Processing lexicality in Alzheimer’s disease and healthy aging

Words in the World / Mots dans le Monde Forums Proposals for Collaboration Processing lexicality in Alzheimer’s disease and healthy aging

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    • #741
      Laura Teddiman
      Keymaster

      Posted on behalf of Nancy Azevedo, University of Montreal/McGill University, Eva Kehayia, McGill University, & Gonia Jarema, University of Montreal

      Motivation:

      Processing lexicality is known to be influenced by many factors, including the number of lexical neighbours an item has. In young adults (YAs), neighbourhood density (N) has been found to influence a person’s ability to make lexicality judgements (Andrews, 1997). Called the N effect, a large lexical neighbourhood facilitates word access but is inhibitory for pseudowords for young adults (YAs). In order to investigate changes in how N is processed in healthy aging we ran a visual lexical decision task on monolingual English-speaking YAs in Kansas and on dominant English-speaking older adults (OAs) in Montreal. Data from this task showed two main findings. 1) While YAs showed the predicted N effect for words and pseudowords, OAs showed an N effect for pseudowords only. 2) YAs made significantly more errors to high-N pseudowords than OAs (but not to low-N pseudowords nor to high- or low-N words). While we initially attributed these differences to age differences between the groups, it is possible that they may have been related to differences in language background between the groups (YAs were monolinguals from the US while OAs were bi-multilinguals from Canada).

      In an attempt to disentangle the effects of language background and age on the N effect we are currently running the experiment on a group of YAs in Montreal who have a similar language background to the OAs from the initial study, i.e. bilingual or multilingual dominant English-speakers.
      However, in order to complete the study, we are seeking to recruit a group of Canadian monolingual English YAs and of OAs that we do not have access to in the Montreal area.

      Theoretical and applied impact:

      Although the effects of N on lexical processing in young adults are believed to be fairly well understood, our understanding of these effects across the adult lifespan is much poorer. A closer examination of how N affects lexical processing across the adult lifespan and how this may be affected by language background may provide insight into potential changes in organization or timing within the mental lexicon, thus enhancing our understanding of lexical processing across the lifespan.

      What contributions do we ask for:

      – Recruit monolingual English healthy young (age 18-30, n=25) and older (age 50-85, n=25) adults and conduct two behavioral experiments that have already been developed (visual lexical decision and number Stroop).
      – Your contribution will involve allocating lab time, a student or research assistant (or allowing a research assistant from our lab to come there), and possibly equipment (a laptop or desktop computer running E-Prime 2.0) for participant recruitment and data collection.
      – In addition, collaborators may also participate in data preparation, statistical analyses, manuscript development, and conference presentations.
      What do we offer:
      – We will provide both experiment scripts (in E-Prime 2.0).
      – We will be responsible for data preparation, statistical analyses, manuscript development, and conference presentations (or we are open to a collaboration in which these will be shared and thus authorship will also be shared).
      – Partial or full funding of a research assistant (we do not have ethics approval to compensate participants).

      Contact info:
      Nancy Azevedo, azevedo.nancy1 – at – gmail.com

    • #743
      Pablo Gomez
      Guest

      Would the team be interested in diffusion modeling this data?

    • #1161
      Nancy Azevedo
      Guest

      Hello Pablo,

      I apologize for the delay in replying. We would be very interested in talking about the possibility of diffusion modeling the data.

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