Sustained Experience of Emotion After Loss of Memory in Patients with Amnesia
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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. -
Why Feelings Stray: Sources of Affective Misforecasting in Consumer Behavior Vanessa M
Why Feelings Stray: Sources of Affective Misforecasting in Consumer Behavior Vanessa M. Patrick, University of Georgia Deborah J. MacInnis, University of Southern California ABSTRACT drivers of AMF has considerable import for consumer behavior, Affective misforecasting (AMF) is defined as the gap between particularly in the area of consumer satisfaction, brand loyalty and predicted and experienced affect. Based on prior research that positive word-of-mouth. examines AMF, the current study uses qualitative and quantitative Figure 1 depicts the process by which affective misforecasting data to examine the sources of AMF (i.e., why it occurs) in the occurs (for greater detail see MacInnis, Patrick and Park 2005). As consumption domain. The authors find evidence supporting some Figure 1 suggests, affective forecasts are based on a representation sources of AMF identified in the psychology literature, develop a of a future event and an assessment of the possible affective fuller understanding of others, and, find evidence for novel sources reactions to this event. AMF occurs when experienced affect of AMF not previously explored. Importantly, they find consider- deviates from the forecasted affect on one or more of the following able differences in the sources of AMF depending on whether dimensions: valence, intensity and duration. feelings are worse than or better than forecast. Since forecasts can be made regarding the valence of the feelings, the specific emotions expected to be experienced, the INTRODUCTION intensity of feelings or the duration of a projected affective re- Before purchase: “I can’t wait to use this all the time, it is sponse, consequently affective misforecasting can occur along any going to be so much fun, I’m going to go out with my buddies of these dimensions. -
Classification of Human Emotions from Electroencephalogram (EEG) Signal Using Deep Neural Network
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 8, No. 9, 2017 Classification of Human Emotions from Electroencephalogram (EEG) Signal using Deep Neural Network Abeer Al-Nafjan Areej Al-Wabil College of Computer and Information Sciences Center for Complex Engineering Systems Imam Muhammad bin Saud University King Abdulaziz City for Science and Technology Riyadh, Saudi Arabia Riyadh, Saudi Arabia Manar Hosny Yousef Al-Ohali College of Computer and Information Sciences College of Computer and Information Sciences King Saud University King Saud University Riyadh, Saudi Arabia Riyadh, Saudi Arabia Abstract—Estimation of human emotions from [1]. Recognizing a user‘s affective state can be used to Electroencephalogram (EEG) signals plays a vital role in optimize training and enhancement of the BCI operations [2]. developing robust Brain-Computer Interface (BCI) systems. In our research, we used Deep Neural Network (DNN) to address EEG is often used in BCI research experimentation because EEG-based emotion recognition. This was motivated by the the process is non-invasive to the research subject and minimal recent advances in accuracy and efficiency from applying deep risk is involved. The devices‘ usability, reliability, cost- learning techniques in pattern recognition and classification effectiveness, and the relative convenience of conducting applications. We adapted DNN to identify human emotions of a studies and recruiting participants due to their portability have given EEG signal (DEAP dataset) from power spectral density been cited as factors influencing the increased adoption of this (PSD) and frontal asymmetry features. The proposed approach is method in applied research contexts [3], [4]. These advantages compared to state-of-the-art emotion detection systems on the are often accompanied by challenges such as low spatial same dataset. -
What We Mean When We Talk About Suffering—And Why Eric Cassell Should Not Have the Last Word
What We Mean When We Talk About Suffering—and Why Eric Cassell Should Not Have the Last Word Tyler Tate, Robert Pearlman Perspectives in Biology and Medicine, Volume 62, Number 1, Winter 2019, pp. 95-110 (Article) Published by Johns Hopkins University Press For additional information about this article https://muse.jhu.edu/article/722412 Access provided at 26 Apr 2019 00:52 GMT from University of Washington @ Seattle What We Mean When We Talk About Suffering—and Why Eric Cassell Should Not Have the Last Word Tyler Tate* and Robert Pearlman† ABSTRACT This paper analyzes the phenomenon of suffering and its relation- ship to medical practice by focusing on the paradigmatic work of Eric Cassell. First, it explains Cassell’s influential model of suffering. Second, it surveys various critiques of Cassell. Next it outlines the authors’ concerns with Cassell’s model: it is aggressive, obscure, and fails to capture important features of the suffering experience. Finally, the authors propose a conceptual framework to help clarify the distinctive nature of sub- jective patient suffering. This framework contains two necessary conditions: (1) a loss of a person’s sense of self, and (2) a negative affective experience. The authors suggest how this framework can be used in the medical encounter to promote clinician-patient communication and the relief of suffering. *Center for Ethics in Health Care and School of Medicine, Oregon Health and Science University, Portland. †National Center for Ethics in Health Care, Washington, DC, and School of Medicine, University of Washington, Seattle. Correspondence: Tyler Tate, Oregon Health and Science University, School of Medicine, Depart- ment of Pediatrics, 3181 SW Sam Jackson Park Road, Portland, OR 97239-3098. -
Memory for Emotional and Nonemotional Events in Depression: a Question of Habit?
