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The integration of emotional intelligence in machines is an important step in advancing human-computer interaction. This demands the development of reliable end-to-end emotion recognition systems. However, the scarcity of public affective datasets presents a challenge. In this literature review, we emphasize the use of generative models to address this issue in neurophysiological signals, particularly Electroencephalogram (EEG) and Functional Near-Infrared Spectroscopy (fNIRS). We provide a comprehensive analysis of different generative models used in the field, examining their input formulation, deployment strategies, and methodologies for evaluating the quality of synthesized data. This review serves as a comprehensive overview, offering insights into the advantages, challenges, and promising future directions in the application of generative models in emotion recognition systems. Through this review, we aim to facilitate the progression of neurophysiological data augmentation, thereby supporting the development of more efficient and reliable emotion recognition systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Past studies clarified the relationship between dimensions of teaching and achievement emotions. However, more information is needed about the underlying process behind this relationship among students with different mathematical abilities., Aims: This study examined the association between students' perceived teaching quality and achievement emotions in Chinese mathematics classrooms, focusing on students with different mathematics achievements., Samples: There are 1045 secondary school students (49.1% girls; M age  = 13.90, SD = .84) from Chinese mathematics classrooms in the present study., Methods: A multi-group structural equation model was adopted to test the relationship between teaching quality and achievement emotions between low- and high-achieving students., Results: Control-value appraisals mediated in teacher support and achievement emotions in both student groups. At the same time, control-value appraisals failed to mediate cognitive activation and achievement emotions in low-achieving students, while the mediating effect of control-value appraisals was identified in high-achieving students. Besides, classroom management was related to achievement emotions via academic value only in low-achieving students. In contrast, it was related to achievement emotions via control-value appraisals in high-achieving students., Conclusions: The results clarified the mediation roles of control-value appraisals in teaching quality and achievement emotions in students with low- and high-achieving achievements. Similarities and differences were also identified between the two student groups. Teacher support was beneficial to students' positive emotions while classroom management helped to lessen students' negative emotions. High-achieving students benefited more from activating teaching compared with low-achieving students., (© 2024 British Psychological Society.)

The future is bound to bring rapid methodological changes to psychological research. One such promising candidate is the use of webcam-based eye tracking. Earlier research investigating the quality of online eye-tracking data has found increased spatial and temporal error compared to infrared recordings. Our studies expand on this work by investigating how this spatial error impacts researchers' abilities to study psychological phenomena. We carried out two studies involving emotion-attention interaction tasks, using four participant samples. In each study, one sample involved typical in-person collection of infrared eye-tracking data, and the other involved online collection of webcam-based data. We had two main findings: First, we found that the online data replicated seven of eight in-person results, although the effect sizes were just 52% [42%, 62%] the size of those seen in-person. Second, explaining the lack of replication in one result, we show how online eye tracking is biased toward recording more gaze points near the center of participants' screen, which can interfere with comparisons if left unchecked. Overall, our results suggest that well-powered online eye-tracking research is highly feasible, although researchers must exercise caution, collecting more participants and potentially adjusting their stimulus designs or analytic procedures., (© 2023. The Psychonomic Society, Inc.)

Reinforcement learning (RL) is an effective method in training dialogue policies to steer the conversation towards successful task completion. However, most RL-based methods only rely on semantic inputs that lack empathy as they ignore the user emotional information. Moreover, these methods suffer from delayed rewards caused by the user simulator returning valuable results only at dialogue end. Recently, some methods have been proposed to learn the reward function together with user emotions, but they omit considering user emotion in each dialogue turn. In this paper, we proposed an emotion-sensitive dialogue policy model (ESDP), it incorporates user emotions information into dialogue policy and selects the optimal action by the combination of top-k actions with the user emotions. The user emotion information in each turn is used as an immediate reward for the current dialogue state to solve sparse rewards and the dependency on termination. Extensive experiments validate that our method outperforms the baseline approaches when combined with different Q-Learning algorithms, and also surpasses other popular existing dialog policies' performance., (© 2024. The Author(s).)

Different empathic responses are often reported in autism but remain controversial. To investigate which component of empathy is most affected by autism, we examined the affective, cognitive, and motivational components of empathy in 25 5- to 8-year-old autistic and 27 neurotypical children. Participants were presented with visual stimuli depicting people's limbs in painful or nonpainful situations while their eye movements, pupillary responses, and verbal ratings of pain intensity and empathic concern were recorded. The results indicate an emotional overarousal and reduced empathic concern to others' pain in autism. Compared with neurotypical children, autistic children displayed larger pupil dilation accompanied by attentional avoidance to others' pain. Moreover, even though autistic children rated others in painful situations as painful, they felt less sorry than neurotypical children. Interestingly, autistic children felt more sorry in nonpainful situations compared with neurotypical children. These findings demonstrated an emotional overarousal in response to others' pain in autistic children, and provide important implications for clinical practice aiming to promote socio-emotional understanding in autistic children., (© 2024 International Society for Autism Research and Wiley Periodicals LLC.)

The proper measurement of emotion is vital to understanding the relationship between emotional expression in social media and other factors, such as online information sharing. This work develops a standardized annotation scheme for quantifying emotions in social media using recent emotion theory and research. Human annotators assessed both social media posts and their own reactions to the posts' content on scales of 0 to 100 for each of 20 (Study 1) and 23 (Study 2) emotions. For Study 1, we analyzed English-language posts from Twitter (N = 244) and YouTube (N = 50). Associations between emotion ratings and text-based measures (LIWC, VADER, EmoLex, NRC-EIL, Emotionality) demonstrated convergent and discriminant validity. In Study 2, we tested an expanded version of the scheme in-country, in-language, on Polish (N = 3648) and Lithuanian (N = 1934) multimedia Facebook posts. While the correlations were lower than with English, patterns of convergent and discriminant validity with EmoLex and NRC-EIL still held. Coder reliability was strong across samples, with intraclass correlations of .80 or higher for 10 different emotions in Study 1 and 16 different emotions in Study 2. This research improves the measurement of emotions in social media to include more dimensions, multimedia, and context compared to prior schemes., (© 2023. The Psychonomic Society, Inc.)

This study is based on an original eight-wave longitudinal survey conducted in the Czech Republic (N = 1622, national quota sample). Structural equation modeling (SEM) was employed to create a mediation model to test whether democratic spirit assessed in March 2021 (1 year before the Russian invasion) predicted responses to the major crisis (measured immediately, 2 months, and 9 months after the invasion). The Russian invasion of February 2022 deeply impacted Czech democrats. They reacted by a strong increase in positive emotions toward Ukraine/Ukrainians (e.g., compassion, admiration to courage), a milder increase in negative emotions (e.g., anger) and physiological discomfort. The Russian invasion further strengthened the democratic identity of the Czech citizens which increased their willingness to help Ukraine, both personally and by government. Finally, the democratic spirit of 2021 predicted hope for Ukraine and for Czechia in late 2022 when various crises cumulated. Notably, the direct effect of democratic spirit on future hope was non-significant unless respondents were concerned with some aid to Ukrainians. Help completely mediated the democratic spirit and was linked to hope. The relationship between democratic values and hope was strong and spanned almost 2 years and cumulated crises. The study suggests that democratic values are significantly related to positive reactions to stressful conditions. The protective effect of the democratic spirit seemed beneficial both to one's health and delivering help to victims., (© 2023 The Authors. Applied Psychology: Health and Well‐Being published by John Wiley & Sons Ltd on behalf of International Association of Applied Psychology.)

