In 1952 Alan Hodgkin and Andrew Huxley clamped the giant axon of a squid — thick enough to thread a wire down — and worked out the equations firing in your head right now. Four numbers describe the patch: the voltage V, and three gates m, h, n that open and close as the voltage changes.
A spike is all-or-none. Below a threshold the leak wins and the bump fizzles. Cross it and sodium's positive feedback runs away — m³h gates fling open, V rockets toward E_Na (+50 mV), then the slower potassium gate n⁴ repolarizes it. The peak is set by the ion gradients, not by how hard you pushed.
For a few milliseconds after, the axon is deaf: sodium's h gate is inactivated and must recover, capping how fast it can fire. A steady current makes a rhythmic train whose rate — not size — codes the stimulus strength.
Set the sodium density to zero and nothing fires at any push: that is tetrodotoxin, the pufferfish poison. The model here is fully deterministic — same push, same spike, every time — which is exactly why it became the template for all of computational neuroscience.
Something in the simulation stopped unexpectedly — the lesson continues without it. You can move on; nothing you did was wrong.