The essential difference between spiking neural networks and earlier generation ANN's

Question

I have been studying Spiking Neural Networks online from various papers, mainly Maass (1997). I am not entirely sure I understand what makes SNN's pulse-code in contrast to earlier ANNs which are considered rate-code. I have background in neuroscience so I understand the terms and ratio, I'm asking regarding the actual implementation.

Is the practical difference in the fact that when each neuron updates its current state in an SNN it deals with the entire history of every pre-synaptic neuron and not only the last step? Is that what gives it temporal characteristics which previous generation ANN's lack?

Answer 1

Yeah; each neuron in the spiking network integrates its input, instead of just summing the input of the previous timestep as in the old analog model.