This research investigated children's and adults' understanding of the mind by assessing beliefs about the temporal features of mental states. English-speaking North American participants, varying in socioeconomic status (Study 1: N = 50 adults; Study 2: N = 112, 8- to 10-year-olds and adults; and Study 3: N = 116, 5- to 7-year-olds and adults; tested 2017-2022), estimated the duration (seconds to a lifetime) of emotions, desires (wanting), preferences (liking), and control trials (e.g., napping and having eyes). Participants were 56% female and 44% male; 32% Asian, 1% Black, 13% Hispanic/Latino, 38% White (non-Hispanic/Latino), and 16% multiracial or another race/ethnicity. Children and adults judged that preferences last longer than emotions and desires, with age differences in distinguishing specific emotions by duration ( η p 2 s > .03 ). By 5 to 7 years, ideas about the mind include consideration of time., (© 2024 The Authors. Child Development published by Wiley Periodicals LLC on behalf of Society for Research in Child Development.)

Background: Students' initial experiences at university often shape their attendance and attainment. For some students, university is a positive experience, whereas others seemingly struggle and have more negative emotions. Unearthing distinctions in first-year students' emotionality may be valuable in understanding their academic engagement and performance., Aims: The study's aim was to identify distinct profiles of students based on their achievement emotions and explore whether these profiles differed in university attendance and attainment. At least three emotional profiles were hypothesized (positive; moderate; negative) with a positive profile expected to display the highest attendance and attainment., Sample: Participants were 294 first-year undergraduate students from a university in the United Kingdom (M age  = 19.33 years; 127 men; 162 women)., Methods: Students completed self-report measures of eight achievement emotions for general learning. Attendance and attainment data were collected from official records. Hierarchical cluster analysis was performed to profile students on their achievement emotions. Analysis of covariance explored profile differences in attendance and attainment., Results: Four emotional profiles emerged: positive; moderate; negative; mixed-valence (both positive and negative activating emotions). The positive and mixed-valence groups displayed equally high attendance compared to the moderate and negative groups. The positive group obtained higher academic attainment than the mixed-valence and negative emotion groups, but not the moderate group., Conclusions: The findings highlight the diverse emotional experiences of first-year university students and the existence of co-occurring positive and negative activation emotions. This evidence may be of practical worth to educators in understanding variability in students' emotions, attendance and attainment., (© 2024 The Authors. British Journal of Educational Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.)

Purpose: This study aimed to identify research trends related to emotional leadership among nurse managers by conducting a systematic literature review and meta-analysis. This study sought to derive insights that could contribute to improving emotional leadership in nursing practice., Methods: A systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) and Meta-Analysis Of Observational Studies in Epidemiology (MOOSE) guidelines. Databases including PubMed, Cumulative Index to Nursing and Allied Health Literature, Scopus, Web of Science, Research Information Sharing Service, Koreanstudies Information Service System, Korean Medical Database, KoreaMed, ScienceON, and DBpia were searched to obtain papers published in English and Korean. Literature searches and screenings were conducted for the period December 1, 2023 to December 17, 2023. The effect size correlation (ESr) was calculated for each variable and the meta-analysis was performed using the statistical software SPSS 29.0, R 4.3.1., Results: Twenty-five (four personal, six job, and fifteen organizational) relevant variables were identified through the systematic review. The results of the meta-analysis showed that the total overall effect size was ESr = .33. Job satisfaction (ESr = .40) and leader-member exchange (ESr = .75) had the largest effect size among the job and organizational-related factors., Conclusion: Emotional leadership helps promote positive changes within organizations, improves organizational effectiveness, and increases member engagement and satisfaction. Therefore, it is considered an important strategic factor in improving organizational performance., Competing Interests: The authors declared no conflict of interest., (© 2024 Korean Society of Nursing Science.)

In his book Aion, Jung describes something like a quasi-Hegelian progressive historical realization of the Self in a perspective similar to Fernand Braudel's longue durée history. This article deals with a similar perspective, as it tries to focus on what we may call a "cultural complex" yet within its unfolding in historical time and belonging not to just one specific cultural group, but to a large cultural basin, which we may indicate as the "West". This complex marks the birth and development of modernity. The depth, pervasiveness and duration of this cultural complex permeates the lives and psychologies of all of those that are part of it. Therefore, every analytical project must take into account the underlying emotional, epistemic and social field within which this complex constellates. One of the main features of this (trans)cultural complex, strictly connected with the progressive fragmentation of the self and the transformation of the numinosum with its meaning-giving force, is paranoia. This article analyses the historical and cultural features that produce paranoia and fragmentation and determine paranoid symptoms and attitudes., (© 2024 The Society of Analytical Psychology.)

Objective: Self-control supports many positive life outcomes. However, the processes underlying the development of self-control are not well understood. Drawing on the TESSERA model of personality development, we examined whether weekly schoolwork effort predicts self-control (in the subsequent week). We also examined the role of schoolwork emotions and whether these emotions moderated the impact of schoolwork effort on self-control based on predictions from the TESSERA model., Methods: Data are from a weekly diary study (N = 98) that measured children's schoolwork effort, schoolwork emotions, and self-control during five consecutive weeks. Data were analyzed at the between- and within-person levels using multilevel models., Results: Between-person results show that schoolwork effort is related to variations in children's self-control. Furthermore, some emotions moderated the influence of schoolwork effort on self-control at the between- and within-person levels., Conclusion: In line with the TESSERA model of personality development, positive state expressions of effort during schoolwork (e.g., putting in effort) predicted higher self-control in the subsequent week. However, this finding was dependent on the reactions and reinforcement children felt about their effort (e.g., emotional responses to their remote schoolwork). The discussion examines how these findings extend to previous literature., (© 2023 The Authors. Journal of Personality published by Wiley Periodicals LLC.)