Trinity University Digital Commons @ Trinity Psychology Faculty Research Psychology Department 2004 Memory for Emotional and Nonemotional Events in Depression: A Question of Habit? Paula T. Hertel Trinity University, [email protected] Follow this and additional works at: https://digitalcommons.trinity.edu/psych_faculty Part of the Psychology Commons Publication Details Memory and Emotion Repository Citation Hertel, P. T. (2004). Memory for emotional and nonemotional events in depression: A question of habit? In D. Reisberg & P. Hertel (Eds.), Memory and emotion (pp. 186-216). Oxford University Press. This Contribution to Book is brought to you for free and open access by the Psychology Department at Digital Commons @ Trinity. It has been accepted for inclusion in Psychology Faculty Research by an authorized administrator of Digital Commons @ Trinity. For more information, please contact [email protected]. MEMORY FOR EMOTIONAL AND NONEMOTIONAL EVENTS IN DEPRESSION A Question of Habit? PAULA HERTEL he truest claim that cognitive science can make might also be the Tleast sophisticated: the mind tends to do what it has done before. In previous centuries philosophers and psychologists invented constructs such as associations, habit strength, and connectivity to formalize the truism, but others have known about it, too. In small towns in the Ozarks, for example, grandmothers have been overheard doling out warnings such as, "Don't think those ugly thoughts; your mind will freeze that way." Depressed persons, like most of us, usually don't heed this advice. The thoughts frozen in their minds might not be "ugly," but they often reflect disappointments, losses, failures, other unhappy events, and a generally negative interpretive stance toward ongoing experience. -
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. . -
The Memory-Modifying Potential of Optogenetics and the Need for Neuroethics
Nanoethics https://doi.org/10.1007/s11569-020-00377-1 ORIGINAL RESEARCH PAPER The Memory-Modifying Potential of Optogenetics and the Need for Neuroethics Agnieszka K. Adamczyk & Przemysław Zawadzki Received: 21 December 2019 /Accepted: 30 September 2020 # The Author(s) 2020 Abstract Optogenetics is an invasive neuromodulation Keywords Optogenetics . Memory modification technology involving the use of light to control the technologies (MMTs) . Memory . Neuroethics . Safety . activity of individual neurons. Even though Moral obligations . Autonomy . Exploitation optogenetics is a relatively new neuromodulation tool whose various implications have not yet been scruti- nized, it has already been approved for its first clinical trials in humans. As optogenetics is being intensively What Is Optogenetics? investigated in animal models with the aim of develop- ing novel brain stimulation treatments for various neu- Combining genetic engineering with optics, optogenetics rological and psychiatric disorders, it appears crucial to enables the user not only to record but also to manipulate consider both the opportunities and dangers such ther- the activity of individual neurons in living tissue with the apies may offer. In this review, we focus on the use of light and to observe the effects of such manipula- memory-modifying potential of optogenetics, investi- tion in real time [1, 2]. To this end, neurons of interest are gating what it is capable of and how it differs from genetically modified to be made responsive to light, other memory modification technologies (MMTs). We which is done by means of inserting opsin genes (genes then outline the safety challenges that need to be ad- that express light-sensitive proteins). -
Emotionally Charged Autobiographical Memories Across the Life Span: the Recall of Happy, Sad, Traumatic, and Involuntary Memories
Psychology and Aging Copyright 2002 by the American Psychological Association, Inc. 2002, Vol. 17, No. 4, 636–652 0882-7974/02/$5.00 DOI: 10.1037//0882-7974.17.4.636 Emotionally Charged Autobiographical Memories Across the Life Span: The Recall of Happy, Sad, Traumatic, and Involuntary Memories Dorthe Berntsen David C. Rubin University of Aarhus Duke University A sample of 1,241 respondents between 20 and 93 years old were asked their age in their happiest, saddest, most traumatic, most important memory, and most recent involuntary memory. For older respondents, there was a clear bump in the 20s for the most important and happiest memories. In contrast, saddest and most traumatic memories showed a monotonically decreasing retention