aeif_psc_delta_clopath – Adaptive exponential integrate-and-fire neuron¶
Description¶
aeif_psc_delta_clopath
is an implementation of the neuron model as it is used
in 1. It is an extension of the aeif_psc_delta
model and capable of
connecting to a Clopath synapse.
Note that there are two points that are not mentioned in the paper but
present in a MATLAB implementation by Claudia Clopath 3. The first one is the
clamping of the membrane potential to a fixed value after a spike occured to
mimik a real spike and not just the upswing. This is important since the finite
duration of the spike influences the evolution of the convolved versions
(u_bar_[plus/minus]
) of the membrane potential and thus the change of the
synaptic weight. Secondly, there is a delay with which u_bar_[plus/minus]
are
used to compute the change of the synaptic weight.
Note: Neither the clamping nor the delayed processing of u_bar_[plus/minus] are mentioned in 1. However, they are part of an reference implementation by Claudia Clopath et al. that can be found on ModelDB 3. The clamping is important to mimic a spike which is otherwise not described by the aeif neuron model.
For implementation details see the aeif_models_implementation notebook.
See also 2.
Parameters¶
The following parameters can be set in the status dictionary.
Dynamic state variables |
||
V_m |
mV |
Membrane potential |
w |
pA |
Spike-adaptation current |
z |
pA |
Spike-adaptation current |
V_th |
mV |
Adaptive spike initiation threshold |
u_bar_plus |
mV |
Low-pass filtered Membrane potential |
u_bar_minus |
mV |
Low-pass filtered Membrane potential |
u_bar_bar |
mV |
Low-pass filtered u_bar_minus |
Spike adaptation parameters |
||
a |
nS |
Subthreshold adaptation |
b |
pA |
Spike-triggered adaptation |
Delta_T |
mV |
Slope factor |
tau_w |
ms |
Adaptation time constant |
tau_z |
ms |
Spike afterpotential current time constant |
I_sp |
pA |
Depolarizing spike afterpotential current magnitude |
V_peak |
mV |
Spike detection threshold |
V_th_max |
mV |
Value of V_th afer a spike |
V_th_rest |
mV |
Resting value of V_th |
Clopath rule parameters |
||
A_LTD |
1/mV |
Amplitude of depression |
A_LTP |
1/mV^2 |
Amplitude of facilitation |
theta_plus |
mV |
Threshold for u |
theta_minus |
mV |
Threshold for u_bar_[plus/minus] |
A_LTD_const |
boolean |
Flag that indicates whether A_LTD_ should be constant (true, default) or multiplied by u_bar_bar^2 / u_ref_squared (false). |
delay_u_bars |
real |
Delay with which u_bar_[plus/minus] are processed to compute the synaptic weights. |
U_ref_squared |
real |
Reference value for u_bar_bar_^2. |
Integration parameters |
||
gsl_error_tol |
real |
This parameter controls the admissible error of the GSL integrator. Reduce it if NEST complains about numerical instabilities. |
Sends¶
SpikeEvent
Receives¶
SpikeEvent, CurrentEvent, DataLoggingRequest
References¶
- 1(1,2)
Clopath et al. (2010). Connectivity reflects coding: a model of voltage-based STDP with homeostasis. Nature Neuroscience 13(3):344-352. DOI: https://doi.org/10.1038/nn.2479
- 2
Clopath and Gerstner (2010). Voltage and spike timing interact in STDP – a unified model. Frontiers in Synaptic Neuroscience. 2:25 DOI: https://doi.org/10.3389/fnsyn.2010.00025
- 3(1,2)
Voltage-based STDP synapse (Clopath et al. 2010) on ModelDB https://senselab.med.yale.edu/ModelDB/showmodel.cshtml?model=144566&file=%2f modeldb_package%2fVoTriCode%2faEIF.m
See also¶
Neuron, Adaptive Threshold, Integrate-And-Fire, Clopath Plasticity, Current-Based