hh_cond_exp_traub – Hodgkin-Huxley model for Brette et al (2007) review

Description

hh_cond_exp_traub is an implementation of a modified Hodgkin-Huxley model.

This model was specifically developed for a major review of simulators 1, based on a model of hippocampal pyramidal cells by Traub and Miles 2. The key differences between the current model and the model in 2 are:

  • This model is a point neuron, not a compartmental model.

  • This model includes only I_Na and I_K, with simpler I_K dynamics than in 2, so it has only three instead of eight gating variables; in particular, all Ca dynamics have been removed.

  • Incoming spikes induce an instantaneous conductance change followed by exponential decay instead of activation over time.

This model is primarily provided as reference implementation for hh_coba example of the Brette et al (2007) review. Default parameter values are chosen to match those used with NEST 1.9.10 when preparing data for 1. Code for all simulators covered is available from ModelDB 3.

Note: In this model, a spike is emitted if \(V_m \geq V_T + 30\) mV and \(V_m\) has fallen during the current time step.

To avoid that this leads to multiple spikes during the falling flank of a spike, it is essential to chose a sufficiently long refractory period. Traub and Miles used \(t_{ref} = 3\) ms (2, p 118), while we used \(t_{ref} = 2\) ms in 2.

Parameters

The following parameters can be set in the status dictionary.

V_m

mV

Membrane potential

V_T

mV

Voltage offset that controls dynamics. For default parameters, V_T = -63mV results in a threshold around -50mV.

E_L

mV

Leak reversal potential

C_m

pF

Capacity of the membrane

g_L

nS

Leak conductance

tau_syn_ex

ms

Time constant of the excitatory synaptic exponential function

tau_syn_in

ms

Time constant of the inhibitory synaptic exponential function

t_ref

ms

Duration of refractory period (see Note).

E_ex

mV

Excitatory synaptic reversal potential

E_in

mV

Inhibitory synaptic reversal potential

E_Na

mV

Sodium reversal potential

g_Na

nS

Sodium peak conductance

E_K

mV

Potassium reversal potential

g_K

nS

Potassium peak conductance

I_e

pA

External input current

References

1(1,2)

Brette R et al. (2007). Simulation of networks of spiking neurons: A review of tools and strategies. Journal of Computational Neuroscience 23:349-98. DOI: https://doi.org/10.1007/s10827-007-0038-6

2(1,2,3,4,5)

Traub RD and Miles R (1991). Neuronal networks of the hippocampus. Cambridge University Press, Cambridge UK.

3

http://modeldb.yale.edu/83319

Sends

SpikeEvent

Receives

SpikeEvent, CurrentEvent, DataLoggingRequest