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Stigzelius Saskia - One of the best experts on this subject based on the ideXlab platform.

  • Narcissism through the psychophysiological looking glass : physiological and self-reported emotional responses to negative evaluation in individuals with narcissistic traits
    Helsingfors universitet, 2020
    Co-Authors: Stigzelius Saskia
    Abstract:

    Objectives. Narcissism is a concept often used in everyday language to signify an overly positive self-image, but as a scientific term, it has multiple layers. There are many different disciplines studying narcissism, and recently the recognition of two phenotypic dimensions of narcissism has emerged. The two different dimensions of narcissism are an overt grandiose side and a covert vulnerable side. The most widely used measure of trait narcissism is the Narcissistic Personality Inventory (NPI), a self-report questionnaire measuring non-pathological narcissism. Even though the measure has been proved useful, self-reports are sensitive to self-enhancing bias, a central characteristic of narcissism. This has led to research based on methods measuring implicit responses, including physiological reactions that are difficult to hide. Research has already found an indication of a differing physiological reactivity to psychosocial stress, such as social evaluation, in individuals with high trait narcissism. The current study used measures of heart rate and facial Muscle activity to measure changes during a negative evaluation, changes that can reflect hidden emotions. In addition, self-reports were used to measure explicit emotional responses to the evaluation and to measure trait narcissism. The aim was to examine whether people scoring high in trait narcissism had different physiological and self-reported emotional reactions to negative social evaluation than those scoring low in trait narcissism. Methods. The study sample consisted of students from different universities in the Helsinki metropolitan area. The final sample included 52 participants, of which 63.2% were women, and the mean age was 27.16 years. The research followed a one-way repeated measures design, with feedback (negative vs. neutral) as a factor. All participants received both negative and neutral feedback from successive memory tasks. Prior to the lab session, participants had answered an e-form, including background information and the Narcissistic Personality Inventory (NPI). During the lab session, participants’ emotional states were measured with self-reports (subjective estimates on memory task performances, emotional reactions checklist, and Self-Assessment Manakin [SAM] including the emotional states valence, arousal, and dominance), and different physiological measures (heart rate with electrocardiography [ECG] and facial Muscles zygomaticus major, orbicularis oculi, and corrugator supercilii with facial electromyography [EMG]). The data was analysed with paired samples t-test, Wilcoxon signed-rank test, and multilevel (hierarchical) linear modeling (MLM). Results and conclusions. Negative feedback predicted more negative self-reported emotional valence and lower dominance, independent of trait narcissism. As for the physiological measures, negative feedback predicted lower heart rate and higher activity in the Face Muscle corrugator supercilii (CS), which is thought to reflect negative emotions. The physiological reactions were also independent of trait narcissism. However, trait narcissism predicted higher activity in CS despite the nature of the feedback. In conclusion, individuals with prominent narcissistic traits differed from those with non-prominent traits in only one aspect; they had an overall heightened activity in CS when being evaluated. On the other hand, previous research has also found CS activity to be associated with heightened attention, therefore an overall vigilance for self-related information could be an alternative explanation for the reaction of individuals with high trait narcissism. The results partially support the earlier discoveries of people with prominent narcissistic traits reacting with a heightened physiological responsiveness and vigilance to situations potentially threatening their self-view. However, the reactivity could also reflect alertness to all kind of self-relevant feedback, not just self-threatening information. The NPI used in the current study is thought to reflect more the grandiose dimension, and future research should therefore investigate emotional responses to self-threatening information in vulnerable narcissists. Also, further research on attentive processes in trait narcissism, both grandiose and vulnerable dimensions, are needed

  • Narcissism through the psychophysiological looking glass – Physiological and self-reported emotional responses to negative evaluation in individuals with narcissistic traits
    Helsingfors universitet, 2020
    Co-Authors: Stigzelius Saskia
    Abstract:

