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

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.


Published in:
Advances in Neural Information Processing Systems 17, 1409-1416
Year:
2005
Publisher:
MIT Press
Note:
incollection
Laboratories:




 Record created 2006-12-12, last modified 2018-01-27

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