Standard models


Standard models are neuron models that are available in at least two of the simulation engines supported by PyNN. PyNN performs automatic translation of parameter names, types and units. Only a handful of models are currently available, but the list will be expanded in future releases. To obtain a list of all the standard models available in a given simulator, use the list_standard_models() function, e.g.:

>>> from pyNN import neuron
>>> neuron.list_standard_models()
[<class 'pyNN.neuron.cells.IF_cond_alpha'>, <class 'pyNN.neuron.cells.IF_curr_exp'>,
 <class 'pyNN.neuron.cells.SpikeSourceArray'>, <class 'pyNN.neuron.cells.IF_cond_exp'>,
 <class 'pyNN.neuron.cells.IF_facets_hardware1'>, <class 'pyNN.neuron.cells.SpikeSourcePoisson'>,
 <class 'pyNN.neuron.cells.EIF_cond_alpha_isfa_ista'>, <class 'pyNN.neuron.cells.IF_curr_alpha'>]

Integrate-and-fire neurons

IF_curr_alpha

Leaky integrate and fire model with fixed threshold and alpha-function-shaped post-synaptic current.

Availability: NEST v1, NEST v2, NEURON, PCSIM

Name Default value Units Description
v_rest -65.0 mV Resting membrane potential
cm 1.0 nF Capacity of the membrane
tau_m 20.0 ms Membrane time constant
tau_refrac 0.0 ms Duration of refractory period
tau_syn 5.0 ms Rise time of the synaptic alpha function
i_offset 0.0 nA Offset current
v_reset -65.0 mV Reset potential after a spike
v_thresh -50.0 mV Spike threshold
v_init -65.0 mV Membrane potential at t = 0

IF_curr_exp

Leaky integrate and fire model with fixed threshold and decaying-exponential post-synaptic current. (Separate synaptic currents for excitatory and inhibitory synapses.

Availability: NEST v1, NEST v2, NEURON, PCSIM

Name Default value Units Description
v_rest -65.0 mV Resting membrane potential
cm 1.0 nF Capacity of the membrane
tau_m 20.0 ms Membrane time constant
tau_refrac 0.0 ms Duration of refractory period
tau_syn_E 5.0 ms Decay time of excitatory synaptic current
tau_syn_I 5.0 ms Decay time of inhibitory synaptic current
i_offset 0.0 nA Offset current
v_reset -65.0 mV Reset potential after a spike
v_thresh -50.0 mV Spike threshold
v_init -65.0 mV Membrane potential t = 0

IF_cond_alpha

Leaky integrate and fire model with fixed threshold and alpha-function-shaped post-synaptic conductance.

Availability: NEST v1, NEST v2, NEURON, PCSIM

Name Default value Units Description
v_rest -65.0 mV Resting membrane potential
cm 1.0 nF Capacity of the membrane
tau_m 20.0 ms Membrane time constant
tau_refrac 0.0 ms Duration of refractory period
tau_syn_E 5.0 ms Rise time of the excitatory synaptic alpha function
tau_syn_I 5.0 ms Rise time of the inhibitory synaptic alpha function
e_rev_E 0.0 mV Reversal potential for excitatory input
e_rev_I -70.0 mV Reversal potential for inhibitory input
v_thresh -50.0 mV Spike threshold
v_reset -65.0 mV Reset potential after a spike
i_offset 0.0 nA Offset current
v_init -65.0 mV Membrane potential at t = 0

IF_cond_exp

Leaky integrate and fire model with fixed threshold and decaying-exponential post-synaptic conductance.

Availability: NEST v2, NEURON, PCSIM

Name Default value Units Description
v_rest -65.0 mV Resting membrane potential
cm 1.0 nF Capacity of the membrane
tau_m 20.0 ms Membrane time constant
tau_refrac 0.0 ms Duration of refractory period
tau_syn_E 5.0 ms Decay time of the excitatory synaptic conductance
tau_syn_I 5.0 ms Decay time of the inhibitory synaptic conductance
e_rev_E 0.0 mV Reversal potential for excitatory input
e_rev_I -70.0 mV Reversal potential for inhibitory input
v_thresh -50.0 mV Spike threshold
v_reset -65.0 mV Reset potential after a spike
i_offset 0.0 nA Offset current
v_init -65.0 mV Membrane potential at t = 0

HH_cond_exp

Single-compartment Hodgkin-Huxley-type neuron with transient sodium and delayed-rectifier potassium currents using the ion channel models from ???Traub?.

Availability: NEST v2, NEURON, PCSIM

Name Default value Units Description
gbar_Na 20000.0    
gbar_K 6000.0    
g_leak 10.0    
cm 0.2 nF  
v_offset -63.0 mV  
e_rev_Na 50.0 mV  
e_rev_K -90.0 mV  
e_rev_leak -65.0 mV  
e_rev_E 0.0 mV  
e_rev_I -80.0 mV  
tau_syn_E 0.2 ms  
tau_syn_I 2.0 ms  
i_offset 0.0 nA  
v_init -65.0 mV  

EIF_cond_alpha_isfa_ista

Adaptive exponential integrate and fire neuron according to
Brette R and Gerstner W (2005) Adaptive Exponential Integrate-and-Fire Model as an Effective Description of Neuronal Activity. J Neurophysiol 94:3637-3642

Availability: NEST v2, NEURON, PCSIM

Name Default value Units Description
v_init -70.6 mV Initial membrane potential
w_init 0.0 nA Spike-adaptation current
cm 0.281 nF Capacity of the membrane
tau_refrac 0.0 ms Duration of refractory period
v_spike 0.0 mV Spike detection threshold
v_reset -70.6 mV Reset value for membrane potential after a spike
v_rest -70.6 mV Resting membrane potential (Leak reversal potential)
tau_m 9.3667 ms Membrane time constant
i_offset 0.0 nA Offset current
a 4.0 nS Subthreshold adaptation conductance
b 0.0805 nA Spike-triggered adaptation
delta_T 2.0 mV Slope factor
tau_w 144.0 ms Adaptation time constant
v_thresh -50.4 mV Spike initiation threshold
e_rev_E 0.0 mV Excitatory reversal potential
tau_syn_E 5.0 ms Rise time of excitatory synaptic conductance (alpha function)
e_rev_I -80.0 mV Inhibitory reversal potential
tau_syn_I 5.0 ms Rise time of the inhibitory synaptic conductance (alpha function)

Spike sources

SpikeSourcePoisson

Spike source, generating spikes according to a Poisson process.

Availability: NEST, NEURON, PCSIM [note problems with this in NEST]

Name Default value Units Description
rate 0.0 s^`-1` Mean spike frequency
start 0.0 ms Start time
duration 10^9 ms Duration of spike sequence

SpikeSourceArray

Spike source generating spikes at the times given in the spike_times array.

Availability: NEST, NEURON, PCSIM

Name Default value Units Description
spike_times [] ms list or numpy array containing spike times