicate that attention to affective content conveyed by the eyes can not only amplify the perceptual analysis of emotional eye regions but also facilitate the processing of a subsequent target.

Emotional body postures affect inhibitory control only when task-relevant.

A classical theoretical frame to interpret motor reactions to emotional stimuli is that such stimuli, particularly those threat-related, are processed preferentially, i.e., they are capable of capturing and grabbing attention automatically. Research has recently challenged this view, showing that the task relevance of emotional stimuli is crucial to having a reliable behavioral effect. Such evidence indicated that emotional facial expressions do not automatically influence motor responses in healthy young adults, but they do so only when intrinsically pertinent to the ongoing subject's goals. Given the theoretical relevance of these findings, it is essential to assess their generalizability to different, socially relevant emotional stimuli such as emotional body postures. To address this issue, we compared the performance of 36 right-handed participants in two different versions of a Go/No-go task. In the Emotional Discrimination task, participants were required to withhold their responses at the display of emotional body postures (fearful or happy) and to move at the presentation of neutral postures. Differently, in the control task, the same images were shown, but participants had to respond according to the color of the actor/actress' t-shirt, disregarding the emotional content. Results showed that participants made more commission errors (instances in which they moved even though the No-go signal was presented) for happy than fearful body postures in the Emotional Discrimination task. However, this difference disappeared in the control task. Such evidence indicates that, like facial emotion, emotional body expressions do not influence motor control automatically, but only when they are task-relevant.

Social-Emotional and Behavioural Difficulties in Children with Neurodevelopmental Disorders: Emotion Perception in Daily Life and in a Formal Assessment Context

Children with neurodevelopmental disorders often have social-emotional and behavioural difficulties. The present study explored these difficulties in children (n = 50, aged 6–10 years) with autism spectrum disorder, attention-deficit/hyperactivity disorder and developmental language disorder. Parents, teachers and therapists evaluated children’s social-emotional and behavioural difficulties through a self-devised questionnaire and the Strengths and Difficulties Questionnaire. Additionally, the children, along with their typically developing age peers (n = 106), completed six emotion discrimination tasks. Analysis revealed some impaired emotion discrimination skills that were predictive for behavioural challenges in daily life and associated with the parent-reported existence of friends. Timely intervention in these children is needed, and it should also include emotion perception training.

Sensitivity to trustworthiness cues in own- and other-race faces: The role of spatial frequency information.

Research has shown that adults are better at processing faces of the most represented ethnic group in their social environment compared to faces from other ethnicities, and that they rely more on holistic/configural information for identity discrimination in own-race than other-race faces. Here, we applied a spatial filtering approach to the investigation of trustworthiness perception to explore whether the information on which trustworthiness judgments are based differs according to face race. European participants (N = 165) performed an online-delivered pairwise preference task in which they were asked to select the face they would trust more within pairs randomly selected from validated White and Asian broad spectrum, low-pass filter and high-pass filter trustworthiness continua. Results confirmed earlier demonstrations that trustworthiness perception generalizes across face ethnicity, but discrimination of trustworthiness intensity relied more heavily on the LSF content of the images for own-race faces compared to other-race faces. Results are discussed in light of previous work on emotion discrimination and the hypothesis of overlapping perceptual mechanisms subtending social perception of faces.

Network Media Public Opinion and Social Governance Supported by the Internet-of-Things Big Data

The purpose is to make for the traditional Network Public Opinion (NPO) analysis methods’ inadequacy in the era of big data and provide a sufficient decision-making basis for managers. Based on the Internet of Things (IoT) and big data, this work applies Natural Language Processing (NLP) to NPO analysis. Additionally, it takes the content of Microblog text format as the main collection target, constructs a big data collection tool, and establishes Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Deep Pyramid Convolutional Neural Network (DPCNN) based on Tensorflow and other deep learning models. It is also improved in combination with the characteristics of the model, and a new model is proposed. Finally, the performance of various models is compared and analyzed through experiments, and the path is proposed for the government to use big data to improve the ability to govern NPO and help social governance. The results show that the improved LSTM model can correctly classify the extracted Microblog text’s emotion by as much as 80.00%. It improves the classification accuracy by nearly two percentage points under the ideal condition. Thus, by adding residual connection and attention mechanism, the model can extract the emotional features in the text better and improve the emotional discrimination ability. The public opinion of online media without effective control will have great security risks to social governance under the big data and IoT. The proposed method is of great help in analyzing NPO through the accurate analysis of Microblog text.

