Development and Validation of Brief Measures of Positive and Negative Affect: the PANAS Scales
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The Influence of Emotional States on Short-Term Memory Retention by Using Electroencephalography (EEG) Measurements: a Case Study
The Influence of Emotional States on Short-term Memory Retention by using Electroencephalography (EEG) Measurements: A Case Study Ioana A. Badara1, Shobhitha Sarab2, Abhilash Medisetty2, Allen P. Cook1, Joyce Cook1 and Buket D. Barkana2 1School of Education, University of Bridgeport, 221 University Ave., Bridgeport, Connecticut, 06604, U.S.A. 2Department of Electrical Engineering, University of Bridgeport, 221 University Ave., Bridgeport, Connecticut, 06604, U.S.A. Keywords: Memory, Learning, Emotions, EEG, ERP, Neuroscience, Education. Abstract: This study explored how emotions can impact short-term memory retention, and thus the process of learning, by analyzing five mental tasks. EEG measurements were used to explore the effects of three emotional states (e.g., neutral, positive, and negative states) on memory retention. The ANT Neuro system with 625Hz sampling frequency was used for EEG recordings. A public-domain library with emotion-annotated images was used to evoke the three emotional states in study participants. EEG recordings were performed while each participant was asked to memorize a list of words and numbers, followed by exposure to images from the library corresponding to each of the three emotional states, and recall of the words and numbers from the list. The ASA software and EEGLab were utilized for the analysis of the data in five EEG bands, which were Alpha, Beta, Delta, Gamma, and Theta. The frequency of recalled event-related words and numbers after emotion arousal were found to be significantly different when compared to those following exposure to neutral emotions. The highest average energy for all tasks was observed in the Delta activity. Alpha, Beta, and Gamma activities were found to be slightly higher during the recall after positive emotion arousal. -
Anger in Negotiations: a Review of Causes, Effects, and Unanswered Questions David A
Negotiation and Conflict Management Research Anger in Negotiations: A Review of Causes, Effects, and Unanswered Questions David A. Hunsaker Department of Management, University of Utah, Salt Lake City, UT, U.S.A. Keywords Abstract anger, negotiation, emotion, attribution. This article reviews the literature on the emotion of anger in the negotia- tion context. I discuss the known antecedents of anger in negotiation, as Correspondence well as its positive and negative inter- and intrapersonal effects. I pay par- David Hunsaker, David Eccles ticular attention to the apparent disagreements within the literature con- School of Business, Spencer Fox cerning the benefits and drawbacks of using anger to gain advantage in Eccles Business Building, negotiations and employ Attribution Theory as a unifying mechanism to University of Utah, 1655 East Campus Center Drive, Salt Lake help explain these diverse findings. I call attention to the weaknesses evi- City, UT 84112, U.S.A.; e-mail: dent in current research questions and methodologies and end with sug- david.hunsaker@eccles. gestions for future research in this important area. utah.edu. What role does anger play in the negotiation context? Can this emotion be harnessed and manipulated to increase negotiating power and improve negotiation outcomes, or does it have inevitable downsides? The purpose of this article is to review the work of scholars that have focused on the emotion of anger within the negotiation context. I begin by offering some background on the field of research to be reviewed. I then explain why Attri- bution Theory is particularly helpful in making sense of diverse findings in the field. -
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. -
1 the Development of Empathy: How, When, and Why Nicole M. Mcdonald & Daniel S. Messinger University of Miami Department Of
1 The Development of Empathy: How, When, and Why Nicole M. McDonald & Daniel S. Messinger University of Miami Department of Psychology 5665 Ponce de Leon Dr. Coral Gables, FL 33146, USA 2 Empathy is a potential psychological motivator for helping others in distress. Empathy can be defined as the ability to feel or imagine another person’s emotional experience. The ability to empathize is an important part of social and emotional development, affecting an individual’s behavior toward others and the quality of social relationships. In this chapter, we begin by describing the development of empathy in children as they move toward becoming empathic adults. We then discuss biological and environmental processes that facilitate the development of empathy. Next, we