stdp_synapse - Synapse type for spike-timing dependent
plasticity.
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
stdp_synapse 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.
\verbatim embed:rst
========= ======= ======================================================
tau_plus ms Time constant of STDP window, potentiation
(tau_minus defined in post-synaptic neuron)
lambda real Step size
alpha real Asymmetry parameter (scales depressing increments as
alpha*lambda)
mu_plus real Weight dependence exponent, potentiation
mu_minus real Weight dependence exponent, depression
Wmax real Maximum allowed weight
========= ======= ======================================================
\endverbatim
SpikeEvent
\verbatim embed:rst
.. [1] Guetig et al. (2003). Learning input correlations through nonlinear
temporally asymmetric hebbian plasticity. Journal of Neuroscience,
23:3697-3714 DOI: https://doi.org/10.1523/JNEUROSCI.23-09-03697.2003
.. [2] Rubin J, Lee D, Sompolinsky H (2001). Equilibrium
properties of temporally asymmetric Hebbian plasticity. Physical Review
Letters, 86:364-367. DOI: https://doi.org/10.1103/PhysRevLett.86.364
.. [3] Song S, Miller KD, Abbott LF (2000). Competitive Hebbian learning
through spike-timing-dependent synaptic plasticity. Nature Neuroscience
3(9):919-926.
DOI: https://doi.org/10.1038/78829
.. [4] van Rossum MCW, Bi G-Q, Turrigiano GG (2000). Stable Hebbian learning
from spike timing-dependent plasticity. Journal of Neuroscience,
20(23):8812-8821.
DOI: https://doi.org/10.1523/JNEUROSCI.20-23-08812.2000
\endverbatim
Moritz Helias, Abigail Morrison
Adapted by: Philipp Weidel
March 2006
/var/www/debian/nest/nest-simulator-2.20.0/models/stdp_connection.h