What Emotion Does the “Facial Expression of Disgust” Express?
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Applying a Discrete Emotion Perspective
AROUSAL OR RELEVANCE? APPLYING A DISCRETE EMOTION PERSPECTIVE TO AGING AND AFFECT REGULATION SARA E. LAUTZENHISER Bachelor of Science in Psychology Ashland University May 2015 Submitted in partial fulfillment of requirements for the degree MASTER OF ARTS IN PSYCHOLOGY At the CLEVELAND STATE UNIVERSITY May 2019 We hereby approve this thesis For SARA E. LAUTZENHISER Candidate for the Master of Arts in Experimental Research Psychology For the Department of Psychology And CLEVELAND STATE UNIVERSITY’S College of Graduate Studies by __________________________ Eric Allard, Ph.D. __________________________ Department & Date __________________________ Andrew Slifkin, Ph. D. (Methodologist) __________________________ Department & Date __________________________ Conor McLennan, Ph.D. __________________________ Department & Date __________________________ Robert Hurley, Ph. D. __________________________ Department & Date Student’s Date of Defense May 10, 2019 AROUSAL OR RELEVANCE? APPLYING A DISCRETE EMOTION PERSPECTIE TO AGING AND AFFECT REGULATION SARA E. LAUTZENHISER ABSTRACT While research in the psychology of human aging suggests that older adults are quite adept at managing negative affect, emotion regulation efficacy may depend on the discrete emotion elicited. For instance, prior research suggests older adults are more effective at dealing with emotional states that are more age-relevant/useful and lower in intensity (i.e., sadness) relative to less relevant/useful or more intense (i.e., anger). The goal of the present study was to probe this discrete emotions perspective further by addressing the relevance/intensity distinction within a broader set of negative affective states (i.e., fear and disgust, along with anger and sadness). Results revealed that participants reported relatively high levels of the intended emotion for each video, while also demonstrating significant affective recovery after the attentional refocusing task. -
DISGUST: Features and SAWCHUK and Clinical Implications
Journal of Social and Clinical Psychology, Vol. 24, No. 7, 2005, pp. 932-962 OLATUNJIDISGUST: Features AND SAWCHUK and Clinical Implications DISGUST: CHARACTERISTIC FEATURES, SOCIAL MANIFESTATIONS, AND CLINICAL IMPLICATIONS BUNMI O. OLATUNJI University of Massachusetts CRAIG N. SAWCHUK University of Washington School of Medicine Emotions have been a long–standing cornerstone of research in social and clinical psychology. Although the systematic examination of emotional processes has yielded a rather comprehensive theoretical and scientific literature, dramatically less empirical attention has been devoted to disgust. In the present article, the na- ture, experience, and other associated features of disgust are outlined. We also re- view the domains of disgust and highlight how these domains have expanded over time. The function of disgust in various social constructions, such as cigarette smoking, vegetarianism, and homophobia, is highlighted. Disgust is also becoming increasingly recognized as an influential emotion in the onset, maintenance, and treatment of various phobic states, Obsessive–Compulsive Disorder, and eating disorders. In comparison to the other emotions, disgust offers great promise for fu- ture social and clinical research efforts, and prospective studies designed to improve our understanding of disgust are outlined. The nature, structure, and function of emotions have a rich tradition in the social and clinical psychology literature (Cacioppo & Gardner, 1999). Although emotion theorists have contested over the number of discrete emotional states and their operational definitions (Plutchik, 2001), most agree that emotions are highly influential in organizing thought processes and behavioral tendencies (Izard, 1993; John- Preparation of this manuscript was supported in part by NIMH NRSA grant 1F31MH067519–1A1 awarded to Bunmi O. -
About Emotions There Are 8 Primary Emotions. You Are Born with These