Emotion is closely associated with language, but we know very little about how children express emotion in their own writing. We used a large-scale, cross-sectional, and data-driven approach to investigate emotional expression via writing in children of different ages, and whether it varies for boys and girls. We first used a lexicon-based bag-of-words approach to identify emotional content in a large corpus of stories (N>100,000) written by 7- to 13-year-old children. Generalized Additive Models were then used to model changes in sentiment across age and gender. Two other machine learning approaches (BERT and TextBlob) validated and extended these analyses, converging on the finding that positive sentiments in children's writing decrease with age. These findings echo reports from previous studies showing a decrease in mood and an increased use of negative emotion words with age. We also found that stories by girls contained more positive sentiments than stories by boys. Our study shows the utility of large-scale data-driven approaches to reveal the content and nature of children's writing. Future experimental work should build on these observations to understand the likely complex relationships between written language and emotion, and how these change over development., (© 2024 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

In cross-sectional research, subjective well-being and grit are found to be positively correlated. Their mutually reinforcing effects are particularly relevant for youth entering early adolescence because, during this developmental period, both well-being and grit have been shown to predict consequential outcomes later in life. However, their mutual relation has not yet been investigated in early adolescence. This study, therefore, examined the possibility of a virtuous cycle linking subjective well-being and grit during early adolescence. Self-report questionnaires of grit and subjective well-being were completed by N = 5291 children in China (47.6% girls; initial M age  = 9.69, SD age  = 0.59) on six occasions over 3 academic years. In random-intercept cross-lagged panel models (RI-CLPMs), within-person changes in grit predicted within-person changes in subjective well-being 6 months later, and vice versa. Notably, analyses revealed an asymmetry in this cycle: paths from subjective well-being to grit were stronger and more reliable than the converse. Likewise, facet-level analyses showed that the predictive power of the perseverance component (of grit) and the affective component (of subjective well-being), respectively, was greater than the passion and cognitive components, respectively. These findings highlight the potential of boosting happiness for catalyzing positive youth development and, in addition, foreground the utility of studying these composite constructs at the facet level., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

During mother-infant interaction, shared emotional experiences, defined as reciprocal and synchronous emotional sharing between mother and infant, are an indicator of early relational health. Yet, it is unclear how mothers' efforts to engage with their infants relate to dyadic-level shared emotional experiences. Utilizing a sample of 80 randomly selected videos of the NICHD Study of Early Child Care and Youth Development, we examined how mothers' bids for interaction with their 6-month-old infants related to the duration of shared emotional experiences. An event sampling, sequential coding system was used to identify a maternal bid for interaction (i.e., with toy, without toy) and the subsequent presence or absence of a shared emotional experience, including duration of the shared emotional experience. Results indicated that shared emotional experiences were longer following mothers' efforts to engage their infants in play without toys. Findings suggest that methods matter; researchers and practitioners interested in studying and promoting shared emotional experiences between mothers and infants may wish to focus on dyadic interactions without toys., (© 2023 Michigan Association for Infant Mental Health.)

