Journal of Vision Cover Image for Volume 17, Issue 10
September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
The Functional Limit in Visual Working Memory Storage: The Tale Is In The Tail
Author Affiliations
  • Marcus Cappiello
    Department of Psychology, University of California, Riverside
  • Weiwei Zhang
    Department of Psychology, University of California, Riverside
Journal of Vision August 2017, Vol.17, 110. doi:https://doi.org/10.1167/17.10.110
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      Marcus Cappiello, Weiwei Zhang; The Functional Limit in Visual Working Memory Storage: The Tale Is In The Tail. Journal of Vision 2017;17(10):110. https://doi.org/10.1167/17.10.110.

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

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Abstract

Although working memory plays a significant role in a wide range of cognitive domains, its storage capacity is highly limited. The nature of this limit in visual working memory (VWM) has been the subject of considerable controversy. The discrete-slot model attributes the bottleneck in VWM storage to capacity (i.e., a limited number of discrete slots). In contrast, the variable precision model replaces the capacity limit with variable mnemonic precision in that the variance in precision could produce extremely low precision that behaviorally resembles random memory responses. One common misconception about the discrete-slot model assumes no variance in mnemonic precision across items and trials, potentially leading to the model's poor performance in comparison to the variable precision model. More importantly, the most fundamental difference between the two models is the presence (discrete-slot model) or absence (variable precision model) of guessing for a large number of to-be-remembered items (i.e. a capacity limit). The present study thus adopted four approaches to establish this discrete nature of VWM storage. First, the slot model with variability sufficiently accounted for residual errors in model fits. Second, the slot model outperformed the variable precision model at large memory set sizes when capacity constrained recall performance more than precision. Thirdly, the variable precision model produced increasing proportion of extremely low precision trials that are indistinguishable from guessing (and hence functionally equivalent to capacity) over memory set sizes. Lastly, non-parametric modeling of recall data showed strong evidence for two discrete clustering of precision in the true underlying distribution (one for guessing and the other for graded memory representation). Together these results provide strong support for the slot model of VWM storage limit.

Meeting abstract presented at VSS 2017

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