Statistical learning and retrieval-based inference in the acquired equivalence paradigm

Memory Cognitive Psychology Social and Behavioral Sciences
DOI: 10.31234/osf.io/bdpn6 Publication Date: 2023-10-26T05:00:45Z
ABSTRACT
Introduction: Generalization is fundamental to cognition. In acquired equivalence, twostimuli that share a common association become treated as equivalent, with informationacquired about one stimulus generalizing to the other. Acquired equivalence has beenthought to rely on integrating related memories as they are encoded, resulting in fastspontaneous generalization, but other studies suggested effortful on-demand recombinationof initially separate memories at retrieval. Here, we tested whether the tendency to separateversus integrate related information may depend on a methodological detail of a traditionalacquired equivalence paradigm.Methods: Human participants underwent feedback-based learning of overlapping face-sceneassociations, choosing a correct scene for a face from two options on each trial. Foil(incorrect) scenes were controlled for half of the participants to ensure that they can onlylearn from corrective feedback. The other half had foils selected randomly on each trial,allowing statistical learning of face-scene co-occurrence to supplement feedback-basedlearning. We hypothesized that the opportunity for statistical learning would boost learningand generalization and facilitate memory integration.Results: The opportunity for statistical learning increased associative learning andgeneralization. However, rather than integrated memories, generalization was increasedthrough learning during test.Discussion: The results indicate that the tendency for generalization in the acquiredequivalence is rather small, with no evidence for integrative encoding irrespective of group.They also highlight that methodological details of how associations are learned and testedmodulates performance and the involvement of cognitive processes that underlie it.
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