Inhibitory Nodes
I 've long conjectured that the reason we have an inhibitory network in our brains is to prevent an epileptic burst and it seems that this thought has some truth. In my early simulations of neurons, I found quickly that excitatory networks would get to a tipping point where they would just start firing uncontrollably; i.e. every neuron (node) would be firing as fast as it could and the output would end up being a jumbled mess of motor neurons all firing, all the time. I even continue to experience this sometimes in more true emulations due to the timing or the number of neurons aren't in a correct balance so that the inhibitory neurons aren't in a great enough strength to overcome the excitation. In AI/Deep Learning (et al), inhibitory networks don't exist. The excitatory network is refined by the error factors and outcomes are created by numeric voting. DL tunes an excitatory network by weighted factors. There is a delicate balance between the excitatory network