Emotional Cues Research Articles

DailyConnect: Piloting Interventions of Situation-Based Emotional Understanding in Naturalistic Home Settings for Children with Autism Spectrum Disorder

DailyConnect is a visual-based mobile application that supports children with autism spectrum disorder (ASD) in recalling memories by reviewing photos through discrete trial training (DTT) to understand situation-based emotions. To assess DailyConnect and its adaptability to a child’s characteristics and emotional situations, a pilot study was conducted that included 15 children with ASD and their parents and teachers. The DTT steps—memory recall and situation recognition, emotion recognition, emotion cues, facial expression recognition, and response behavior—were reliable in assessing the understanding of emotional situations when compared before and after the intervention in four categories of emotional situations, namely, happiness, sadness, anger, and fear. The results revealed that DailyConnect improves the understanding of situation-based emotions, particularly negative emotions (e.g., sadness: mean diff = −.687, sig. < .01, T = −3.866, d = 1.006; anger: mean diff = −.952, sig. < .01, T = −6.187, d = .705; fear: mean diff = −.961, sig. < .01, T = −5.522, d = .627); however, its effectiveness varied for children in different emotional situations. Furthermore, subjective feedback from participants and users (parents and teachers) provided insights into design considerations for similar mobile aids.

Episodic memory through a social and emotional lens.

Negative emotion enhances item memory but may reduce associative memory. Social information may also enhance memory, yet how social and emotional cues combine to affect memory for focal and surrounding details is unknown. Gender differences may also exist, but whether women and men encode and remember negative and social information differently is unclear. This study examines how social information contributes to or interacts with emotion to influence item and associative memory, and whether gender plays a role in how social and/or emotional information is recognized. Discovery and replication samples (N = 706) were recruited. Stimuli included (1) images with varying social and emotional content categorized into four conditions: negative social, negative nonsocial, neutral social, neutral nonsocial and (2) neutral images of objects paired with target stimuli to assess associative memory. Participants viewed the image pairings (Encoding). Twenty-four hours later, item and associative recognition memory were tested. Item recognition memory was better for negative vs. neutral and social vs. nonsocial images. By contrast, associative recognition memory was worse for negative vs. neutral, but better for social vs. nonsocial images. Finally, women demonstrated similar item memory performance compared to men but better associative recognition memory performance overall compared to men. Emotional and social cues impart distinct effects on how we form holistic episodic memories, highlighting the importance of considering these critical factors when striving to understand how and what we remember. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Emotional Perception: Divergence of Early and Late Event-related Potential Modulation.

The early posterior negativity (EPN) is a mid-latency ERP component that is reliably enhanced by emotional cues, with a deflection beginning between 150 and 200 msec after stimulus onset. The brief, bilateral occipital EPN is followed by the centroparietal late positive potential (LPP), a long duration slow-wave that is strongly associated with emotional arousal ratings of scenes. A recent study suggests that the EPN is particularly sensitive to human bodies in scenes, independent of emotional intensity. Here, we directly investigate the influence of human body features on EPN modulation, using emotional and neutral scenes depicting people across a range of body exposures and orientations, in addition to scenes of pleasant, neutral, and unpleasant animals. The results demonstrate that the EPN is quite sensitive to human body features and weakly related to arousal ratings, whereas the LPP is strongly modulated by scenes that receive high arousal ratings. Based on these results and relevant work on body-specific visual perception, we speculate that modulation of the EPN may strongly reflect the early detection of human bodies, which serves as a predictor of emotional significance, whereas LPP modulation is more closely associated with the extended elaborative processing of scenes that are explicitly judged to be emotionally arousing.

The Persuasive Power of Emoticons in Electronic Word-of-Mouth Communication on Social Networking Services

Emotional expressions are ubiquitous in electronic word-of-mouth (eWOM) communication, but their effect on eWOM persuasiveness and the underlying mechanisms in the context of social networking services (SNS) have been underexplored. This research focuses on an extensively used nonverbal emotional cue in computer-mediated communication—the emoticon. Drawing on the emotion as social information model (EASI), we propose a conceptual framework to understand whether, how, and when emoticons influence the persuasiveness of eWOM on SNS. Results from a field experiment and a series of online experiments show that emoticons can increase eWOM persuasiveness through the mediating effects of enhanced recipient empathy and trust toward the sender and that these effects vary across situations. Specifically, the persuasive effect of emoticons occurs for both positive and negative eWOM when recipients and senders are close to each other. However, this effect occurs only for negative eWOM when recipients and senders have distant relationships. We discuss the theoretical and practical implications of these findings and identify several opportunities for future research.

