Change search
ReferencesLink to record
Permanent link

Direct link
A working memory model based on fast Hebbian learning
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
2003 (English)In: Network, ISSN 0954-898X, E-ISSN 1361-6536, Vol. 14, no 4, 789-802 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2003. Vol. 14, no 4, 789-802 p.
Keyword [en]
long-term potentiation, prefrontal cortex, associative memory, attractor network, recurrent network, spiking neurons, visual-cortex, dynamics, mechanisms, synapses
URN: urn:nbn:se:kth:diva-22988ISI: 000186809100009OAI: diva2:341686
QC 20100525Available from: 2010-08-10 Created: 2010-08-10Bibliographically approved

Open Access in DiVA

No full text

Search in DiVA

By author/editor
Lansner, Anders
By organisation
Numerical Analysis and Computer Science, NADA
In the same journal

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 23 hits
ReferencesLink to record
Permanent link

Direct link