No Evidence for an Item Limit in Change Detection

  title={No Evidence for an Item Limit in Change Detection},
  author={Shaiyan Keshvari and Ronald Van den Berg and Wei Ji Ma},
  booktitle={PLoS Computational Biology},
Change detection is a classic paradigm that has been used for decades to argue that working memory can hold no more than a fixed number of items ("item-limit models"). Recent findings force us to consider the alternative view that working memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size ("continuous-resource models"). Most previous studies that used the change detection paradigm have ignored effects of limited encoding precision by… CONTINUE READING
Related Discussions
This paper has been referenced on Twitter 4 times. VIEW TWEETS

From This Paper

Figures, tables, and topics from this paper.

Explore Further: Topics Discussed in This Paper


Publications citing this paper.
Showing 1-10 of 32 extracted citations

The binding pool: a model of shared neural resources for distinct items in visual working memory.

Attention, perception & psychophysics • 2014
View 11 Excerpts
Highly Influenced


Publications referenced by this paper.
Showing 1-10 of 79 references

From distributed resources to limited slots in multiple-item working memory: a spiking network model with normalization.

The Journal of neuroscience : the official journal of the Society for Neuroscience • 2012
View 2 Excerpts

Variability in encoding precision accounts for visual short-term memory limitations.

Proceedings of the National Academy of Sciences of the United States of America • 2012
View 10 Excerpts

Similar Papers

Loading similar papers…