5 ms·

No way. From what I've understood, we are so far from understanding even how a single neuron works. There's still plenty of debate about that.

staticassertion 5y ago
I agree that this seems farfetched. At the same time, I don't think we need to understand how the brain works in order to mimic or copy it, right? At a somewhat absurd level, we give birth to humans with brains without understanding brains. The goal here seems to be to start by copying it without understanding in order to gain understanding. AFAIK we already simulate brains of silk worms or some such thing?
- deleted 5y ago
  [deleted]
- falcor84 5y ago
  Yeah, agreed. I think it's a bit like working with a legacy system, where you might begin by testing and measuring its interactions with external interfaces, and then can start to gradually replace pieces with new components.
- spywaregorilla 5y ago
  > AFAIK we already simulate brains of silk worms or some such thing? I'm pretty sure OpenWorm has not achieved its goal. My take on this would be, sure, copying it is an important step, but they don't know to copy it, so it won't work.
- tsimionescu 5y ago
  > AFAIK we already simulate brains of silk worms or some such thing? There is research into mapping the complete neural structure of a nematode worm called C. elegans [0] - one of the simplest known organisms that has some kind of a nervous system (the entire worm has 959 cells for hermaphrodite individuals, or 1035 for males; of these, 302 are neurons - and yes, this is not a typo, these are not hundreds or thousands of cells, just cells - that's how tiny it is). Its entire nervous system has been mapped out, including all connections, in [0]. Note that its neural cells are not like mammal neurons, they lack many of the known processes present in even a single mammal neuron. However, the project to simulate this simplest of organisms, OpenWorm [1], has not yet achieved its goals (which is also somewhat reduced - they only intend to simulate the motor system initially, not the entire organism). Silkworms (which are moths) are waaaay beyond any imaginable simulation capability at the moment. [0] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889226/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889226/ [1] https://github.com/openworm/OpenWorm/milestones https://github.com/openworm/OpenWorm/milestones
  - staticassertion 5y ago
    Right, I was just bringing that up as an example of simulating without understanding. The paper is talking about taking another approach. Whether it will work or not is not something I could comment on. Another example is how we have a very imperfect model for the universe, and yet we use our models to make strikingly accurate predictions. Huge gaps in our knowledge exist, but that doesn't stop us from using approximations to do interesting things.
    - tsimionescu 5y ago
      > Right, I was just bringing that up as an example of simulating without understanding. But that's just it - first they spent some time understanding how the system works,painstakingly mapping out each connection, the role of each individual cell (literally), they studied the chemistry inside each neural cell etc. The simulation effort started after all of this was done. If anything, I would say OpenWorm is a counter-example to the idea that you can simulate such a system without understanding it. Similarly, with our model of the universe, while gaps exist, the extent of those gaps and approximations is mostly known, and the areas affected by those gaps are exactly where we can't make predictions (e.g. the internal structure of a black hole). Not to mention, we had a massive piece of good luck there: it turns out that particles are described by linear equations, which have extremely nice properties for approximations. Already with GR we are in much worse territory with it's nonlinear equations, but at least we understand these well enough to create some linear approximations - or so we think.
- boxed 5y ago
  Simulating without understanding isn't actually a thing. You neeed to know what to simulate and what to ignore. For example: do we need to simulate all the DNA transcription to make a virtual neuron? Currently this is unknown. And if it is required it's pretty much game over already. I don't believe you need that level of fidelity but that's more of a hope than a scientific standpoint.
  - kwhitefoot 5y ago
    > You neeed to know what to simulate and what to ignore. And often the fastest and most economical way to find out is to try doing it. Also simulations need not be perfect to be useful. I spent a large fraction of my life writing object oriented simulations of transformers. We simplified everything (reduced detail, reduced number of dimensions, rules of thumb where there was no analytical formula) but still succeeded in designing better transformers than before. The next generation will be more precise and even more useful but you can't always get there in one jump.
LeifCarrotson 5y ago
Biology (and, indeed, physics) contains fractal levels of complexity. The existence of debate does not mean that we don't understand it well enough to mimic it. At one time, people had no idea how the brain worked at all. Now we know that the brain is a collection of neurons, special cells which have filaments called an axon and dendrites that extend from it to other neurons at junctions we call synapses. At these synapses, electrochemical signals are transmitted to and from other neurons. When a neuron receives certain signals, it may transmit that signal on to other neurons. That's basically the Anatomy 101 chapter on the nervous system, and has been pretty well established for about a century. It's true that we're constantly learning new things about diseases that affect the function of the nervous system. There remains some debate on how exactly neurons arrange themselves, repair themselves, and change. We're still investigating internal computations within the dendrites to see how those work to decide when to propagate a signal or not. The signals are analog in some ways, but mostly digital 'all or nothing' responses, there's time coding, different types of discharge patterns...fractal complexity. If you set the goalposts at a comprehensive understanding of every bit of trivial minutiae that exists in the human body, yeah, we are (and probably will always be) far off. If you just want to predict the function of a nematode worm with 302 neurons, observing that if you engage this particular set of sensory neurons, then these few hundred synapses are activated with this pattern of impulses, and soon those other motor neurons are stimulated and the worm curls in that direction...that seems entirely within the realm of possibility. In my opinion, the goalposts ought to be "A better understanding than what we have today". We'll reach them by tomorrow, and move them forward again!
aperrien 5y ago
So, I keep reading responses such as this on the subject of neuron/brain emulation, and I have a question to ask back. Is it possible to understand a neuron at all? It appears that we have some understanding, given that we can decode some of the electrical and chemical signals coming from them and to them, but it seems that the zeitgeist is that these things are inherently impossible to understand. If so, as a layperson why waste the resources trying to advance this branch of science? (Note I personally fully support advancing this branch of science.) Why not spend the effort on something with positive tangible results, like space travel or clean power?
- BrianOnHN 5y ago
  I'd say a single neuron should be understandable given that the network effects DO NOT have sufficient impact. Given that "sufficient impact", then the "system understanding itself" issue arises. However, if you believe the neuron is the same as the neuron in the worm, then the concept of how it works should (by my best guess and nothing else) be adequately simple for human understanding.
- eminence32 5y ago
  > Why not spend the effort on something with positive tangible results, like space travel or clean power? Effort/interest is not really fungible or spendable like this. People work and study on the things that are interesting to them. We can't just flip a switch to get everyone who's researching brains to transition to researching space travel.
- zyngaro 5y ago
  Why do you think these things are impossible to understand? Serious question
  - aperrien 5y ago
    I do not think that they are. However, whenever this topic comes up, there are people who immediately jump out and state that is basically is, simply because we don't know enough about the underlying science yet. Which is strange, as studying the underlying science to understand the situation is exactly what we should be doing... It's just so backwards, and it confuses me.
inasio 5y ago
There's a fair bit that is well understood, specifically the chemical processes that drive the signals (and that are present in many other types of cells), and there are mathematical models that have been tested in-vivo and reasonably replicate some dynamics (for example the Hodgkin-Huxley model). But neurons are indeed complicated, and there are a lot of them...
- deleted 5y ago
  [deleted]

