Literature DB >> 15948610

How is the serial order of a verbal sequence coded? Some comparisons between models.

Graham J Hitch1, Maria Chiara Fastame, Brenda Flude.   

Abstract

Current models of verbal short-term memory (STM) propose various mechanisms for serial order. These include a gradient of activation over items, associations between items, and associations between items and their positions relative to the start or end of a sequence. We compared models using a variant of Hebb's procedure in which immediate serial recall of a sequence improves if the sequence is presented more than once. However, instead of repeating a complete sequence, we repeated different aspects of serial order information common to training lists and a subsequent test list. In Experiment 1, training lists repeated all the item-item pairings in the test list, with or without the position-item pairings in the test list. Substantial learning relative to a control condition was observed only when training lists repeated item-item pairs with position-item pairs, and position was defined relative to the start rather than end of a sequence. Experiment 2 attempted to analyse the basis of this learning effect further by repeating fragments of the test list during training, where fragments consisted of either isolated position-item pairings or clusters of both position-item and item-item pairings. Repetition of sequence fragments led to only weak learning effects. However, where learning was observed it was for specific position-item pairings. We conclude that positional cues play an important role in the coding of serial order in memory but that the information required to learn a sequence goes beyond position-item associations. We suggest that whereas STM for a novel sequence is based on positional cues, learning a sequence involves the development of some additional representation of the sequence as a whole.

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Mesh:

Year:  2005        PMID: 15948610     DOI: 10.1080/09658210344000314

Source DB:  PubMed          Journal:  Memory        ISSN: 0965-8211


  11 in total

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10.  Is long-term memory used in a visuo-spatial change-detection paradigm?

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