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Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model

T. Toyoizumi, J.-P. Pfister, K. Aihara, and W. Gerstner (2005)
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Advances in Neural Information Processing Systems 17,
edited by L.K. Saul and Y. Weiss and L. Bottou (MIT-Press), pp.
1409-1416
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We derive an optimal learning rule
in the sense of mutual information maximization for a spiking neuron model.
Under the assumption of small
fluctuations of the input, we find a spike-timing
dependent plasticity (STDP) function which depends
on the time course of excitatory postsynaptic potentials (EPSPs) an
d the autocorrelation function of
the postsynaptic neuron. We show that the STDP function has both
positive and negative phases.
The positive phase is related to the shape of the EPSP
while the negative phase is controlled by neuronal refractoriness.