staticassertion 5y ago

I agree that this seems farfetched. At the same time, I don't think we need to understand how the brain works in order to mimic or copy it, right? At a somewhat absurd level, we give birth to humans with brains without understanding brains. The goal here seems to be to start by copying it without understanding in order to gain understanding. AFAIK we already simulate brains of silk worms or some such thing?

deleted 5y ago
[deleted]
falcor84 5y ago
Yeah, agreed. I think it's a bit like working with a legacy system, where you might begin by testing and measuring its interactions with external interfaces, and then can start to gradually replace pieces with new components.
spywaregorilla 5y ago
> AFAIK we already simulate brains of silk worms or some such thing? I'm pretty sure OpenWorm has not achieved its goal. My take on this would be, sure, copying it is an important step, but they don't know to copy it, so it won't work.
tsimionescu 5y ago
> AFAIK we already simulate brains of silk worms or some such thing? There is research into mapping the complete neural structure of a nematode worm called C. elegans [0] - one of the simplest known organisms that has some kind of a nervous system (the entire worm has 959 cells for hermaphrodite individuals, or 1035 for males; of these, 302 are neurons - and yes, this is not a typo, these are not hundreds or thousands of cells, just cells - that's how tiny it is). Its entire nervous system has been mapped out, including all connections, in [0]. Note that its neural cells are not like mammal neurons, they lack many of the known processes present in even a single mammal neuron. However, the project to simulate this simplest of organisms, OpenWorm [1], has not yet achieved its goals (which is also somewhat reduced - they only intend to simulate the motor system initially, not the entire organism). Silkworms (which are moths) are waaaay beyond any imaginable simulation capability at the moment. [0] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889226/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889226/ [1] https://github.com/openworm/OpenWorm/milestones https://github.com/openworm/OpenWorm/milestones
- staticassertion 5y ago
  Right, I was just bringing that up as an example of simulating without understanding. The paper is talking about taking another approach. Whether it will work or not is not something I could comment on. Another example is how we have a very imperfect model for the universe, and yet we use our models to make strikingly accurate predictions. Huge gaps in our knowledge exist, but that doesn't stop us from using approximations to do interesting things.
  - tsimionescu 5y ago
    > Right, I was just bringing that up as an example of simulating without understanding. But that's just it - first they spent some time understanding how the system works,painstakingly mapping out each connection, the role of each individual cell (literally), they studied the chemistry inside each neural cell etc. The simulation effort started after all of this was done. If anything, I would say OpenWorm is a counter-example to the idea that you can simulate such a system without understanding it. Similarly, with our model of the universe, while gaps exist, the extent of those gaps and approximations is mostly known, and the areas affected by those gaps are exactly where we can't make predictions (e.g. the internal structure of a black hole). Not to mention, we had a massive piece of good luck there: it turns out that particles are described by linear equations, which have extremely nice properties for approximations. Already with GR we are in much worse territory with it's nonlinear equations, but at least we understand these well enough to create some linear approximations - or so we think.
boxed 5y ago
Simulating without understanding isn't actually a thing. You neeed to know what to simulate and what to ignore. For example: do we need to simulate all the DNA transcription to make a virtual neuron? Currently this is unknown. And if it is required it's pretty much game over already. I don't believe you need that level of fidelity but that's more of a hope than a scientific standpoint.
- kwhitefoot 5y ago
  > You neeed to know what to simulate and what to ignore. And often the fastest and most economical way to find out is to try doing it. Also simulations need not be perfect to be useful. I spent a large fraction of my life writing object oriented simulations of transformers. We simplified everything (reduced detail, reduced number of dimensions, rules of thumb where there was no analytical formula) but still succeeded in designing better transformers than before. The next generation will be more precise and even more useful but you can't always get there in one jump.

