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Network. 2003 Nov;14(4):789-802.

A working memory model based on fast Hebbian learning.

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Department of Numerical Analysis and Computer Science, Royal Institute of Technology, 100 44 Stockholm, Sweden.


Recent models of the oculomotor delayed response task have been based on the assumption that working memory is stored as a persistent activity state (a 'bump' state). The delay activity is maintained by a finely tuned synaptic weight matrix producing a line attractor. Here we present an alternative hypothesis, that fast Hebbian synaptic plasticity is the mechanism underlying working memory. A computational model demonstrates a working memory function that is more resistant to distractors and network inhomogeneity compared to previous models, and that is also capable of storing multiple memories.

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