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Transforming valences through transitive inference: How are faces emotionally dissonant?

Amd, Micah and Roche, Bryan (2017) Transforming valences through transitive inference: How are faces emotionally dissonant? Quarterly Journal of Experimental Psychology, 70 (12). pp. 2478-2496. ISSN 0033-555X

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    Information that is emotionally incongruous with self-concepts can produce feelings of unease. This implies that embedding incongruous information in newly formed relational structures would have little effect on their previous emotive properties. Alternatively, Relational Frame Theory highlights the importance of contextualized stimulus-stimulus relations, where the structure of a relational series is key in determining the function of its elements. To see whether series membership can mitigate ‘dissonance’ when a salient element is employed, the present investigation trained and tested a seven-term relational series (X>A>B>C>D>E>Y) using blurred faces as stimuli. Specifically, Stimuli X, A, B, D, E and Y were blurred unfamiliar faces and Stimulus C constituted of the participant’s own blurred face, assumed to be more salient than the former. To assess how the valences of the related stimuli were transformed by relational series membership, self-report ratings and electroencephalographic (EEG) recordings were collected before and after training the X>A>B>C>D>E>Y series. These pre vs. post contrasts revealed that, for unfamiliar faces, stimulus valence transformed as a function of relational structure. Conversely, the lack of difference in pre vs. post contrasts of Stimulus C, which maintained a high valence, suggest that relational series membership may not suffice to mitigate emotionally dissonant information.

    Item Type: Journal Article
    Subjects: B Philosophy. Psychology. Religion > BF Psychology
    H Social Sciences > H Social Sciences (General)
    Divisions: Faculty of Arts, Law and Education (FALE) > School of Social Sciences
    Depositing User: Micah Ahmad
    Date Deposited: 15 Jul 2019 16:04
    Last Modified: 18 Oct 2019 08:17

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