    Objectives. Narcissism is a concept often used in everyday language to signify an overly positive self-image, but as a scientific term, it has multiple layers. There are many different disciplines studying narcissism, and recently the recognition of two phenotypic dimensions of narcissism has emerged. The two different dimensions of narcissism are an overt grandiose side and a covert vulnerable side. The most widely used measure of trait narcissism is the Narcissistic Personality Inventory (NPI), a self-report questionnaire measuring non-pathological narcissism. Even though the measure has been proved useful, self-reports are sensitive to self-enhancing bias, a central characteristic of narcissism. This has led to research based on methods measuring implicit responses, including physiological reactions that are difficult to hide. Research has already found an indication of a differing physiological reactivity to psychosocial stress, such as social evaluation, in individuals with high trait narcissism. The current study used measures of heart rate and facial Muscle activity to measure changes during a negative evaluation, changes that can reflect hidden emotions. In addition, self-reports were used to measure explicit emotional responses to the evaluation and to measure trait narcissism. The aim was to examine whether people scoring high in trait narcissism had different physiological and self-reported emotional reactions to negative social evaluation than those scoring low in trait narcissism. Methods. The study sample consisted of students from different universities in the Helsinki metropolitan area. The final sample included 52 participants, of which 63.2% were women, and the mean age was 27.16 years. The research followed a one-way repeated measures design, with feedback (negative vs. neutral) as a factor. All participants received both negative and neutral feedback from successive memory tasks. Prior to the lab session, participants had answered an e-form, including background information and the Narcissistic Personality Inventory (NPI). During the lab session, participants’ emotional states were measured with self-reports (subjective estimates on memory task performances, emotional reactions checklist, and Self-Assessment Manakin [SAM] including the emotional states valence, arousal, and dominance), and different physiological measures (heart rate with electrocardiography [ECG] and facial Muscles zygomaticus major, orbicularis oculi, and corrugator supercilii with facial electromyography [EMG]). The data was analysed with paired samples t-test, Wilcoxon signed-rank test, and multilevel (hierarchical) linear modeling (MLM). Results and conclusions. Negative feedback predicted more negative self-reported emotional valence and lower dominance, independent of trait narcissism. As for the physiological measures, negative feedback predicted lower heart rate and higher activity in the Face Muscle corrugator supercilii (CS), which is thought to reflect negative emotions. The physiological reactions were also independent of trait narcissism. However, trait narcissism predicted higher activity in CS despite the nature of the feedback. In conclusion, individuals with prominent narcissistic traits differed from those with non-prominent traits in only one aspect; they had an overall heightened activity in CS when being evaluated. On the other hand, previous research has also found CS activity to be associated with heightened attention, therefore an overall vigilance for self-related information could be an alternative explanation for the reaction of individuals with high trait narcissism. The results partially support the earlier discoveries of people with prominent narcissistic traits reacting with a heightened physiological responsiveness and vigilance to situations potentially threatening their self-view. However, the reactivity could also reflect alertness to all kind of self-relevant feedback, not just self-threatening information. The NPI used in the current study is thought to reflect more the grandiose dimension, and future research should therefore investigate emotional responses to self-threatening information in vulnerable narcissists. Also, further research on attentive processes in trait narcissism, both grandiose and vulnerable dimensions, are needed

S. Kollias - One of the best experts on this subject based on the ideXlab platform.

  • Towards modeling embodied conversational agent character profiles using appraisal theory predictions in expression synthesis
    Applied Intelligence, 2009
    Co-Authors: L. Malatesta, A. Raouzaiou, K. Karpouzis, S. Kollias
    Abstract:

    Appraisal theories in psychology study facial expressions in order to deduct information regarding the underlying emotion elicitation processes. Scherer’s component process model provides predictions regarding particular Face Muscle deformations that are attributed as reactions to the cognitive appraisal stimuli in the study of emotion episodes. In the current work, MPEG-4 facial animation parameters are used in order to evaluate these theoretical predictions for intermediate and final expressions of a given emotion episode. We manipulate parameters such as intensity and temporal evolution of synthesized facial expressions. In emotion episodes originating from identical stimuli, by varying the cognitive appraisals of the stimuli and mapping them to different expression intensities and timings, various behavioral patterns can be generated and thus different agent character profiles can be defined. The results of the synthesis process are consequently applied to Embodied Conversational Agents (ECAs), aiming to render their interaction with humans, or other ECAs, more affective.