The emotions effect on a virtual characters design–A student perspective analysis

Interaction between people and virtual characters through digital and electronic devices is a reality. In this context, the design of virtual characters must incorporate emotional expression at a nonverbal level looking for effective communication with the user. This exploratory study investigates the design features of an avatar functioning as a virtual assistant in educational contexts. From a multidisciplinary approach, the user's research was elaborated by a semi-open questionnaire of self-perception of emotional characteristics: likeability, attractiveness, and applicability of a set of six 2D and 3D characters. The results extracted from a sample of 69 university students provide a relevant information on design features and open new lines for future research. Aspects such as Ekman's basic emotion discrimination and the design of facial expression are analyzed. The incorporation of other body parts, their spatial orientation and contextual elements, seems to contribute to effective emotional communication. The results also highlight how the design of a virtual character should take into consideration the complexity involved in facial gestures and changes in relation to the vertical axis and planes of movement. Finally, this article discusses the complexity involved in expressing a given emotion in a virtual character.

Progressively Discriminative Transfer Network for Cross-Corpus Speech Emotion Recognition

Cross-corpus speech emotion recognition (SER) is a challenging task, and its difficulty lies in the mismatch between the feature distributions of the training (source domain) and testing (target domain) data, leading to the performance degradation when the model deals with new domain data. Previous works explore utilizing domain adaptation (DA) to eliminate the domain shift between the source and target domains and have achieved the promising performance in SER. However, these methods mainly treat cross-corpus tasks simply as the DA problem, directly aligning the distributions across domains in a common feature space. In this case, excessively narrowing the domain distance will impair the emotion discrimination of speech features since it is difficult to maintain the completeness of the emotion space only by an emotion classifier. To overcome this issue, we propose a progressively discriminative transfer network (PDTN) for cross-corpus SER in this paper, which can enhance the emotion discrimination ability of speech features while eliminating the mismatch between the source and target corpora. In detail, we design two special losses in the feature layers of PDTN, i.e., emotion discriminant loss and distribution alignment loss . By incorporating prior knowledge of speech emotion into feature learning (i.e., high and low valence speech emotion features have their respective cluster centers), we integrate a valence-aware center loss and an emotion-aware center loss as the to guarantee the discriminative learning of speech emotions except an emotion classifier. Furthermore, a multi-layer distribution alignment loss is adopted to more precisely eliminate the discrepancy of feature distributions between the source and target domains. Finally, through the optimization of PDTN by combining three losses, i.e., cross-entropy loss , , and , we can gradually eliminate the domain mismatch between the source and target corpora while maintaining the emotion discrimination of speech features. Extensive experimental results of six cross-corpus tasks on three datasets, i.e., Emo-DB, eNTERFACE, and CASIA, reveal that our proposed PDTN outperforms the state-of-the-art methods.

Automated video analysis of emotion and dystonia in epileptic seizures

ObjectiveTo investigate the accuracy of deep learning methods applied to seizure video data, in discriminating individual semiologic features of dystonia and emotion in epileptic seizures. MethodsA dataset of epileptic seizure videos was used from patients explored with stereo-EEG for focal pharmacoresistant epilepsy. All patients had hyperkinetic (HKN) seizures according to ILAE definition. Presence or absence of (1) dystonia and (2) emotional features in each seizure was documented by an experienced clinician. A deep learning multi-stream model with appearance and skeletal keypoints, face and body information, using graph convolutional neural networks, was used to test discrimination of dystonia and emotion. Classification accuracy was assessed using a leave-one-subject-out analysis. ResultsWe studied 38 HKN seizure videos in 19 patients. By visual analysis based on ILAE criteria, 9/19 patients were considered to have dystonia and 9/19 patients were considered to have emotional signs. Two patients had both dystonia and emotional signs. Applying the deep learning multistream model, spatiotemporal features of facial appearance showed best accuracy for emotion detection (F1 score 0.84), while skeletal keypoint detection performed best for dystonia (F1 score 0.83). SignificanceHere, we investigated deep learning of video data for analyzing individual semiologic features of dystonia and emotion in hyperkinetic seizures. Automated classification of individual semiologic features is possible and merits further study.

Research on the Construction of Emergency Network Public Opinion Emotional Dictionary Based on Emotional Feature Extraction Algorithm.

How to strengthen emergency management and improve the ability to prevent and respond to emergencies is an important part of building a harmonious socialist society. This paper proposes a domain emotion dictionary construction method for network public opinion analysis of public emergencies. Using the advantages of corpus and semantic knowledge base, this paper extracts the seed words based on the large-scale network public opinion corpus and combined with the existing emotion dictionary, trains the word vector through the word2vec model in deep learning, expands the emotion words, and obtains the candidate emotion words according to the semantic similarity calculation, So as to generate a domain emotion dictionary. The accuracy rate of emotion discrimination by the emotion dictionary constructed in this paper is 0.86, the recall rate is 0.92. Through the verification of accuracy and recall rate, the construction method proposed in this paper has good accuracy and reliability. Because of the great differences in different experiences and situations of different groups, there will be great differences in views and perspectives on the same event. The key to prevent the public from blindly following the crowd should be to reach groups close to emotional distance, and targeted prevention and control of public opinion can be conducted according to different characteristics of different groups.

