Spike-timing dependent plasticity (STDP)
In standard Hebbian learning, a synaptic weight is increased if presynaptic and postsynaptic neuron are `simultaneously' active. If neurons communicate by spikes, the concept of simultaneity implies the pre- and postsynaptic spikes occur within some time window. Theory predicts that these time windows could have two phases corresponding to an increase (potentitiation) or decrease (depresseion) of the synaptic weight depending on the relative timing of pre- and postsynaptic spike. Such asymmetric learning rules with two phases have been found in recent experiments. We try to model such learning rules.
In this project we study neural network models with spiking neurons. We address, among others, the following questions:
Clopath, Claudia ; Büsing, Lars ; Vasilaki, Eleni ; Gerstner, Wulfram (2010)
Vasilaki, Eleni ; Frémaux, Nicolas ; Urbanczik, Robert ; Senn, Walter (2009)
Clopath, Claudia ; Ziegler, Lorric ; Vasilaki, Eleni ; Büsing, Lars ; Gerstner, Wulfram (2008)
Pfister, T. Toyoizumi, D. Barber, W. Gerstner (2006)
T. Toyoizumi, J.-P. Pfister, K. Aihara, and W. Gerstner (2005)
W. Gerstner and W. Kistler (2002).
R. Kempter, W. Gerstner, and J. L. van Hemmen (1999)
Gerstner W, Kempter R, van Hemmen JL, and Wagner H (1996)
For additional references, consult the list of Publications of W. Gerstner.
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