But knowing that still doesn't bring you that much closer to simulating it. There's a couple a of great papers where they got biologists to attempt to figure out how relatively simple, very well known things worked - one was a radio, one was an old Atari chip. So they used biological techniques used to try to figure out how brains worked. For example lesions - they took transistors out of the arcade machine and tested if the game still started up. And if, say, they found that taking a and b out stopped Donkey Kong from working, and x and y stopped space invaders working, then maybe they could make the assumption that a and b were the Donkey Kong transistors, etc. Or if they destroyed tiny parts of the radio circuit board and it still appeared to work, then those parts were junk, unnecessary. But of course that's completely misleading. It doesn't matter how much data they had either.
It's not to say the data that is currently held isn't important; it is, but it doesn't then translate to 'we can model this insanely complex system', because there's so, so much missing from the understanding of how it works
Also see, Could a neuroscientist understand a microprocessor? http://biorxiv.org/content/biorxiv/early/2016/05/26/055624.f...
They use various neuroscience techniques to see how far they can get reverse engineering an Atari.