iaf_cond_exp

iaf_cond_exp - Simple conductance based leaky integrate-and-fire neuron model

Description

iaf_cond_exp is an implementation of a spiking neuron using IAF dynamics with conductance-based synapses. Incoming spike events induce a post-synaptic change of conductance modelled by an exponential function. The exponential function is normalised such that an event of weight 1.0 results in a peak conductance of 1 nS.

References

See also

iaf_psc_delta, iaf_psc_exp, iaf_cond_exp

Parameters

Name

Physical unit

Default value

Description

V_th

mV

-55mV

Threshold potential

V_reset

mV

-60mV

Reset potential

t_ref

ms

2ms

Refractory period

g_L

nS

16.6667nS

Leak conductance

C_m

pF

250pF

Membrane capacitance

E_exc

mV

0mV

Excitatory reversal potential

E_inh

mV

-85mV

Inhibitory reversal potential

E_L

mV

-70mV

Leak reversal potential (aka resting potential)

tau_syn_exc

ms

0.2ms

Synaptic time constant of excitatory synapse

tau_syn_inh

ms

2ms

Synaptic time constant of inhibitory synapse

I_e

pA

0pA

constant external input current

State variables

Name

Physical unit

Default value

Description

r

integer

0

counts number of tick during the refractory period

V_m

mV

E_L

membrane potential

Equations

\[\frac{ dV_{m} } { dt }= \frac 1 { C_{m} } \left( { (-I_{leak} - I_{syn,exc} - I_{syn,inh} + I_{e} + I_{stim}) } \right)\]

Source code

The model source code can be found in the NESTML models repository here: iaf_cond_exp.

Characterisation

Synaptic response

iaf_cond_exp_nestml

f-I curve

iaf_cond_exp_nestml