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Title: Autonomic specificity of discrete emotion and dimensions of affective space: a multivariate approach
Author(s): I.C. Christie and B.H. Friedman
Journal: Int.J.Psychophysiol.
Year: 2004
Volume: 51
Issue: 2
Pages: 143--153
Publisher address: Department of Psychology, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0436, USA. bhfried@vt.edu
File URL: vuams-pubs/Christie___Friedman_2004.pdf
Keywords: Adolescent, Adult, Affect, analysis, Anger, Autonomic Nervous System, blood, Blood Pressure, classification, Electric Conductivity, Electrocardiography, Emotions, Female, Galvanic Skin Response, Heart, Heart Rate, Humans, instrumentation, Male, methods, Motion Pictures as Topic, Multivariate Analysis, Photic Stimulation, physiology, Pressure, psychology, Questionnaires, Skin Physiological Phenomena
Abstract: The present study addressed autonomic nervous system (ANS) patterning during experimentally manipulated emotion. Film clips previously shown to induce amusement, anger, contentment, disgust, fear and sadness, in addition to a neutral control film, were presented to 34 college-aged subjects while skin conductance, blood pressure and the electrocardiogram (ECG) were recorded, as was self-reported affect. Both mean of and mean successive difference of heart period were derived from the ECG. Pattern classification analyses revealed emotion-specific autonomic patterning for all emotion conditions except disgust; all emotion conditions exhibited significant patterning using self-report. Discriminant function analysis was used to describe the location of discrete emotions within dimensional affective space using both self-report and ANS variables. Findings suggest that the dimensions of valence and activation portray the structure of self-reported emotion, but that valence is more accurately described as approach-withdrawal when applied to autonomic responses during discrete emotions. The findings provide further support for the existence of emotion-specific ANS activity, and are consistent with a hybrid discrete-dimensional model of affective space

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