Literature DB >> 31313637

Mapping the Passions: Toward a High-Dimensional Taxonomy of Emotional Experience and Expression.

Alan Cowen1, Disa Sauter2, Jessica L Tracy3, Dacher Keltner1.   

Abstract

What would a comprehensive atlas of human emotions include? For 50 years, scientists have sought to map emotion-related experience, expression, physiology, and recognition in terms of the "basic six"-anger, disgust, fear, happiness, sadness, and surprise. Claims about the relationships between these six emotions and prototypical facial configurations have provided the basis for a long-standing debate over the diagnostic value of expression (for review and latest installment in this debate, see Barrett et al., p. 1). Building on recent empirical findings and methodologies, we offer an alternative conceptual and methodological approach that reveals a richer taxonomy of emotion. Dozens of distinct varieties of emotion are reliably distinguished by language, evoked in distinct circumstances, and perceived in distinct expressions of the face, body, and voice. Traditional models-both the basic six and affective-circumplex model (valence and arousal)-capture a fraction of the systematic variability in emotional response. In contrast, emotion-related responses (e.g., the smile of embarrassment, triumphant postures, sympathetic vocalizations, blends of distinct expressions) can be explained by richer models of emotion. Given these developments, we discuss why tests of a basic-six model of emotion are not tests of the diagnostic value of facial expression more generally. Determining the full extent of what facial expressions can tell us, marginally and in conjunction with other behavioral and contextual cues, will require mapping the high-dimensional, continuous space of facial, bodily, and vocal signals onto richly multifaceted experiences using large-scale statistical modeling and machine-learning methods.

Entities:  

Keywords:  affect; emotion; expression; face; semantic space; signal; voice

Year:  2019        PMID: 31313637      PMCID: PMC6675572          DOI: 10.1177/1529100619850176

Source DB:  PubMed          Journal:  Psychol Sci Public Interest        ISSN: 1529-1006


  11 in total

1.  Toward Multimodal Modeling of Emotional Expressiveness.

Authors:  Victoria Lin; Jeffrey M Girard; Michael A Sayette; Louis-Philippe Morency
Journal:  Proc ACM Int Conf Multimodal Interact       Date:  2020-10

2.  The Development of Negative Event-Emotion Matching in Infancy: Implications for Theories in Affective Science.

Authors:  Ashley L Ruba; Andrew N Meltzoff; Betty M Repacholi
Journal:  Affect Sci       Date:  2020-04-16

3.  A systematic review of neural, cognitive, and clinical studies of anger and aggression.

Authors:  Yuliya Richard; Nadia Tazi; Dorota Frydecka; Mohamed S Hamid; Ahmed A Moustafa
Journal:  Curr Psychol       Date:  2022-06-08

4.  What music makes us feel: At least 13 dimensions organize subjective experiences associated with music across different cultures.

Authors:  Alan S Cowen; Xia Fang; Disa Sauter; Dacher Keltner
Journal:  Proc Natl Acad Sci U S A       Date:  2020-01-06       Impact factor: 11.205

5.  The Neural Representation of Visually Evoked Emotion Is High-Dimensional, Categorical, and Distributed across Transmodal Brain Regions.

Authors:  Tomoyasu Horikawa; Alan S Cowen; Dacher Keltner; Yukiyasu Kamitani
Journal:  iScience       Date:  2020-04-17

Review 6.  Music Lessons for the Study of Affect.

Authors:  Robert R McCrae
Journal:  Front Psychol       Date:  2021-11-29

7.  Classification of emotion categories based on functional connectivity patterns of the human brain.

Authors:  Heini Saarimäki; Enrico Glerean; Dmitry Smirnov; Henri Mynttinen; Iiro P Jääskeläinen; Mikko Sams; Lauri Nummenmaa
Journal:  Neuroimage       Date:  2021-12-09       Impact factor: 6.556

8.  Editorial: Imaginative culture and human nature: Evolutionary perspectives on the arts, religion, and ideology.

Authors:  Joseph Carroll; John A Johnson; Emelie Jonsson; Rex E Jung; Valerie van Mulukom
Journal:  Front Psychol       Date:  2022-08-31

9.  Universal facial expressions uncovered in art of the ancient Americas: A computational approach.

Authors:  Alan S Cowen; Dacher Keltner
Journal:  Sci Adv       Date:  2020-08-19       Impact factor: 14.136

10.  Statistical pattern recognition reveals shared neural signatures for displaying and recognizing specific facial expressions.

Authors:  Sofia Volynets; Dmitry Smirnov; Heini Saarimäki; Lauri Nummenmaa
Journal:  Soc Cogn Affect Neurosci       Date:  2020-10-08       Impact factor: 3.436

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