LeifCarrotson 5y ago

Biology (and, indeed, physics) contains fractal levels of complexity. The existence of debate does not mean that we don't understand it well enough to mimic it. At one time, people had no idea how the brain worked at all. Now we know that the brain is a collection of neurons, special cells which have filaments called an axon and dendrites that extend from it to other neurons at junctions we call synapses. At these synapses, electrochemical signals are transmitted to and from other neurons. When a neuron receives certain signals, it may transmit that signal on to other neurons. That's basically the Anatomy 101 chapter on the nervous system, and has been pretty well established for about a century. It's true that we're constantly learning new things about diseases that affect the function of the nervous system. There remains some debate on how exactly neurons arrange themselves, repair themselves, and change. We're still investigating internal computations within the dendrites to see how those work to decide when to propagate a signal or not. The signals are analog in some ways, but mostly digital 'all or nothing' responses, there's time coding, different types of discharge patterns...fractal complexity. If you set the goalposts at a comprehensive understanding of every bit of trivial minutiae that exists in the human body, yeah, we are (and probably will always be) far off. If you just want to predict the function of a nematode worm with 302 neurons, observing that if you engage this particular set of sensory neurons, then these few hundred synapses are activated with this pattern of impulses, and soon those other motor neurons are stimulated and the worm curls in that direction...that seems entirely within the realm of possibility. In my opinion, the goalposts ought to be "A better understanding than what we have today". We'll reach them by tomorrow, and move them forward again!

aperrien 5y ago

So, I keep reading responses such as this on the subject of neuron/brain emulation, and I have a question to ask back. Is it possible to understand a neuron at all? It appears that we have some understanding, given that we can decode some of the electrical and chemical signals coming from them and to them, but it seems that the zeitgeist is that these things are inherently impossible to understand. If so, as a layperson why waste the resources trying to advance this branch of science? (Note I personally fully support advancing this branch of science.) Why not spend the effort on something with positive tangible results, like space travel or clean power?

BrianOnHN 5y ago
I'd say a single neuron should be understandable given that the network effects DO NOT have sufficient impact. Given that "sufficient impact", then the "system understanding itself" issue arises. However, if you believe the neuron is the same as the neuron in the worm, then the concept of how it works should (by my best guess and nothing else) be adequately simple for human understanding.
eminence32 5y ago
> Why not spend the effort on something with positive tangible results, like space travel or clean power? Effort/interest is not really fungible or spendable like this. People work and study on the things that are interesting to them. We can't just flip a switch to get everyone who's researching brains to transition to researching space travel.
zyngaro 5y ago
Why do you think these things are impossible to understand? Serious question
- aperrien 5y ago
  I do not think that they are. However, whenever this topic comes up, there are people who immediately jump out and state that is basically is, simply because we don't know enough about the underlying science yet. Which is strange, as studying the underlying science to understand the situation is exactly what we should be doing... It's just so backwards, and it confuses me.

inasio 5y ago

There's a fair bit that is well understood, specifically the chemical processes that drive the signals (and that are present in many other types of cells), and there are mathematical models that have been tested in-vivo and reasonably replicate some dynamics (for example the Hodgkin-Huxley model). But neurons are indeed complicated, and there are a lot of them...

deleted 5y ago
[deleted]