Study on emotion recognition bias in different regional groups

Human-machine communication can be substantially enhanced by the inclusion of high-quality real-time recognition of spontaneous human emotional expressions. However, successful recognition of such expressions can be negatively impacted by factors such as sudden variations of lighting, or intentional obfuscation. Reliable recognition can be more substantively impeded due to the observation that the presentation and meaning of emotional expressions can vary significantly based on the culture of the expressor and the environment within which the emotions are expressed. As an example, an emotion recognition model trained on a regionally-specific database collected from North America might fail to recognize standard emotional expressions from another region, such as East Asia. To address the problem of regional and cultural bias in emotion recognition from facial expressions, we propose a meta-model that fuses multiple emotional cues and features. The proposed approach integrates image features, action level units, micro-expressions and macro-expressions into a multi-cues emotion model (MCAM). Each of the facial attributes incorporated into the model represents a specific category: fine-grained content-independent features, facial muscle movements, short-term facial expressions and high-level facial expressions. The results of the proposed meta-classifier (MCAM) approach show that a) the successful classification of regional facial expressions is based on non-sympathetic features b) learning the emotional facial expressions of some regional groups can confound the successful recognition of emotional expressions of other regional groups unless it is done from scratch and c) the identification of certain facial cues and features of the data-sets that serve to preclude the design of the perfect unbiased classifier. As a result of these observations we posit that to learn certain regional emotional expressions, other regional expressions first have to be “forgotten”.

Informational vs. emotional B2B firm-generated-content on social media engagement: Computerized visual and textual content analysis

While social media marketing plays an increasingly significant role in the B2B context, there is still limited research examining how to increase B2B social media engagement. The need for more research is becoming more pressing given the recent shift in social media content from text-centric to image-oriented experience. Building on the elaboration likelihood model and employing computerized visual and textual analysis tools, the present research investigates how informational and emotional cues in B2B social media content influence viewer engagement. By analyzing 5362 single-image posts from the Instagram accounts of 10 B2B companies across five industries, this research demonstrates that informational cues are more effective than emotional cues in driving viewer engagement, and that informational cues are even more effective when presented in visual content, as compared to textual content. The findings of this research contribute to the literature on B2B social media literature and offer managerial implications for B2B social media marketing.

Behavioral Insights from Crowdfunding Financing: What Do Social Media Ties, Emotional Cues and Sentiment Tell Us?

Behavioral Insights from Crowdfunding Financing: What Do Social Media Ties, Emotional Cues and Sentiment Tell Us?

The Pragmatics of Fiction: Literature, Stage and Screen Discourse

The Pragmatics of Fiction: Literature, Stage and Screen Discourse

The relationship between facilitating emotional cues and medical students’ clinical communication performance in qualifying exams

A cross-sectional study design explored the relationship between medical students’ Objective Structured Clinical Examination (OSCE) clinical communication ratings and their responsiveness to simulated patient (SP) verbal emotional cues in their qualifying OSCE. Data were collected from two cohorts of fourth-year medical students (n = 37), and responses to patient cues that facilitated further disclosure or related discussion – known as provide space responses – from two OSCE communication stations were measured by coding video footage with the Verona Coding Definition of Emotional Sequences (VR-CoDES). The 37 medical students were representative of the larger cohort (n = 508) in terms of age. A significant positive correlation with a medium effect was found between OSCE clinical communication ratings and provide space responses. OSCE clinical communication ratings could differentiate between students who adopted patient-centred facilitative behaviours and those who did not.

An Automatic Classification Method for Multiple Music Genres by Integrating Emotions and Intelligent Algorithms

ABSTRACT In this paper, we present an approach to improve the effectiveness of automatic classification of music genres by integrating emotion and intelligent algorithms. We propose an automatic recognition and classification algorithm for music spectra, which takes into account emotional cues that can be extracted from music to improve classification accuracy. To achieve this goal, we set different weight coefficients, which are continuously adjusted based on the convergence process of the previous iteration. The size of each weighting coefficient is adaptively controlled to reduce the number of iterations of the reconstruction process, thereby reducing the algorithm’s computational complexity and speeding up its convergence. We conducted several experiments to evaluate the effectiveness of our proposed method. The experimental results demonstrate that the automatic classification method of music genres, which integrates emotion and intelligent algorithms, can significantly improve the accuracy of automatic music genre classification. Moreover, our approach reduces the algorithm’s computational complexity, resulting in a faster convergence speed. Our proposed approach provides a promising solution for automatic music genre classification that takes into account emotional cues. The integration of emotion and intelligent algorithms can help achieve higher accuracy and reduce computational complexity, making the proposed method applicable in various scenarios.