About Emotions There are 8 primary emotions. You are born with these emotions wired into your brain. That wiring causes your body to react in certain ways and for you to have certain urges when the emotion arises. Here is a list of primary emotions: Eight Primary Emotions Anger: fury, outrage, wrath, irritability, hostility, resentment and violence. Sadness: grief, sorrow, gloom, melancholy, despair, loneliness, and depression. Fear: anxiety, apprehension, nervousness, dread, fright, and panic. Joy: enjoyment, happiness, relief, bliss, delight, pride, thrill, and ecstasy. Interest: acceptance, friendliness, trust, kindness, affection, love, and devotion. Surprise: shock, astonishment, amazement, astound, and wonder. Disgust: contempt, disdain, scorn, aversion, distaste, and revulsion. Shame: guilt, embarrassment, chagrin, remorse, regret, and contrition. All other emotions are made up by combining these basic 8 emotions. Sometimes we have secondary emotions, an emotional reaction to an emotion. We learn these. Some examples of these are: o Feeling shame when you get angry. o Feeling angry when you have a shame response (e.g., hurt feelings). o Feeling fear when you get angry (maybe you’ve been punished for anger). There are many more. These are NOT wired into our bodies and brains, but are learned from our families, our culture, and others. When you have a secondary emotion, the key is to figure out what the primary emotion, the feeling at the root of your reaction is, so that you can take an action that is most helpful. . -
Disgust: Evolved Function and Structure
Psychological Review © 2012 American Psychological Association 2013, Vol. 120, No. 1, 65–84 0033-295X/13/$12.00 DOI: 10.1037/a0030778 Disgust: Evolved Function and Structure Joshua M. Tybur Debra Lieberman VU University Amsterdam University of Miami Robert Kurzban Peter DeScioli University of Pennsylvania Brandeis University Interest in and research on disgust has surged over the past few decades. The field, however, still lacks a coherent theoretical framework for understanding the evolved function or functions of disgust. Here we present such a framework, emphasizing 2 levels of analysis: that of evolved function and that of information processing. Although there is widespread agreement that disgust evolved to motivate the avoidance of contact with disease-causing organisms, there is no consensus about the functions disgust serves when evoked by acts unrelated to pathogen avoidance. Here we suggest that in addition to motivating pathogen avoidance, disgust evolved to regulate decisions in the domains of mate choice and morality. For each proposed evolved function, we posit distinct information processing systems that integrate function-relevant information and account for the trade-offs required of each disgust system. By refocusing the discussion of disgust on computational mechanisms, we recast prior theorizing on disgust into a framework that can generate new lines of empirical and theoretical inquiry. Keywords: disgust, adaptation, evolutionary psychology, emotion, cognition Research concerning disgust has expanded in recent years (Ola- selection pressure driving the evolution of the disgust system, but tunji & Sawchuk, 2005; Rozin, Haidt, & McCauley, 2009), and there has been less precision in identifying the selection pressures contemporary disgust researchers generally agree that an evolu- driving the evolution of disgust systems unrelated to pathogen tionary perspective is necessary for a comprehensive understand- avoidance (e.g., behavior in the sexual and moral domains). -
Bodily Maps of Emotions
Bodily maps of emotions Lauri Nummenmaaa,b,c,1, Enrico Glereana, Riitta Harib,1, and Jari K. Hietanend aDepartment of Biomedical Engineering and Computational Science and bBrain Research Unit, O. V. Lounasmaa Laboratory, School of Science, Aalto University, FI-00076, Espoo, Finland; cTurku PET Centre, University of Turku, FI-20521, Turku, Finland; and dHuman Information Processing Laboratory, School of Social Sciences and Humanities, University of Tampere, FI-33014, Tampere, Finland Contributed by Riitta Hari, November 27, 2013 (sent for review June 11, 2013) Emotions are often felt in the body, and somatosensory feedback independence of bodily topographies across emotions. We pro- has been proposed to trigger conscious emotional experiences. pose that consciously felt emotions are associated with culturally Here we reveal maps of bodily sensations associated with different universal, topographically distinct bodily sensations that may emotions using a unique topographical self-report method. In five support the categorical experience of different emotions. n = experiments, participants ( 701) were shown two silhouettes of Results bodies alongside emotional words, stories, movies, or facial expres- sions. They were asked to color the bodily regions whose activity We ran five experiments, with 36–302 participants in each. In they felt increasing or decreasing while viewing each stimulus. experiment 1, participants reported bodily sensations associated “ ” “ ” Different emotions were consistently associated with statistically with six basic and seven nonbasic ( complex ) emotions, as separable bodily sensation maps across experiments. These maps well as a neutral state, all described by the corresponding emo- were concordant across West European and East Asian samples. tion words. Fig. 2 shows the bodily sensation maps associated Statistical classifiers distinguished emotion-specific activation maps with each emotion. -
