neurotools.obsolete.models.izh module
Izhikevich model
- neurotools.obsolete.models.izh.dv_izh(u, v, I)[source]
Time derivative for $v$ variable in Izhikevich model
- Parameters:
u (float) – current state of u variable
v (float) – current state of v variable
I (float) – applied current
- Returns:
dv – dv/dt
- Return type:
float
- neurotools.obsolete.models.izh.du_izh(u, v, a, b)[source]
Time derivative for $u$ variable in Izhikevich model
- Parameters:
u (float) – current state of u variable
v (float) – current state of v variable
a (float) – a parameter from Izhikevich model
b (float) – b parameter from Izhikevich model
- Returns:
du – du/dt
- Return type:
float
- neurotools.obsolete.models.izh.update_izh(u, v, a, b, c, d, I, dt=1)[source]
Izhikevich neuron state update
- Parameters:
u (float) – current state of u variable
v (float) – current state of v variable
a (float) – a parameter from Izhikevich model
b (float) – b parameter from Izhikevich model
c (float) – c parameter from Izhikevich model
d (float) – d parameter from Izhikevich model
I (float) – applied current
dt (float, default 1.0) – Time step
- Returns:
u (float) – Updated u variable
v (float) – Updated v variable
y (float) – If a spike occurs, y will be a unit-volume probability mass i.e. 1.0/dt
- neurotools.obsolete.models.izh.sim_izh(a, b, c, d, signal, dt=1)[source]
Simulate response of Izhikevich neuron model to signal
- Parameters:
a (float) – a parameter from Izhikevich model
b (float) – b parameter from Izhikevich model
c (float) – c parameter from Izhikevich model
d (float) – d parameter from Izhikevich model
signal (np.array) – applied current over time
dt (float, default 1.0) – Time step
- Returns:
state – Ntimes x 3 array of model state. First column is u variable Second column is v variable Third column is spiking density
- Return type:
array