**Name:**

stdp_synapse_hom - Synapse type for spike-timing dependent

plasticity using homogeneous parameters.

**Examples:**

multiplicative STDP [2] mu_plus = mu_minus = 1.0

additive STDP [3] mu_plus = mu_minus = 0.0

Guetig STDP [1] mu_plus = mu_minus = [0.0,1.0]

van Rossum STDP [4] mu_plus = 0.0 mu_minus = 1.0

**Description:**

stdp_synapse_hom is a connector to create synapses with spike time

dependent plasticity (as defined in [1]). Here the weight dependence

exponent can be set separately for potentiation and depression.

Parameters controlling plasticity are identical for all synapses of the

model, reducing the memory required per synapse considerably.

**Parameters:**

tau_plus double - Time constant of STDP window, potentiation in ms

(tau_minus defined in post-synaptic neuron)

lambda double - Step size

alpha double - Asymmetry parameter (scales depressing increments as

alpha*lambda)

mu_plus double - Weight dependence exponent, potentiation

mu_minus double - Weight dependence exponent, depression

Wmax double - Maximum allowed weight

**Transmits:**

SpikeEvent

**Remarks:**

The parameters are common to all synapses of the model and must be set using

SetDefaults on the synapse model.

**References:**

[1] Guetig et al. (2003) Learning Input Correlations through Nonlinear

Temporally Asymmetric Hebbian Plasticity. Journal of Neuroscience

[2] Rubin, J., Lee, D. and Sompolinsky, H. (2001). Equilibrium

properties of temporally asymmetric Hebbian plasticity, PRL

86,364-367

[3] Song, S., Miller, K. D. and Abbott, L. F. (2000). Competitive

Hebbian learning through spike-timing-dependent synaptic

plasticity,Nature Neuroscience 3:9,919--926

[4] van Rossum, M. C. W., Bi, G-Q and Turrigiano, G. G. (2000).

Stable Hebbian learning from spike timing-dependent

plasticity, Journal of Neuroscience, 20:23,8812--8821

**Author:**

Moritz Helias, Abigail Morrison

**FirstVersion:**

March 2006

**SeeAlso:**

**Source:**

/home/graber/work-nest/nest-git/nest-simulator/models/stdp_connection_hom.h