3 ms·

This, to me, seems incredible stuff. Can someone with some knowledge of the field point out if this is really ground-breaking?

aurellem 8y ago
Yes, this is an important advance in the field. Google's been working on this for the past few years after convincing Viren Jain (https://www.janelia.org/our-research/former-labs/jain-lab https://www.janelia.org/our-research/former-labs/jain-lab) to leave Janelia and perfect this technology. Very cool stuff! Even as early as two years ago, it generally took a grad student months to years of work to manually reconstruct 50-100 neurons (see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4844839/); https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4844839/); now this same process can be done in virtually no time at all. Expect to see several more papers in the future involving reconstructions of thousands to tens of thousands of neurons, instead of the hundreds we've been seeing. Exciting times!
- legatus 8y ago
  Thanks for the response! I think the link you provided includes the ");" at the end, leading to an error page. Removing ");" leads to the article I think you wanted to mention. Anyway am I correct in saying this may allow research to analyze bigger and bigger neural networks (the biological ones)? I remember OpenWorm (http://openworm.org/science.html http://openworm.org/science.html) which was able to recreate virtually the nematode's brain thanks to a few "maps" of its brain. Could this technology (coupled with the improvements that will come in the next years) allow something of the OpenWorm kind with more and more complex organisms?
  - saltcured 8y ago
    To really extract networks, you would need to either image synapses (very, very difficult since they are sub-micron sizes) to determine how cells connect, or image something like calcium potential to infer a circuit of active neurons as a very sparse subset of a larger set of observed cells during a particular kind of neural activity.
    - legatus 8y ago
      The paper (available at https://sci-hub.tw/https://www.nature.com/articles/s41592-018-0049-4 https://sci-hub.tw/https://www.nature.com/articles/s41592-01...) says that the part of the zebra finch brain analyzed had a resolution of 9 x 9 x 20 nanometers. If I'm reading it correctly, should they not be able to analyze synapses, too? At that resolution, shouldn't synapses have been imaged too?
      - jmrko 8y ago
        That's correct - I imaged the volume and we extracted the synapses before (https://www.nature.com/articles/nmeth.4206 https://www.nature.com/articles/nmeth.4206).
      - deleted 8y ago
        [deleted]
    - jmrko 8y ago
      One of the authors here; Imaging synapses is really no problem with electron microscopy resolution. In fact, you can see automatically extracted synapses (little spheres) in the video of the blog post, this was done a year earlier already!
      - saltcured 8y ago
        Oops, sorry, I have been talking to folks doing en vivo fluorescent imaging and didn't notice that this was electron microscopy! Not only is the resolution a lot worse for optics, but I understand that the signal to noise ratio is much lower when avoiding destructive imaging methods.

aurellem 8y ago

Yes, this is an important advance in the field. Google's been working on this for the past few years after convincing Viren Jain (https://www.janelia.org/our-research/former-labs/jain-lab https://www.janelia.org/our-research/former-labs/jain-lab) to leave Janelia and perfect this technology. Very cool stuff! Even as early as two years ago, it generally took a grad student months to years of work to manually reconstruct 50-100 neurons (see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4844839/); https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4844839/); now this same process can be done in virtually no time at all. Expect to see several more papers in the future involving reconstructions of thousands to tens of thousands of neurons, instead of the hundreds we've been seeing. Exciting times!

legatus 8y ago
Thanks for the response! I think the link you provided includes the ");" at the end, leading to an error page. Removing ");" leads to the article I think you wanted to mention. Anyway am I correct in saying this may allow research to analyze bigger and bigger neural networks (the biological ones)? I remember OpenWorm (http://openworm.org/science.html http://openworm.org/science.html) which was able to recreate virtually the nematode's brain thanks to a few "maps" of its brain. Could this technology (coupled with the improvements that will come in the next years) allow something of the OpenWorm kind with more and more complex organisms?
- saltcured 8y ago
  To really extract networks, you would need to either image synapses (very, very difficult since they are sub-micron sizes) to determine how cells connect, or image something like calcium potential to infer a circuit of active neurons as a very sparse subset of a larger set of observed cells during a particular kind of neural activity.
  - legatus 8y ago
    The paper (available at https://sci-hub.tw/https://www.nature.com/articles/s41592-018-0049-4 https://sci-hub.tw/https://www.nature.com/articles/s41592-01...) says that the part of the zebra finch brain analyzed had a resolution of 9 x 9 x 20 nanometers. If I'm reading it correctly, should they not be able to analyze synapses, too? At that resolution, shouldn't synapses have been imaged too?
    - jmrko 8y ago
      That's correct - I imaged the volume and we extracted the synapses before (https://www.nature.com/articles/nmeth.4206 https://www.nature.com/articles/nmeth.4206).
    - deleted 8y ago
      [deleted]
  - jmrko 8y ago
    One of the authors here; Imaging synapses is really no problem with electron microscopy resolution. In fact, you can see automatically extracted synapses (little spheres) in the video of the blog post, this was done a year earlier already!
    - saltcured 8y ago
      Oops, sorry, I have been talking to folks doing en vivo fluorescent imaging and didn't notice that this was electron microscopy! Not only is the resolution a lot worse for optics, but I understand that the signal to noise ratio is much lower when avoiding destructive imaging methods.