aeif_cond_exp – Conductance based exponential integrate-and-fire neuron model¶
Description¶
aeif_cond_exp is the adaptive exponential integrate and fire neuron according to Brette and Gerstner (2005), with postsynaptic conductances in the form of truncated exponentials.
This implementation uses the embedded 4th order Runge-Kutta-Fehlberg solver with adaptive stepsize to integrate the differential equation.
The membrane potential is given by the following differential equation:
and
Note that the spike detection threshold V_peak is automatically set to \(V_th+10 mV\) to avoid numerical instabilites that may result from setting V_peak too high.
For implementation details see the aeif_models_implementation notebook.
Parameters:¶
The following parameters can be set in the status dictionary.
Dynamic state variables: |
||
V_m |
mV |
Membrane potential |
g_ex |
nS |
Excitatory synaptic conductance |
g_in |
nS |
Inhibitory synaptic conductance |
w |
pA |
Spike-adaptation current |
Membrane Parameters |
||
C_m |
pF |
Capacity of the membrane |
t_ref |
ms |
Duration of refractory period |
V_reset |
mV |
Reset value for V_m after a spike |
E_L |
mV |
Leak reversal potential |
g_L |
nS |
Leak conductance |
I_e |
pA |
Constant external input current |
Spike adaptation parameters |
||
a |
nS |
Subthreshold adaptation |
b |
pA |
Spike-triggered adaptation |
Delta_T |
mV |
Slope factor |
tau_w |
ms |
Adaptation time constant |
V_th |
mV |
Spike initiation threshold |
V_peak |
mV |
Spike detection threshold |
Synaptic parameters |
||
E_ex |
mV |
Excitatory reversal potential |
tau_syn_ex |
ms |
Exponential decay time constant of excitatory synaptic conductance kernel |
E_in |
mV |
Inhibitory reversal potential |
tau_syn_in |
ms |
Exponential decay time constant of inhibitory synaptic conductance kernel |
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
Brette R and Gerstner W (2005). Adaptive Exponential Integrate-and-Fire Model as an Effective Description of Neuronal Activity. J Neurophysiol 94:3637-3642. DOI: https://doi.org/10.1152/jn.00686.2005
See also¶
Neuron, Adaptive Threshold, Integrate-And-Fire, Conductance-Based