Emotion influences human life and impacts daily life activities. During emotional processes, physiological signals interact with each other instead of functioning separately. Although unimodal and multimodal approaches have been explored for emotion classification, there is a lack of inclusion of central and peripheral nervous system signal interaction-based approaches. In this study, an attempt has been made to characterize valance emotional states using Electroencephalogram (EEG)- Electrodermal activity (EDA) based coupling. For this, multimodal signals are obtained from the publicly available DEAP database (n=32 subjects). The EEG signals are decomposed into θ, α, β, and bands and EDA signals are decomposed into phasic and tonic components. Then two EEG, three EDA, and two EEG-EDA coupling-based features are extracted and applied to three classifiers namely Random Forest (RF), Linear discriminant analysis, and Adaptive boosting. In addition, SHAP analysis is performed to explain classifiers\' performance with respect to features. The result shows that the proposed approach is able to classify valence emotional states. The feature combination of EEG, EDA, and EEG-EDA coupling-based features with an RF classifier performs best with an F1-score of 68.21%. SHAP analysis in frontal electrodes with γ band obtained better discrimination among different valance states. This study underscores the significance of the coupling studies of EEG with EDA in classifying emotion. Therefore, the proposed approach can be extended to emotional state assessment in clinical settings.

Emotional reactions to salient stimuli are well documented in psychophysiological research. However, some individual variables that can influence how people process emotions (i.e., empathy traits) have received little consideration. The present study investigated the relationship between emotions and empathy. Forty participants completed the Interpersonal Reactivity Index, a questionnaire that measure general and specific empathy dimensions. Then, emotional (erotic and mutilation) and non-emotional pictures were presented, during electroencephalographic recording. Valence and arousal were evaluated for each stimulus. Behavioral results revealed a positive correlation between the arousal induced by mutilation pictures and personal distress (i.e., feeling discomfort in emergency situations). At the electrophysiological level, theta activity elicited by positive and negative emotion processing in the superior frontal gyrus was associated with personal distress. Moreover, erotic-related theta in the middle frontal gyrus was associated with subjective judgement of erotic stimulus valence. Overall, theta activity modulated the interplay between emotions and empathy.

We introduce a novel dataset of affective, semantic, and descriptive norms for all facial emojis at the point of data collection. We gathered and examined subjective ratings of emojis from 138 German speakers along five essential dimensions: valence, arousal, familiarity, clarity, and visual complexity. Additionally, we provide absolute frequency counts of emoji use, drawn from an extensive Twitter corpus, as well as a much smaller WhatsApp database. Our results replicate the well-established quadratic relationship between arousal and valence of lexical items, also known for words. We also report associations among the variables: for example, the subjective familiarity of an emoji is strongly correlated with its usage frequency, and positively associated with its emotional valence and clarity of meaning. We establish the meanings associated with face emojis, by asking participants for up to three descriptions for each emoji. Using this linguistic data, we computed vector embeddings for each emoji, enabling an exploration of their distribution within the semantic space. Our description-based emoji vector embeddings not only capture typical meaning components of emojis, such as their valence, but also surpass simple definitions and direct emoji2vec models in reflecting the semantic relationship between emojis and words. Our dataset stands out due to its robust reliability and validity. This new semantic norm for face emojis impacts the future design of highly controlled experiments focused on the cognitive processing of emojis, their lexical representation, and their linguistic properties.

UNASSIGNED: Cochlear implants (CI) provide users with a spectrally degraded acoustic signal that could impact their auditory emotional experiences. This study evaluated the effects of CI-simulated spectral degradation on emotional valence and arousal elicited by environmental sounds.
UNASSIGNED: Thirty emotionally evocative sounds were filtered through a noise-band vocoder. Participants rated the perceived valence and arousal elicited by each of the full-spectrum and vocoded stimuli. These ratings were compared across acoustic conditions (full-spectrum, vocoded) and as a function of stimulus type (unpleasant, neutral, pleasant).
UNASSIGNED: Twenty-five young adults (age 19 to 34 years) with normal hearing.
UNASSIGNED: Emotional responses were less extreme for spectrally degraded (i.e., vocoded) sounds than for full-spectrum sounds. Specifically, spectrally degraded stimuli were perceived as more negative and less arousing than full-spectrum stimuli.
UNASSIGNED: By meticulously replicating CI spectral degradation while controlling for variables that are confounded within CI users, these findings indicate that CI spectral degradation can compress the range of sound-induced emotion independent of hearing loss and other idiosyncratic device- or person-level variables. Future work will characterize emotional reactions to sound in CI users via objective, psychoacoustic, and subjective measures.

