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    Is the devil in the detail? Evidence for S-S learning after unconditional stimulus revaluation in human evaluative conditioning under a broader set of experimental conditions

    260673.pdf (441.2Kb)
    Access Status
    Open access
    Authors
    Jensen-Fielding, H.
    Luck, Camilla
    Lipp, Ottmar
    Date
    2017
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Jensen-Fielding, H. and Luck, C. and Lipp, O. 2017. Is the devil in the detail? Evidence for S-S learning after unconditional stimulus revaluation in human evaluative conditioning under a broader set of experimental conditions. Cognition and Emotion. 32 (6): pp. 1275-1290.
    Source Title
    Cognition and Emotion
    DOI
    10.1080/02699931.2017.1408573
    ISSN
    0269-9931
    School
    School of Psychology
    URI
    http://hdl.handle.net/20.500.11937/62464
    Collection
    • Curtin Research Publications
    Abstract

    Whether valence change during evaluative conditioning is mediated by a link between the conditional stimulus (CS) and the unconditional stimulus (US; S-S learning) or between the CS and the unconditional response (S-R learning) is a matter of continued debate. Changing the valence of the US after conditioning, known as US revaluation, can be used to dissociate these accounts. Changes in CS valence after US revaluation provide evidence for S-S learning but if CS valence does not change, evidence for S-R learning is found. Support for S-S learning has been provided by most past revaluation studies, but typically the CS and US have been from the same stimulus category, the task instructions have suggested that judgements of the CS should be based on the US, and USs have been mildly valenced stimuli. These factors may bias the results in favour of S-S learning. We examined whether S-R learning would be evident when CSs and USs were taken from different categories, the task instructions were removed, and more salient USs were used. US revaluation was found to influence explicit US evaluations and explicit and implicit CS evaluations, supporting an S-S learning account and suggesting that past results are stable across procedural changes.

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