August 2023
Volume 23, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2023
Investigating visual working memory capacity using a highly reliable change localization task
Author Affiliations & Notes
  • Temilade Adekoya
    University of Chicago
  • Chong Zhao
    Mila - Québec AI Institute, Montréal, QC, Canada
  • Edward Vogel
    Université de Montréal, Montreal, QC, Canada
  • Edward Awh
    National Research Council Canada (NRC), Ottawa, OT, Canada
  • Footnotes
    Acknowledgements  We acknowledge the funding from National Institute of Mental Health (grant ROIMH087214); Office of Naval Research (grant N00014-12-1-0972).
Journal of Vision August 2023, Vol.23, 5652. doi:
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      Temilade Adekoya, Chong Zhao, Edward Vogel, Edward Awh; Investigating visual working memory capacity using a highly reliable change localization task. Journal of Vision 2023;23(9):5652.

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      © ARVO (1962-2015); The Authors (2016-present)

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In change detection tasks, observers are asked to store a handful of items in working memory, and then subsequently indicate whether one of those items has changed in a test display. This task provides highly reliable estimates of working memory capacity, and exhibits robust correlations with outcome variables of interest, such as fluid intelligence. Here, we present a variant of this task, called change localization. This task closely resembles change detection, except that an item changes on every trial, and the observer’s task is to indicate which item changed. Using both color and shape stimuli, we show that performance on this task is strongly correlated with change detection performance, suggesting that change localization measures the same aspects of working memory ability. Moreover, change localization scores achieve high reliability with less than half of the trials required with change detection. Likewise, far fewer trials were required to detect known empirical effects, such as the impact of larger set sizes and the correlation between working memory capacity and the harmful effects of overload. Thus, change localization provides a highly reliable and efficient method for obtaining precise estimates of working memory performance. Finally, we will discuss data from an ongoing study in which we examine the consequences of stimulus heterogeneity on storage in visual working memory. While some theorists have proposed that working memory storage should be easier with heterogeneous displays, homogeneous displays may reduce competitions within cellular assemblies coding for a specific feature. Here we aim to test the hypothesis using the change localization paradigm. Specifically, we are interested in whether participants exhibit different capacity estimates between homogeneous arrays that contain only one type of feature (color or shape) or heterogeneous arrays that include both color and shape memoranda.


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