What Disgust Does and Does Not Do for Moral Cognition Jared Piazzaa
What Disgust Does and Does Not Do for Moral Cognition Jared Piazzaa, Justin F. Landyb, Alek Chakroffc Liane Youngd, Emily Wassermand a Lancaster University, Department of Psychology b University of Chicago Booth School of Business cCharlie Finance Co., San Francisco, CA dBoston College, Psychology Department 2 1. Introduction Disgust is typically characterized as a negative emotion associated with the rejection of distasteful or contaminating objects (Rozin and Fallon 1987). The physiological aspects of disgust involve nausea and loss of appetite, and the bodily expression of disgust includes behaviors (e.g., gagging, vomiting) designed to orally block or expel noxious substances (Ekman and Friesen 1971; Royzman, Leeman and Sabini 2008; Rozin, Haidt and McCauley 2008; Yoder, Widen and Russell 2016). The canonical elicitors of disgust are well documented: many people report feeling nauseous or sick at the sight or smell of oral contaminants (e.g., rotten food, bodily waste) and/or disease vectors (e.g., blood, skin maladies, sexual fluids, certain animals; Curtis, Aunger and Rabie, 2004; Haidt, McCauley and Rozin, 1994; Olatunji et al. 2007). It is uncontroversial that disgust can also be evoked in the context of a moral offense. What remains controversial is disgust’s role or relevance within a moral context. When Armin Meiwes, the Rotenburg Cannibal, was discovered to have eaten the severed penis of his voluntary victim, before killing him and consuming his flesh over the next ten months, the story of this crime undoubtedly aroused disgust (and horror) in many of us. The relevant question is not whether we felt disgust about this crime—for most of us, human penis is not on the menu, and the thought of Meiwes’ preferred cuisine is deeply distasteful. -
Emotion Classification Based on Biophysical Signals and Machine Learning Techniques
S S symmetry Article Emotion Classification Based on Biophysical Signals and Machine Learning Techniques Oana Bălan 1,* , Gabriela Moise 2 , Livia Petrescu 3 , Alin Moldoveanu 1 , Marius Leordeanu 1 and Florica Moldoveanu 1 1 Faculty of Automatic Control and Computers, University POLITEHNICA of Bucharest, Bucharest 060042, Romania; [email protected] (A.M.); [email protected] (M.L.); fl[email protected] (F.M.) 2 Department of Computer Science, Information Technology, Mathematics and Physics (ITIMF), Petroleum-Gas University of Ploiesti, Ploiesti 100680, Romania; [email protected] 3 Faculty of Biology, University of Bucharest, Bucharest 030014, Romania; [email protected] * Correspondence: [email protected]; Tel.: +40722276571 Received: 12 November 2019; Accepted: 18 December 2019; Published: 20 December 2019 Abstract: Emotions constitute an indispensable component of our everyday life. They consist of conscious mental reactions towards objects or situations and are associated with various physiological, behavioral, and cognitive changes. In this paper, we propose a comparative analysis between different machine learning and deep learning techniques, with and without feature selection, for binarily classifying the six basic emotions, namely anger, disgust, fear, joy, sadness, and surprise, into two symmetrical categorical classes (emotion and no emotion), using the physiological recordings and subjective ratings of valence, arousal, and dominance from the DEAP (Dataset for Emotion Analysis using EEG, Physiological and Video Signals) database. The results showed that the maximum classification accuracies for each emotion were: anger: 98.02%, joy:100%, surprise: 96%, disgust: 95%, fear: 90.75%, and sadness: 90.08%. In the case of four emotions (anger, disgust, fear, and sadness), the classification accuracies were higher without feature selection. -