Cortical haemodynamic responses predict individual ability to recognise vocal emotions with uninformative pitch cues but do not distinguish different emotions.

We investigated the cortical representation of emotional prosody in normal-hearing listeners using functional near-infrared spectroscopy (fNIRS) and behavioural assessments. Consistent with previous reports, listeners relied most heavily on F0 cues when recognizing emotion cues; performance was relatively poor-and highly variable between listeners-when only intensity and speech-rate cues were available. Using fNIRS to image cortical activity to speech utterances containing natural and reduced prosodic cues, we found right superior temporal gyrus (STG) to be most sensitive to emotional prosody, but no emotion-specific cortical activations, suggesting that while fNIRS might be suited to investigating cortical mechanisms supporting speech processing it is less suited to investigating cortical haemodynamic responses to individual vocal emotions. Manipulating emotional speech to render F0 cues less informative, we found the amplitude of the haemodynamic response in right STG to be significantly correlated with listeners' abilities to recognise vocal emotions with uninformative F0 cues. Specifically, listeners more able to assign emotions to speech with degraded F0 cues showed lower haemodynamic responses to these degraded signals. This suggests a potential objective measure of behavioural sensitivity to vocal emotions that might benefit neurodiverse populations less sensitive to emotional prosody or hearing-impaired listeners, many of whom rely on listening technologies such as hearing aids and cochlear implants-neither of which restore, and often further degrade, the F0 cues essential to parsing emotional prosody conveyed in speech.

Angry, Sad, or Scared? Within-valence Mapping of Emotion Words to Facial and Body Cues in 2 to 4-Year-Old Children

The acquisition of emotion words is critical to children’s socio-emotional development. Previous studies report that children acquire emotion words gradually during ages 3–5 and beyond. The majority of this work, however, has used demanding tasks for young children (e.g., asking children to label emotion-related facial configurations) and has predominantly relied on facial configurations. Here we designed a child-friendly, word-comprehension task incorporating both facial configurations and body language. In two preregistered online experiments, we asked two to four-year-olds (N = 96) to connect emotion words—happy, sad, angry, and scared—to either facial configurations (Experiment 1) or combined facial and body cues (Experiment 2). We found relatively early competence in understanding emotion words, especially those of the same-valence. All age groups, including 2-year-olds, successfully linked emotion words to corresponding facial configurations (Experiment 1). Experiment 2 replicated this pattern and further showed that children performed equally well (though not substantially better) when given additional body cues. Parental reports of children’s exposure to and use of masks during the COVID-19 pandemic did not correlate with children’s performance in either experiment. Even before children can produce emotion words in an adult-like manner, they possess at least a partial understanding of those words and can map them to emotion cues within valence domains.

Algorithmic voice transformations reveal the phonological basis of language-familiarity effects in cross-cultural emotion judgments.

People have a well-described advantage in identifying individuals and emotions in their own culture, a phenomenon also known as the other-race and language-familiarity effect. However, it is unclear whether native-language advantages arise from genuinely enhanced capacities to extract relevant cues in familiar speech or, more simply, from cultural differences in emotional expressions. Here, to rule out production differences, we use algorithmic voice transformations to create French and Japanese stimulus pairs that differed by exactly the same acoustical characteristics. In two cross-cultural experiments, participants performed better in their native language when categorizing vocal emotional cues and detecting non-emotional pitch changes. This advantage persisted over three types of stimulus degradation (jabberwocky, shuffled and reversed sentences), which disturbed semantics, syntax, and supra-segmental patterns, respectively. These results provide evidence that production differences are not the sole drivers of the language-familiarity effect in cross-cultural emotion perception. Listeners' unfamiliarity with the phonology of another language, rather than with its syntax or semantics, impairs the detection of pitch prosodic cues and, in turn, the recognition of expressive prosody.

A graph attention network utilizing multi-granular information for emotion-cause pair extraction

Emotion-cause pair extraction (ECPE) aims to extract emotion and cause clauses underlying a text and pair them. Most of the recent approaches to this problem adopt deep neural networks to model the inter-clause dependency, without making full use of information at word level and document level. In this paper, we propose a model that utilizes multi-granular information, including word-level, clause-level, and document-level information, to facilitate emotion-cause pair extraction. Our model consists of two fully-connected clause graphs, including emotion graph and cause graph, and graph attention is applied to learn emotion-specific and cause-specific representations which are then used to generate document-level representations. To exploit the mutual indication between emotion and cause, a cross-graph co-attention mechanism is proposed. Moreover, external knowledge of emotional and causal cues is incorporated to provide word-level indicative information for emotion-cause pair extraction. The proposed model is tested on both Chinese [1] and English [2] datasets, and the results show that our model achieves the state-of-the-art performance on both datasets.