Weidong Cai - One of the best experts on this subject based on the ideXlab platform.

  • ICE-GAN: Identity-aware and Capsule-Enhanced GAN for Micro-Expression Recognition and Synthesis.
    arXiv: Computer Vision and Pattern Recognition, 2020
    Co-Authors: Chaoyi Zhang, Yang Song, Weidong Cai
    Abstract:

    Micro-expressions can reflect peoples true feelings and motives, which attracts an increasing number of researchers into the studies of automatic facial micro-expression recognition (MER). The detection window of micro-expressions is too short in duration to be perceived by human eye, while their subtle Face Muscle movements also make MER a challenging task for pattern recognition. To this end, we propose a novel Identity-aware and Capsule-Enhanced Generative Adversarial Network (ICE-GAN), which is adversarially completed with the micro-expression synthesis (MES) task, where synthetic Faces with controllable micro-expressions can be produced by the generator with distinguishable identity information to improve the MER performance. Meanwhile, the capsule-enhanced discriminator is optimized to simultaneously detect the authenticity and micro-expression class labels. Our ICE-GAN was evaluated on the 2nd Micro-Expression Grand Challenge (MEGC2019) and outperformed the winner by a significant margin (7%). To the best of our knowledge, we are the first work generating identity-preserving Faces with different micro-expressions based on micro-expression datasets only.

Cai Weidong - One of the best experts on this subject based on the ideXlab platform.

  • ICE-GAN: Identity-aware and Capsule-Enhanced GAN for Micro-Expression Recognition and Synthesis
    2020
    Co-Authors: Yu Jianhui, Zhang Chaoyi, Song Yang, Cai Weidong
    Abstract:

    Micro-expressions can reflect peoples true feelings and motives, which attracts an increasing number of researchers into the studies of automatic facial micro-expression recognition (MER). The detection window of micro-expressions is too short in duration to be perceived by human eye, while their subtle Face Muscle movements also make MER a challenging task for pattern recognition. To this end, we propose a novel Identity-aware and Capsule-Enhanced Generative Adversarial Network (ICE-GAN), which is adversarially completed with the micro-expression synthesis (MES) task, where synthetic Faces with controllable micro-expressions can be produced by the generator with distinguishable identity information to improve the MER performance. Meanwhile, the capsule-enhanced discriminator is optimized to simultaneously detect the authenticity and micro-expression class labels. Our ICE-GAN was evaluated on the 2nd Micro-Expression Grand Challenge (MEGC2019) and outperformed the winner by a significant margin (7%). To the best of our knowledge, we are the first work generating identity-preserving Faces with different micro-expressions based on micro-expression datasets only.Comment: 13 pages, 5 figure

Y. Chrysanthou - One of the best experts on this subject based on the ideXlab platform.

  • Visualisation Tool for Representing Synthetic Facial Emotional Expressions
    2008 International Conference Visualisation, 2008
    Co-Authors: A. Loizides, S. L. Himona, Y. Chrysanthou
    Abstract:

    This paper describes a Face-Muscle model system capable of emoting avatars in a variety of applications. The presented model produces dynamically changing facial expressions on computer generated Faces, using mathematically modeled Muscle deformations. The Muscle model used to distort sets of vertices in a 3D space, is independent of the geometric model and hence it can be applied to arbitrary Face meshes. The work presented here is based on the theories of Keith Waters and Fred Parke as detailed in their book Computer Facial Animation. The original GeoFace program was written by Keith Waters in 1994 at Cambridge Research Laboratories, and is available from the OpenGL organisation as part of a demo package.