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Fine-Grained, Local Maps and Coarse, Global Representations Support Human Spatial Working Memory

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  • Mohammad Zia Ul Haq Katshu
  • Giovanni d'Avossa

Abstract

While sensory processes are tuned to particular features, such as an object's specific location, color or orientation, visual working memory (vWM) is assumed to store information using representations, which generalize over a feature dimension. Additionally, current vWM models presume that different features or objects are stored independently. On the other hand, configurational effects, when observed, are supposed to mainly reflect encoding strategies. We show that the location of the target, relative to the display center and boundaries, and overall memory load influenced recall precision, indicating that, like sensory processes, capacity limited vWM resources are spatially tuned. When recalling one of three memory items the target distance from the display center was overestimated, similar to the error when only one item was memorized, but its distance from the memory items' average position was underestimated, showing that not only individual memory items' position, but also the global configuration of the memory array may be stored. Finally, presenting the non-target items at recall, consequently providing landmarks and configurational information, improved precision and accuracy of target recall. Similarly, when the non-target items were translated at recall, relative to their position in the initial display, a parallel displacement of the recalled target was observed. These findings suggest that fine-grained spatial information in vWM is represented in local maps whose resolution varies with distance from landmarks, such as the display center, while coarse representations are used to store the memory array configuration. Both these representations are updated at the time of recall.

Suggested Citation

  • Mohammad Zia Ul Haq Katshu & Giovanni d'Avossa, 2014. "Fine-Grained, Local Maps and Coarse, Global Representations Support Human Spatial Working Memory," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-13, September.
  • Handle: RePEc:plo:pone00:0107969
    DOI: 10.1371/journal.pone.0107969
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    References listed on IDEAS

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    1. J. Jay Todd & René Marois, 2004. "Capacity limit of visual short-term memory in human posterior parietal cortex," Nature, Nature, vol. 428(6984), pages 751-754, April.
    2. Edward K. Vogel & Maro G. Machizawa, 2004. "Neural activity predicts individual differences in visual working memory capacity," Nature, Nature, vol. 428(6984), pages 748-751, April.
    3. Edward K. Vogel & Andrew W. McCollough & Maro G. Machizawa, 2005. "Neural measures reveal individual differences in controlling access to working memory," Nature, Nature, vol. 438(7067), pages 500-503, November.
    4. Stephenie A. Harrison & Frank Tong, 2009. "Decoding reveals the contents of visual working memory in early visual areas," Nature, Nature, vol. 458(7238), pages 632-635, April.
    5. Weiwei Zhang & Steven J. Luck, 2008. "Discrete fixed-resolution representations in visual working memory," Nature, Nature, vol. 453(7192), pages 233-235, May.
    6. Steven J. Luck & Edward K. Vogel, 1997. "The capacity of visual working memory for features and conjunctions," Nature, Nature, vol. 390(6657), pages 279-281, November.
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