Show Reference: "Spike-timing-dependent synaptic plasticity: from single spikes to spike trains"

Spike-timing-dependent synaptic plasticity: from single spikes to spike trains Neurocomputing, Vol. 58-60 (June 2004), pp. 365-371, doi:10.1016/j.neucom.2004.01.068 by Christo Panchev, Stefan Wermter
@article{panchev-and-wermter-2004,
    abstract = {We present a neurobiologically motivated model of a neuron with active dendrites and dynamic synapses, and a training algorithm which builds upon single spike-timing-dependent synaptic plasticity derived from neurophysiological evidence. We show that in the presence of a moderate level of noise, the plasticity rule can be extended from single to multiple pre-synaptic spikes and applied to effectively train a neuron in detecting temporal sequences of spike trains. The trained neuron responds reliably under different regimes and types of noise.},
    author = {Panchev, Christo and Wermter, Stefan},
    doi = {10.1016/j.neucom.2004.01.068},
    issn = {09252312},
    journal = {Neurocomputing},
    keywords = {ann, learning, som, suppression, unsupervised-learning},
    month = jun,
    pages = {365--371},
    posted-at = {2012-01-19 09:29:34},
    priority = {0},
    title = {Spike-timing-dependent synaptic plasticity: from single spikes to spike trains},
    url = {http://www.informatik.uni-hamburg.de/WTM/ps/neuro-panwer.pdf},
    volume = {58-60},
    year = {2004}
}

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