Connectionist Model Accounting for Retardation of Cognitive-Dissonance Reduction Caused by Attention-Focus Switching

Connectionist Model Accounting for Retardation of Cognitive-Dissonance Reduction Caused by Attention-Focus Switching Takao Matsumoto (matsumoto@c.dendai.ac.jp) Tokyo Denki University 5 Senju-Asahi-cho, Adachi-ku, Tokyo 120-8551, Japan Abstract A novel connectionist model accounting for cognitive dissonance is described, in which the concepts of self and attention are considered. The model makes it possible to use mathematical formulas to represent the cognitive-dissonance process. Analysis reveals that the model fits experimental data of major paradigms in cognitive dissonance theory and that attention-focus switching causes building-up of cognitive dissonance and retardation of its reduction. Keywords: cognitive dissonance; connectionist model; attention; self-concept; mathematical analysis Introduction Cognitive dissonance theory insists that dissonance is a psychological state of tension that people are motivated to reduce (Festinger, 1957). Dissonance causes feelings of discomfort, unhappiness, or distress. Any two cognitions are dissonant when one of them follows from the obverse of the other. To reduce dissonance, people add consonant cognitions or change evaluations for one or both cognitions to make them more consistent. Cognitive dissonance theory makes a clear prediction when a firm expectancy is involved as one of the cognitions in question (Aronson, 1969). A well-known example of this is the famous Aesop’s fable “The fox and the grapes. ” In the story, a fox wanted to get some grapes hanging high on vines and leaped with effort, but couldn’t get them. Walking away, the fox said, “The grapes are surely sour, and I do not need them. ” Since the expectation and experience were inconsistent, the fox had cognitive dissonance, which he reduced by convincing himself that the expectation was not appropriate. Shultz and Lepper (1996) proposed a connectionist model accounting specifically for the mechanism of cognitive dissonance. A constraint satisfaction neural network model was used to simulate data from the several major cognitive dissonance paradigms (Shultz, Leveille, & Lepper, 1999). In it weights between nodes are fixed and activations of units are changed. Dissonance is defined by a formula that is a function of activations of units and weights applied to links in the network. Networks tend to settle into a less dissonant state as activations of units are changed according to update rules. Another connectionist model was proposed by Van Overwalle and colleagues (2002, 2005). They represented attitudes in a feed-forward neural network with the delta- learning rule in which weights are allowed to change. Input nodes represent the features of the environment and two output ports represent behavior and affect. Dissonance is defined as the discrepancy between expected and actual outcomes. They also simulated the experimental results of major cognitive dissonance paradigms. Several other computational models have been reported that deal with attitude phenomena through simulation using constraint- satisfaction or non-constraint-satisfaction networks (Mosler et al., 2001; Petty & Cacioppo, 1986; Read & Miller; 1994; Spellman, Ullman, & Holyoak, 1993). People are motivated to prioritize to protect their self- system. Self-consistency theory (Aronson, 1969; Thibodeau and Aronson, 1992) emphasizes that self is involved in dissonance arousal and that not only cognitions but also self-concept need to be considered in discussing dissonance. Judgment and assessment for cognitions performed by self possibly become motives for arousal of cognitive dissonance. On the other hand, attention is an important phenomenon of information processing in cognitive systems (Pisapia, Repovs, & Braver, 2008). It is a function for selecting and enhancing a limited area of information, while suppressing other areas. Cognitions are included in these areas of information. To the author’s knowledge, connectionist models for cognitive dissonance taking the concepts of self and attention into account have not been presented. In this paper, a novel model considering these concepts is described and reduction of cognitive dissonance based on the model is discussed. Connectionist Model Figure 1 shows our connectionist model accounting for cognitive dissonance. In accordance with the cognitive dissonance theory (Festinger, 1957), two cognitions are adopted in the model, which are depicted as units R and I. We assume that unit R is a reality-based cognition such as the cognition of behavior, experience, or actual situation, while unit I is an imagination-based cognition such as the cognition of expectancy, hope, or belief. In the case of the previously mentioned fable, the imagination-based cognition held by the fox is “The grapes can stave off my hunger” and the reality-based cognition is “The grapes do not stave off my hunger. ” Attention plays an important role in cognitive systems. It selects and enhances limited cognitions and suppresses others. If we consider two cognitions alone, when one of them is selected and enhanced, the other is rejected and