Goldman-Hodgkin-Katz and Nernst formalisms in NeuroML2
======================================================

Sample [LEMS & NeuroML 2](https://github.com/OpenSourceBrain/ghk-nernst/tree/master/NeuroML2) files implementing a single compartment model, containing *HH* type Na⁺/K⁺ channels, a Ca⁺⁺ channel and pool. The Calcium current through the channel can be calculated either through the [GHK flux equation](http://en.wikipedia.org/wiki/GHK_flux_equation), or using the [Nernst Equation](http://en.wikipedia.org/wiki/Nernst_equation) to approximate its reversal potential.

The same mechanisms are implemented in *NEURON* as a comparison. Notice that *NEURON* has built in support for calculating reversal potentials via the Nernst equation, which can be compared to our implementation written from scratch by running [Native NEURON](https://github.com/OpenSourceBrain/ghk-nernst/blob/master/NEURON/nernstnat_na_k_ca.py) , [from scratch](https://github.com/OpenSourceBrain/ghk-nernst/blob/master/NEURON/nernst_na_k_ca.py) ; see also [native Nernst modfile](https://github.com/OpenSourceBrain/ghk-nernst/blob/master/NEURON/cachan_nernst_native.mod) and [from scratch modfile](https://github.com/OpenSourceBrain/ghk-nernst/blob/master/NEURON/cachan_nernst.mod)

Running tests
-------------

The following tests can be run to compare the usage of GHK/Nernst from *NEURON/LEMS*: *NEURON\_/\_LEMS*:

git clone git@github.com:OpenSourceBrain/ghk-nernst.git
cd ghk-nernst/NEURON/
nrnivmodl
./ghk_na_k_ca.py
./nernst_na_k_ca.py


</pre>
<pre>
cd ../NeuroML2
jnml LEMS_ghk_na_k_ca.xml
jnml LEMS_nernst_na_k_ca.xml


</pre>
<pre>
cd ../
python compare.py

neuroConstruct
--------------

Recent versions of neuroConstruct support GHK, generating NeuroML2 and NEURON code accordingly. In order to use the GHK flux equation instead
of Ohm’s law for a particular mechanism, set an extra parameter GHK\_permeability (in m/s) using the **Edit Density Mechs** dialog.

Definitions
-----------

From [Wikipedia](http://en.wikipedia.org/wiki/GHK_flux_equation)


From Steuber et al DCN model:

A = exp(-23.20764929 * v / T) = exp((-z * F * (0.001) * v) / (R * T))

ical = perm * m*m * h * (4.47814e6 * v / T) * ((cali/1000) - (calo/1000) * A) / (1 - A)

(z^2 * F^2 * (0.001) * v) / (R * T)

From [GENESIS](http://www.genesis-sim.org/GENESIS/gum-tutorials/beeman/Hyperdoc/Manual-26.html#ss26.30)

valency * F
K = - - - - - - -
R * (T + 273)

Cin * exp(K * Vm) - Cout
Ik = -p * F * K * Vm - - - - - - - - - - - -
exp(K * Vm) - 1

(it is missing one valency factor in comparison to the others, check genesis source)