Especially, axons are 0.2-20 um in diameter. With a resolution of 20 um you won't really find them, but with 0.01 um, you will certainly be able to identify them. This could lead to new anatomical insights in human brains. I remember recently someone complaining on hn that a new finding about a connection of two brain regions in mice hasn't been confirmed in humans yet . If scans of entire human brains at 0.01 um resolutions were available, you could verify claims like these by just checking the data.
Edit: corrected the BigBrain resolution.
Everything should be experessed in nanometers only, and avoid micrometers, since expressing nanometer sizes in micrometer units requires confusing decimal points, and an extra cognitive load to translate fractional proportions.
Axons are 200 to 2000 nanometers in diameter.
Anyway, we’d need thousands of desireable human brains to draw conclusions. And my desireable, I mean smart, sociable people mostly. You’ll want total morons in the data set too, but only to distinguish total assholes in the training data, when we use AI to rationalize their extermination. That way, the Hitlers go to the concentration camp, this time.
Also, I just looked at the paper  and here it says:
> To generate a data set with isotropic resolution, we down-scaled all images to 20 µm by 20 µm to match the section thickness of 20 µm.
So that confirms the 20 um per direction, no?
Edit: oh no, I just see that I wrote 1 um above, not 20. Not that 2.71 is correct but I guess that's what confused you. Corrected. Thanks!
"The new technology combines a method for expanding brain tissue, making it possible to image at higher resolution, with a rapid 3-D microscopy technique known as lattice light-sheet microscopy. In a paper appearing in Science Jan. 17, the researchers showed that they could use these techniques to image the entire fruit fly brain, as well as large sections of the mouse brain, much faster than has previously been possible."
--> I mean, are they pumping the tissue up like a balloon or what?
Multiply this by a hundred million to get mammalian complexity