August 2012
Volume 12, Issue 9
Vision Sciences Society Annual Meeting Abstract  |   August 2012
Integrated Model of Visual Working Memory
Author Affiliations
  • Wilson Chu
    Department of Cognitive Sciences, University of California, Irvine, CA 92697-5100
  • Barbara Dosher
    Department of Cognitive Sciences, University of California, Irvine, CA 92697-5100
  • Zhong-Lin Lu
    Department of Psychology, The Ohio State University, Columbus, OH 43210\nDepartment of Psychology, University of Southern California, Los Angeles, CA 90089
Journal of Vision August 2012, Vol.12, 713. doi:
  • Views
  • Share
  • Tools
    • Alerts
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Wilson Chu, Barbara Dosher, Zhong-Lin Lu; Integrated Model of Visual Working Memory. Journal of Vision 2012;12(9):713.

      Download citation file:

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

  • Supplements

Models of visual working memory (VWM) have recently been assessed using cued feature report, predicting performance for clearly visible stimuli by estimating the probability of being in VWM and the variability of feature encoding (Zhang & Luck, 2008; Bays, et al., 2009). However, VWM presumably must operate on low contrast and noisy stimuli, not just on highly visible ones. We report an integrated multi-alternative template model of VWM with stimulus variations of contrast and external noise that provide demanding new tests. 900 ms after display, the observers were cued to report the orientation of one of up to four briefly presented Gabors from a selection of 20 orientations (every 9°). We measured display size effects (1, 2, 4) with and without external noise for Gabors at eight contrast levels. Memory report was systematically affected by display size, Gabor contrast, and external noise, varying from poor to excellent. Yet, there is a surprising similarity of the spread of the reports around the correct orientation for conditions at many levels of performance. A multi-alternative perceptual template model provides a full account of the data. Twenty templates respond with gains depending on the match between each template and the cued target stimulus. Additive and multiplicative noises are added to the outputs of the templates. A max rule chooses the response. Focal attention in smaller displays enhances the representations by reducing internal additive noise and improved filtering of external noise, so estimates of total internal noise increase with display size (Wilken & Ma, 2004). However, the spread of the distribution of the reported orientations does not vary with display size – it is determined by the tuning of the competing templates. The multi-alternative template model provides a parameter-efficient and counter-intuitive integrated account of VWM and attention over many display conditions, challenging existing VWM model.

Meeting abstract presented at VSS 2012


This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.