Pattern recognition based on network connections has recently been applied to the brain-computer interface (BCI) research, offering new ideas for emotion recognition using Electroencephalogram (EEG) signal. However unified standards are currently lacking for selecting emotional signals in emotion recognition research, and potential associations between activation differences in brain regions and network connectivity pattern are often being overlooked. To bridge this technical gap, a data-driven signal auto-segmentation and feature fusion algorithm (DASF) is proposed in this paper. First, the Phase Locking Value (PLV) method was used to construct the brain functional adjacency matrix of each subject, and the dynamic brain functional network across subjects was then constructed. Next, tucker decomposition was performed and the Grassmann distance of the connectivity submatrix was calculated. Subsequently, different brain network states were distinguished and signal segments under emotional states were automatically extract using data-driven methods. Then, tensor sparse representation was adopted on the intercepted EEG signals to effectively extract functional connections under different emotional states. Finally, power-distribution related features (differential entropy and energy feature) and brain functional connection features were effectively combined for classification using the support vector machines (SVM) classifier. The proposed method was validated on ERN and DEAP datasets. The single-feature emotion classification accuracy of 86.57 % and 87.74 % were achieved on valence and arousal dimensions, respectively. The accuracy of the proposed feature fusion method was achieved at 89.14 % and 89.65 %, accordingly, demonstrating an improvement in emotion recognition accuracy. The results demonstrated the superior classification performance of the proposed data-driven signal auto-segmentation and feature fusion algorithm in emotion recognition compared to state-of-the-art classification methods., Competing Interests: Declaration of competing interest The authors declared that they have no conflicts of interest to this work., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Musical emotions have received increasing attention over the years. To better recognize the emotions by brain-computer interface (BCI), the random music-playing and sequential music-playing experimental paradigms are proposed and compared in this paper. Two experimental paradigms consist of three positive pieces, three neutral pieces and three negative pieces of music. Ten subjects participate in two experimental paradigms. The features of electroencephalography (EEG) signals are firstly analyzed in the time, frequency and spatial domains. To improve the effect of emotion recognition, a recognition model is proposed with the optimal channels selecting by Pearson's correlation coefficient, and the feature fusion combining differential entropy and wavelet packet energy. According to the analysis results, the features of sequential music-playing experimental paradigm are more different among three emotions. The classification results of sequential music-playing experimental paradigm are also better, and its average results of positive, neutral and negative emotions are 78.53%, 72.81% and 77.35%, respectively. The more obvious the changes of EEG induced by the emotions, the higher the classification accuracy will be. After analyzing two experimental paradigms, a better way for music to induce the emotions can be explored. Therefore, our research offers a novel perspective on affective BCIs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The developmental trajectory of emotion recognition (ER) skills is thought to vary by nonverbal modality, with vocal ER becoming mature later than facial ER. To investigate potential neural mechanisms contributing to this dissociation at a behavioural level, the current study examined whether youth's neural functional connectivity during vocal and facial ER tasks showed differential developmental change across time. Youth ages 8-19 (n = 41) completed facial and vocal ER tasks while undergoing functional magnetic resonance imaging, at two timepoints (1 year apart; n = 36 for behavioural data, n = 28 for neural data). Partial least squares analyses revealed that functional connectivity during ER is both distinguishable by modality (with different patterns of connectivity for facial vs. vocal ER) and across time-with changes in connectivity being particularly pronounced for vocal ER. ER accuracy was greater for faces than voices, and positively associated with age; although task performance did not change appreciably across a 1-year period, changes in latent functional connectivity patterns across time predicted participants' ER accuracy at Time 2. Taken together, these results suggest that vocal and facial ER are supported by distinguishable neural correlates that may undergo different developmental trajectories. Our findings are also preliminary evidence that changes in network integration may support the development of ER skills in childhood and adolescence., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Emotional elicitation during wine consumption is a complex fenomena based on subjective experience and influence by physiological, cognitive and behavioural changes. The present study used a quasi-experimental design to examine consumers' emotional responses during blind tastings of sherry wines, considering variables such as consumer experience, gender and Emotional Intelligence (EI). 66 participants were classified as non-expert (34) and expert (32) consumers to participate in blind tastings. Their emotional responses were measured using the EsSense25 Scale and the Perceived Emotional Intelligence was assessed through the Trait Meta-Mood Scale. Few differences were observed on emotional elicitation based on gender or consumer experience (non-expert vs expert), however the interaction of these variables was a good predictor of emotional response variance. Wine type also has an effect on emotional response, emphasising the role of sherry wine characteristics in consumer emotions. Furthermore, the Emotional Attention, one of the three dimensions of Emotional Intelligence, was found as a good predictor for the emotional responses to wine consumption. This relationship may be a key factor in understanding the differences between responsible consumption and excessive consumption, as indicated by research focused on binge drinking., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Sensory cues like music can influence our behaviour towards food. In the present study, the effect of music on hunger, fullness, desire to eat and liking of foods, while viewing real lunch food items, was investigated. To this end, emotions and physiological measures were obtained to understand the changes in hunger, fullness, desire to eat and liking. The study aimed to examine changes in hunger, fullness, desire to eat, and liking when viewing a lunch meal under silent and varying music conditions. Additionally, the study explored the potential role of emotions to explain these changes. A crossover experimental design was employed using 50 participants (17 males and 33 females) who observed lunch food items during a silent condition (control), or while listening to either liked or disliked music. The findings demonstrate the cross-modal influence of music on hunger and food liking ratings when viewing food. Hunger ratings were higher and more negative emotions were evoked while viewing lunch food items and listening to disliked music. In contrast, in the silent and liked music conditions, which elicited more positive emotions, there were increased ratings of healthy and unhealthy food pleasantness, overall food liking, and food satisfaction. Electrophysiological measures of heart rate (HR) and skin conductance (SC) were obtained while listening to music and viewing a lunch meal. Viewing food items while listening to disliked music evoked negative emotions and significantly increased SC compared to liked music or silent conditions. Viewing the food items under the silent condition evoked positive emotions and significantly increased HR compared to listening to liked and disliked music. This study showed that the participants' emotions, hunger level, liking, and electrophysiological responses when viewing food are influenced by music that varied with liking. Results from this study may assist in enhancing dining experiences, as well as influencing food choices and satisfaction with meals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Emotion recognition based on electroencephalogram (EEG) signals is crucial in understanding human affective states. Current research has limitations in extracting local features. The representation capabilities of local features are limited, making it difficult to comprehensively capture emotional information. In this study, a novel approach is proposed to enhance local representation learning through global-local integration with functional connectivity for EEG-based emotion recognition. By leveraging the functional connectivity of brain regions, EEG signals are divided into global embeddings that represent comprehensive brain connectivity patterns throughout the entire process and local embeddings that reflect dynamic interactions within specific brain functional networks at particular moments. Firstly, a convolutional feature extraction branch based on the residual network is designed to extract local features from the global embedding. To further improve the representation ability and accuracy of local features, a multidimensional collaborative attention (MCA) module is introduced. Secondly, the local features and patch embedded local embeddings are integrated into the feature coupling module (FCM), which utilizes hierarchical connections and enhanced cross-attention to couple region-level features, thereby enhancing local representation learning. Experimental results on three public datasets show that compared with other methods, this method improves accuracy by 4.92% on the DEAP, by 1.11% on the SEED, and by 7.76% on the SEED-IV, demonstrating its superior performance in emotion recognition tasks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Aleksandr Luria repeatedly emphasised the importance of emotions and the right hemisphere in his neuropsychological writings. It is surprising, therefore, that Luria's most influential book, The Working Brain, appears to lack an explicit section on these topics. This is especially notable because of a comment in the book's English-language Introduction, by Karl Pribram, referencing Luria's thoughts about precisely this material. Remarkably, it seems that Luria did write such an explicit chapter, in the original Russian edition. However, in the English-language version, the relevant sections were separated, embedded elsewhere without chapter headings, and altered, presumably following an explicit translation decision. The present paper tracks the nature of these changes and, 50 years later, presents the material for the first time translated and reunited in English, as Luria intended. After the translation, we offer a brief commentary, on the ways in which Luria's ideas were in some respects prescient, and in other respects less well-informed about the brain basis of emotions and the right hemisphere. This reunification offers an interesting time capsule on the opinions of one of neuropsychology's greatest minds, on a topic which Luria admits had, at the time, only a modest empirical foundation., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Speech emotion recognition (SER) stands as a prominent and dynamic research field in data science due to its extensive application in various domains such as psychological assessment, mobile services, and computer games, mobile services. In previous research, numerous studies utilized manually engineered features for emotion classification, resulting in commendable accuracy. However, these features tend to underperform in complex scenarios, leading to reduced classification accuracy. These scenarios include: 1. Datasets that contain diverse speech patterns, dialects, accents, or variations in emotional expressions. 2. Data with background noise. 3. Scenarios where the distribution of emotions varies significantly across datasets can be challenging. 4. Combining datasets from different sources introduce complexities due to variations in recording conditions, data quality, and emotional expressions. Consequently, there is a need to improve the classification performance of SER techniques. To address this, a novel SER framework was introduced in this study. Prior to feature extraction, signal preprocessing and data augmentation methods were applied to augment the available data, resulting in the derivation of 18 informative features from each signal. The discriminative feature set was obtained using feature selection techniques which was then utilized as input for emotion recognition using the SAVEE, RAVDESS, and EMO-DB datasets. Furthermore, this research also implemented a cross-corpus model that incorporated all speech files related to common emotions from three datasets. The experimental outcomes demonstrated the superior performance of SER framework compared to existing frameworks in the field. Notably, the framework presented in this study achieved remarkable accuracy rates across various datasets. Specifically, the proposed model obtained an accuracy of 95%, 94%,97%, and 97% on SAVEE, RAVDESS, EMO-DB and cross-corpus datasets respectively. These results underscore the significant contribution of our proposed framework to the field of SER., Competing Interests: Declaration of competing interest The author declare that he has no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In this paper, a novel skipping spatial-spectral-temporal network (S 3 T-Net) is developed to handle intra-individual differences in electroencephalogram (EEG) signals for accurate, robust, and generalized emotion recognition. In particular, aiming at the 4D features extracted from the raw EEG signals, a multi-branch architecture is proposed to learn spatial-spectral cross-domain representations, which benefits enhancing the model generalization ability. Time dependency among different spatial-spectral features is further captured via a bi-directional long-short term memory module, which employs an attention mechanism to integrate context information. Moreover, a skip-change unit is designed to add another auxiliary pathway for updating model parameters, which alleviates the vanishing gradient problem in complex spatial-temporal network. Evaluation results show that the proposed S 3 T-Net outperforms other advanced models in terms of the emotion recognition accuracy, which yields an performance improvement of 0.23% , 0.13%, and 0.43% as compared to the sub-optimal model in three test scenes, respectively. In addition, the effectiveness and superiority of the key components of S 3 T-Net are demonstrated from various experiments. As a reliable and competent emotion recognition model, the proposed S 3 T-Net contributes to the development of intelligent sentiment analysis in human-computer interaction (HCI) realm., Competing Interests: Declaration of competing interest None Declared., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Traditional media such as text, images, audio, and video primarily target specific senses like vision and hearing. In contrast, multiple sensorial media aims to create immersive experiences by integrating additional sensory modalities such as touch, smell, and taste where applicable. Tactile enhanced audio-visual content leverages the sense of touch in addition to visual and auditory stimuli, aiming to create a more immersive and engaging interaction for users. Previously, tactile enhanced content has been explored in 2D emotional space (valence and arousal). In this paper, EEG data against tactile enhanced audio-visual content is labeled based on a self-assessment manikin scale in 3 dimensions i.e., valence, arousal, and dominance. Statistical significance (with a 95% confidence interval) is also established based on gathered scores, highlighting a significant difference in the arousal and dominance dimension of traditional media and tactile enhanced media. A new methodology is proposed using classifier-dependent feature selection approach to classify valence, arousal, and dominance states using three different classifiers. A highest accuracy of 75%, 73.8%, and 75% is achieved for classifying valence, arousal, and dominance states, respectively. The proposed scheme outperforms previous emotion recognition based studies in response to enhanced multimedia content in terms of accuracy, F-score, and other error parameters., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Diagnosis and severity assessment of tinnitus are mostly based on the patient's descriptions and subjective questionnaires, which lacks objective means of diagnosis and assessment bases, the accuracy of which fluctuates with the clarity of the patient's description. This complicates the timely modification of treatment strategies or therapeutic music to improve treatment efficacy., New Method: We employed a novel random convolutional kernel-based method for electrocardiogram (ECG) signal analysis to identify patients' emotional states during Music Tinnitus Sound Therapy (Music-TST) sessions. Then analyzed correlations between emotional changes in different treatment phase and Tinnitus Handicap Inventory (THI) score differences to determine the impact of emotions on tinnitus treatment efficacy., Results: This study revealed a significant correlation between patients' emotion changes during Music-TST and the therapy's effectiveness. Changes in arousal and dominance dimension, were strongly linked to THI variations. These findings highlight the substantial impact of emotional responses on sound therapy's efficacy, offering a new perspective for understanding and optimizing tinnitus treatment., Comparison With Existing Methods: Compared to existing methods, we proposed an objective indicator to assess the progress of sound therapy, the indicator could also be used to provide feedback to optimize sound therapy music., Conclusions: This study revealed the critical role of emotion changes in tinnitus sound therapy. By integrating objective ECG-based emotion analysis with traditional subjective scale like THI, we present an innovative approach to assess and potentially optimize therapy effectiveness. This finding could lead to more personalized and effective treatment strategies for tinnitus sound therapy., Competing Interests: Declaration of Competing Interest The authors of this work declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. All authors have approved the manuscript for submission and without any potential competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Electroencephalogram (EEG) signals are derived from the central nervous system and inherently difficult to camouflage, leading to the recent popularity of EEG-based emotion recognition. However, due to the non-stationary nature of EEG, inter-subject variabilities become obstacles for recognition models to well adapt to different subjects. In this paper, we propose a novel approach called semi-supervised bipartite graph construction with active EEG sample selection (SBGASS) for cross-subject emotion recognition, which offers two significant advantages. Firstly, SBGASS adaptively learns a bipartite graph to characterize the underlying relationships between labeled and unlabeled EEG samples, effectively implementing the semantic connection for samples from different subjects. Secondly, we employ active sample selection technique in this paper to reduce the impact of negative samples (outliers or noise in the data) on bipartite graph construction. Drawing from the experimental results with the SEED-IV data set, we have gained the following three insights. (1) SBGASS actively rejects negative labeled samples, which helps mitigate the impact of negative samples when constructing the optimal bipartite graph and improves the model performance. (2) Through the learned optimal bipartite graph in SBGASS, the transferability of labeled EEG samples is quantitatively analyzed, which exhibits a decreasing tendency as the distance between each labeled sample and the corresponding class centroid increases. (3) Besides the improved recognition accuracy, the spatial-frequency patterns in emotion recognition are investigated by the acquired projection matrix., (© 2024. International Federation for Medical and Biological Engineering.)