The McNorm library: creating and validating a new library of emotionally expressive whole body dance movements

The ability to exchange affective cues with others plays a key role in our ability to create and maintain meaningful social relationships. We express our emotions through a variety of socially salient cues, including facial expressions, the voice, and body movement. While significant advances have been made in our understanding of verbal and facial communication, to date, understanding of the role played by human body movement in our social interactions remains incomplete. To this end, here we describe the creation and validation of a new set of emotionally expressive whole-body dance movement stimuli, named the Motion Capture Norming (McNorm) Library, which was designed to reconcile a number of limitations associated with previous movement stimuli. This library comprises a series of point-light representations of a dancer’s movements, which were performed to communicate to observers neutrality, happiness, sadness, anger, and fear. Based on results from two validation experiments, participants could reliably discriminate the intended emotion expressed in the clips in this stimulus set, with accuracy rates up to 60% (chance = 20%). We further explored the impact of dance experience and trait empathy on emotion recognition and found that neither significantly impacted emotion discrimination. As all materials for presenting and analysing this movement library are openly available, we hope this resource will aid other researchers in further exploration of affective communication expressed by human bodily movement.

The Relationship between Crawling and Emotion Discrimination in 9- to 10-Month-Old Infants.

The present study examined whether infants’ crawling experience is related to their sensitivity to fearful emotional expressions. Twenty-nine 9- to 10-month-old infants were tested in a preferential looking task, in which they were presented with different pairs of animated faces on a screen displaying a 100% happy facial expression and morphed facial expressions containing varying degrees of fear and happiness. Regardless of their crawling experiences, all infants looked longer at more fearful faces. Additionally, infants with at least 6 weeks of crawling experience needed lower levels of fearfulness in the morphs in order to detect a change from a happy to a fearful face compared to those with less crawling experience. Thus, the crawling experience seems to increase infants’ sensitivity to fearfulness in faces.

Worry Modifies the Relationship between Locus Coeruleus Activity and Emotional Mnemonic Discrimination.

Background: The locus coeruleus (LC) plays a critical role in modulating emotional memory performance via widespread connections to the medial temporal lobe (MTL). Interestingly, both the LC and MTL are affected during aging. Therefore, we aimed to investigate whether worry during cognitive aging changes the relationship between memory performance and the neural activity patterns during an emotional memory task. Methods: Twenty-eight participants aged 60–83 years from the Maastricht Aging study conducted an emotional mnemonic discrimination task during a 7T fMRI-scan. We performed a robust multiple linear regression to examine the association between worry and mnemonic memory performance under different levels of arousal. Subsequently, we examined if worry modifies the relationship between neuronal activity and mnemonic memory performance. Results: We observed that under low arousal, only participants with low compared to high levels of worry benefitted from additional LC activity. Under high arousal, additional LC activity was associated with lower mnemonic memory performance. Conclusion: Our results suggest there might be an optimal involvement of the NA-system for optimal memory discrimination performance, as we observed that under low levels of worry and with lower levels of arousal, higher LC activity might be needed to achieve similar levels of optimal memory performance as achieved under higher arousal when LC activity remained lower.

Sex differences in automatic emotion regulation in adolescents with autism spectrum disorder.

Autism may be underdiagnosed in females because their social difficulties are often less noticeable. This study explored sex differences in automatic facial emotion processing in 45 adolescents with autism spectrum disorder (22 female, 23 male), age 10-16 years, performing active target detection task and Go/NoGo tasks where faces with positive and negative emotional expressions served as irrelevant distractors. The combined sample demonstrated more accurate performance on the target detection (response initiation) than the Go/NoGo task (response inhibition), replicating findings previously reported in typical participants. Females exhibited greater difficulty than males with response initiation in the target detection task, especially in the context of angry faces, while males found withholding a response in the Go/NoGo block with happy faces more challenging. Electrophysiological data revealed no sex differences or emotion discrimination effects during the early perceptual processing of faces indexed by the occipitotemporal N170. Autistic males demonstrated increased frontal N2 and parietal P3 amplitudes compared to females, suggesting greater neural resource allocation to automatic emotion regulation processes. The associations between standardized behavioral measures (autism severity, theory of mind skills) and brain responses also varied by sex: more adaptive social functioning was related to the speed of perceptual processing (N170 latency) in females and the extent of deliberate attention allocation (P3 amplitudes) in males. Together, these findings suggest that males and females with autism may rely on different strategies for social functioning and highlight the importance of considering sex differences in autism. LAY SUMMARY: Females with autism may exhibit less noticeable social difficulties than males. This study demonstrates that autistic females are more successful than males at inhibiting behavioral responses in emotional contexts, while males are more likely to initiate a response. At the neural level, social functioning in females is related to the speed of automatic perceptual processing of facial cues, and in males, to the extent of active attention allocation to the stimuli. These findings highlight the importance of considering sex differences in autism diagnosis and treatment selection.