title: A working memory model based on fast Hebbian learning.
abstract: 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.
authors.affiliation: Department of Numerical Analysis and Computer Science, Royal Institute of Technology, 100 44 Stockholm, Sweden. asa@nada.kth.se
authors.forename: A
authors.initials: A
authors.lastname: Sandberg
authors.forename: J
authors.initials: J
authors.lastname: Tegnér
authors.forename: A
authors.initials: A
authors.lastname: Lansner
mesh_terms: D003198:Computer Simulation; D005133:Eye Movements; D006801:Humans; D008570:Memory, Short-Term / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net; D016571:Neural Networks, Computer; D009473:Neuronal Plasticity / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D017397:Prefrontal Cortex / Q000166:cytology / Q000502:physiology; D013569:Synapses / Q000502:physiology*; D013997:Time Factors