A multifactor-system dynamics theory of emotion

Abstract

In multifactor individuality theory, emotion is treated as the product of the interaction of the cognitive and affective systems, where the cognitive system is defined as a multidimensional, hierarchical system that transforms information in order to detect environmental invariants, and the affective system is defined as a multidimensional hierarchical system that transforms information into arousal states. The highest order dimensions of the cognitive system are conceptual, perceptual, and symbolizing; the highest order dimensions of the affective system are emotional independence, introversion — extroversion, and emotional stability. The concept of arousal provides a key to understanding the complex interactions between cognition and affect. It is hypothesized that specifiable subsets of cognitive and affective dimensions conform to either the facilitative or decremental effects of arousal, and that the Yerkes-Dodson inverted-U function is a composite of both effects. An explanation for the differentiation of distinct emotional states is also presented. Essentially, emotions are differentiated by different weightings of the affective and cognitive dimensions. A theoretical framework for studying the temporal sequencing of phases of emotional behavior is presented as well.