Literature DB >> 15342436

Multi-item working memory--a behavioral study.

Volodya Yakovlev1, Alberto Bernacchia, Tanya Orlov, Shaul Hochstein, Daniel Amit.   

Abstract

Macaque monkeys were trained to recognize the repetition of one of the images already seen in a sequence of random length. On average, performance decreased with sequence length. However, this was due to a complex combination of factors, as follows: performance was found to decrease with the separation in the sequence of the test (repetition image) from the cue (its first appearance in the sequence), for trials with sequences of fixed length. In contrast, performance improved as a function of sequence length, for equal cue-test separations. Reaction times followed a complementary trend: they increased with cue-test separation and decreased with sequence length. The frequency of false positives (FPs) indicates that images are not always removed from working memory between successive trials, and that the monkeys rarely confuse different images. The probability of miss errors depends on number of intervening stimulus presentations, while FPs depend on elapsed time. A simple two-state stochastic model of multi-item working memory is proposed that guides the account for the main effects of performance and false positives, as well as their interaction. In the model, images enter WM when they are presented, or by spontaneous jump-in. Misses are due to spontaneous jump-out of images previously seen.

Mesh:

Year:  2004        PMID: 15342436     DOI: 10.1093/cercor/bhh161

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  6 in total

1.  Cortical Networks Involved in Memory for Temporal Order.

Authors:  Anna Manelis; Vencislav Popov; Christopher Paynter; Matthew Walsh; Mark E Wheeler; Keith M Vogt; Lynne M Reder
Journal:  J Cogn Neurosci       Date:  2017-03-15       Impact factor: 3.225

2.  Modeling behavior in different delay match to sample tasks in one simple network.

Authors:  Yali Amit; Volodya Yakovlev; Shaul Hochstein
Journal:  Front Hum Neurosci       Date:  2013-07-30       Impact factor: 3.169

3.  Monkeys rely on recency of stimulus repetition when solving short-term memory tasks.

Authors:  John H Wittig; Barry J Richmond
Journal:  Learn Mem       Date:  2014-05-16       Impact factor: 2.460

4.  Humans and monkeys use different strategies to solve the same short-term memory tasks.

Authors:  John H Wittig; Barak Morgan; Evan Masseau; Barry J Richmond
Journal:  Learn Mem       Date:  2016-10-17       Impact factor: 2.460

5.  Effective visual working memory capacity: an emergent effect from the neural dynamics in an attractor network.

Authors:  Laura Dempere-Marco; David P Melcher; Gustavo Deco
Journal:  PLoS One       Date:  2012-08-29       Impact factor: 3.240

6.  It's hard to forget: resetting memory in delay-match-to-multiple-image tasks.

Authors:  Volodya Yakovlev; Yali Amit; Shaul Hochstein
Journal:  Front Hum Neurosci       Date:  2013-11-14       Impact factor: 3.169

  6 in total

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