Behind the magical numbers: Hierarchical chunking and the human working memory capacity
To explore the influence of chunking on the capacity limits of working memory, a model for chunking in sequential working memory is proposed, using hierarchical bidirectional inhibition-connected neural networks with winnerless competition. With the assumption of the existence of an upper bound to t...
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sg-smu-ink.sis_research-82682022-09-15T07:35:46Z Behind the magical numbers: Hierarchical chunking and the human working memory capacity LI, Guoqi NING, Ning RAMANATHAN, Kiruthika HE, Wei PAN, Li SHI, Luping To explore the influence of chunking on the capacity limits of working memory, a model for chunking in sequential working memory is proposed, using hierarchical bidirectional inhibition-connected neural networks with winnerless competition. With the assumption of the existence of an upper bound to the inhibitory weights in neurobiological networks, it is shown that chunking increases the number of memorized items in working memory from the "magical number 7" to 16 items. The optimal number of chunks and the number of the memorized items in each chunk are the "magical number 4". 2013-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/7265 info:doi/10.1142/S0129065713500196 https://ink.library.smu.edu.sg/context/sis_research/article/8268/viewcontent/IJNS_MagicNumber.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University working memory cognitive systems hierarchical chunking Databases and Information Systems OS and Networks |
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working memory cognitive systems hierarchical chunking Databases and Information Systems OS and Networks LI, Guoqi NING, Ning RAMANATHAN, Kiruthika HE, Wei PAN, Li SHI, Luping Behind the magical numbers: Hierarchical chunking and the human working memory capacity |
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To explore the influence of chunking on the capacity limits of working memory, a model for chunking in sequential working memory is proposed, using hierarchical bidirectional inhibition-connected neural networks with winnerless competition. With the assumption of the existence of an upper bound to the inhibitory weights in neurobiological networks, it is shown that chunking increases the number of memorized items in working memory from the "magical number 7" to 16 items. The optimal number of chunks and the number of the memorized items in each chunk are the "magical number 4". |
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text |
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LI, Guoqi NING, Ning RAMANATHAN, Kiruthika HE, Wei PAN, Li SHI, Luping |
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LI, Guoqi NING, Ning RAMANATHAN, Kiruthika HE, Wei PAN, Li SHI, Luping |
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LI, Guoqi |
title |
Behind the magical numbers: Hierarchical chunking and the human working memory capacity |
title_short |
Behind the magical numbers: Hierarchical chunking and the human working memory capacity |
title_full |
Behind the magical numbers: Hierarchical chunking and the human working memory capacity |
title_fullStr |
Behind the magical numbers: Hierarchical chunking and the human working memory capacity |
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Behind the magical numbers: Hierarchical chunking and the human working memory capacity |
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behind the magical numbers: hierarchical chunking and the human working memory capacity |
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Institutional Knowledge at Singapore Management University |
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2013 |
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https://ink.library.smu.edu.sg/sis_research/7265 https://ink.library.smu.edu.sg/context/sis_research/article/8268/viewcontent/IJNS_MagicNumber.pdf |
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