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Item strength affects working memory capacity

Overview of attention for article published in Memory & Cognition, October 2017
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Title
Item strength affects working memory capacity
Published in
Memory & Cognition, October 2017
DOI 10.3758/s13421-017-0758-4
Pubmed ID
Authors

Zhangfan Shen, Vencislav Popov, Anita B. Delahay, Lynne M. Reder

Abstract

Do the processing and online manipulation of stimuli that are less familiar require more working memory (WM) resources? Is it more difficult to solve demanding problems when the symbols involved are less rather than more familiar? We explored these questions with a dual-task paradigm in which subjects had to solve algebra problems of different complexities while simultaneously holding novel symbol-digit associations in WM. The symbols were previously unknown Chinese characters, whose familiarity was manipulated by differential training frequency with a visual search task for nine hour-long sessions over 3 weeks. Subsequently, subjects solved equations that required one or two transformations. Before each trial, two different integers were assigned to two different Chinese characters of the same training frequency. Half of the time, those characters were present as variables in the equation and had to be substituted for the corresponding digits. After attempting to solve the equation, subjects had to recognize which two characters were shown immediately before that trial and to recall the integer associated with each. Solution accuracy and response times were better when the problems required one transformation only; variable substitution was not required; or the Chinese characters were high frequency. The effects of stimulus familiarity increased as the WM demands of the equation increased. Character-digit associations were also recalled less well with low-frequency characters. These results provide strong support that WM capacity depends not only on the number of chunks of information one is attempting to process but also on their strength or familiarity.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 72 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 15%
Researcher 9 13%
Student > Ph. D. Student 9 13%
Professor 4 6%
Student > Bachelor 4 6%
Other 12 17%
Unknown 23 32%
Readers by discipline Count As %
Psychology 28 39%
Neuroscience 6 8%
Social Sciences 3 4%
Computer Science 2 3%
Mathematics 2 3%
Other 7 10%
Unknown 24 33%