stdp_nn_symm_synapse – Synapse type for spike-timing dependent plasticity with symmetric nearest-neighbour spike pairing scheme

Description

stdp_nn_symm_synapse is a connector to create synapses with spike time dependent plasticity with the symmetric nearest-neighbour spike pairing scheme 1.

When a presynaptic spike occurs, it is taken into account in the depression part of the STDP weight change rule with the nearest preceding postsynaptic one, and when a postsynaptic spike occurs, it is accounted in the facilitation rule with the nearest preceding presynaptic one (instead of pairing with all spikes, like in stdp_synapse). For a clear illustration of this scheme see fig. 7A in 2.

The pairs exactly coinciding (so that presynaptic_spike == postsynaptic_spike + dendritic_delay), leading to zero delta_t, are discarded. In this case the concerned pre/postsynaptic spike is paired with the second latest preceding post/presynaptic one (for example, pre=={10 ms; 20 ms} and post=={20 ms} will result in a potentiation pair 20-to-10).

The implementation involves two additional variables - presynaptic and postsynaptic traces 2. The presynaptic trace decays exponentially over time with the time constant tau_plus and increases to 1 on a pre-spike occurrence. The postsynaptic trace (implemented on the postsynaptic neuron side) decays with the time constant tau_minus and increases to 1 on a post-spike occurrence.

Parameters

tau_plus

ms

Time constant of STDP window, potentiation (tau_minus defined in postsynaptic 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

Transmits

SpikeEvent

References

1

Morrison A., Aertsen A., Diesmann M. (2007) Spike-timing dependent plasticity in balanced random networks, Neural Comput. 19:1437–1467

2(1,2)

Morrison A., Diesmann M., and Gerstner W. (2008) Phenomenological models of synaptic plasticity based on spike timing, Biol. Cybern. 98, 459–478