function. Happy involuntary memories were over twice as common as unhappy ones, and only happy involuntary memories showed a bump in the 20s. Life scripts favoring positive events in young adulthood can account for the findings. Standard accounts of the bump need to be modified, for example, by repression or reduced rehearsal of negative events due to life change or social censure. Many studies have examined the distribution of autobiographi- (1885/1964) drew attention to conscious memories that arise un- cal memories across the life span. No studies have examined intendedly and treated them as one of three distinct classes of whether this distribution is different for different classes of emo- memory, but did not study them himself. In his well-known tional memories. Here, we compare the event ages of people’s textbook, Miller (1962/1974) opened his chapter on memory by most important, happiest, saddest, and most traumatic memories quoting Marcel Proust’s description of how the taste of a Made- and most recent involuntary memory to explore whether different leine cookie unintendedly brought to his mind a long-forgotten kinds of emotional memories follow similar patterns of retention. -
Emotion Classification Using Physiological Signals
Emotion Classification Using Physiological Signals Byoung-Jun Park1, Eun-Hye Jang1, Myoung Ae Chung1, Sang-Hyeob Kim1*, Jin Hun Sohn2* 1IT Convergence Technology Research Laboratory, Electronics and Telecommunications Research Institute, Daejeon, 305-700 2Department of Psychology/Brain Research Institute, Chungnam National University, Daejeon, 305-765 ABSTRACT Objective: The aim of this study is to discriminate negative emotions, such as sadness, fear, surprise, and stress using physiological signals. Background: Recently, the main topic of emotion classification research is to recognize human’s feeling or emotion using various physiological signals. It is one of the core processes to implement emotional intelligence in human computer interaction (HCI) research. Method: Electrodermal activity (EDA), electrocardiogram (ECG), skin temperature (SKT), and photoplethysmography (PPG) are recorded and analyzed as physiological signals. And emotional stimuli are audio-visual film clips which have examined for their appropriateness and effectiveness through preliminary experiment. For classification of negative emotions, five machine learning algorithms, i.e., LDF, CART, SOM, and Naïve Bayes are used. Results: Result of emotion classification shows that an accuracy of emotion classification by CART (84.0%) was the highest and by LDA (50.7%) was the lowest. SOM showed emotion classification accuracy of 51.2% and Naïve Bayes was 76.2%. Conclusion: We could identify that CART was the optimal emotion classification algorithm for classifying 4 negative emotions (sadness, fear, surprise, and stress). Application: This result can be helpful to provide the basis for the emotion recognition technique in HCI. Keywords: Emotion classification, Negative emotion, Machine learning algorithm, Physiological signal 1. Introduction Nasoz, Alvarez, Lisetti, and Finkelstein, 2003). -
Examining Affective Forecasting and Its Practical and Ethical Implications
Examining Affective Forecasting and its Practical and Ethical Implications Emily Susan Brindley BSc Psychology 2009 Supervisor: Prof. David Clarke Contents Page Introduction 1 1. Affective Forecasting – What do we know? 1 2. Biases – Why people cannot predict their emotions accurately 3 2.1 Impact Bias 3 2.2 ‘Focalism’ 4 2.3 Immune Neglect 4 2.4 Dissimilar Context 4 3. The Self-Regulating Emotional System 5 4. Affective Forecasting Applied 6 4.1 Healthcare 6 4.2 Law 7 5. Can AFing be improved? 8 6. Ethics: Should people be taught to forecast more accurately? 10 Conclusions 12 References 13 Examining Affective Forecasting and its Practical and Ethical Implications Introduction Emotions are important in guiding thoughts and behaviour to the extent that they are used as heuristics (Slovic, Finucane, Peters & MacGregor, 2007), and are crucial in decision-making (Anderson, 2003). Affective forecasting (AFing) concerns an individual’s judgemental prediction of their or another’s future emotional reactions to events. It is suggested that “affective forecasts are among the guiding stars by which people chart their life courses and steer themselves into the future” (Gilbert, Pinel, Wilson, Blumberg & Wheatley, 1998; p.617), as our expected reactions to emotional events can assist in avoiding or approaching certain possibilities. We can say with certainty that we will prefer good experiences over bad (ibid); however AFing research demonstrates that humans are poor predictors of their emotional states, regularly overestimating their reactions. Further investigation of these findings shows that they may have critical implications outside of psychology. If emotions are so influential on behaviour, why are people poor at AFing? Furthermore, can and should individuals be assisted in forecasting their emotions? These issues, along with the function of AFing in practical applications, are to be considered and evaluated. -
