3 ms·
>> Neurons in our brain operate fundamentally differently. They work by transient spikes and information is carried not by the intensity of the spike voltage, b
by phkahler 3y ago
>> Neurons in our brain operate fundamentally differently. They work by transient spikes and information is carried not by the intensity of the spike voltage, but by the frequency of spiking.
I thought they worked like accumulators where the spike "energy" accumulates until the output "fires". If that's the case then the artificial NNs are still an approximation of that process. I agree that this is a significant difference, but the mathematical version is still a rough approximation inspired by the biological one.
- srean 3y agoSandpile mathematics, something that is studied by computer scientists and mathematicians, would be an approximation. Its not so much the level of the spike that matters but how often they spike is what conveys the signal. The temporal behavior is supremely important. It used to be believed that the rate is all that matters, but now, no longer. There are ANN models that model these spike trains (that's what these 'avalanches' are called), these do work similar to real neurons, but they are not part of the deep neural network popularity [0,1]. Besides, backpropagation is not what goes on in the brain, its known to be biologically infeasible. So all in all the traditional ANNs are nothing like real neural networks. That's ok, aeroplanes do not fly like birds, but they do still 'fly'. [0] https://en.wikipedia.org/wiki/Spiking_neural_network https://en.wikipedia.org/wiki/Spiking_neural_network [1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313413/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313413/