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Category relevance attenuates overshadowing in human predictive learning.

José A. Alcalá; José Prados; Gonzalo P. Urcelay

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Title: Category relevance attenuates overshadowing in human predictive learning.
Author: José A. Alcalá; José Prados; Gonzalo P. Urcelay
Source: Journal of Experimental Psychology. Animal Learning and Cognition · DOI 10.1037/xan0000357 Published 2023-07-01 · Open source record
License: CC BY 4.0 deed

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In situations in which multiple predictors anticipate the presence or absence of an outcome, cues compete to anticipate the outcome, resulting in a loss of associative strength compared to control conditions without additional cues. Critically, there are multiple factors modulating the magnitude and direction of such competition, although in some scenarios the effect of these factors remains unexplored. We sought to assess whether the relative salience of the elements in a compound of cues modulates the magnitude of the overshadowing effect in human predictive learning. Two separable categories (i.e., colors and symbols) were used in a predictive learning task. In Experiment 1, different groups of participants were granted with different time of exposure to a compound of cues belonging to different categories (color and symbol) to evaluate potential differences in the magnitude of overshadowing. Furthermore, we used posttest questionnaires to assess whether participants used either only one or both categories during training, and assessed if this impacted the magnitude of overshadowing. In general, overshadowing was not modulated by the time of exposition, except in the case of very short time of exposition with prominent learning about the most salient category. In Experiment 2, the relative salience of a category was biased via prior experience either with a biconditional discrimination or attending only the relevant category (either color or symbol). The previously relevant category was less prone to overshadowing, but not the alternative one. Results are discussed in light of attentional and configural theories of associative learning.

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Original journal: Journal of Experimental Psychology. Animal Learning and Cognition
Published: 2023-07-01
DOI: 10.1037/xan0000357
Open record: PMC10339660

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