preprint - a connectionist model of STM for serial order

[Dr Neil Burgess - Anatomy UCL London]

anonymous ftp host: archive.cis.ohio-state.edu (128.146.8.52)
file: pub/neuroprose/burgess.serial_order.ps.Z

I have just put the following pre-print in the neuroprose archive (see
above). Cheers,
Neil 
(n.burgess at ucl.ac.uk)

_________________________________________________________________________

	    A SOLVABLE CONNECTIONIST MODEL OF IMMEDIATE 
		     RECALL OF ORDERED LISTS

		Neil Burgess, Department of Anatomy,
	University College London, London WC1E 6BT, England.

			ABSTRACT
A model of short-term memory for serially ordered lists of verbal stimuli 
is proposed as an implementation of the `articulatory loop' thought to 
mediate this type of memory (Baddeley, 1986). The model predicts the 
presence of a repeatable time-varying `context' signal coding the timing 
of items' presentation in addition to a store of phonological information 
and a process of serial rehearsal. Items are associated with context nodes 
and phonemes by Hebbian connections showing both short and long term 
plasticity. Items are activated by phonemic input during presentation and 
reactivated by context and phonemic feedback during output. Serial 
selection of items occurs via a winner-take-all interaction amongst items, 
with the winner subsequently receiving decaying inhibition. An approximate 
analysis of error probabilities due to Gaussian noise during output is 
presented. The model provides an explanatory account of the probability of 
error as a function of serial position, list length, word length, phonemic 
similarity, temporal grouping, item and list familiarity, and is proposed 
as the starting point for a model of rehearsal and vocabulary acquisition. 

This paper is 8 pages, 0.2Mbytes uncompressed, and will be published in NIPS 7.