discuss important social outcomes associated with empathic ability. Finally, we describe atypical empathy development, exploring the disorders of autism and psychopathy in an attempt to learn about the consequences of not having an intact ability to empathize. Development of Empathy in Children Early theorists suggested that young children were too egocentric or otherwise not cognitively able to experience empathy (Freud 1958; Piaget 1965). However, a multitude of studies have provided evidence that very young children are, in fact, capable of displaying a variety of rather sophisticated empathy related behaviors (Zahn-Waxler et al. 1979; Zahn-Waxler et al. 1992a; Zahn-Waxler et al. 1992b). Measuring constructs such as empathy in very young children does involve special challenges because of their limited verbal expressiveness. Nevertheless, young children also present a special opportunity to measure constructs such as empathy behaviorally, with less interference from concepts such as social desirability or skepticism. -
Attitudes Toward Emotions
Journal of Personality and Social Psychology © 2011 American Psychological Association 2011, Vol. 101, No. 6, 1332–1350 0022-3514/11/$12.00 DOI: 10.1037/a0024951 Attitudes Toward Emotions Eddie Harmon-Jones and Cindy Harmon-Jones David M. Amodio Texas A&M University New York University Philip A. Gable University of Alabama The present work outlines a theory of attitudes toward emotions, provides a measure of attitudes toward emotions, and then tests several predictions concerning relationships between attitudes toward specific emotions and emotional situation selection, emotional traits, emotional reactivity, and emotion regula- tion. The present conceptualization of individual differences in attitudes toward emotions focuses on specific emotions and presents data indicating that 5 emotions (anger, sadness, joy, fear, and disgust) load on 5 separate attitude factors (Study 1). Attitudes toward emotions predicted emotional situation selection (Study 2). Moreover, attitudes toward approach emotions (e.g., anger, joy) correlated directly with the associated trait emotions, whereas attitudes toward withdrawal emotions (fear, disgust) correlated inversely with associated trait emotions (Study 3). Similar results occurred when attitudes toward emotions were used to predict state emotional reactivity (Study 4). Finally, attitudes toward emotions predicted specific forms of emotion regulation (Study 5). Keywords: discrete emotions, approach motivation, withdrawal motivation, emotion regulation, behav- ioral activation system (BAS) Emotions pervade subjective experience (Izard, 2009), and al- theory by assessing relationships between attitudes toward specific though often perceived as a single subjective state, emotional emotions and emotional traits, emotional reactivity, emotional experience is likely composed of many different elements. Tom- situation selection, and emotion regulation. kins (1962, 1963) and others (Ellsworth, 1994; Izard, 1971) sug- gested that the evaluation of an emotion is part of the experience of emotion. -
The Somatic Marker Hypothesis: a Neural Theory of Economic Decision
Games and Economic Behavior 52 (2005) 336–372 www.elsevier.com/locate/geb The somatic marker hypothesis: A neural theory of economic decision Antoine Bechara ∗, Antonio R. Damasio Department of Neurology, University of Iowa, 200 Hawkins Drive, Iowa City, IA 52242, USA Received 8 June 2004 Available online 23 September 2004 Abstract Modern economic theory ignores the influence of emotions on decision-making. Emerging neuro- science evidence suggests that sound and rational decision making, in fact, depends on prior accurate emotional processing. The somatic marker hypothesis provides a systems-level neuroanatomical and cognitive framework for decision-making and its influence by emotion. The key idea of this hypothe- sis is that decision-making is a process that is influenced by marker signals that arise in bioregulatory processes, including those that express themselves in emotions and feelings. This influence can oc- cur at multiple levels of operation, some of which occur consciously, and some of which occur non-consciously. Here we review studies that confirm various predictions from the hypothesis, and propose a neural model for economic decision, in which emotions are a major factor in the interac- tion between environmental conditions and human decision processes, with these emotional systems providing valuable implicit or explicit knowledge for making fast and advantageous decisions. 2004 Elsevier Inc. All rights reserved. Introduction Modern economic theory assumes that human decision-making involves rational Bayesian maximization of expected utility, as if humans were equipped with unlim- ited knowledge, time, and information-processing power. The influence of emotions on * Corresponding author. E-mail address: [email protected] (A. -
