third_factor_stdp_synapse
third_factor_stdp_synapse - Synapse model for spike-timing dependent plasticity with postsynaptic third-factor modulation
Description
third_factor_stdp_synapse is a synapse with spike time dependent plasticity (as defined in [1]). Here the weight dependence exponent can be set separately for potentiation and depression. Examples:
Multiplicative STDP [2] mu_plus = mu_minus = 1 Additive STDP [3] mu_plus = mu_minus = 0 Guetig STDP [1] mu_plus, mu_minus in [0, 1] Van Rossum STDP [4] mu_plus = 0 mu_minus = 1
The weight changes are modulated by a “third factor”, in this case the postsynaptic dendritic current I_post_dend.
I_post_dend “gates” the weight update, so that if the current is 0, the weight is constant, whereas for a current of 1 pA, the weight change is maximal.
Do not use values of I_post_dend larger than 1 pA!
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
Parameters
Name |
Physical unit |
Default value |
Description |
|---|---|---|---|
d |
ms |
1ms |
Synaptic transmission delay |
lambda |
real |
0.01 |
|
tau_tr_pre |
ms |
20ms |
|
tau_tr_post |
ms |
20ms |
|
alpha |
real |
1.0 |
|
mu_plus |
real |
1.0 |
|
mu_minus |
real |
1.0 |
|
Wmax |
real |
100.0 |
|
Wmin |
real |
0.0 |
State variables
Name |
Physical unit |
Default value |
Description |
|---|---|---|---|
w |
real |
1.0 |
Synaptic weight |
Source code
The model source code can be found in the NESTML models repository here: third_factor_stdp_synapse.