Background and Objectives: Rituals are common among healthy individuals and across cultures and often serve adaptive purposes. In individuals with obsessive-compulsive disorder (OCD), rituals become compulsive, time-consuming and distressing, and may lead to functional impairment. Previous research has examined the functions and characteristics of compulsive rituals, but there is paucity of in-depth, first-person reports about this topic., Method: We used a qualitative approach to explore thoughts, feelings, and behavioral patterns that characterize OCD rituals. Ten individuals with OCD participated in a semi-structured interview that focused on their most prominent compulsive ritual. The interviews were subjected to a thematic analysis., Results: Eight themes emerged from the analysis and were organized in two main categories: Micro Level perspective, comprising triggers, attention, emotional changes, and stopping criteria; and Macro Level perspective, comprising feelings and perceptions, change over time, motives, and inhibitors. The findings shed light on the role of fixed rules and feelings of "completeness" in OCD rituals, the nature of emotional and attentional characteristics during rituals performance, and the evolution of compulsive rituals over time., Limitations: This study used a qualitative approach based on a small number of participants, which limits the generalizability of the findings., Conclusion: Our results, if replicated, may have clinical implications. The reported patterns of anxiety reduction during ritual performance may contribute to the fine-tuning of CBT for OCD. The findings concerning the nature of attention during ritual performance and the development of rituals over time may be important for understanding the mechanisms that maintain compulsive rituals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Pressure is an innate feature of competition and stimulates cognitions and emotions that can both reduce and enhance performance. Similarly, teams are ubiquitous in sport and influence their members in various ways. Yet, we know little about the ways in which teams influence their members' responses to pressure, whether they are an added demand, inducing social indispensability and exacerbating the effects of pressure, or a resource, providing shared responsibility and buffering pressure effects. We conducted a field experiment across two samples of skilled handball players (N = 189) to test how outcome interdependence vs. independence influenced athletes' appraisals of task importance and coping prospects, anxiety and excitement, and penalty shooting performance under lower vs. higher situational pressure, and to what extent performance order and teammate skill moderated these effects. We found that pressure increased task importance and emotional intensity yet being part of a team or not made little difference. Descriptively, interdependence did attenuate the increase in anxiety under higher pressure and, if paired with skilled teammates, strengthen the increase in excitement. Yet, weak pressure manipulations, insensitive samples and measures require replication and prohibit conclusive interpretations regarding the influence of teams on members' responses to pressure., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In this study, we examined the effects of female coaches' nonverbal pride and shame expressions on female field hockey players' emotions and performance and considered the role of two potential moderating factors. Across two experiments, a between (emotional expression manipulation) within (pre- and post-manipulation) subjects design was employed. A female hockey coach was scripted to deliver performance feedback randomly displaying pride or shame to skilled players (Experiment 1, n = 38; Experiment 2, n = 44) after they had performed a passing test. Players then performed the passing test for a second time. In both experiments, players reported their emotions, perceptions of the coach, and connection with the coach. In Experiment 2, players also rated their emotion regulation ability. The results showed that displayed pride elicited pride in players while displayed shame elicited shame in players. Further, coaches' pride and shame expressions had differential effects on players' performance. Displayed pride consistently improved players' performance. Displayed shame mainly worsened performance, but players' ability to regulate their own emotions seemed to buffer these negative effects. There was further evidence that players' emotions could underpin the performance effects, particularly when players knew the coach. These findings advance the literature by providing further experimental evidence for when and how coaches' pride and shame expressions influence players' emotions and performance and have important practical implications for coaches aiming to optimize performance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Across sensory systems, several stimulus collative characteristics, including intensity, novelty, complexity and perceived dangerousness, are known to elicit high levels of physiological and psychological arousal. It has become apparent that food rejections by both children and adults are frequently linked to such arousal-inducing characteristics. This paper examines how arousal and arousability are important elements in responding to stimuli generally, but specifically to foods, ultimately influencing food preferences and choices. It is clear that responses to sensory properties are subject not just to variations in perceptual sensitivity due to genetics or experience-as in the case of widely rejected qualities such as bitterness or pungency-but also to the arousal potential of those stimuli. Moreover, this is linked to various enduring aspects of personality, suggesting that the impact of arousal on food choices is merely one aspect of a more general sensory sensitivity. The impact of diet on various health outcomes underlines the importance of understanding the relationship of arousal to food choices. This article is part of the theme issue 'Sensing and feeling: an integrative approach to sensory processing and emotional experience'.

