Preexisting semantic representation improves working memory performance in the visuospatial domain

Mary Rudner, Eleni Orfanidou, Velia Cardin, Cheryl M. Capek, Bencie Woll, Jerker Rönnberg

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Working memory (WM) for spoken language improves when the to-be-remembered items correspond to preexisting representations in long-term memory. We investigated whether this effect generalizes to the visuospatial domain by administering a visual n-back WM task to deaf signers and hearing signers, as well as to hearing nonsigners. Four different kinds of stimuli were presented: British Sign Language (BSL; familiar to the signers), Swedish Sign Language (SSL; unfamiliar), nonsigns, and nonlinguistic manual actions. The hearing signers performed better with BSL than with SSL, demonstrating a facilitatory effect of preexisting semantic representation. The deaf signers also performed better with BSL than with SSL, but only when WM load was high. No effect of preexisting phonological representation was detected. The deaf signers performed better than the hearing nonsigners with all sign-based materials, but this effect did not generalize to nonlinguistic manual actions. We argue that deaf signers, who are highly reliant on visual information for communication, develop expertise in processing sign-based items, even when those items do not have preexisting semantic or phonological representations. Preexisting semantic representation, however, enhances the quality of the gesture-based representations temporarily maintained in WM by this group, thereby releasing WM resources to deal with increased load. Hearing signers, on the other hand, may make strategic use of their speech-based representations for mnemonic purposes. The overall pattern of results is in line with flexible-resource models of WM.

Original languageEnglish
Pages (from-to)608-620
Number of pages13
JournalMemory & Cognition
Issue number4
Early online date22 Jan 2016
Publication statusPublished - May 2016


  • Working memory
  • Visuospatial
  • Sign language
  • Deafness
  • Semantic

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