The key bottleneck with all connectome projects is still reconstruction. There's on the order of a hundred billion neurones in the human brain; they're connected via 1,000-10,000 times the number of synapses. Current machine learning approaches are decent, but still require massive amounts of proof-reading.
Circuit neuroscience in Drosophila or the mammalian retina suggests neurones and synapses are indeed the level of detail we'll need in order to gain insight into computational mechanisms. So we're a long, long way off -- don't be too impressed by this particular dataset (which is insanely coarse!).
Hey if you guys want to help out with the proof reading effort, we've got a cool dataset that has a resolution of 16.5 nm x 16.5 nm x 23 nm at http://eyewire.org ^_^
The resolution is some of the best in the business, so to speak, but the biological interpretation of all MRI-derived metrics are still hotly debated. So the true level is detail is sort of dependent on something we don't know yet.
Yes, but this does not include any functional data, arguably a huge contribution of the HCP project. The history of neuroscience has taught us that you can only look so far by looking at anatomy alone!
Circuit neuroscience in Drosophila or the mammalian retina suggests neurones and synapses are indeed the level of detail we'll need in order to gain insight into computational mechanisms. So we're a long, long way off -- don't be too impressed by this particular dataset (which is insanely coarse!).