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> the mind/brain is too complex to describe at any single level of abstraction Sure, but now we're talking about a single neuron... > Wikipedia lists 22 disti

> the mind/brain is too complex to describe at any single level of abstraction Sure, but now we're talking about a single neuron... > Wikipedia lists 22 distinct branches of neuroscience [1], and each has their own set of problems they are trying to answer. Sure, but only one or two of those 22 are about single neurons... In artificial neural networks neurons are approximated basically as a weighted summation and a thresholding/sigmoid/rectified linear operation. It would be interesting to know how far from the truth this is. Is the biological neuron doing something entirely different than what our artificial neurons are? That's what I feel would be a pressing research question.

shmageggy 11y ago
> Sure, but only one or two of those 22 are about single neurons... I count four or five, but I agree that may not be the best example for my point, which is that (even within those few subfields) there are many valid levels of description. > Is the biological neuron doing something entirely different than what our artificial neurons are? Yes, very; they are highly non-linear and have complex timing dependencies. This illustrates the point. Once you model all those intricate biological details it's unclear how to translate that into a mathematical function that we can understand for the purposes of higher level computation. Not to mention, we're still talking about spiking models, so we'd also have to abstract away spiking in order to look like an artificial neuron. The gulf between the level of description that you and I want and what biologically realistic models provide is huge.