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A Neural Network Model of Verbal Working Memory Based on Transitory Activation Patterns.pdf

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A Neural Network Model of Verbal Working Memory Based on Transitory Activation Patterns.pdf

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A Neural Network Model of Verbal Working Memory Based on Transitory Activation Patterns.pdf

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文档介绍:A WORK MODEL OF VERBAL WORKING
MEMORY BASED ON TRANSITORY ACTIVATION
PATTERNS*
Shane T. Mueller and David E. Meyer
University of Michigan
Sponsored by the . Office of Naval Research
*Poster Presented at the Eighth Annual
Meeting of the Cognitive Neuroscience
Society, March 25-27, 2001.
1
Abstract
Traditionally, cognitive neuroscientists have represented long-term memory in
terms of the structure of a work’s connections and short-term memory in terms
of the patterns of activation across work (., Hebb, 1949; Caianiello, 1961).
However, recent work models of short-term verbal working memory (VWM)
have used modifiable structural connections to encode item and order information
(Hartley & Houghton, 1996; Burgess & Hitch, 1999). In these models, words are stored
by changing the connection weights between linguistic units, and phenomena related to
VWM are thus modeled with long-term memory structures and mechanisms. Although it
may be possible for neural connections to change rapidly (., see Jensen et al., 1996),
this latter approach to modeling VWM does not appear to be motivated by neurobiology.
Consequently, we have formulated a work model of VWM that stores and
maintains item and order information as a pattern of activation within a fixed-structure
network whose connections remain constant. Performance with work is affected
by many of the standard factors that influence VWM performance, such as phonological
similarity, articulatory duration, and word frequency. Our work demonstrates that the
embodiment of short-term memory based on patterns work activation is feasible,
parsimonious, and merits more investigation. Furthermore, from our work it appears that
both the biology and psychology of specific mental processes must be understood more
fully before works can be deemed “neurally plausible”.
2
Background and Present Goals
• Hebb (1949) tried to determine whether neural coding depends on:
(1) the activation of speci