Two good reasons to say 'change!' – ensemble representations as well as item representations impact standard measures of VWM capacity.

Visual working memory (VWM) is a central bottleneck in human information processing. Its capacity is most often measured in terms of how many individual‐item representations VWM can hold (k). In the standard task employed to estimate k, an array of highly discriminable colour patches is maintained a...

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Published in:British Journal of Psychology Vol. 110; no. 2; pp. 328 - 357
Main Authors: Liesefeld, Heinrich René, Liesefeld, Anna M., Müller, Hermann J.
Format: Article
Published: Wiley-Blackwell May2019
Subjects:
Online Access:View this record in EBSCOhost
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        atl: Two good reasons to say 'change!' – ensemble representations as well as item representations impact standard measures of VWM capacity.
      aug:
        au:
          Liesefeld, Heinrich René
          Liesefeld, Anna M.
          Müller, Hermann J.
        affil:
          Department Psychologie, Ludwig‐Maximilians‐Universität München, Germany
          Graduate School of Systemic Neurosciences, Ludwig‐Maximilians‐Universität München, Germany
          Department of Psychological Sciences, Birkbeck College, University of London, UK
      su:
        Task performance
        Color vision testing
        Short-term memory
        Visual perception
        Statistical models
      sug:
        subj:
          Task performance
          Color vision testing
          Short-term memory
          Visual perception
          Statistical models
      keyword:
        change detection
        change localization
        cognitive modelling
        visual short‐term memory
        working memory capacity
        change detection
        change localization
        cognitive modelling
        visual short‐term memory
        working memory capacity
      ab: Visual working memory (VWM) is a central bottleneck in human information processing. Its capacity is most often measured in terms of how many individual‐item representations VWM can hold (k). In the standard task employed to estimate k, an array of highly discriminable colour patches is maintained and, after a short retention interval, compared to a test display (change detection). Recent research has shown that with more complex, structured displays, change‐detection performance is, in addition to individual‐item representations, supported by ensemble representations formed as a result of spatial subgroupings. Here, by asking participants to additionally localize the change, we reveal indication for an influence of ensemble representations even in the very simple, unstructured displays of the colour‐patch change‐detection task. Critically, pure‐item models from which standard formulae of k are derived do not consider ensemble representations and, therefore, potentially overestimate k. To gauge this overestimation, we develop an item‐plus‐ensemble model of change detection and change localization. Estimates of k from this new model are about 1 item (~30%) lower than the estimates from traditional pure‐item models, even if derived from the same data sets.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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