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The role of working memory loads on immediate and long-term sentence recall

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ABSTRACT It is well-established that both phonological and semantic knowledge influence verbal working memory. However, the focus has primarily been on understanding phonological effects despite evidence of semantic influences. Articulatory… Click to show full abstract

ABSTRACT It is well-established that both phonological and semantic knowledge influence verbal working memory. However, the focus has primarily been on understanding phonological effects despite evidence of semantic influences. Articulatory suppression is a well-established task for preventing phonological processing. Methods to prevent semantic processing have rarely been used in the past, highlighting a need for developing a semantic interference task. We, therefore, conceptualised two novel tasks – an animacy categorisation and semantic relatedness judgement task. This study explored the impact of phonological (articulatory suppression) and semantic loads (animacy categorisation and semantic relatedness judgement) on immediate and delayed sentence recall. Additionally, sentence concreteness (concrete vs. abstract sentences) indexed semantic knowledge in verbal working memory. Across two studies, immediate recall revealed that articulatory suppression (preventing phonological processing) increased the size of the concreteness effect, while the novel semantic tasks (preventing semantic processing) reduced it suggesting that our semantic tasks were indeed imposing a semantic load. Further, relative long-term performance showed that more new words were remembered in articulatory suppression, whereas recall was disproportionately impaired in the semantic relatedness task. Our experimental paradigm offers phonological and semantic suppression tasks that can be used in parallel to investigate the interactions between working memory and language.

Keywords: long term; working memory; sentence recall; memory; articulatory suppression

Journal Title: Memory
Year Published: 2022

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