Literature DB >> 22419756

Capacity and precision in an animal model of visual short-term memory.

Antonio H Lara1, Jonathan D Wallis.   

Abstract

Temporary storage of information in visual short-term memory (VSTM) is a key component of many complex cognitive abilities. However, it is highly limited in capacity. Understanding the neurophysiological nature of this capacity limit will require a valid animal model of VSTM. We used a multiple-item color change detection task to measure macaque monkeys' VSTM capacity. Subjects' performance deteriorated and reaction times increased as a function of the number of items in memory. Additionally, we measured the precision of the memory representations by varying the distance between sample and test colors. In trials with similar sample and test colors, subjects made more errors compared to trials with highly discriminable colors. We modeled the error distribution as a Gaussian function and used this to estimate the precision of VSTM representations. We found that as the number of items in memory increases the precision of the representations decreases dramatically. Additionally, we found that focusing attention on one of the objects increases the precision with which that object is stored and degrades the precision of the remaining. These results are in line with recent findings in human psychophysics and provide a solid foundation for understanding the neurophysiological nature of the capacity limit of VSTM.

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Year:  2012        PMID: 22419756      PMCID: PMC3549639          DOI: 10.1167/12.3.13

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


  26 in total

1.  Storage of features, conjunctions and objects in visual working memory.

Authors:  E K Vogel; G F Woodman; S J Luck
Journal:  J Exp Psychol Hum Percept Perform       Date:  2001-02       Impact factor: 3.332

2.  The magical number 4 in short-term memory: a reconsideration of mental storage capacity.

Authors:  N Cowan
Journal:  Behav Brain Sci       Date:  2001-02       Impact factor: 12.579

3.  Microsaccades as an overt measure of covert attention shifts.

Authors:  Ziad M Hafed; James J Clark
Journal:  Vision Res       Date:  2002-10       Impact factor: 1.886

4.  Fixational eye movements are not an index of covert attention.

Authors:  Todd S Horowitz; Elisabeth M Fine; David E Fencsik; Sergey Yurgenson; Jeremy M Wolfe
Journal:  Psychol Sci       Date:  2007-04

5.  Discrete fixed-resolution representations in visual working memory.

Authors:  Weiwei Zhang; Steven J Luck
Journal:  Nature       Date:  2008-04-02       Impact factor: 49.962

6.  Modulation of microsaccades in monkey during a covert visual attention task.

Authors:  Ziad M Hafed; Lee P Lovejoy; Richard J Krauzlis
Journal:  J Neurosci       Date:  2011-10-26       Impact factor: 6.167

Review 7.  Neural mechanisms of selective visual attention.

Authors:  R Desimone; J Duncan
Journal:  Annu Rev Neurosci       Date:  1995       Impact factor: 12.449

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

Authors:  Liqiang Huang
Journal:  J Vis       Date:  2010-12-06       Impact factor: 2.240

9.  Comment on "Dynamic shifts of limited working memory resources in human vision".

Authors:  Nelson Cowan; Jeffrey N Rouder
Journal:  Science       Date:  2009-02-13       Impact factor: 47.728

10.  Dynamic shifts of limited working memory resources in human vision.

Authors:  Paul M Bays; Masud Husain
Journal:  Science       Date:  2008-08-08       Impact factor: 47.728

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  28 in total

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

Authors:  Ronald van den Berg; Hongsup Shin; Wen-Chuang Chou; Ryan George; Wei Ji Ma
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-11       Impact factor: 11.205

2.  Monkey prefrontal neurons during Sternberg task performance: full contents of working memory or most recent item?

Authors:  R O Konecky; M A Smith; C R Olson
Journal:  J Neurophysiol       Date:  2017-03-22       Impact factor: 2.714

3.  Variable precision in visual perception.

Authors:  Shan Shen; Wei Ji Ma
Journal:  Psychol Rev       Date:  2018-10-18       Impact factor: 8.934

4.  Slot-like capacity and resource-like coding in a neural model of multiple-item working memory.

Authors:  Dominic Standage; Martin Paré
Journal:  J Neurophysiol       Date:  2018-06-27       Impact factor: 2.714

5.  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

6.  Restoring Latent Visual Working Memory Representations in Human Cortex.

Authors:  Thomas C Sprague; Edward F Ester; John T Serences
Journal:  Neuron       Date:  2016-08-03       Impact factor: 17.173

Review 7.  Changing concepts of working memory.

Authors:  Wei Ji Ma; Masud Husain; Paul M Bays
Journal:  Nat Neurosci       Date:  2014-02-25       Impact factor: 24.884

8.  Synaptic efficacy shapes resource limitations in working memory.

Authors:  Nikhil Krishnan; Daniel B Poll; Zachary P Kilpatrick
Journal:  J Comput Neurosci       Date:  2018-03-15       Impact factor: 1.621

9.  The same type of visual working memory limitations in humans and monkeys.

Authors:  Deepna T Devkar; Anthony A Wright; Wei Ji Ma
Journal:  J Vis       Date:  2015       Impact factor: 2.240

10.  Monkeys and humans take local uncertainty into account when localizing a change.

Authors:  Deepna Devkar; Anthony A Wright; Wei Ji Ma
Journal:  J Vis       Date:  2017-09-01       Impact factor: 2.240

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