[erikerikson]

I'm sure that there exist people who get lost in the analogies. Practitioners are generally not confused that ANNs are simplifications of the brain. The questions are which simplifications are most relevant and whether complexities can be added that yield better results. My own research was about reintroducing absolute location. I'm standard ANNs location is relative within a graph model of the network. I'm the real brain blood vessels and other macrostructures deliver materials used to grow and modify the neurons and these affect the network based on physical location. I'm fact, by adding these back in we bypassed the XOR limitation (i.e. Minsky's result leading to back propagation). Concretely, we observed learning XOR over the inputs within a Hopfield network using Hebbian learning modulated by spatially modulated trophic factor).