This seems to be more simply all the data about the physical orientations and positions of neurons in a fly's nervous system.
I'd guess there is still humongous amounts of data missing that would be necessary for a simulation:
- the exact biological and chemical makeup of each neuron
- the biological and chemical environment in which those neurons exist
- the exact physics that govern the biological and chemical reactions happening in and around the neurons (and the ability to accurately simulate those physics)
- maybe most importantly, even if we have all those above (i.e. the ability to fully and accurately simulate biological systems as complex as individual cells), we may still missing the electro-chemical activation "state" of the neurons that allows the fly to operate as a cohesive whole. (as if we had all of the hardware of a computer, but none of the software)
The GP asked about "a fly simulation that works", and I think we won't need anything similar to your proposed demands. I'd wager that we can approach this decently well with a "basic" mathematical model run at discrete steps on the order of 0.1ms.
I suppose that we'll hit a big wall once we reach simulation time frames which involves changes in protein expression, but I think we'll have a decent simulation of what a "static" fly long before the end of the decade.
You don't necessarily need to understand something to a deep degree in order to simulate it. Ptolemy created a very accurate simulation of the solar system with a wildly poor understanding of how things moved, just because the system was simple and very consistent.
Simulating a fly is obviously a much larger task, but "we can't possibly simulate it unless we understand X" seems to me a misguided criticism.
Sure, hopefully there are many details which we could ignore, like we can ignore what the planets are made of. But from what we know about how nature works, I suspect a lot of little details are going to matter.
Flies are pretty highly optimised, and nature is happy to optimise all the way down to the single-molecule level. In fact there has to be a good reason to do something at the whole-neuron level, as this is vastly more expensive than doing it with a molecular machine. That reason is often speed, as electrical impulses give fast long-distance communication. But if you can do some of the computation with a molecular machine before sending that fast signal, why wouldn't you do this? So I'd bet that the hardware is customised many different ways invisible to this kind of scanning.
It seems to me that fundamentally people assume that simulating a neuron is vastly, vastly simpler than simulating a bacterium. Ok, you can assume that. But what gives you confidence in that? Do you think that simulating a bacterium is less complex than simulating a fly, or about the same?
It all depends on what questions you want to answer with your simulation. If what you care about is where in the room the thing will be after 10 seconds at a resolution of 1 cubic centimeter, then yes, simulating a bacterium is vastly simpler.
In principle I agree with you, but unfortunately we already know from other research that specific neuro-transmitters have specific effects on observable thought processes. Some neurons also sometimes 'broadcast' neuro transmitters by releasing them in an area around them, not just through direct synapses.
To me it would be highly surprising if these effects were not absolutely necessary to the brain's working.
the fact is that the connections and knowledge about the proteins are probably enough. consider: when something as complicated as a human brain is completely disrupted (with severe hypothermia, general anesthesia, a strong seizure) the "stuff" of their intellectual identity is preserved if the insult is removed. Therefore, it's extremely accurate to say that "we have everything we need" if the structure and protein expression within that structure is known.
"Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster."[1]
This doesn't touch the totality of the brain and says nothing of the CNS or PNS.
I'd guess there is still humongous amounts of data missing that would be necessary for a simulation:
- the exact biological and chemical makeup of each neuron
- the biological and chemical environment in which those neurons exist
- the exact physics that govern the biological and chemical reactions happening in and around the neurons (and the ability to accurately simulate those physics)
- maybe most importantly, even if we have all those above (i.e. the ability to fully and accurately simulate biological systems as complex as individual cells), we may still missing the electro-chemical activation "state" of the neurons that allows the fly to operate as a cohesive whole. (as if we had all of the hardware of a computer, but none of the software)