Reducing spike train variability: A computational theory of spike-timing dependent plasticity

2007-02-01

Neural Computation , Volume 19 p. 371- 403

Additional Metadata
Keywords	spiking neurons, hebbian learning, spike timing dependent plasticity
MSC	Neural nets and related approaches (msc 62M45)
THEME	Software (theme 1), Logistics (theme 3), Energy (theme 4)
Publisher	MIT Press
Journal	Neural Computation
Project	Scalable Reinforcement Learning and Information Processing with Timed spikes in Scalable Networks of Spiking Neural networks
Organisation	Intelligent and autonomous systems
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Bohte, S., & Mozer, M. C. (2007). Reducing spike train variability: A computational theory of spike-timing dependent plasticity. Neural Computation, 19, 371–403.

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