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OpenWorm – A computational model of C. elegans worm

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Re: OpenWorm – A computational model of C. elegans worm

#31
I was lucky enough to do some programming work, very many years ago, in the 1990s, in the laboratory of Ralph Siegel (https://en.wikipedia.org/wiki/Ralph_Siegel_(scientist)), who among other things worked on this type of worm connectome models. He used the Hodgkin-Huxley equations to simulate neuron responses on the connectome. The Hodkin-Huxley model, as someone explained to me, is kind of like modeling a human leg as three rigid blocks connected by hinges - it's enough to be useful in many models, but of course it's not a full description. Also, it may not the right model for worm neurons, because worm neurons are non-spiking, and the HH equations describe neurons that produce trains of spikes; they exist in more complicated nervous systems. The HH equations are used in simulations because it's the mathematical model we have, and it seems that they're still used by the OpenWorm project. (I am not very sure about properties of worm neurons, I heard about this a long time ago and the information may be out of date).

I think it's great that this work is still going on, it may produce insights about functioning of nervous systems. But the difficulties are fierce, and we're making very slow and difficult progress in an immense unknown area.

Re: OpenWorm – A computational model of C. elegans worm

#32

As an amateur scientist with an interest in neurodegenerative diseases, I am interested in neurons simulations. As a model with neurons and muscles, Openworm looks very interesting for application in ALS (Lou Gherig's disease).

Have a look to Neuron / Core neuron (https://www.neuron.yale.edu/neuron/ / https://github.com/BlueBrain/CoreNeuron), Nest (https://www.nest-simulator.org/) and for the ultra low level STEPS (https://github.com/CNS-OIST/STEPS). For most computational neuroscientist, they are the bread and butter.

Re: OpenWorm – A computational model of C. elegans worm

#33

This project has existed for something like a decade. Does anyone know if there was any progress with it in the last few years?

I did my Ph.D. in computational neuroscience (2020 grad).

This project is often used to joke about the limitation of computational modelling of nervous system. If you can't compute the behavious of an effing worm with mere ~300 neurons, whats the point of all hot-air around connectomics (mapping connections of the brain). Connectomics used to be a big word when I started my Ph.D.. The apologists are always like, "real neuron is way too complicated!".

IMHO, chemical computations are often over-looked in neural "computation" communities which are extremely hard to model. Forgetting modelling, we don't know reaction parameters of most proteins and other molecules involved. Electrical side of computation is easy to measure and one can understand why we started with it. There are a thousands types of proteins even in a small structure such as synapse, and individual protein can implement interesting non-linear computation. E.g. CaMKII can implement and bistable switch (flip-flop) and thus store 1-bit of memory using just a few molecules (the real story is a much more complicated).

https://youtu.be/vJBUaS0r9IU

Re: OpenWorm – A computational model of C. elegans worm

#34
I love it when anything Caenorhabditis elegans (C. Elegans) related pops up because this little biological organism sits at this beautiful intersection between technology and biology and philosophy. The successful emulation of C. Elegans would represent a concrete step towards whole brain emulation and all the transhuman and ethical and moral quandaries that would bring. The general idea is that the human brain has billions of neurons, Elegans has hundreds (and we've had them mapped since 1986). If one can successfully "upload" Elegans, then humans are just a matter of scale.

However, it should be noted that the field, and specifically this line of research, hasn't produced much in the way of results in 10+ years. University of Oregon planned (though I can't tell if they ever developed) NemaSys[0] ~1997. OpenWorm has been exploring this since 2011. Project Nemaload explored it a bit from 2011-2013.[1] But each project ran into three problems:

- Knowing the connections isn't enough. We also need to know the weights and thresholds. We don't know how to read them from a living worm.[2]

- C. elegans is able to learn by changing the weights. We don't know how weights and thresholds are changed in a living worm.[2]

- Funding [3]

The best we can do is modeling a generic worm - pretraining and running the neural network with fixed weights. Thus, no worm is "uploaded" because we can't read the weights, and these simulations are far from realistic because they are not capable of learning. Hence, it's merely a boring artificial neural network, not a brain emulation. Relevant neural recording technologies are needed to collect data from living worms, but they remain undeveloped (but in progress?[4][5][6]), and the funding simply isn't there.

