Category relevance attenuates overshadowing in human predictive learning
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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 post-test 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). Previously relevant categories were less prone to overshadowing, but not in the alternative one. Results are discussed in light of attentional and configural theories of associative learning.
- Paired-association learning
- overshadowing, pretraining, elemental, configural, intradimensional
- Biological Sciences::Psychology::Cognitive & affective psychology::Psychology of memory & learning
- B Philosophy. Psychology. Religion::BF Psychology
- University of Nottingham, UK Campus::Faculty of Science::School of Psychology
Data typeBehavioural results of predictive learning experiments. During training, participants need to predict whether an outcome will occur on the basis of signals by answering yes or no. During test, participants give a predictive rating for each signal, indication (from 0 to 100) whether the outcome will occur in the presence of the signal.
- Alcalá, José A
- Prados, Jose
- Economic & Social Research Council
Data collection methodOnline data collection. Participants were recruited through Prolific.