Several theories suggest that people differ significantly in their environmental sensitivity, defined as the capacity to perceive and process information about the environment. More sensitive people, who make up between 25% and 30% of the population, are not only more negatively affected by adverse experiences but also benefit disproportionately from positive ones, in line with differential susceptibility theory. Heightened emotional reactivity has been identified as one of the key markers of sensitivity. However, the current understanding of the relationship between sensitivity and the experience and processing of emotions remains limited. In the current paper we propose a new conceptual framework for the multiple ways in which environmental sensitivity may impact on different aspects of the experience and processing of emotions. This includes heightened perception of emotions, increased emotional reactivity, as well as the important role of emotion regulation for the well-being of highly sensitive people. In addition, we also consider rearing experiences in shaping sensitivity and emotion regulation. The reviewed empirical studies largely support the conceptual model but more research is needed to explore the dynamics between sensitivity and emotions further. Finally, we discuss several implications for well-being before making a case for the inclusion of individual differences in environmental sensitivity in affective science. This article is part of the theme issue 'Sensing and feeling: an integrative approach to sensory processing and emotional experience'.

Music is an important part of life for many people. It can evoke a wide range of emotions, including sadness, happiness, anger, tension, relief and excitement. People with hearing loss and people with cochlear implants have reduced abilities to discriminate some of the features of musical sounds that may be involved in evoking emotions. This paper reviews these changes in perceptual abilities and describes how they affect the perception of emotion in music. For people with acquired partial hearing loss, it appears that the perception of emotion in music is almost normal, whereas congenital partial hearing loss is associated with impaired perception of music emotion. For people with cochlear implants, the ability to discriminate changes in fundamental frequency (associated with perceived pitch) is much worse than normal and musical harmony is hardly perceived. As a result, people with cochlear implants appear to judge emotion in music primarily using tempo and rhythm cues, and this limits the range of emotions that can be judged. This article is part of the theme issue 'Sensing and feeling: an integrative approach to sensory processing and emotional experience'.

Early life adversity has been linked with a higher probability of developing behavioral impairments and environmental manipulation is a strategy that may reduce the negative effects of exposure to adversity in early life. Here, we focused on exploring the influence of environmental enrichment (EE) as a protective factor in the context of early life adversity. We hypothesized that 24 hours of maternal deprivation (MD), in the second week of life, could induce anxiety-like behavior alterations and that exposure to EE could induce resilience to these behaviors due to alterations in the serotonergic system. Male Wistar rats were exposed to MD, on postnatal days 11 and 13, and to EE, after weaning. In adulthood, we performed a series of behavioral tests for fear, anxiety, and locomotor activity. We also measured the levels of serotonin in the amygdala and dorsal raphe nucleus. Our results revealed that MD does not impact fear behavior or the levels of serotonin, while EE decreases locomotor activity in a novel environment and enhances exploration in the predator odor test. EE also decreases serotonin in the amygdala and increases its turnover rate levels. Our findings provide insights into the critical timeframe during which stress exposure impacts the development and confirm that exposure to EE has an independent and protective effect for anxiety-like behaviors later in life., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: This paper is devoted to a narrative review of the literature on emotions and academic performance in medicine. The review aims to examine the role emotions play in the academic performance of undergraduate medical students., Methods: Eight electronic databases were used to search the literature from 2013 to 2023, including Academic Search Ultimate, British Education Index, CINAHL, Education Abstract, ERIC, Medline, APA Psych Articles and APA Psych Info. Using specific keywords and terms in the databases, 3,285,208 articles were found. After applying the predefined exclusion and inclusion criteria to include only medical students and academic performance as an outcome, 45 articles remained, and two reviewers assessed the quality of the retrieved literature; 17 articles were selected for the narrative synthesis., Result: The findings indicate that depression and anxiety are the most frequently reported variables in the reviewed literature, and they have negative and positive impacts on the academic performance of medical students. The included literature also reported that a high number of medical students experienced test anxiety during their study, which affected their academic performance. Positive emotions lead to positive academic outcomes and vice versa. However, Feelings of shame did not have any effect on the academic performance of medical students., Discussion: The review suggests a significant relationship between emotions and academic performance among undergraduate medical students. While the evidence may not establish causation, it underscores the importance of considering emotional factors in understanding student performance. However, reliance on cross-sectional studies and self-reported data may introduce recall bias. Future research should concentrate on developing anxiety reduction strategies and enhancing mental well-being to improve academic performance., (© 2024. The Author(s).)

Recent advancements in large language models (LLMs) have sparked considerable interest in their potential applications across various healthcare domains. One promising prospect is leveraging these generative models to accurately predict children's emotions by combining computer vision and natural language processing techniques. However, understanding children's emotional states based on their artistic expressions is equally crucial. To address this challenge, this paper presents a pipelined architecture comprising YOLOv7 and the powerful GPT-3.5 Turbo language model, where YOLOv7 is employed for object detection using art therapy imaging annotations, while GPT-3.5 interprets the sketches. After rigorously evaluating the proposed framework through a series of comprehensive experiments, we observed that our model achieved high confidence scores for both object detection and emotion interpretation. The robust performance of the proposed framework not only aids in explaining children's art but also provides valuable insights for parents and therapists. This capability enables them to better understand children's emotional states based on their artistic expressions, ultimately facilitating improved support and care.

Introduction: No studies systematically examined sex differences in neural mechanisms underlying depression and mania/hypomania risk., Method: 80 females and 35 males, n = 115(age21.6±1.90) were scanned using 3TfMRI during an implicit emotional-faces task. We examined neural activation to all emotional faces versus baseline, using an anatomical region-of-interest mask comprising regions supporting emotion and salience processing. Sex was a covariate. Extracted parameter estimates(FWE < 0.05,k > 15), age, IQ and their sex interactions were independent variables(IV) in two penalized regression models: dependent variable either MOODS-SR-lifetime, depressive or manic domain score as measures of mania and depression risk. Subsequent Poisson regression models included the non-zero variables identified in the penalized regression models. We tested each model in 2 independent samples. Test sample-I,n = 108(21.6 ± 2.09 years,males/females = 33/75); Test sample-II,n = 93(23.7 ± 2.9 years,males/females = 31/62)., Results: Poisson regression models yielded significant relationships with depression and mania risk: Positive correlations were found between right fusiform activity and depression(beta = 0.610) and mania(beta = 0.690) risk. There was a significant interaction between sex and right fusiform activity(beta = -0.609) related to depression risk, where females had a positive relationship than; and a significant interaction(beta = 0.743) between sex and left precuneus activity related to mania risk, with a more negative relationship in females than males. All findings were replicated in the test samples(qs < 0.05,FDR)., Limitations: No longitudinal follow-up., Conclusion: Greater visual attention to emotional faces might underlie greater depression and mania risk, and confer greater vulnerability to depression in females, because of heightened visual attention to emotional faces. Females have a more negative relationship between mania risk and left precuneus activity, suggesting heightened empathy might be associated with reduced mania/hypomania risk in females more than males., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Better communication with older people requires not only improving speech intelligibility but also understanding how well emotions can be conveyed and the effect of age and hearing loss (HL) on emotion perception. In this paper, emotion discrimination experiments were conducted using a vocal morphing method and an HL simulator in young normal hearing (YNH) and older participants. Speech sounds were morphed to represent intermediate emotions between all combinations of happiness, sadness, and anger. Discrimination performance was compared when the YNH listened to normal sounds, when the same YNH listened to HL simulated sounds, and when older people listened to the same normal sounds. The results showed that there was no significant difference between discrimination with and without HL simulation, suggesting that peripheral HL may not affect emotion perception. The discrimination performance of the older participants was significantly worse only for the anger-happiness pair than for the other emotion pairs and for the YNH. It was also found that the difficulty increases with age, not just with hearing level., (© 2024. The Author(s).)

