iaf_psc_alpha
iaf_psc_alpha  Leaky integrateandfire neuron model
Description
iaf_psc_alpha is an implementation of a leaky integrateandfire model with alphafunction kernel synaptic currents. Thus, synaptic currents and the resulting postsynaptic potentials have a finite rise time.
The threshold crossing is followed by an absolute refractory period during which the membrane potential is clamped to the resting potential.
The general framework for the consistent formulation of systems with neuron like dynamics interacting by point events is described in [1]. A flow chart can be found in [2].
Critical tests for the formulation of the neuron model are the comparisons of simulation results for different computation step sizes.
The iaf_psc_alpha is the standard model used to check the consistency of the nest simulation kernel because it is at the same time complex enough to exhibit nontrivial dynamics and simple enough compute relevant measures analytically.
Note
If tau_m is very close to tau_syn_exc or tau_syn_inh, numerical problems may arise due to singularities in the propagator matrics. If this is the case, replace equalvalued parameters by a single parameter.
For details, please see IAF_neurons_singularity.ipynb
in
the NEST source code (docs/model_details
).
References
See also
iaf_psc_delta, iaf_psc_exp, iaf_cond_alpha
Parameters
Name 
Physical unit 
Default value 
Description 

C_m 
pF 
250pF 
Capacitance of the membrane 
tau_m 
ms 
10ms 
Membrane time constant 
tau_syn_inh 
ms 
2ms 
Time constant of synaptic current 
tau_syn_exc 
ms 
2ms 
Time constant of synaptic current 
refr_T 
ms 
2ms 
Duration of refractory period 
E_L 
mV 
70mV 
Resting potential 
V_reset 
mV 
70mV 
Reset potential of the membrane 
V_th 
mV 
55mV 
Spike threshold potential 
I_e 
pA 
0pA 
constant external input current 
State variables
Name 
Physical unit 
Default value 
Description 

V_m 
mV 
E_L 

refr_t 
ms 
0ms 
Refractory period timer 
is_refractory 
boolean 
false 
Equations
Source code
The model source code can be found in the NESTML models repository here: iaf_psc_alpha.