Literature DB >> 21135255

Visual working memory is better characterized as a distributed resource rather than discrete slots.

Liqiang Huang1.   

Abstract

A recent important debate in the field of visual working memory has focused on whether it represents a small set of high-precision representations (the "slot" model) or all items in parallel (the "resource" model). When faced with a large number of items, the slot model claims that high-precision representations of several items are stored and no information is retained about the other items, whereas the resource model claims that some imperfect information about each of the items can be stored. In this study, the observers tried to memorize and then recall six (out of eight possible) colors. The distribution of their scores (i.e., the number of correct responses) was modeled, and the empirical pattern of distribution fitted precisely with the prediction of the resource model but clearly differed from that of the slot model. Dependence analysis also revealed that the reports of items were approximately independent of each other, suggesting that all of the items were represented in parallel, as predicted by the resource model but not by the slot model. Overall, the data favored the resource model, not the slot model.

Entities:  

Mesh:

Year:  2010        PMID: 21135255     DOI: 10.1167/10.14.8

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  22 in total

1.  Does high memory load kick task-irrelevant information out of visual working memory?

Authors:  Jun Yin; Jifan Zhou; Haokui Xu; Junying Liang; Zaifeng Gao; Mowei Shen
Journal:  Psychon Bull Rev       Date:  2012-04

2.  Contralateral Delay Activity Tracks Fluctuations in Working Memory Performance.

Authors:  Kirsten C S Adam; Matthew K Robison; Edward K Vogel
Journal:  J Cogn Neurosci       Date:  2018-01-08       Impact factor: 3.225

3.  Re-evaluating the relationships among filtering activity, unnecessary storage, and visual working memory capacity.

Authors:  Stephen M Emrich; Michael A Busseri
Journal:  Cogn Affect Behav Neurosci       Date:  2015-09       Impact factor: 3.282

4.  Obligatory encoding of task-irrelevant features depletes working memory resources.

Authors:  Louise Marshall; Paul M Bays
Journal:  J Vis       Date:  2013-02-18       Impact factor: 2.240

5.  Object features fail independently in visual working memory: evidence for a probabilistic feature-store model.

Authors:  Daryl Fougnie; George A Alvarez
Journal:  J Vis       Date:  2011-10-06       Impact factor: 2.240

6.  Real-time triggering reveals concurrent lapses of attention and working memory.

Authors:  Megan T deBettencourt; Paul A Keene; Edward Awh; Edward K Vogel
Journal:  Nat Hum Behav       Date:  2019-05-20

Review 7.  A review of visual memory capacity: Beyond individual items and toward structured representations.

Authors:  Timothy F Brady; Talia Konkle; George A Alvarez
Journal:  J Vis       Date:  2011-05-26       Impact factor: 2.240

8.  Confident failures: Lapses of working memory reveal a metacognitive blind spot.

Authors:  Kirsten C S Adam; Edward K Vogel
Journal:  Atten Percept Psychophys       Date:  2017-07       Impact factor: 2.199

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

Authors:  Ziqiang Wei; Xiao-Jing Wang; Da-Hui Wang
Journal:  J Neurosci       Date:  2012-08-15       Impact factor: 6.167

10.  Strategic trade-offs between quantity and quality in working memory.

Authors:  Daryl Fougnie; Sarah M Cormiea; Anish Kanabar; George A Alvarez
Journal:  J Exp Psychol Hum Percept Perform       Date:  2016-03-07       Impact factor: 3.332

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