Noradrenergic Projections from the Locus Coeruleus to the Amygdala Constrain Fear Memory Reconsolidation Josue´ Haubrich1*, Matteo Bernabo2, Karim Nader1
RESEARCH ARTICLE Noradrenergic projections from the locus coeruleus to the amygdala constrain fear memory reconsolidation Josue´ Haubrich1*, Matteo Bernabo2, Karim Nader1 1Department of Psychology, McGill University, Montreal, Canada; 2Department of Neurology and Neurosurgery, McGill University, Montreal, Canada Abstract Memory reconsolidation is a fundamental plasticity process in the brain that allows established memories to be changed or erased. However, certain boundary conditions limit the parameters under which memories can be made plastic. Strong memories do not destabilize, for instance, although why they are resilient is mostly unknown. Here, we investigated the hypothesis that specific modulatory signals shape memory formation into a state that is reconsolidation- resistant. We find that the activation of the noradrenaline-locus coeruleus system (NOR-LC) during strong fear memory encoding increases molecular mechanisms of stability at the expense of lability in the amygdala of rats. Preventing the NOR-LC from modulating strong fear encoding results in the formation of memories that can undergo reconsolidation within the amygdala and thus are vulnerable to post-reactivation interference. Thus, the memory strength boundary condition on reconsolidation is set at the time of encoding by the action of the NOR-LC. Introduction New memories do not form instantly at the moment of an experience, but rather undergo a stabiliza- tion period during which they are gradually consolidated into a stable, long-term *For correspondence: memory (Asok et al., 2019). Later, recall may cause the memory to return to an unstable state (i.e. [email protected] destabilized) where it can be modified. Importantly, the memory must undergo a re-stabilization pro- cess called reconsolidation in order to persist (Haubrich and Nader, 2016). -
Religious Perspectives on Human Suffering: Implications for Medicine and Bioethics
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Sydney eScholarship Postprint This is a pre-copyedited, author-produced PDF of an article accepted for publication in [Journal of Religion and Health] following peer review. The definitive publisher-authenticated version [Fitzpatrick SJ, Kerridge IH, Jordens CFC, Zoloth L, Tollefsen C, Tsomo KL, Jensen MP, Sachedina A, Sarma D. Religious perspectives on human suffering: Implications for medicine and bioethics. Journal of Religion and Health 2016; 55:159–173] is available online at http://link.springer.com/article/10.1007/s10943-015-0014-9 Please cite as: Fitzpatrick SJ, Kerridge IH, Jordens CFC, Zoloth L, Tollefsen C, Tsomo KL, Jensen MP, Sachedina A, Sarma D. Religious perspectives on human suffering: Implications for medicine and bioethics. Journal of Religion and Health 2016; 55:159–173. Religious perspectives on human suffering: Implications for medicine and bioethics Scott J FitzpatrickA,B, Ian H KerridgeB, Christopher F C JordensB , Laurie ZolothC, Christopher TollefsenD, Karma Lekshe TsomoE, Michael P JensenF, Abdulaziz SachedinaG, Deepak SarmaH (2015/16) ACentre for Rural and Remote Mental Health, University of Newcastle, Orange, Australia; BCentre for Values, Ethics and the Law in Medicine (VELiM), University of Sydney, Sydney, Australia; CCentre for Bioethics, Science and Society, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA; DDepartment of Philosophy, University of South Carolina, Colombia, South Carolina, USA USA; EDepartment of Theology and Religious Studies, University of San Diego, San Diego, California, USA; FMoore Theological College, Sydney, Australia; GAli Vural Ak Centre for Global Islamic Studies, George Mason University, Fairfax, Virginia, USA; HReligious Studies, Case Western Reserve University, Cleveland, Ohio, USA.