> If we assume that every synapse can be considered like a "weight" in a neural network, we have a model that is much much bigger than anything developed to dat

> If we assume that every synapse can be considered like a "weight" in a neural network, we have a model that is much much bigger than anything developed to date. This is a very bad assumption. Each synapse is a highly complex chemical computer, and its "weight" with regard to its contribution to the postsynaptic neuron's activation at any point in time depends on a multitude of factors. Those factors include dozens of interacting metabolic pathways, the interactions of various neurotransmitter systems which each have distinct behavior, and things like where the individual synapses sit relative to one another on the dendritic arbor. There's even evidence that at least in some neurons the activation pattern may influence RNA production in the neuron, creating a kind of recording which influences the behavior of the cell. Current ANN models should be considered a very low dimensional approximation of the real thing.