What leaps in technology would be needed to scan the total state of the human brain? What technological leaps would be necessary to capture the absolute state of the brain? This would need to include:


a representation of each neuron
a representation of each neural connection
the chemical balances of the dendral connections between each neuron


And maybe we would also need to capture:


the current synaptic activity of each neuron


I'm not sure if we need that, perhaps if you lose the flow of synapses, you break the mind, or perhaps the state of the neurons will continue to work properly the next time synaptic input is introduced and the mind will "wake up".

Either way, that's an incredible amount of detail, especially chemical information, that would have to be captured so we could convert it into a virtual simulation of the functional aspects of each neuron making up that brain. 

What are the major technological gaps that we would need to overcome in order to scan the brain with that level of detail? I'm interested in the specific aspects of scanning technology that would have to be invented beyond our current brain scanning technology.
Your question can be reduced to "What level of detail do we need to know about a brain to be able to simulate it?"

The answer to this question is we have no idea. The Blue Brain project has bet on the synaptic level, but they haven't been able to scale up to behaviour yet. But why stop at the synaptic level? Why not go down to molecules or atoms? Sure the computational power required goes up, but then we get a better model! And computers are getting faster and lower power all the time, right?

Actually, traditional processors have hit a wall in terms of power efficiency [1]. So you do end up needing to choose a reasonable level of detail for what you're choosing to model, since detail for detail's sake isn't going to get you anywhere [2]. Once we can understand the basic functions the brain is computing and how it's computing them, we can start looking for that level of detail in the human brain for simulation.

In conclusion, rather than a simple technological advancement, we need a theoretical advancement in understanding what the brain is even doing in the first place before we can use the data meaningfully.



[1] "Finding a roadmap to achieve large neuromorphic hardware systems" by  Jennifer Hasler and Bo Marr. Specifically, Figure 17 shows the "power efficiency wall".

[2] "The use and abuse of large-scale brain models" by Chris Eliasmith and Oliver Trujillo