An Automatic Stress Analysis and Emotion Detection Framework for Humans Based on Several Brain Signals

In common parlance, stress is the feeling people get when they have a lot on their plates and are having trouble keeping up with everything. Although some degree of stress might be useful in the short term, chronic stress has serious negative effects on health, including increased risk of cardiovascular problems such heart disease, high blood pressure, and stroke. Depression, anxiety, and personality disorders are also possible outcomes. Hence, stress detection is helpful for managing stress-related health problems. Perceptual, behavioural, and physiological reactions all provide useful indicators of stress levels. Based on feature extraction and classification methods, numerous researchers have presented a wide variety of methods. Some of these methods are difficult to implement and produce unreliable outcomes when applied to the study of human stress.Patient denial, insensitivity, subjective biases, and inaccuracy are only some of the issues that arise from relying solely on doctor-patient interaction and scale analysis when diagnosing Stress. To better predict clinical results, a computerised, objective system is needed for Stress diagnosis and treatment. In an effort to better detect Stress, this research modifies EEG data and use machine learning algorithms. Ten participants' EEGs were recorded using a Narosky system while they were exposed to various emotional face cues. Psychologists relied on the EEG signal as a diagnostic tool for Stress. Both machine learning and deep learning were used to analyse the features. Using PCA, ICA, and EMD for BCI applications yields significant results. With SVM, a programmer can reap many benefits: PCA has great generalisation properties, and it can detect tension and pressure from EEG signals. The effect of overtraining is particularly vulnerable to the curse-of-dimensionality when the signals are negative. By analysing EEG waves, we were able to detect Stress with these benefits. The experimental study provides a somewhat comprehensive summary of the various methods, all of which rely on frequency domain analysis of 14 EEG data.

Randomized Trial of Telegenetic Counseling for Gene Testing in Huntington’s Disease (P1-11.011)

<h3>Objective:</h3> To determine the feasibility and patient satisfaction of telegenetic counseling for Huntington’s Disease (HD). <h3>Background:</h3> Genetic counseling is necessary for pre-symptomatic or symptomatic HD genetic testing, but the lack of access to counseling due to geography or expense is a critical gap for many patients. The hypothesis of this study was that there would be no difference in patient satisfaction between telegenetic counseling (teleGC) or in-person counseling (in-personGC) for HD testing. <h3>Design/Methods:</h3> This was a prospective, randomized, unblinded study of either teleGC or in-personGC for HD gene testing. Participants had standardized genetic counseling from a certified genetic counselor in the clinic or via HIPPA appropriate telemedicine platform first, then crossed over. A study coordinator interviewed the participant using a telehealth survey after each encounter. <h3>Results:</h3> 19 in-personGC and 15 teleGC participants were included: 68% women, 41±15 yrs, 80% white, 10% Hispanic, and +CAG=45±4.4 (n=15) (P&gt;0.1). All participants were satisfied with their initial counseling experience when asked to rate on a scale of 1–10 (median 10/10, p=0.94). The majority of symptomatic HD participants (5/7) preferred in-person GC. The main advantage of teleGC was reduction in travel time for the in-personGC first (n=16) and teleGC first (n=11) groups. Technical challenges were reported (n=11) and the counseling slide deck was difficult to see (n=4) with teleGC. Visually seeing the genetic counselor improved understanding for both in-personGC (n=10) and teleGC (n=8) participants. Participants felt they were able to pick up on emotional cues (n=33) and were comfortable asking questions (n=34). <h3>Conclusions:</h3> Telegenetic counseling is a feasible option for HD gene testing, if patients are able to overcome technical issues. Having a video visit, rather than a phone call, should be considered when using telegenetic counseling for HD gene testing. In-person counseling may be preferred to increase understanding of the material in some patients, such as motor manifest HD. <b>Disclosure:</b> Dr. Hall has received personal compensation in the range of $10,000-$49,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for American Academy of Neurology. Dr. Hall has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Elsevier - Parkinsonism and Related Disorders. Dr. Hall has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Annals of Neurology. The institution of Dr. Hall has received research support from Parkinson’s Foundation. The institution of Dr. Hall has received research support from CHDI. The institution of Dr. Hall has received research support from Biohaven. The institution of Dr. Hall has received research support from Neurocrine. The institution of Dr. Hall has received research support from Uniqure. Dr. Hall has received personal compensation in the range of $500-$4,999 for serving as a Study section with NIH. Dr. Rosenbaum has nothing to disclose. Jacob Hawkins has nothing to disclose. Bichum Ouyang has nothing to disclose. Christa Suzanne Cooper, PA has nothing to disclose. Dr. Patel has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Abbott Laboratories. Dr. Patel has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Abbvie Pharmaceuticals. Dr. Patel has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Teva Pharmaceuticals.

