Autonomic Differentiation of Emotions: A Cluster Analysis Approach
The autonomic specificity of emotion is intrinsic for many major theories of emotion.
One of the goals of this study was to validate a standardized set of music clips to be used
in studies of emotion and affect. This was accomplished using self-reported affective
responses to 40 music pieces, noise, and silence clips in a sample of 71 college-aged
individuals. Following the music selection phase of the study; the validated music clips as
well as film clips previously shown to induce a wide array of emotional responses were
presented to 50 college-aged subjects while a montage of autonomic variables were
measured. Evidence for autonomic discrimination of emotion was found via pattern
classification analysis replicating findings from previous research. It was theorized that
groups of individuals could be identified based upon individual response specificity using
cluster analytic techniques. Single cluster solutions for all emotion conditions indicated
that stimulus response stereotypy of emotions was more powerful than individual
patterns. Results from pattern classification analysis and cluster analysis support the
concept of autonomic specificity of emotion.