In this review, we consider the definitions and experimental approaches to emotional contagion and prosocial behaviour in mammals and explore their evolutionary conceptualisation for studying their occurrence in the evolutionarily divergent vertebrate group of ray-finned fish. We present evidence for a diverse set of fish phenotypes that meet definitional criteria for prosocial behaviour and emotional contagion and discuss conserved mechanisms that may account for some preserved social capacities in fish. Finally, we provide some considerations on how to address the question of interdependency between emotional contagion and prosocial response, highlighting the importance of recognition processes, decision-making systems, and ecological context for providing evolutionary explanations., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests or personal relationships that influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Wine is a cultural product capable of arousing emotions. Measuring emotions and figuring out how much they could influence preferences or purchase decisions of consumers is a new trend in sensory and consumer research. However, the complexity of feelings makes the measure of emotions extremely challenging. Thus, a comprehensive understanding of emotions related to sensory stimuli in wine tasting is still missing. The purpose of the study is to evaluate the emotional power of tasting red wines using a multidisciplinary approach, combining sensory analysis performed by trained panelists, implicit and explicit measurements of emotions and chemical analysis of the wines tasted. Various red wines, renowned for their high polyphenol content and expected to exhibit rich texture, mouthfeel, and aging potential, have been utilized to this extent. The results obtained showed that the emotions measured were well-correlated with quantitative and hedonic attributes obtained using classic sensory analysis. Some aromatic molecules can be identified as markers capable of eliciting positive and negative emotional reactions. While increasing literature in the topic is recently available, our study appears to be the first highlighting the presence of autonomic nervous system (ANS) differences verified by means of electrocardiogram (ECG) features, related to explicit and complete sensory patterns, in response to sensory stimuli related to emotional wine, with higher sympathetic values at extrema and vagal increase in the presence of neutral sensory compounds., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Background and Objectives: Convolutional neural networks (CNNs) are the most widely used deep-learning framework for decoding electroencephalograms (EEGs) due to their exceptional ability to extract hierarchical features from high-dimensional EEG data. Traditionally, CNNs have primarily utilized multi-channel raw EEG data as the input tensor; however, the performance of CNN-based EEG decoding may be enhanced by incorporating phase information alongside amplitude information., Methods: This study introduces a novel CNN architecture called the Hilbert-transformed (HT) and raw EEG network (HiRENet), which incorporates both raw and HT EEG as inputs. This concurrent use of HT and raw EEG aims to integrate phase information with existing amplitude information, potentially offering a more comprehensive reflection of functional connectivity across various brain regions. The HiRENet model was developed using two CNN frameworks: ShallowFBCSPNet and a CNN with a residual block (ResCNN). The performance of the HiRENet model was assessed using a lab-made EEG database to classify human emotions, comparing three input modalities: raw EEG, HT EEG, and a combination of both signals. Additionally, the computational complexity was evaluated to validate the computational efficiency of the ResCNN design., Results: The HiRENet model based on ResCNN achieved the highest classification accuracy, with 86.03% for valence and 84.01% for arousal classifications, surpassing traditional CNN methodologies. Considering computational efficiency, ResCNN demonstrated superiority over ShallowFBCSPNet in terms of speed and inference time, despite having a higher parameter count., Conclusion: Our experimental results showed that the proposed HiRENet can be potentially used as a new option to improve the overall performance for deep learning-based EEG decoding problems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Against the backdrop of the COVID-19 pandemic, workplace wellbeing is a key priority for employers. Severe market and health conditions continue to bring inevitable problems that could be reduced with the application of psychological interventions to prevent mental and physical health issues, making this study a highly pertinent and valuable contribution to the field. This paper reports the effects of a rational emotive behaviour therapy (REBT) programme on the irrational beliefs and emotional reactivity of 56 office-based sales professionals located in the northwest region of the UK. A pre-test, post-test experimental design was utilised, and a mixed model ANOVA (repeated measures) was adopted to assess changes in mean differences concerning irrational beliefs and emotional reactivity at pre and post-test stages for the intervention group, in comparison to a control group. Results indicate that those in the REBT group reported significant reductions in irrational beliefs and emotional reactivity, whilst those in the control group reported no such changes. It is recommended that future research studies consider utilizing a mixed methods design and focus on a strategic collaboration of organisational and individual level interventions for improving the psychological wellbeing and performance of sales personnel., (© 2024 The Authors. Stress and Health published by John Wiley & Sons Ltd.)

Research documents how abortion can be emotionally difficult and stigmatising, but generally has not considered whether and how involvement in abortion may be a source of positive emotions, including pleasure, belonging and even joy. The absence of explorations that start from the possibility of abortion pleasure and joy represents an epistemic foreclosure. Moreover, it highlights how social science literature has tended to emphasise the negative aspects of abortion care in ways that produce or amplify normative negative associations. In this paper, we investigate the positive emotions, pleasure and joy of abortion involvement by drawing on interviews conducted in 2019 with 28 abortion accompaniers in Argentina, Chile, and Ecuador about their experiences accompanying abortions after 17 weeks' gestation. Abortion accompaniment is a response to unsafe and/or inaccessible abortion whereby volunteer activists guide abortion seekers through a medication abortion. Interviewees described how the practice of accompaniment generated positive emotions by building a feminist community, shared intimacy among women, and witnessing aborting people claim their strength. Importantly, these positive emotional experiences of involvement with abortion were not distinct from the broader marginalisation of abortion but were, instead, rooted in its marginalisation.

