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Dimensions of Appraisal and Physiological Response in Emotion

Authors:
  • Peabody College of Vanderbilt University

Abstract

Appraisal theorists propose physiological activity in emotion to be systematically organized around appraisal of the adaptational significance of the environment in ways that promote two functions commonly ascribed to emotion: communication and preparation for coping. However, relations between appraisal and physiological activity remain largely untested. This article reviews existing evidence to generate specific hypotheses linking appraisal to physiological activity and presents an imagery-based experimental test of a subset of these hypotheses. No evidence was found for a relation between other-agency and the eyebrow frown, but brow activity and heart rate were affected by effort-related appraisals: Anticipated effort influenced heart rate, and perceived goal-obstacles influenced the eyebrow frown. Implications of the findings and theoretical approach are discussed.
... Then, we applied specific signal processing techniques to extract a combination of features from these signals. Additionally, the participants reported subjective ratings for each presented film clip using the self-assessment manikin (SAM) (Bradley and Lang 1994) and an ad-hoc self-reported appraisal instrument developed for this study (Scherer et al. 2001;Smith 1989;Reisenzein et al. 2019;Aue et al. 2007;Denson et al. 2009). ...
... The anticipatory effort is related to the appraisal of a situation as objectively relaxing or requiring effort. Thus, the higher the effort, the higher the activation of the activity of the Corrugator muscle (EMG) (Smith 1989). The perceived obstacles appraisal is related to the presence vs absence of resistance between the person and their goal, leading to a higher heart rate (ECG) (Smith and Ellsworth 1985). ...
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Affective computing has been widely used to detect and recognize emotional states. The main goal of this study was to detect emotional states using machine learning algorithms automatically. The experimental procedure involved eliciting emotional states using film clips in an immersive and non-immersive virtual reality setup. The participants' physiological signals were recorded and analyzed to train machine learning models to recognize users' emotional states. Furthermore, two subjective ratings emotional scales were provided to rate each emotional film clip. Results showed no significant differences between presenting the stimuli in the two degrees of immersion. Regarding emotion classification, it emerged that for both physiological signals and subjective ratings, user-dependent models have a better performance when compared to user-independent models. We obtained an average accuracy of 69.29 ± 11.41% and 71.00 ± 7.95% for the subjective ratings and physiological signals, respectively. On the other hand, using user-independent models, the accuracy we obtained was 54.0 ± 17.2% and 24.9 ± 4.0%, respectively. We interpreted these data as the result of high inter-subject variability among participants, suggesting the need for user-dependent classification models. In future works, we intend to develop new classification algorithms and transfer them to real-time implementation. This will make it possible to adapt to a virtual reality environment in real-time, according to the user's emotional state.
... Then, we applied specific signal processing techniques to extract a combination of features from these signals. Additionally, the participants reported subjective ratings for each presented film clip using the self-assessment manikin (SAM) (Bradley and Lang 1994) and an ad-hoc self-reported appraisal instrument developed for this study (Scherer et al. 2001;Smith 1989;Reisenzein et al. 2019;Aue et al. 2007;Denson et al. 2009). ...
... The anticipatory effort is related to the appraisal of a situation as objectively relaxing or requiring effort. Thus, the higher the effort, the higher the activation of the activity of the Corrugator muscle (EMG) (Smith 1989). The perceived obstacles appraisal is related to the presence vs absence of resistance between the person and their goal, leading to a higher heart rate (ECG) (Smith and Ellsworth 1985). ...
Article
Full-text available
Affective computing has been widely used to detect and recognize emotional states. The main goal of this study was to detect emotional states using machine learning algorithms automatically. The experimental procedure involved eliciting emotional states using film clips in an immersive and non-immersive virtual reality setup. The participants’ physiological signals were recorded and analyzed to train machine learning models to recognize users’ emotional states. Furthermore, two subjective ratings emotional scales were provided to rate each emotional film clip. Results showed no significant differences between presenting the stimuli in the two degrees of immersion. Regarding emotion classification, it emerged that for both physiological signals and subjective ratings, user-dependent models have a better performance when compared to user-independent models. We obtained an average accuracy of 69.29 ± 11.41% and 71.00 ± 7.95% for the subjective ratings and physiological signals, respectively. On the other hand, using user-independent models, the accuracy we obtained was 54.0 ± 17.2% and 24.9 ± 4.0%, respectively. We interpreted these data as the result of high inter-subject variability among participants, suggesting the need for user-dependent classification models. In future works, we intend to develop new classification algorithms and transfer them to real-time implementation. This will make it possible to adapt to a virtual reality environment in real-time, according to the user’s emotional state.
