jonke_synapse – Synapse type for spike-timing dependent plasticity with additional additive factors.¶
Description¶
jonke_synapse is a connector to create synapses with spike time
dependent plasticity. Unlike stdp_synapse
, we use the update equations:
where
and
This makes it possible to implement update rules which approximate the rule stated in 1, and for examples, the rules given in 2 and 3.
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¶
lambda |
double |
Step size |
Wmax |
double |
Maximum allowed weight, note that this scales each weight update |
alpha |
double |
Determine shape of depression term |
mu_plus |
double |
Set weight dependency of facilitating update |
mu_minus |
double |
Set weight dependency of depressing update |
tau_plus |
double |
Time constant of STDP window, potentiation in ms |
beta |
double |
Set negative offset for both updates |
(tau_minus is defined in the postsynaptic neuron.)
Transmits¶
SpikeEvent
References¶
- 1
Nessler, Bernhard, et al. “Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticity.” PLoS computational biology 9.4 (2013): e1003037.
- 2
Legenstein, Robert, et al. “Assembly pointers for variable binding in networks of spiking neurons.” arXiv preprint arXiv:1611.03698 (2016).
- 3
Jonke, Zeno, et al. “Feedback inhibition shapes emergent computational properties of cortical microcircuit motifs.” arXiv preprint arXiv:1705.07614 (2017).