The ability to focus on and increase positive emotion in response to mental imagery may play a key role in emotional wellbeing. Moreover, deficits in this ability might underlie emotional disorders such as depression. Here, we set out to determine whether people could use savoring to upregulate subjective and electrocortical response to mental imagery of previously viewed positive and neutral pictures, and whether this would be negatively affected by depression. On each trial, participants (N = 49) viewed a positive or neutral picture, prior to simply re-imagining the previously presented picture ("view") or re-imagining the picture while savoring it ("savor"). Results showed that savoring increased electrocortical and subjective response to imagined stimuli; however, this effect was only evident at the electrocortical level when controlling for depression. Moreover, depression moderated electrocortical findings, such that individuals who were more depressed showed a reduced effect of savoring on neural response to mental imagery. Results are in line with recent work that has shown the benefits of positive affect treatment for depression, to suggest that deficits in savoring mental imagery may play a role in the development and/or maintenance of depression., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In this paper I discuss the main models that have tried to explain brain asymmetries for emotions. The first models, based on clinical observations, proposed either a general right hemisphere dominance for emotions (the'right hemisphere') model or a different specialization of the right hemisphere for negative and of the left hemisphere for positive emotions (the'valence' model). In more recent times new models, based on partly modified versions of the previous ones have been proposed. The revised version of the 'valence' model, labeled the 'approach-avoidance' model maintained that hemispheric asymmetries are not related to the valence of the emotional stimulus but to the motivational (approach vs avoidance) system that is engaged by that stimulus. On the contrary, revised versions of the 'right hemisphere' hypothesis proposed graded versions of this model, maintaining that only some kinds or some levels of emotions are clearly right lateralized. One version of these models (the'emotion type hypothesis') assumed that only elementary basic emotions should be subsumed by the right hemisphere, wheres more complex social emotions should be subtended by the left hemisphere. The other version (the 'schematic level of emotion hypothesis') assumed that the right hemisphere should subsume only the basic 'schematic' level of emotions, characterized by an automatic and unconscious processing, whereas the more propositional and conscious 'conceptual' level could be less lateralized or subsumed by the left hemisphere. This last model is supported by the obsevation that the right hemisphere reveals a modus operandi (i.e. a prevalence of the 'automatic' over the 'intentional' and of the 'unconscious' over the 'conscious' functional processing) that is typical of the 'schematic level of emotions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Graph convolutional network (GCN) based on the brain network has been widely used for EEG emotion recognition. However, most studies train their models directly without considering network dimensionality reduction beforehand. In fact, some nodes and edges are invalid information or even interference information for the current task. It is necessary to reduce the network dimension and extract the core network. To address the problem of extracting and utilizing the core network, a core network extraction model (CWGCN) based on channel weighting and graph convolutional network and a graph convolutional network model (CCSR-GCN) based on channel convolution and style-based recalibration for emotion recognition have been proposed. The CWGCN model automatically extracts the core network and the channel importance parameter in a data-driven manner. The CCSR-GCN model innovatively uses the output information of the CWGCN model to identify the emotion state. The experimental results on SEED show that: 1) the core network extraction can help improve the performance of the GCN model; 2) the models of CWGCN and CCSR-GCN achieve better results than the currently popular methods. The idea and its implementation in this paper provide a novel and successful perspective for the application of GCN in brain network analysis of other specific tasks.

To support investigation of the etiology and psychophysiology of medical traumatic stress, we developed a standardized set of emotionally-salient medical images, called the 'MEDical Image Collection' (MEDIC), for use in neuroimaging or psychological research. This study aimed to establish internal consistency, test re-test reliability, and congruent validity of the image set. A representative sample of 300 adults in the United States were recruited via research recruitment platform, Prolific. Participants rated 124 images depicting medical stimuli on one of two dimensions: emotional arousal (i.e., how strongly an evoked emotion is felt) or affective valence (i.e., how positive or negative the evoked emotion is). Sociodemographic and health-related characteristics, including experiences during the COVID-19 pandemic, were also assessed. To assess test re-test reliability, a subset (n = 200) rated the images on the same dimension a second time, 3 months later. The MEDIC image set was found to: (a) elicit a range of emotional arousal and valence ratings, (b) have excellent inter-rater reliability, (c) moderate test-retest reliability, and (d) good face validity. Results indicate the new MEDIC 124-image set is a reliable and valid instrument, enabling researchers to provide context-specific and emotionally-salient stimuli to individuals when studying affective responses in relation to health and medicine., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Data on the emotionality of words is important for the selection of experimental stimuli and sentiment analysis on large bodies of text. While norms for valence and arousal have been thoroughly collected in English, most languages do not have access to such large datasets. Moreover, theoretical developments lead to new dimensions being proposed, the norms for which are only partially available. In this paper, we propose a transformer-based neural network architecture for semantic and emotional norms extrapolation that predicts a whole ensemble of norms at once while achieving state-of-the-art correlations with human judgements on each. We improve on the previous approaches with regards to the correlations with human judgments by Δr = 0.1 on average. We precisely discuss the limitations of norm extrapolation as a whole, with a special focus on the introduced model. Further, we propose a unique practical application of our model by proposing a method of stimuli selection which performs unsupervised control by picking words that match in their semantic content. As the proposed model can easily be applied to different languages, we provide norm extrapolations for English, Polish, Dutch, German, French, and Spanish. To aid researchers, we also provide access to the extrapolation networks through an accessible web application., (© 2023. The Author(s).)

Speech emotion recognition (SER) technology involves feature extraction and prediction models. However, recognition efficiency tends to decrease because of gender differences and the large number of extracted features. Consequently, this paper introduces a SER system based on gender. First, gender and emotion features are extracted from speech signals to develop gender recognition and emotion classification models. Second, according to gender differences, distinct emotion recognition models are established for male and female speakers. The gender of speakers is determined before executing the corresponding emotion model. Third, the accuracy of these emotion models is enhanced by utilizing an advanced differential evolution algorithm (ADE) to select optimal features. ADE incorporates new difference vectors, mutation operators, and position learning, which effectively balance global and local searches. A new position repairing method is proposed to address gender differences. Finally, experiments on four English datasets demonstrate that ADE is superior to comparison algorithms in recognition accuracy, recall, precision, F1-score, the number of used features and execution time. The findings highlight the significance of gender in refining emotion models, while mel-frequency cepstral coefficients are important factors in gender differences., (© 2024. The Author(s).)

Aiming at the problem that existing emotion recognition methods fail to make full use of the information in the time, frequency, and spatial domains in the EEG signals, which leads to the low accuracy of EEG emotion classification, this paper proposes a multi-feature, multi-frequency band-based cross-scale attention convolutional model (CATM). The model is mainly composed of a cross-scale attention module, a frequency-space attention module, a feature transition module, a temporal feature extraction module, and a depth classification module. First, the cross-scale attentional convolution module extracts spatial features at different scales for the preprocessed EEG signals; then, the frequency-space attention module assigns higher weights to important channels and spatial locations; next, the temporal feature extraction module extracts temporal features of the EEG signals; and, finally, the depth classification module categorizes the EEG signals into emotions. We evaluated the proposed method on the DEAP dataset with accuracies of 99.70% and 99.74% in the valence and arousal binary classification experiments, respectively; the accuracy in the valence-arousal four-classification experiment was 97.27%. In addition, considering the application of fewer channels, we also conducted 5-channel experiments, and the binary classification accuracies of valence and arousal were 97.96% and 98.11%, respectively. The valence-arousal four-classification accuracy was 92.86%. The experimental results show that the method proposed in this paper exhibits better results compared to other recent methods, and also achieves better results in few-channel experiments.