June 1, 2020 Dear Massart Community, Pain. Grief. Anxiety. Disgust. Anger. Rage. All Fitting Emotions in Response to the Killing
June 1, 2020 Dear MassArt Community, Pain. Grief. Anxiety. Disgust. Anger. Rage. All fitting emotions in response to the killing of George Floyd. Just two weeks ago, we noted to our campus community acts of racism in our nation, including the murder of Ahmaud Arbery in Georgia. Last week we learned of the racist incident involving Christian Cooper in New York City. And now this. Protests are occurring in our city and around the nation, with riots in many places. We grieve that people of color, in this case, the black community, once again bear the burden of our nation’s continued failure to create a more just and equitable society. If you find yourself wearied and burdened, so do I. But I, a white man of privilege, along with all my white colleagues and friends, don’t experience weariness and burden in any way like those who are the targets of racism. We need to carry this burden more than we ever have. I have said on more than one occasion that we have for too long burdened people of color not only with systemic racism and discrimination, but we also inordinately burden people of color with the burden of solving these problems on their own. The stark truth is that we white people created the problem and it is on us to remedy it. We know that where there is injustice there is no peace. We hope for justice to be done on behalf of George Floyd and his family, and we hope for peace to come to Minneapolis and our nation. -
Emotion Classification Based on Brain Wave: a Survey
Li et al. Hum. Cent. Comput. Inf. Sci. (2019) 9:42 https://doi.org/10.1186/s13673-019-0201-x REVIEW Open Access Emotion classifcation based on brain wave: a survey Ting‑Mei Li1, Han‑Chieh Chao1,2* and Jianming Zhang3 *Correspondence: [email protected] Abstract 1 Department of Electrical Brain wave emotion analysis is the most novel method of emotion analysis at present. Engineering, National Dong Hwa University, Hualien, With the progress of brain science, it is found that human emotions are produced by Taiwan the brain. As a result, many brain‑wave emotion related applications appear. However, Full list of author information the analysis of brain wave emotion improves the difculty of analysis because of the is available at the end of the article complexity of human emotion. Many researchers used diferent classifcation methods and proposed methods for the classifcation of brain wave emotions. In this paper, we investigate the existing methods of brain wave emotion classifcation and describe various classifcation methods. Keywords: EEG, Emotion, Classifcation Introduction Brain science has shown that human emotions are controlled by the brain [1]. Te brain produces brain waves as it transmits messages. Brain wave data is one of the biological messages, and biological messages usually have emotion features. Te feature of emo- tion can be extracted through the analysis of brain wave messages. But because of the environmental background and cultural diferences of human growth, the complexity of human emotion is caused. Terefore, in the analysis of brain wave emotion, classifcation algorithm is very important. In this article, we will focus on the classifcation of brain wave emotions. -
Emotion Autonomic Arousal
PSYC 100 Emotions 2/23/2005 Emotion ■ Emotions reflect a “stirred up’ state ■ Emotions have valence: positive or negative ■ Emotions are thought to have 3 components: ß Physiological arousal ß Subjective experience ß Behavioral expression Autonomic Arousal ■ Increased heart rate ■ Rapid breathing ■ Dilated pupils ■ Sweating ■ Decreased salivation ■ Galvanic Skin Response 2/23/2005 1 Theories of Emotion James-Lange ■ Each emotion has an autonomic signature 2/23/2005 Assessment of James-Lange Theory of Emotion ■ Cannon’s arguments against the theory: ß Visceral response are slower than emotions ß The same visceral responses are associated with many emotions (Î heart rate with anger and joy). ■ Subsequent research provides support: ß Different emotions are associated with different patterns of visceral activity ß Accidental transection of the spinal cord greatly diminishes emotional reactivity (prevents visceral signals from reaching brain) 2 Cannon-Bard Criticisms ■ Arousal without emotion (exercise) 2/23/2005 Facial Feedback Model ■ Similar to James-Lange, but not autonomic signature; facial signature associated with each emotion. 