A working memory model based on fast Hebbian learning

Sandberg, A. (author): Dept. of Numer. Anal. and Comp. Sci., Royal Institute of Technology, 100 44 Stockholm, Sweden

Tegnér, Jesper (author): Linköpings universitet,Karolinska Institutet,Tekniska högskolan,Biologiska Beräkningar

Lansner, Anders (author): KTH,Numerisk analys och datalogi, NADA,Dept. of Numer. Anal. and Comp. Sci., Royal Institute of Technology, 100 44 Stockholm, Sweden

Karolinska Institutet Dept of Numer. Anal. and Comp. Sci., Royal Institute of Technology, 100 44 Stockholm, Sweden (creator_code:org_t)

Related links:: https://urn.kb.se/re...; show more...; https://doi.org/10.1...; http://kipublication...; https://urn.kb.se/re...; show less...

Abstract Subject headings

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.

By the university: Royal Institute of Technology; Karolinska Institutet; Linköping University

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