OpenWorm got the idea to plug their connectome into a Lego robot[7] and got it to exhibit the tap-withdrawal behavior of the nematode, but it had technical limitations preventing easy modification of the connectome or introduction of new models of neural dynamics. JHU Applied Physics Lab extended the work by using a basic integrate and fire model to simulate the neurons and assigned weights by determining the proportion to the total number of synapses the two neurons on either side of the synapses shared and in the end got the simulated worm to reverse direction when bumping into walls.[8] At this point, humanity seems to have abandoned emulated worm driven mechanisms which is honestly kind of a loss.

There's no real ending to this comment. Love this project, loves what it stands for, looking forward to seeing progress in this field. And a lot of this information was pulled from this blog post[9] which was also mentioned in the comments somewhere.

[0] https://web.archive.org/web/20030115124331/http://www.csi.uo...

[1] https://github.com/nemaload

[2] https://www.jefftk.com/p/we-havent-uploaded-worms

[3] https://www.quora.com/Is-Larry-Page-funding-any-neuroscience...

[4] https://arxiv.org/pdf/2109.10474.pdf

[5] https://onlinelibrary.wiley.com/doi/10.1002/cyto.a.24483

[6] https://www.sciencedirect.com/science/article/pii/S095943882...

[7] https://www.cnn.com/2015/01/21/tech/mci-lego-worm/

[8] https://ccneuro.org/2018/proceedings/1149.pdf

[9] https://www.lesswrong.com/posts/mHqQxwKuzZS69CXX5/whole-brai...

Re: OpenWorm – A computational model of C. elegans worm

#35
post #3

Earlier quoted context omitted.

How can we exactly replicate something if we don't even know all the laws of physics?

The same way we can simulate the movements of the planets - it will never be exact, but the better we understand it, the more precisely we can simulate it

Well the question asked if it was exact. I pointed out why it can't be.

Re: OpenWorm – A computational model of C. elegans worm

#36
post #3

Earlier quoted context omitted.

How can we exactly replicate something if we don't even know all the laws of physics?

This is a fundamentally flawed way of questionning, "knowing all the laws of physics" is probably impossible to achieve, but we still produce accurate predictions for a lot of phenomena. You can see that we do in fact "replicate" (predict would be a more proper term) things despite not knowing all the laws of physics: weather, movement of the stars, cooking time for a browned piece of bread...

I was replying to someone asking if it was "exact"… and no it isn't… You listing a bunch of simulations, that are notoriously not 100% correct proves my point, thanks.

Re: OpenWorm – A computational model of C. elegans worm

#37
post #20

Earlier quoted context omitted.

This. Submarines don't swim like fish, airplanes don't fly like birds and cars don't run like gepards. Edit: I am surprised at the downvotes. In general, we learn from the nature, but aping it usually proved too difficult and often unpractical at the same time. Do we really want to replicate worm intelligence for practical purposes, or do we want something different? I would say that a machine which can, say, analyze…

And for some reason it is because somehow life is not able the produce rotating axles?

Not only, it's also because of the square/cube law making it impossible to have a 50 ton flyer that flies in the same manner as a 5 kg flyer, you can't simply scale things up.

Re: OpenWorm – A computational model of C. elegans worm

#39
post #32

As an amateur scientist with an interest in neurodegenerative diseases, I am interested in neurons simulations. As a model with neurons and muscles, Openworm looks very interesting for application in ALS (Lou Gherig's disease).

Have a look to Neuron / Core neuron ( https://www.neuron.yale.edu/neuron/ / https://github.com/BlueBrain/CoreNeuron ), Nest ( https://www.nest-simulator.org/ ) and for the ultra low level STEPS ( https://github.com/CNS-OIST/STEPS ). For most computational neuroscientist, they are the bread and butter.

Thanks!
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