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

Description

stdp_nn_restr_synapse is a connector to create synapses with spike time dependent plasticity with the restricted symmetric nearest-neighbour spike pairing scheme (fig. 7C in 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, but only if the latter occured not earlier than the previous presynaptic one. When a postsynaptic spike occurs, it is accounted in the facilitation rule with the nearest preceding presynaptic one, but only if the latter occured not earlier than the previous postsynaptic one. So, a spike can participate neither in two depression pairs nor in two potentiation pairs.

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 relies on an additional variable - the postsynaptic eligibility trace 1 (implemented on the postsynaptic neuron side). It decays exponentially with the time constant tau_minus and increases to 1 on a post-spike occurrence (instead of increasing by 1 as in stdp_synapse).

Warning

This synaptic plasticity rule does not take precise spike timing into account. When calculating the weight update, the precise spike time part of the timestamp is ignored.

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(1,2)

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