You could write the same article in reverse: how many neurons does it take to simulated an ANN? A lot, because neither system is a good basis for representing the other. You need a lot of tanh functions to fit a spiking neuron and a lot of spiking neurons to represent a single tanh. This fact doesn’t say anything about the “computational power” of either system.

I am all starting to feel like it is borderline malpractice to talk about neuron/silicon performance comparisons without acknowledging that perhaps the driving design constraint in wetware is energy usage, and considering the implications this has for optimal architecture.