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

N Burgess; G Hitch

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

N Burgess, G Hitch

Psychology

Research output: Contribution to journal › Literature review › peer-review

Abstract

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.

Original language	English
Pages (from-to)	535-541
Number of pages	7
Journal	Trends in Cognitive Sciences
Volume	9
Issue number	11
Publication status	Published - Nov 2005

Keywords

IMMEDIATE SERIAL-RECALL
NETWORK MODEL
ASSOCIATIVE MEMORY
PHONOLOGICAL LOOP
ORDER
HIPPOCAMPUS
PATTERNS
REPRESENTATION
RECOGNITION
EVENTS

Cite this

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title = "Computational models of working memory: putting long-term memory into context",

abstract = "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.",

keywords = "IMMEDIATE SERIAL-RECALL, NETWORK MODEL, ASSOCIATIVE MEMORY, PHONOLOGICAL LOOP, ORDER, HIPPOCAMPUS, PATTERNS, REPRESENTATION, RECOGNITION, EVENTS",

author = "N Burgess and G Hitch",

year = "2005",

month = nov,

language = "English",

volume = "9",

pages = "535--541",

journal = "Trends in Cognitive Sciences",

issn = "1364-6613",

publisher = "Elsevier",

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T1 - Computational models of working memory: putting long-term memory into context

AU - Burgess, N

AU - Hitch, G

PY - 2005/11

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N2 - 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.

AB - 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.

KW - IMMEDIATE SERIAL-RECALL

KW - NETWORK MODEL

KW - ASSOCIATIVE MEMORY

KW - PHONOLOGICAL LOOP

KW - ORDER

KW - HIPPOCAMPUS

KW - PATTERNS

KW - REPRESENTATION

KW - RECOGNITION

KW - EVENTS

M3 - Literature review

SN - 1364-6613

VL - 9

SP - 535

EP - 541

JO - Trends in Cognitive Sciences

JF - Trends in Cognitive Sciences

IS - 11

ER -