Comment author:davidad
31 October 2011 09:46:47AM
30 points
[-]
That's me. In short form, my justification for working on such a project where many have failed before me is:
The "connectome" of C. elegans is not actually very helpful information for emulating it. Contrary to popular belief, connectomes are not the biological equivalent of circuit schematics. Connectomes are the biological equivalent of what you'd get if you removed all the component symbols from a circuit schematic and left only the wires. Good luck trying to reproduce the original functionality from that data.
What you actually need is to functionally characterize the system's dynamics by performing thousands of perturbations to individual neurons and recording the results on the network, in a fast feedback loop with a very very good statistical modeling framework which decides what perturbation to try next.
With optogenetic techniques, we are just at the point where it's not an outrageous proposal to reach for the capability to read and write to anywhere in a living C. elegans nervous system, using a high-throughput automated system. It has some pretty handy properties, like being transparent, essentially clonal, and easily transformed. It also has less handy properties, like being a cylindrical lens, being three-dimensional at all, and having minimal symmetry in its nervous system. However, I am optimistic that all these problems can be overcome by suitably clever optical and computational tricks.
I'm a disciple of Kurzweil, and as such I'm prone to putting ridiculously near-future dates on major breakthroughs. In particular, I expect to be finished with C. elegans in 2-3 years. I would be Extremely Suprised, for whatever that's worth, if this is still an open problem in 2020.
Comment author:Sickle_eye
16 January 2012 02:27:30PM
2 points
[-]
Ha, I'll keep an eye out for your publications. I'm particularly interested at the distance you'll have to go in gathering data, and what will you be able to make out of what is known. I expect that scans aiming for connectome description contain some neuron type data already due to morphological differences in neurons. I don't know what sets of sensors are used for those scans, but maybe getting a broader spectrum could provide clues as to what neuron types occupy which space inside the connectome. SEM can, after all, determine the chemical composition of materials, can't it?. As-is, this seems a pretty neckbreaking undertaking, although I wish you the best of luck.
Predictions for silicon-based processors are pretty optimistic as well - Intel aims to achieve 10nm by 2014, and similar date is pushed by nVidia. Past that date we may see some major leaps in available technology (or not), and development of multi-processor computation algorithms is finally gaining momentum since Von Neumann's Big Mistake.
Maybe the Kurzweil's 2025 date for brain emulation is a bit overoptimistic, but I don't expect that to take much longer. I do think that the first dozen of successful neural structure emulations will become a significant breakthrough, and we'll see a rapid expansion similar to that in genetic sciences not so long ago.
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That's me. In short form, my justification for working on such a project where many have failed before me is:
I'm a disciple of Kurzweil, and as such I'm prone to putting ridiculously near-future dates on major breakthroughs. In particular, I expect to be finished with C. elegans in 2-3 years. I would be Extremely Suprised, for whatever that's worth, if this is still an open problem in 2020.
Ha, I'll keep an eye out for your publications. I'm particularly interested at the distance you'll have to go in gathering data, and what will you be able to make out of what is known. I expect that scans aiming for connectome description contain some neuron type data already due to morphological differences in neurons. I don't know what sets of sensors are used for those scans, but maybe getting a broader spectrum could provide clues as to what neuron types occupy which space inside the connectome. SEM can, after all, determine the chemical composition of materials, can't it?. As-is, this seems a pretty neckbreaking undertaking, although I wish you the best of luck.
In other news, there is, luckily, more and more work in this field: http://www.theverge.com/2011/11/16/2565638/mit-neural-connectivity-silicon-synapse
Predictions for silicon-based processors are pretty optimistic as well - Intel aims to achieve 10nm by 2014, and similar date is pushed by nVidia. Past that date we may see some major leaps in available technology (or not), and development of multi-processor computation algorithms is finally gaining momentum since Von Neumann's Big Mistake.
Maybe the Kurzweil's 2025 date for brain emulation is a bit overoptimistic, but I don't expect that to take much longer. I do think that the first dozen of successful neural structure emulations will become a significant breakthrough, and we'll see a rapid expansion similar to that in genetic sciences not so long ago.