2/23/2005 Facial Expression of Emotion ■ There is an evolutionary link between the experience of emotion and facial expression of emotion: ß Facial expressions serve to inform others of our emotional state ■ Different facial expressions are associated with different emotions ß Ekman’s research ■ Facial expression can alter emotional experience ß Engaging in different facial expressions can alter heart rate and skin temperature 3 Emotions and Darwin ■ Adaptive value ■ Facial expression in infants ■ Facial expression x-cultures ■ Understanding of expressions x-cultures 2/23/2005 Facial Expressions of Emotion ■ Right cortex—left side of face 2/23/2005 Emotions and Learning ■ But experience matters: research with isolated monkeys 2/23/2005 4 Culture and Display Rules ■ Public vs. -
Conceptual Framework for Quantum Affective Computing and Its Use in Fusion of Multi-Robot Emotions
electronics Article Conceptual Framework for Quantum Affective Computing and Its Use in Fusion of Multi-Robot Emotions Fei Yan 1 , Abdullah M. Iliyasu 2,3,∗ and Kaoru Hirota 3,4 1 School of Computer Science and Technology, Changchun University of Science and Technology, Changchun 130022, China; [email protected] 2 College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia 3 School of Computing, Tokyo Institute of Technology, Yokohama 226-8502, Japan; [email protected] 4 School of Automation, Beijing Institute of Technology, Beijing 100081, China * Correspondence: [email protected] Abstract: This study presents a modest attempt to interpret, formulate, and manipulate the emotion of robots within the precepts of quantum mechanics. Our proposed framework encodes emotion information as a superposition state, whilst unitary operators are used to manipulate the transition of emotion states which are subsequently recovered via appropriate quantum measurement operations. The framework described provides essential steps towards exploiting the potency of quantum mechanics in a quantum affective computing paradigm. Further, the emotions of multi-robots in a specified communication scenario are fused using quantum entanglement, thereby reducing the number of qubits required to capture the emotion states of all the robots in the environment, and therefore fewer quantum gates are needed to transform the emotion of all or part of the robots from one state to another. In addition to the mathematical rigours expected of the proposed framework, we present a few simulation-based demonstrations to illustrate its feasibility and effectiveness. This exposition is an important step in the transition of formulations of emotional intelligence to the quantum era. -
EMOTION CLASSIFICATION of COVERED FACES 1 WHO CAN READ YOUR FACIAL EXPRESSION? a Comparison of Humans and Machine Learning Class
journal name manuscript No. (will be inserted by the editor) 1 A Comparison of Humans and Machine Learning 2 Classifiers Detecting Emotion from Faces of People 3 with Different Coverings 4 Harisu Abdullahi Shehu · Will N. 5 Browne · Hedwig Eisenbarth 6 7 Received: 9th August 2021 / Accepted: date 8 Abstract Partial face coverings such as sunglasses and face masks uninten- 9 tionally obscure facial expressions, causing a loss of accuracy when humans 10 and computer systems attempt to categorise emotion. Experimental Psychol- 11 ogy would benefit from understanding how computational systems differ from 12 humans when categorising emotions as automated recognition systems become 13 available. We investigated the impact of sunglasses and different face masks on 14 the ability to categorize emotional facial expressions in humans and computer 15 systems to directly compare accuracy in a naturalistic context. Computer sys- 16 tems, represented by the VGG19 deep learning algorithm, and humans assessed 17 images of people with varying emotional facial expressions and with four dif- 18 ferent types of coverings, i.e. unmasked, with a mask covering lower-face, a 19 partial mask with transparent mouth window, and with sunglasses. Further- Harisu Abdullahi Shehu (Corresponding author) School of Engineering and Computer Science, Victoria University of Wellington, 6012 Wellington E-mail: [email protected] ORCID: 0000-0002-9689-3290 Will N. Browne School of Electrical Engineering and Robotics, Queensland University of Technology, Bris- bane QLD 4000, Australia Tel: +61 45 2468 148 E-mail: [email protected] ORCID: 0000-0001-8979-2224 Hedwig Eisenbarth School of Psychology, Victoria University of Wellington, 6012 Wellington Tel: +64 4 463 9541 E-mail: [email protected] ORCID: 0000-0002-0521-2630 2 Shehu H.