It's a tough question since we still don't understand the brain well enough to know what degree of fidelity of copying it is necessary to achieve the same/simil

It's a tough question since we still don't understand the brain well enough to know what degree of fidelity of copying it is necessary to achieve the same/similar functionality. What is the computational equivalent of a biological neuron? How much of the detailed chemistry is really relevant to it's operation (doing useful computation), or can we just use the ANN model of synapses as weights, and the neuron itself as a summation device plus a non-linearity? Maybe we can functionally model the human brain at a much coarser, more efficient, level than individual neurons - at cortical mini/macro column level perhaps, or as an abstract architecture not directly related to nature's messy implementation?