Literature DB >> 23746292

Behind the magical numbers: hierarchical chunking and the human working memory capacity.

Guoqi Li1, Ning Ning, Kiruthika Ramanathan, Wei He, Li Pan, Luping Shi.   

Abstract

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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Year:  2013        PMID: 23746292     DOI: 10.1142/S0129065713500196

Source DB:  PubMed          Journal:  Int J Neural Syst        ISSN: 0129-0657            Impact factor:   5.866


  5 in total

1.  Memory dynamics in attractor networks.

Authors:  Guoqi Li; Kiruthika Ramanathan; Ning Ning; Luping Shi; Changyun Wen
Journal:  Comput Intell Neurosci       Date:  2015-04-19

2.  Chunking dynamics: heteroclinics in mind.

Authors:  Mikhail I Rabinovich; Pablo Varona; Irma Tristan; Valentin S Afraimovich
Journal:  Front Comput Neurosci       Date:  2014-03-14       Impact factor: 2.380

3.  Chunking improves symbolic sequence processing and relies on working memory gating mechanisms.

Authors:  Oleg Solopchuk; Andrea Alamia; Etienne Olivier; Alexandre Zénon
Journal:  Learn Mem       Date:  2016-02-16       Impact factor: 2.460

4.  Temperature based Restricted Boltzmann Machines.

Authors:  Guoqi Li; Lei Deng; Yi Xu; Changyun Wen; Wei Wang; Jing Pei; Luping Shi
Journal:  Sci Rep       Date:  2016-01-13       Impact factor: 4.379

5.  Entropy Based Modelling for Estimating Demographic Trends.

Authors:  Guoqi Li; Daxuan Zhao; Yi Xu; Shyh-Hao Kuo; Hai-Yan Xu; Nan Hu; Guangshe Zhao; Christopher Monterola
Journal:  PLoS One       Date:  2015-09-18       Impact factor: 3.240

  5 in total

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