BioNSim

A collection of Python scripts to implement biological models of neurons using Python.
Numpy, matplotlib and scipy were used to animate the output.

Available Models :

Hudgkin & Huxley Model

Input

• For each ion, G is the conductance and Eq is the equilibrium potential.
  ```python
  import hudgkin_huxley as hh

cell = hh.Neuron(voltage=np.linspace(-150, 150, 100),
sodium={‘G’ : 120., ‘Eq’ : 120.},
potassium={‘G’ : 36., ‘Eq’ : -12.},
leak={‘G’ : 0.3,’Eq’ :10.6})

cell.simulate(V_init=-10, n_init=0, m_init=0, h_init=1, Tmax=50, inj = 15)

#### Output
![HH simulation](Demo/HHsimulation.gif)
### Hindmarsh & Rose Model
- Model parameters should be specified when instantiating the object, and the initial conditions can be changed when simulating the model.
```python
import hindmarsh_rose as hr
cell = hr.Neuron(r = 0.001, s = 4, xr = -8/5, a = 1, b = 3, c = 1, d = 5, I = 2)
cell.simulate_hind_rose(x_init=-1.5, y_init=-10, z_init=2, Tmax=1000)

Output

Fitzugh & Nagumo Model

import fitzugh-nagumo as fn
cell = fn.Neuron(a=0.7, b=0.8, tau=13)
cell.simulate_fitz_nagu(V_init=-2,w_init=-1.5, I_init=0.5, Tmax=100)

Output

ToDo :

More biological models : IKir, Izhikevich model, ……