Concurrence of rule- and similarity-based mechanisms in artificial grammar learning

Cognitive Psychology
Bertram Opitz, Juliane Hofmann

Abstract

A current theoretical debate regards whether rule-based or similarity-based learning prevails during artificial grammar learning (AGL). Although the majority of findings are consistent with a similarity-based account of AGL it has been argued that these results were obtained only after limited exposure to study exemplars, and performance on subsequent grammaticality judgment tests has often been barely above chance level. In three experiments the conditions were investigated under which rule- and similarity-based learning could be applied. Participants were exposed to exemplars of an artificial grammar under different (implicit and explicit) learning instructions. The analysis of receiver operating characteristics (ROC) during a final grammaticality judgment test revealed that explicit but not implicit learning led to rule knowledge. It also demonstrated that this knowledge base is built up gradually while similarity knowledge governed the initial state of learning. Together these results indicate that rule- and similarity-based mechanisms concur during AGL. Moreover, it could be speculated that two different rule processes might operate in parallel; bottom-up learning via gradual rule extraction and top-down learning via rule ...Continue Reading

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Citations

Sep 22, 2018·Human Brain Mapping·Luyao ChenLiping Feng
May 30, 2019·Psychonomic Bulletin & Review·Raquel G Alhama, Willem Zuidema
Apr 7, 2020·Neurobiology of Learning and Memory·Gesa SchaadtAngela D Friederici

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