Modeling Synaptic Plasticity in Conjunction with the Timing of Pre- and Postsynaptic Action Potentials
By Werner M. Kistler, J. L. V. Hemmen. 2000
185 citations recorded by the source corpus.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cellular and Molecular Neuroscience
- Wulfram Gerstner
- Filip Ponulak
- Andrzej J. Kasinski
- Guy O. Billings
- Mark C. W. van Rossum
- Maoz Shamir
- Yotam Luz
- Switzerland J. Leo van Hemmen
In Cognitive Neuroscience
- Wulfram Gerstner
- Filip Ponulak
- Andrzej J. Kasinski
- Guy O. Billings
- Mark C. W. van Rossum
- Maoz Shamir
- Yotam Luz
- Richard Kempter
In Electrical and Electronic Engineering
- Wulfram Gerstner
- Filip Ponulak
- Andrzej J. Kasinski
- Guy O. Billings
- Mark C. W. van Rossum
- Maoz Shamir
- Yotam Luz
- Switzerland J. Leo van Hemmen
Citations in the corpus
- Balancing Feed-Forward Excitation and Inhibition via Hebbian Inhibitory Synaptic Plasticity (2012, background): “Considerable theoretical effort has been devoted to studying the characteristics of STDP learning of excitatory synapses [23–43].”
- Supervised Learning in Spiking Neural Networks with ReSuMe: Sequence Learning, Classification, and Spike Shifting (2010, methodology): “…reformulate equation 2.2 for the spiking neurons and for the continuous timescale as In order to describe X di ( t ) and X oi ( t ) in a mathematical framework, we adopt a model of spike-timing-based synaptic plasticity proposed by Kistler and van Hemmen (2000) (see also Gerstner & Kistler, 2002).”
- Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning (2001, methodology): “These notations allow us to formulate the spike-based learning rule as (Kempter, et al., 1999a; Kistler & van Hemmen, 2000; van Hemmen, 2000), t w d dt w i ( t) D a 0 C a in 1 S in i ( t) C a out 1 S out ( t) C S in i (t) t Z ¡1 dt 0 W( t ¡ t 0 )S out ( t 0 ) C S out (t) t Z ¡1 dt 0 W( ¡t C t 0 ) S…”
- Memory retention and spike-timing-dependent plasticity. (2009, background): “Inhibitory synapses (conductance-based) are exponential with a time constant of 5 ms and have a reversal potential of 74 mV.”
- Spike-Timing-Dependent Plasticity in Balanced Random Networks (2007, unknown): “This has prompted intense theoretical interest (see, e.g., Kempter, Gerstner, & van Hemmen, 1999; Song, Miller, & Abbott, 2000; van Rossum, Bi, & Turrigiano, 2000; Kistler & van Hemmen, 2000; Rubin, Lee, & Sompolinsky, 2001; Kempter, Gerstner, & van Hemmen, 2001; G¨ utig, Aharonov, Rotter, & Sompo”