I am trying to implement a Biexponential shape conductance base synapse:

\theta, \theta_H and \sigma are constants. Adding H_{\infty} is the question.

Following the documentation I came up to this :

I skipped the H_{\infty} for now:

I think this should be :

\Theta is Heaviside step function. But I used the documentation method for the following.

```
tau_1 = 1 / alpha
tau_2 = 1 / beta
scale_f = (tau_2 / tau_1) ** (tau_1 / (tau_2 - tau_1))
eqs_e = """
VT : volt
IX : amp
Im = IX +
gL * (EL - vm) +
gL * DeltaT * exp((vm - VT) / DeltaT) : amp
ds/dt = -s / Tau_d : siemens
dg_syn/dt = scale_f * (s - g_syn) / Tau_r : siemens
I_syn = g_syn * (Erev - vm): amp
dvm/dt = (Im + I_syn) / C : volt
"""
```

for two neuron and a connection from 1 to two, the neuron 1 get and input current and I record `g_syn`

and `I_syn`

from the second neuron. `tau_1 = 2ms, tau_2=10ms`

Am I right up to now?

The question is how to include H_{\infty}?

or adding H is just complicating and we can safely approximate it.