Computational models of working memory: putting long-term memory into context

被引:100
作者
Burgess, N
Hitch, G
机构
[1] UCL, Inst Cognit Neurosci, London WC1N 3AR, England
[2] UCL, Dept Anat & Dev Biol, London WC1N 3AR, England
[3] Univ York, Dept Psychol, York YO10 5DD, N Yorkshire, England
基金
英国医学研究理事会;
关键词
D O I
10.1016/j.tics.2005.09.011
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
Detailed computational modeling of human memory has typically been aimed at either short-term (working) memory or long-term memory in isolation. However, recent research highlights the importance of interactions between these systems for both item and order information. At the same time, computational models of both systems are beginning to converge onto a common framework in which items are associated with an evolving 'context' signal and subsequently compete with one another at recall. We review some of these models, and discuss a common mechanism capable of modelling working memory and its interaction with long-term memory, focussing on memory for verbal sequences.
引用
收藏
页码:535 / 541
页数:7
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