All good points. I'll need to read the paper to fully grasp this concept. I see standard neural networks as learning relevant patterns + rote memorisation machines, do you mean the spike NNs facilitates better representation by reducing rote memorisation and thus increasing generalisation, since they are not always on but only when needed?