... 1976Obrist, , 1981T. W. Smith, Allred, Morrison, & Carlson, 1989;Wright, Contrada, & Patane, 1986;Wright, Williams, & Dill, 1992). Evidence for adjustments of diastolic blood pressure (DBP; e.g., Storey, Wright, & Williams, 1996) and heart rate (HR; e.g., Elliott, 1969;Fowles, 1988;Gellatly & Meyer, 1992;Gendolla, 1998Gendolla, , 1999Obrist, 1981;C. A. Smith, 1989) is less consistent (Wright, 1996). This is reasonable because SBP is largely determined by myocardial contractility, which in turn depends on (3-adrenergic stimulation of the sympathetic nervous system that is responsible for activation. In this regard, researchers have demonstrated that SBP adjustments in active coping depend directly ...
... ect on autonomic adjustments during the successful mood inductions-a finding that is clearly in contrast to studies that demonstrated autonomic effects of short-lived object-related emotions (e.g., Ax, 1953;Cacioppo et al., 1993;Gross & Levenson, 1997;LeDoux, 1996;Levenson et al., 1990;Prkachin et al., 1999;Schwartz et al., 1981;Sinha et al., 1992;C. A. Smith, 1989;Wagner, 1989). Comparing the aforementioned research with our findings, it is important to note that studies on autonomic concomitants of specific emotions have investigated autonomic effects of short-lived, acute, and object-related affective states. Participants in this research were usually informed that the purpose of administered pr ...
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The impact of mood on effort quantified as autonomic adjustments was investigated in an experiment. The authors induced positive versus negative moods with either 1 of 2 mood induction procedures (music vs. autobiographical recollection) that differed in the extent of required effort. Then participants performed an achievement task after demand appraisals were made. Results were as predicted. During the mood inductions, autonomic reactivity (systolic blood pressure [SBP], diastolic blood pressure, heart rate, skin conductance responses) was stronger in the relatively effortful recollection conditions than in the relatively effortless music conditions. Mood valence had no impact here. But in the context of task performance, the authors found (a) mood congruency effects on the demand appraisals that reflected subjectively higher demand in a negative than in a positive mood, and (b) stronger SBP reactivity in a negative mood compared with a positive mood. Furthermore, SBP reactivity during task performance was correlated with achievement.
... Stance, is therefore an individual or collective perception that communicates one's position on situation(s). Smith [35] and Moors [36] contend that since events occur differently, stance-taking is therefore context-dependent, and depends on the individual's appraisal pattern anchored on certain components. On this, Martin and White [37] , and Pascual and Unger [38] identify three basic components of the ApT: attitude, graduation and engagement. ...
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This paper explores motivations for love as stancetaking in the discourse on romantic relationships among female undergraduates in two Universities in Southern Nigeria. Insights from Community of Practice and Appraisal Theory were used to instantiate the use of situated linguistic choices to establish the different impulses for female undergraduates’ engagement in heterosexual relationships. Data for the study were generated through (non)participant observation, informal interactions and semi-structured interviews involving a representative sample of 44 female undergraduates. The findings show that the participants utilised youth culture of sexual expressiveness to establish their motivations for love, cognitively construed as stancetaking on romantic relationships with their male sexual partners. Participants’ language use shows that the female students’ motivations for loving their male sexual partners include: high sexual performance, good academic performance, financial benefits, intention to get married in future, access to power and security, and physical attractiveness. This study, aside from establishing the increasing practice of heterosexual relationships among Nigerian university undergraduates, has also presented participants’ motivations for sexual the practices as the girls’ peculiar sexual narrations of their worldview. This also shows the creation of situated linguistic choices as outcome of ‘new’ youth expressive culture as demonstrated in the discourse of their sexual relationships and experience within the liberal university environment.
... Stance, whether individually or collectively conceived, represents a resolute position. Stance taking is context-dependent, and may occur differently in different situations, depending on the appraisal pattern of the individuals [40] . Stance taking also varies, and is regulated by several factors, and anchored on practicable components. ...
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This paper investigates the dimensions of emotive language used by women to situate their stances on cheating husbands in Calabar, Southern Nigeria. The data for the study were generated by means of non-participant observation and semi-structured interviews, aided by audiotape recording and field notes. One hundred married women constitute the representative sample from whom the data were elicited. Findings show that the participants used emotional language to establish different stances in discourses on adulterous acts of their husbands. The participants' stances are construed to be nuanced in religious, punitive, revengeful, sociobiological, reconciliatory and legal considerations. Participants' choices were influenced by the women's religious, gendered and sociocultural orientations, educational background and level of exposure, family and social pressure, personal safety and psychological state. These differentials connect the appraisal patterns with the consequences of each stance which should also serves as expository guide on the rational for such decisions by women on cheating spouses. The emotive outbursts by the participants stress the need for men to be faithful to their wives to sustain mutual happiness and peaceful marriages.
... Furthermore, the correct evaluation of emotional states is best performed with a combination of cognitive appraisal and physiological measurements. 42 Thus, integrating algorithms that interpret emotion-related physiological feedback from wearable devices 43 and facial recognition algorithms for emotion recognition may yield the most useful clinical psychiatry applications. ...
