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Can we also map the synaptic strength with this method? If not, I think we only have half the picture; as for brains, configuration of connections are as import

by aavaas 8y ago

Can we also map the synaptic strength with this method? If not, I think we only have half the picture; as for brains, configuration of connections are as important as layout of the circuitry.

aperrien 8y ago
Last week a technique was published that might be able to accomplish this in a reasonable amount of time: https://ai.googleblog.com/2018/07/improving-connectomics-by-order-of.html https://ai.googleblog.com/2018/07/improving-connectomics-by-... One of the authors even stopped by for a chat here about it.
- aavaas 8y ago
  I was talking about synaptic strength (strength of connections between neurons which can vary from +ve to -ve) [0]. There is no mention of synapse in that article. [0] https://en.wikipedia.org/wiki/Synapse https://en.wikipedia.org/wiki/Synapse
  - aperrien 8y ago
    At the bottom of the article: > Next Steps > We will continue to improve connectomics reconstruction technology, with the aim of fully automating synapse-resolution connectomics and contributing to ongoing connectomics projects at the Max Planck Institute and elsewhere. In order to help support the larger research community in developing connectomics techniques, we have also open-sourced the TensorFlow code for the flood-filling network approach, along with WebGL visualization software for 3d datasets that we developed to help us understand and improve our reconstruction results.
    - leemailll 8y ago
      What you quoted is not about synapse strength
leemailll 8y ago
No, EM can’t offer this type of info. If you are interested take a look at C. Elegans. Done for years but this part is still not clear
davi 8y ago
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=183714&xp=504613&tool=navigator&sid0=2&s0=7 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 8y ago
  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 8y ago
    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 8y ago
      Thanks. Can you recommend any books on these topics?

by aavaas 8y ago

Can we also map the synaptic strength with this method? If not, I think we only have half the picture; as for brains, configuration of connections are as important as layout of the circuitry.

aperrien 8y ago

Last week a technique was published that might be able to accomplish this in a reasonable amount of time: https://ai.googleblog.com/2018/07/improving-connectomics-by-order-of.html https://ai.googleblog.com/2018/07/improving-connectomics-by-... One of the authors even stopped by for a chat here about it.

aavaas 8y ago
I was talking about synaptic strength (strength of connections between neurons which can vary from +ve to -ve) [0]. There is no mention of synapse in that article. [0] https://en.wikipedia.org/wiki/Synapse https://en.wikipedia.org/wiki/Synapse
- aperrien 8y ago
  At the bottom of the article: > Next Steps > We will continue to improve connectomics reconstruction technology, with the aim of fully automating synapse-resolution connectomics and contributing to ongoing connectomics projects at the Max Planck Institute and elsewhere. In order to help support the larger research community in developing connectomics techniques, we have also open-sourced the TensorFlow code for the flood-filling network approach, along with WebGL visualization software for 3d datasets that we developed to help us understand and improve our reconstruction results.
  - leemailll 8y ago
    What you quoted is not about synapse strength

leemailll 8y ago

No, EM can’t offer this type of info. If you are interested take a look at C. Elegans. Done for years but this part is still not clear

davi 8y ago

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=183714&xp=504613&tool=navigator&sid0=2&s0=7 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 8y ago
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 8y ago
  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 8y ago
    Thanks. Can you recommend any books on these topics?