The Reliability of Subjective Well-Being Measures by Alan B
The Reliability of Subjective Well-Being Measures by Alan B. Krueger, Princeton University David A. Schkade, University of California, San Diego CEPS Working Paper No. 138 January 2007 The authors thank our colleagues Daniel Kahneman, Norbert Schwarz, and Arthur Stone for helpful comments and the Hewlett Foundation, the National Institute on Aging, and Princeton University’s Woodrow Wilson School and Center for Economic Policy Studies for financial support. Reliability of SWB Measures – 2 Introduction Economists are increasingly analyzing data on subjective well-being. Since 2000, 157 papers and numerous books have been published in the economics literature using data on life satisfaction or subjective well-being, according to a search of Econ Lit.1 Here we analyze the test-retest reliability of two measures of subjective well-being: a standard life satisfaction question and affective experience measures derived from the Day Reconstruction Method (DRM). Although economists have longstanding reservations about the feasibility of interpersonal comparisons of utility that we can only partially address here, another question concerns the reliability of such measurements for the same set of individuals over time. Overall life satisfaction should not change very much from week to week. Likewise, individuals who have similar routines from week to week should experience similar feelings over time. How persistent are individuals’ responses to subjective well-being questions? To anticipate our main findings, both measures of subjective well-being (life satisfaction and affective experience) display a serial correlation of about 0.60 when assessed two weeks apart, which is lower than the reliability ratios typically found for education, income and many other common micro economic variables (Bound, Brown, and Mathiowetz, 2001 and Angrist and Krueger, 1999), but high enough to support much of the research that has been undertaken on subjective well-being. -
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. -
Distinguishing Neurotic from Prosocial "Guilt": Evidence for the Conceptual
Distinguishing Neurotic from Prosocial “Guilt”: Evidence for the Conceptual Distinctiveness of Checklist and Scenario Measures by Stefanie M. Tignor B.A. in Psychology, Binghamton University M.A. in Psychology, Northeastern University A dissertation submitted to The Faculty of the College of Science of Northeastern University in partial fulfillment of the requirements for the degree of Doctor of Philosophy July 28, 2016 Dissertation directed by C. Randall Colvin Associate Professor of Psychology ACKNOWLEDGEMENTS First, thank you to my advisor, Randy Colvin, for your ever-impressive expertise, guidance, and support. From my first day to my last you’ve made the Personality Lab feel like home, and I deeply appreciate all that you have taught me. Thanks for always being willing to chat about research or life, and thanks for always cheering me on. To Judy Hall, thank you for all of your support and mentorship over these past few years. Your immense knowledge of psychology and skills as a researcher are an inspiration to me. And of course, thank you for helping me fall in love with meta-analysis. To Nancy Kim, thank you for your insightful and helpful comments on this dissertation, in meetings and via email. It has been much improved thanks to your guidance, and I have greatly appreciated your help throughout the process. Thanks to the many research assistants who helped with this project: Emily Burke, David Kramer, Megan Pinaire, Christina Tebbe, Ronnie Lo, Simone Grant, Alexa Lambros, Fae Kayarian, Kristen Laws, Catherine Martin, Heather Offermann, and Sangjukta Sen Roy. Thank you to my research “brother” and “sister” Sun Park and Krista Hill; your welcoming nature and willingness to help a lost first-year will never be forgotten. -
Somatic Markers, Working Memory, and Decision Making
