Izhikevich Neuron Model
Visualisation of neuronal spiking dynamics
The Izhikevich model is a simple yet biologically plausible model of neuronal spiking dynamics. It is given by the equations:
\[\frac{dv}{dt} = 0.04v^2 + 5v + 140 - u + I\] \[\frac{du}{dt} = a(bv - u)\]with a reset condition:
\[\text{if } v \geq 30, \text{ then } v \leftarrow c, \quad u \leftarrow u + d\]
{
"data": [
{
"x": [],
"y": [],
"mode": "lines",
"line": {"color": "#007bff", "width": 2},
"name": "Membrane Potential"
}
],
"layout": {
"title": "Izhikevich Neuron Model: Membrane Potential Over Time",
"xaxis": {"title": "Time [ms]"},
"yaxis": {"title": "Membrane Potential [mV]", "range": [-80, 40]},
"margin": {"l": 50, "r": 50, "b": 50, "t": 50}
}
}
Neuron Type Presets
About the Izhikevich Model
The Izhikevich neuron model can reproduce many different firing patterns observed in real neurons. Despite its computational simplicity compared to Hodgkin-Huxley-type models, it can reproduce various firing patterns by adjusting just four parameters: a, b, c, and d.
- Parameter a: The time scale of the recovery variable u. Smaller values result in slower recovery.
- Parameter b: The sensitivity of the recovery variable u to the subthreshold fluctuations of the membrane potential v.
- Parameter c: The after-spike reset value of the membrane potential v.
- Parameter d: The after-spike reset of the recovery variable u.
The interactive visualisation above allows you to adjust these parameters and observe how they affect the spiking behavior of the neuron.