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ChatGPT has sparked extensive discussions within the healthcare community since its November 2022 release. However, potential applications in the field of psychiatry have received limited attention. Deep learning has proven beneficial to psychiatry, and GPT is a powerful deep learning‐based language model with immense potential for this field. Despite the convenience of ChatGPT, this advanced chatbot currently has limited practical applications in psychiatry. It may be used to support psychiatrists in routine tasks such as completing medical records, facilitating communications between clinicians and with patients, polishing academic writings and presentations, and programming and performing analyses for research. The current training and application of ChatGPT require using appropriate prompts to maximize appropriate outputs and minimize deleterious inaccuracies and phantom errors. Moreover, future GPT advances that incorporate empathy, emotion recognition, personality assessment, and detection of mental health warning signs are essential for its effective integration into psychiatric care. In the near future, developing a fully‐automated psychotherapy system trained for expert communication (such as psychotherapy verbatim) is conceivable by building on foundational GPT technology. This dream system should integrate practical ‘real world’ inputs and friendly AI user and patient interfaces via clinically validated algorithms, voice comprehension / generation modules, and emotion discrimination algorithms based on facial expressions and physiological inputs from wearable devices. In addition to the technology challenges, we believe it is critical to establish generally accepted ethical standards for applying ChatGPT‐related tools in all mental healthcare environments, including telemedicine and academic/training settings. This article is protected by copyright. All rights reserved.
Chapter
Neuroscientific research on emotion has developed dramatically over the past decade. The cognitive neuroscience of human emotion, which has emerged as the new and thriving area of 'affective neuroscience', is rapidly rendering existing overviews of the field obsolete. This handbook provides a comprehensive, up-to-date and authoritative survey of knowledge and topics investigated in this cutting-edge field. It covers a range of topics, from face and voice perception to pain and music, as well as social behaviors and decision making. The book considers and interrogates multiple research methods, among them brain imaging and physiology measurements, as well as methods used to evaluate behavior and genetics. Editors Jorge Armony and Patrik Vuilleumier have enlisted well-known and active researchers from more than twenty institutions across three continents, bringing geographic as well as methodological breadth to the collection. This timely volume will become a key reference work for researchers and students in the growing field of neuroscience.
Chapter
Neuroscientific research on emotion has developed dramatically over the past decade. The cognitive neuroscience of human emotion, which has emerged as the new and thriving area of 'affective neuroscience', is rapidly rendering existing overviews of the field obsolete. This handbook provides a comprehensive, up-to-date and authoritative survey of knowledge and topics investigated in this cutting-edge field. It covers a range of topics, from face and voice perception to pain and music, as well as social behaviors and decision making. The book considers and interrogates multiple research methods, among them brain imaging and physiology measurements, as well as methods used to evaluate behavior and genetics. Editors Jorge Armony and Patrik Vuilleumier have enlisted well-known and active researchers from more than twenty institutions across three continents, bringing geographic as well as methodological breadth to the collection. This timely volume will become a key reference work for researchers and students in the growing field of neuroscience.
Chapter
Neuroscientific research on emotion has developed dramatically over the past decade. The cognitive neuroscience of human emotion, which has emerged as the new and thriving area of 'affective neuroscience', is rapidly rendering existing overviews of the field obsolete. This handbook provides a comprehensive, up-to-date and authoritative survey of knowledge and topics investigated in this cutting-edge field. It covers a range of topics, from face and voice perception to pain and music, as well as social behaviors and decision making. The book considers and interrogates multiple research methods, among them brain imaging and physiology measurements, as well as methods used to evaluate behavior and genetics. Editors Jorge Armony and Patrik Vuilleumier have enlisted well-known and active researchers from more than twenty institutions across three continents, bringing geographic as well as methodological breadth to the collection. This timely volume will become a key reference work for researchers and students in the growing field of neuroscience.
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Recent work on natural categories suggests a framework for conceptualizing people's knowledge about emotions. Categories of natural objects or events, including emotions, are formed as a result of repeated experiences and become organized around prototypes (Rosch, 1978); the interrelated set of emotion categories becomes organized within an abstract-to-concrete hierarchy. At the basic level of the emotion hierarchy one finds the handful of concepts (love, joy, anger, sadness, fear, and perhaps, surprise) most useful for making everyday distinctions among emotions, and these overlap substantially with the examples mentioned most readily when people are asked to name emotions (Fehr & Russell, 1984), with the emotions children learn to name first (Bretherton & Beeghly, 1982), and with what theorists have called basic or primary emotions. This article reports two studies, one exploring the hierarchical organization of emotion concepts and one specifying the prototypes, or scripts, of five basic emotions, and it shows how the prototype approach might be used in the future to investigate the processing of information about emotional events, cross-cultural differences in emotion concepts, and the development of emotion knowledge.
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