UNASSIGNED: This study aimed to explore the arousal and valence that people experience in response to Hangul phonemes based on the gender of an AI speaker through comparison with Korean and Chinese cultures.
UNASSIGNED: To achieve this, 42 Hangul phonemes were used, in a combination of three Korean vowels and 14 Korean consonants, to explore cultural differences in arousal, valence, and the six foundational emotions based on the gender of an AI speaker. A total 136 Korean and Chinese women were recruited and randomly assigned to one of two conditions based on voice gender (man or woman).
UNASSIGNED: This study revealed significant differences in arousal levels between Korean and Chinese women when exposed to male voices. Specifically, Chinese women exhibited clear differences in emotional perceptions of male and female voices in response to voiced consonants. These results confirm that arousal and valence may differ with articulation types and vowels due to cultural differences and that voice gender can affect perceived emotions. This principle can be used as evidence for sound symbolism and has practical implications for voice gender and branding in AI applications.

Inequality is often one-sidedly framed as disadvantage, a practice identified as problematic by empirical research and critical scholarship, as it renders privilege invisible and shapes perceptions of and reactions to inequality. Importantly, inequality can mean differences in positive (e.g., promotions) or negative outcomes (e.g., harassment). Drawing on cognitive processes involved in (group) comparisons and the processing of positive and negative content, we predict that the valence of outcomes moderates the preference for disadvantage (vs. advantage) frames. We coded social media posts on gender inequality (Study 1, n = 1,402) and had participants in an online experiment (Study 2, n = 164) describe gender and sexual orientation inequality in positive and negative outcomes. Confirming hypotheses, people overall used disadvantage frames more, but were more likely to use advantage frames for inequality in positive (compared with negative) outcomes. We discuss theoretical implications for inequality framing research and practical implications for privilege awareness interventions.

Several cortical structures are involved in theory of mind (ToM), including the dorsolateral prefrontal cortex (dlPFC), the ventromedial prefrontal cortex (vmPFC), and the right temporo- parietal junction (rTPJ). We investigated the role of these regions in mind reading with respect to the valence of mental states. Sixty-five healthy adult participants were recruited and received transcranial direct current stimulation (tDCS) (1.5 mA, 20 min) with one week interval in three separate studies. The stimulation conditions were anodal tDCS over the dlPFC coupled with cathodal tDCS over the vmPFC, reversed stimulation conditions, and sham in the first study, and anodal tDCS over the vmPFC, or dlPFC, and sham stimulation, with an extracranial return electrode in the second and third study. During stimulation, participants underwent the reading mind from eyes/voice tests (RMET or RMVT) in each stimulation condition. Anodal left dlPFC/cathodal right vmPFC stimulation increased the accuracy of negative mental state attributions, anodal rTPJ decreased the accuracy of negative and neutral mental state attributions, and decreased the reaction time of positive mental state attributions. Our results imply that the neural correlates of ToM are valence-sensitive.

Extensive evaluations exist concerning the linkage between objective task demands and subsequent effects on user performance. However, the human user also experiences a range of emotions related to external task demands. Problematically, little is known about the associations between emotional valence, and arousal associated with the task demand-performance axis. In this paper, we advance a theoretical model concerning such interactive influences using three dimensions: (1) emotional valence, (2) arousal, and (3) task demand. The model evaluates the impact of these dimensions on user performance. It also identifies critical emotional user states, particularly those resulting in negative performance effects, as well as non-critical emotional states that can positively impact performance. Finally, we discuss the implications for affect-adaptive systems that can mitigate the impact of critical emotional states while leveraging the benefits of non-critical ones.
To effectively model performance and prevent errors in safety-critical human-machine systems, it is crucial to consider user states of emotional valence, arousal, and the current task demand. The proposed model enables the classification of critical and non-critical states within affect-adaptive systems. States characterised by negative valence, high arousal, and overload should be avoided to foster high performance, especially in safety-critical environments. Additionally, the present work offers recommendations for preserving and restoring non-critical states to ensure optimal performance and provides implications for training.

OBJECTIVE: Cognitive reappraisal (CR), as an adaptive emotion regulation strategy, may play a role in transforming affect in a positive direction during or after exercise, thereby supporting physical activity (PA) adherence. The present study aimed to test the associations among PA, CR frequency, and affective response to PA, and further to examine the role of CR on PA behavior through affective response.
METHODS: A cross-sectional study was conducted with a sample of 105 adults, 74 of whom were women, with a mean age of 25.91. Self-report scales were used to measure PA, CR, and affective response to PA. Along with scales, demographic questions on age, sex, and education level were included. Data was collected via an online questionnaire.
RESULTS: The frequency of CR use was positively associated with affective response, and affective response with PA behavior. Mediation analysis revealed that affective response mediated the relationship between CR and PA.
CONCLUSIONS: Results were in the expected direction demonstrating the mediating role of affective response between CR and PA which implies that PA adherence might be facilitated by CR engagement. PA intervention programs should consider implementing CR ability and use frequency improving techniques.

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.