Cognitive, Affective, & Behavioral Neuroscience 2002, 2 (4), 341-353 Somatic markers, working memory, and decision making JOHN M. HINSON, TINA L. JAMESON, and PAUL WHITNEY Washington State University, Pullman, Washington The somatic marker hypothesis formulated by Damasio (e.g., 1994; Damasio, Tranel, & Damasio, 1991)argues that affectivereactions ordinarily guide and simplify decision making. Although originally intended to explain decision-making deficits in people with specific frontal lobe damage, the hypothe- sis also applies to decision-making problems in populations without brain injury. Subsequently, the gambling task was developed by Bechara (Bechara, Damasio, Damasio, & Anderson, 1994) as a diag- nostic test of decision-making deficit in neurological populations. More recently, the gambling task has been used to explore implications of the somatic marker hypothesis, as well as to study suboptimal de- cision making in a variety of domains. We examined relations among gambling task decision making, working memory (WM) load, and somatic markers in a modified version of the gambling task. In- creased WM load produced by secondary tasks led to poorer gambling performance. Declines in gam- bling performance were associated with the absence of the affective reactions that anticipate choice outcomes and guide future decision making. Our experiments provide evidence that WM processes contribute to the development of somatic markers. If WM functioning is taxed, somatic markers may not develop, and decision making may thereby suffer. One of the most consistent challenges of daily life is & Damasio, 2000). That is, decision making is guided by the management of information in order to continually the immediate outcomes of actions, without regard to what make decisions about courses of action. -
Trait Positive and Negative Emotionality Differentially Associate Withdiurnal Cortisol Activity Karissa G
Bryn Mawr College Scholarship, Research, and Creative Work at Bryn Mawr College Psychology Faculty Research and Scholarship Psychology 2016 Trait positive and negative emotionality differentially associate withdiurnal cortisol activity Karissa G. Miller Aidan G.C. Wright Laurel M. Peterson Bryn Mawr College, [email protected] Thomas W. Kamarck Barbara A. Anderson See next page for additional authors Let us know how access to this document benefits ouy . Follow this and additional works at: http://repository.brynmawr.edu/psych_pubs Part of the Psychology Commons Custom Citation Miller et al. "Trait positive and negative emotionality differentially associate withdiurnal cortisol activity." Psychoneuroendocrinology 68 (2016); 177-185. This paper is posted at Scholarship, Research, and Creative Work at Bryn Mawr College. http://repository.brynmawr.edu/psych_pubs/47 For more information, please contact [email protected]. Authors Karissa G. Miller, Aidan G.C. Wright, Laurel M. Peterson, Thomas W. Kamarck, Barbara A. Anderson, Clemens Kirschbaum, Anna L. Marsland, and Matthew F. Muldoon This article is available at Scholarship, Research, and Creative Work at Bryn Mawr College: http://repository.brynmawr.edu/ psych_pubs/47 Psychoneuroendocrinology 68 (2016) 177–185 Contents lists available at ScienceDirect Psychoneuroendocrinology journal homepage: www.elsevier.com/locate/psyneuen Trait positive and negative emotionality differentially associate with diurnal cortisol activity a,∗ a b a Karissa G. Miller , Aidan G.C. Wright , Laurel -
Hybrid Approach for Emotion Classification of Audio Conversation Based on Text and Speech Mining
Available online at www.sciencedirect.com ScienceDirect Procedia Computer Science 46 ( 2015 ) 635 – 643 International Conference on Information and Communication Technologies (ICICT 2014) Hybrid Approach for Emotion Classification of Audio Conversation Based on Text and Speech Mining a, a b Jasmine Bhaskar * ,Sruthi K , Prema Nedungadi aDepartment of Compute science , Amrita University, Amrita School of Engineering, Amritapuri, 690525, India bAmrita Create, Amrita University, Amrita School of Engineering, Amritapuri, 690525, India Abstract One of the greatest challenges in speech technology is estimating the speaker’s emotion. Most of the existing approaches concentrate either on audio or text features. In this work, we propose a novel approach for emotion classification of audio conversation based on both speech and text. The novelty in this approach is in the choice of features and the generation of a single feature vector for classification. Our main intention is to increase the accuracy of emotion classification of speech by considering both audio and text features. In this work we use standard methods such as Natural Language Processing, Support Vector Machines, WordNet Affect and SentiWordNet. The dataset for this work have been taken from Semval -2007 and eNTERFACE'05 EMOTION Database. © 20152014 PublishedThe Authors. by ElsevierPublished B.V. by ElsevierThis is an B.V. open access article under the CC BY-NC-ND license (Peer-reviewhttp://creativecommons.org/licenses/by-nc-nd/4.0/ under responsibility of organizing committee). of the International Conference on Information and Communication PeerTechnologies-review under (ICICT responsibility 2014). of organizing committee of the International Conference on Information and Communication Technologies (ICICT 2014) Keywords: Emotion classification;text mining;speech mining;hybrid approach 1.