Even with connection strengths I still don't think we would really have the full connectome. Such a model would completely miss many of the phenomena related to chemical synapses, which involve signal transduction pathways, which are _astoundingly_ complex. Those complexities are part of the algorithm being run though!

(Of course we might still learn useful things from such a model, I just want to be clear that it wouldn't in any sense be a complete one.)

This. I simply cannot even begin to go into the sheer magnitude of the number of ways the fundamental state of a neural simulator changes once you understand that nothing exists monotonically. It's all about the loops, and the interplay between them. So much of our conscious experience is shaped by the fact that at any one time billions upon billions of neural circuits are firing along shared pathways; each internal action fundamentally coloring each emergent perception through the timbre it contributes to the perceptual integration of external stimuli.

It isn't enough to flip switches on and off, and to recognize weights, or even to take a fully formed brain network and simulate it. You have to understand how it developed, what it reacts to, how body shapes mind shapes body, and so on and so forth.

What we're doing now with NN's is mistaking them for the key to making an artificial consciousness, when all we're really playing with is the ML version of one of those TI calculators with the paper roll the accountants and bookkeepers use. They are subunits that may compose together to represent xmcrystalized functional units of expert system logic; but they are no closer to a self-guided, self-aware entity than a toaster.

Agreed, though continuously monitoring the propagation of the signals in vivo would allow us to at least start forming models on temporal or context specific modulation of connection strengths (which in the end is what decides the algorithms of the nervous system I presume)