I wrote to Ken Hayworth who is a neuroscience researcher working on scanning and interested in whole brain emulation, and he wrote back:
I have not read much on the simulation efforts on C. elegans but I have talked several times to one of the chief scientists who collected the original connectome data and has been continuing to collect more electron micrographs (David Hall, in charge of www.wormatlas.org). He has said that the physiological data on neuron and synapse function in C. elegans is really limited and suggests that no one spend time simulating the worm using the existing datasets because of this. I.e. we may know the connectivity but we don't know even the sign of many synapses.
If you look at a system like the retina I would argue that we already have quite good models of its functioning and thus it is a perfect ground for testing emulation from known connectivity.
So the short answer is that I think it may be far easier to emulate a well characterized and mapped part of the mammalian brain than it is to emulate the worm despite its smaller size.
Further exchange:
Me:
So even a nanoscale SEM pass over the whole brain wouldn't be enough unless we could find some way to visually read off the sign of a synapse, perhaps with a stain, perhaps by learning what different types of neurons look like, perhaps by something not yet discovered?
Hayworth:
That is right, but those tell tale signs are well known for certain systems (like the retina) already, and will become more clear for others once large scale em imaging combined with functional recording becomes routine.
Being able to treat the pattern of someone's brain as software to be run on a computer, perhaps in parallel or at a large speedup, would have a huge impact, both socially and economically. Robin Hanson thinks it is the most likely route to artificial intelligence. Anders Sandberg and Nick Bostrom of the Future Of Humanity Institute created out a roadmap for whole brain emulation in 2008, which covers a huge amount of research in this direction, combined with some scale analysis of the difficulty of various tasks.
Because the human brain is so large, and we are so far from having the technical capacity to scan or emulate it, it's difficult to evaluate progress. Some other organisms, however, have much smaller brains: the nematode C. elegans has only 302 cells in its entire nervous system. It is extremely well studied and well understood, having gone through heavy use as a research animal for decades. Since at least 1986 we've known the full neural connectivity of C. elegans, something that would take decades and a huge amount of work to get for humans. At 302 neurons, simulation has been within our computational capacity for at least that long. With 25 years to work on it, shouldn't we be able to 'upload' a nematode by now?
Reading through the research, there's been some work on modeling subsystems and components, but I only find three projects that have tried to integrate this research into a complete simulation: the University of Oregon's NemaSys (~1997), the Perfect C. elegans Project (~1998), and Hiroshima University's Virtual C. Elegans project (~2004). The second two don't have web pages, but they did put out papers: [1], [2], [3].
Another way to look at this is to list the researchers who seem to have been involved with C. elegans emulation. I find:
This seems like a research area where you have multiple groups working at different universities, trying for a while, and then moving on. None of the simulation projects have gotten very far: their emulations are not complete and have some pieces filled in by guesswork, genetic algorithms, or other artificial sources. I was optimistic about finding successful simulation projects before I started trying to find one, but now that I haven't, my estimate of how hard whole brain emulation would be has gone up significantly. While I wouldn't say whole brain emulation could never happen, this looks to me like it is a very long way out, probably hundreds of years.
Note: I later reorganized this into a blog post, incorporating some feed back from these comments.
Papers:
[1] The Perfect C. elegans Project: An Initial Report (1998)
[2] A Dynamic Body Model of the Nematode C. elegans With Neural Oscillators (2005)
[3] A model of motor control of the nematode C. elegans with neuronal circuits (2005)
[4] Robust spacial navigation in a robot inspired by C. elegans (1998)
[5] Neural network models of chemotaxis in the nematode C. elegans (1997)
[6] Chemotaxis control by linear recurrent networks (1998)
[7] Computational rules for chemotaxis in the nematode C. elegans (1999)
[8] A Dynamic Network Simulation of the Nematode Tap Withdrawl Circuit: Predictions Concerning Synaptic Function Using Behavioral Criteria (1996)
[9] A Neural Network Model of Caenorhabditis Elegans: The Circuit of Touch Sensitivity (1997)