Toward a network model of the articulatory loop*1

摘要: The basic features of verbal short-term memory for serially ordered lists are reviewed. A feed-forward network model based on Baddeley's concept an “articulatory loop” is presented. One its aims was to explore mechanisms the storage serial order information in articulatory loop. Information represented locally, learning by “one-shot” Hebbian adjustment weighted connections, corresponding item-item and item-context associations, which decay with time. Items modeled at level phonemes phonemic output fed back next input. At recall, items selected “competitive queuing.” Noisy activation values used, resulting errors during recall. Simulations recall showed good agreement human performance respect span, similarity, word length, patterns error. There but incomplete shape position curve effects suppression. simple modification shown produce correct curve. However, unable simulate sequences containing mixtures phonemically similar dissimilar items. suggested retains central idea using competitive queuing select among noisy described.