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Neural Network Models of Memory Span

Abstract

A model is presented in which short term memory is maintained by movement of vectors from one layer to another. This architecture is ideal for representing item order. Two mechanisms for accounting for serial position curves are considered, lateral inhibition, and noise from neighboring items. These also account for effects of grouping by inserting pauses during presentation. Two other effects, a reverse word-length effect and the effect of phonological similarity, are attributed to the reconstruction of items from partially decayed traces. If all the phonemes in an item are intact at recall, the item is recalled correctly. Otherwise, the subject guesses according to a model developed by Paul Luce for identification of words presented in noise.

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