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Dynamic thresholds for controlling encoding and retrieval operations in localist (or distributed) neural networks: The need for biologically plausible implementations

Pickering, Alan. 2000. Dynamic thresholds for controlling encoding and retrieval operations in localist (or distributed) neural networks: The need for biologically plausible implementations. Behavioral and Brain Sciences, 23(04), pp. 488-489. ISSN 0140-525X [Article]

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Abstract or Description

A dynamic threshold, which controls the nature and course of learning, is a pivotal concept in Page's general localist framework. This commentary addresses various issues surrounding biologically plausible implementations for such thresholds. Relevant previous research is noted and the particular difficulties relating to the creation of so-called instance representations are highlighted. It is stressed that these issues also apply to distributed models.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.1017/S0140525X00463351

Departments, Centres and Research Units:

Psychology

Dates:

DateEvent
August 2000Published

Item ID:

8505

Date Deposited:

18 Mar 2015 10:20

Last Modified:

04 Jul 2017 10:31

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

http://research.gold.ac.uk/id/eprint/8505

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