[davi]

Late to the party, but corresponding author on the paper here. Cool to see this on HN!

We have less than "half the picture" here. Not just weights; also missing electrical synapses, neurotransmitters, etc. We also don't know the spatial scale of neuronal arbor integration. Furthermore these are just the image data, not the complete connectome; people still have to trace circuits by hand in this dataset. Collaborators are starting to crack the segmentation problem, but it is still early days.

Necessary but insufficient class of information!

If anyone is interested you can browse the data live here:https://fafb.catmaid.virtualflybrain.org/?pid=2&zp=131280&yp...

"URL to this view" lets you share URLs to whatever you're looking at.

---- edit:

in mammals there is pretty good circumstantial evidence that post-synaptic density size correlates with evoked postsynaptic potential, but this hasn't been clearly and directly calibrated yet, and could vary from cell type to cell type

[jamesough]

What technology needs to be developed to get the data on synapses and neurotransmitters? A high-resolution Raman imaging microscope? And is a dead brain sufficient, or would you need a real-time noninvasive scan of a living one?

[davi]

In the fruit fly, neuronal cell types are highly morphologically stereotyped and identifiable across animals. This means that for a given cell type, you can collect data on electrical synapses in animal A, on transmitters in animal B, and on electrophysiology in animal C, and in this fashion assemble a unified, multimodal view of the parts involved. Our whole brain EM volume lets you see how those parts are connected.

In the above examples dead brains are okay except for electrophysiology, where the brain needs to be alive.

[jamesough]

Thanks. Can you recommend any books on these topics?