Control Strategy of Synchronous Reluctance Motor Using Empirical Information Brain Emotional Learning Based Intelligent Controller Considering Magnetic Saturation

The synchronous reluctance motor (SynRM) has significant nonlinear characteristics due to the problems of magnetic saturation and cross-coupling and the poor adaptability of the general controller to parameter changes seriously affects the control performance of the motor. In order to solve the above problems, this paper proposed a control system for the SynRM with a brain emotion controller based on empirical information to solve the motor control problem of magnetic saturation. Firstly, the nonlinear mathematical model of the SynRM considering magnetic saturation is established by introducing the magnetic saturation parameter. Secondly, the sensory input function and emotional cue function based on systematic error are given and the vector control system of the SynRM considering magnetic saturation is designed. The influence of the parameters and the learning rate of the brain emotional learning based intelligent controller (EI-BELBIC) on the adjustment range of the controller parameters is studied. Then the SynRM is controlled under different working conditions and the control effect is observed. The results show that the designed vector control system of the SynRM based on EI-BELBIC has strong reliability, accurate control, rapid response, and strong anti-interference ability under magnetic saturation.

Impairments in recognition of emotional facial expressions, affective prosody, and multisensory facilitation of response time in high-functioning autism.

Deficits in emotional perception are common in autistic people, but it remains unclear to which extent these perceptual impairments are linked to specific sensory modalities, specific emotions or multisensory facilitation. This study aimed to investigate uni- and bimodal perception of emotional cues as well as multisensory facilitation in autistic (n = 18, mean age: 36.72 years, SD: 11.36) compared to non-autistic (n = 18, mean age: 36.41 years, SD: 12.18) people using auditory, visual and audiovisual stimuli. Lower identification accuracy and longer response time were revealed in high-functioning autistic people. These differences were independent of modality and emotion and showed large effect sizes (Cohen's d 0.8-1.2). Furthermore, multisensory facilitation of response time was observed in non-autistic people that was absent in autistic people, whereas no differences were found in multisensory facilitation of accuracy between the two groups. These findings suggest that processing of auditory and visual components of audiovisual stimuli is carried out more separately in autistic individuals (with equivalent temporal demands required for processing of the respective unimodal cues), but still with similar relative improvement in accuracy, whereas earlier integrative multimodal merging of stimulus properties seems to occur in non-autistic individuals.

How physicians respond to the emotional expressions of people with cancer

The aim of study is to examine patient emotional cues to oncologists’ responses and explore the association between the concerns and emotional cues during the consultation and the physicians’ response to them throughout treatment, satisfaction, and the assessment of the patients’ perception of the established communication. Cross-sectional design, involved 12 adults patients undergoing cancer treatment and eight physicians in the study. The twelve video-recorded medical consultations werecoded (349 cues/concern) using the Verona coding definitions of emotional sequences (VR-CoDES). A strong association between explicit with reducing space responses and the physiological symptoms cues (x²=6.029; p=0.014), and related to the repetition cue of the content by the patient (x²=5.599; p=0.018) was observed. Patients expressed fewer non-verbal behaviors (for example, crying, silence, silent pauses), as they had been undergoing treatment for a longer time, therefore, provided with more empathic responses from physicians. The identification of emotions can help physicians to further explore patients’ underlying cues that reveal emotional distress concerning illness and treatment in a less explicit way. There is a need for improvement in the physician’s ability to recognize patients’ concerns and to provide space for patients to have comprehensive health care, considering the severity of cancer disease and its negative emotional impacts for patients.

Informational and emotional appeals of cover image in crowdfunding platforms and the moderating role of campaign outputs

The first-stage decision is critical in the decision process in crowdfunding, where the cover image plays an important role in forming first impressions and persuading click funders. This study explores how emotional visual cues (human face) and informational visual cues (visual text) in the cover image affect funders' decisions and how the effects differ across campaigns. The results demonstrate the great persuasive power of human faces and visual text. We further illustrate the effects of joyful expressions and image-text congruency as well as the non-significant influence of the length and polarity of visual text. Moreover, emotional visual cues are more effective in intangible product campaigns, while informational visual cues are more effective in tangible product campaigns, and both are important in social service campaigns. Valuable insight is provided to creators about the design of the cover image.