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iaf_cond_alpha_mc – Multi-compartment conductance-based leaky integrate-and-fire neuron model

Description

THIS MODEL IS A PROTOTYPE FOR ILLUSTRATION PURPOSES. IT IS NOT YET FULLY TESTED. USE AT YOUR OWN PERIL!

iaf_cond_alpha_mc is an implementation of a multi-compartment spiking neuron using IAF dynamics with conductance-based synapses. It serves mainly to illustrate the implementation of ref:multicompartment models <multicompartment-models> in NEST.

The model has three compartments: soma, proximal and distal dendrite, labeled as s, p, and d, respectively. Compartments are connected through passive conductances as follows

\[ \begin{align}\begin{aligned}\begin{split}C_{m.s} d/dt V_{m.s} = \ldots - g_{sp} ( V_{m.s} - V_{m.p} ) \\\end{split}\\\begin{split}C_{m.p} d/dt V_{m.p} = \ldots - g_{sp} ( V_{m.p} - V_{m.s} ) - g_{pd} ( V_{m.p} - V_{m.d} ) \\\end{split}\\C_{m.d} d/dt V_{m.d} = \ldots \qquad - g_{pd} ( V_{m.d} - V_{m.p} )\end{aligned}\end{align} \]

A spike is fired when the somatic membrane potential exceeds threshold, \(V_{m.s} >= V_{th}\). After a spike, somatic membrane potential is clamped to a reset potential, :math:` V_{m.s} == V_{reset}`, for the refractory period. Dendritic membrane potentials are not manipulated after a spike.

There is one excitatory and one inhibitory conductance-based synapse onto each compartment, with alpha-function time course. The alpha function is normalized such that an event of weight 1.0 results in a peak current of 1 nS at \(t = \tau_{syn}\). Each compartment can also receive current input from a current generator, and an external (rheobase) current can be set for each compartment.

Synapses, including those for injection external currents, are addressed through the receptor types given in the receptor_types entry of the state dictionary. Note that in contrast to the single-compartment iaf_cond_alpha model, all synaptic weights must be positive numbers!

Parameters

The following parameters can be set in the status dictionary. Parameters for each compartment are collected in a sub-dictionary; these sub-dictionaries are called “soma”, “proximal”, and “distal”, respectively. In the list below, these parameters are marked with an asterisk.

V_m*

mV

Membrane potential

E_L*

mV

Leak reversal potential

C_m*

pF

Capacity of the membrane

E_ex*

mV

Excitatory reversal potential

E_in*

mV

Inhibitory reversal potential

g_L*

nS

Leak conductance

tau_syn_ex*

ms

Rise time of the excitatory synaptic alpha function

tau_syn_in*

ms

Rise time of the inhibitory synaptic alpha function

I_e*

pA

Constant input current

g_sp

nS

Conductance connecting soma and proximal dendrite

g_pd

nS

Conductance connecting proximal and distal dendrite

t_ref

ms

Duration of refractory period

V_th

mV

Spike threshold in mV

V_reset

mV

Reset potential of the membrane

Sends

SpikeEvent

Receives

SpikeEvent, CurrentEvent, DataLoggingRequest

References

1

Meffin H, Burkitt AN, Grayden DB (2004). An analytical model for the large, fluctuating synaptic conductance state typical of neocortical neurons in vivo. Journal of Computational Neuroscience, 16:159-175. DOI: https://doi.org/10.1023/B:JCNS.0000014108.03012.81

2

Bernander O, Douglas RJ, Martin KAC, Koch C (1991). Synaptic background activity influences spatiotemporal integration in single pyramidal cells. Proceedings of the National Academy of Science USA, 88(24):11569-11573. DOI: https://doi.org/10.1073/pnas.88.24.11569