> It's also very commonly observed that, for instance, the intensity of a stimulus is encoded not in the amplitude of a particular neuron's response but rather in the frequency of a neuron's firing.
This was actually mentioned by Geoff Hinton in his deep learning coursera lectures and the reason why his RBM's were outputting binary signals rather than float values -- the timing was more important than the values. It made a lot of sense when he talked about it. I saw this back in 2012. I assumed this was commonly understood now, but I guess not?
I've hypothesised the optimum way would be to use both binary and floats at the same time after a paper I read that basically said neuron pathways are both digital and analog. Something about the analog (float) being a weight pathway indicator or something. I wish I knew more about neuroscience.
This was actually mentioned by Geoff Hinton in his deep learning coursera lectures and the reason why his RBM's were outputting binary signals rather than float values -- the timing was more important than the values. It made a lot of sense when he talked about it. I saw this back in 2012. I assumed this was commonly understood now, but I guess not?