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Hebbian learning and spiking neurons

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Effect of lateral connections on the accuracy of the population code for a network of spiking neurons

Wulfram Gerstner

We study how neuronal connections in a population of spiking neurons affect the accuracy of stimulus estimation. Neurons in our model code for a one-dimensional orientation variable

\phi

. Connectivity between two neurons depends on the absolute differenc ...

2001

Hebbian learning and spiking neurons

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Phase locking and coincidence detection in threshold coupled neural oscillators

Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning

An algorithm for modifying neurotransmitter release probability based on pre- and postsynaptic spike timing

Coding properties of spiking neurons: reverse- and cross-correlations

Effect of lateral connections on the accuracy of the population code for a network of spiking neurons

Noise and the PSTH response to current transients II. Integrate-and-fire model with slow recovery and application to motoneuron data

A neuronal learning rule for sub-millisecond temporal coding

A biologically motivated and analytically soluble model of collective oscillations in the cortex: I. Theory of weak locking

Noise and the PSTH response to current transients II. Integrate-and-fire model with slow recovery and application to motoneuron data

A neuronal learning rule for sub-millisecond temporal coding

Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning

Phase locking and coincidence detection in threshold coupled neural oscillators

A biologically motivated and analytically soluble model of collective oscillations in the cortex: I. Theory of weak locking

An algorithm for modifying neurotransmitter release probability based on pre- and postsynaptic spike timing

Coding properties of spiking neurons: reverse- and cross-correlations

Effect of lateral connections on the accuracy of the population code for a network of spiking neurons