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Is it simulated to the level where you could give it some visual stimulus and observe the actions it is trying to take? Could it be wired to a remote robotic in

Is it simulated to the level where you could give it some visual stimulus and observe the actions it is trying to take? Could it be wired to a remote robotic insect and control it in real time? I've no idea how detailed these simulation projects and if we are months or decades away from doing what I mentioned

yyyk 4y ago
>Is it simulated to the level where you could give it some visual stimulus and observe the actions it is trying to take? No way. First, this mapping doesn't tell us how the synapses are regulated - if we could 'run' this the weights would stay fixed forever and that's not how a brain works. Second, there must be some neurons dedicated to chemical management, and they'd go haywire unless you found a way to deal with them. It's possible the hardware/software is so intertwined it can't be separated. Or maybe it's just complex, regardless the mapping is of limited use here. Third, you're assuming that the synapses/axons are the only thing that matters. It may well be this is true, but having other processes being involved has not yet been entirely ruled out. If they are, the mapping is incomplete. Lastly, we don't have the computational ability just yet to simulate even the mapping itself.
- BurningFrog 4y ago
  Another approach is to try emulating different models of neurons/synapses/etc, and find models that act similarity to the real organism. Investing the search space, to invent a name, can sometimes be very powerful.
- falcor84 4y ago
  >Lastly, we don't have the computational ability just yet to simulate even the mapping itself. Could you please explain why not? 548,000 synapses sounds entirely feasible to me.
  - yyyk 4y ago
    Neurons and synapses are incredibly complex. Think you're emulating over 3,000 heterogeneous cores with over half a million links while communication must be low-latency-ish. A third of the links seem to join other links and we don't even know what that does. If there's computation there we'll need even more cores.
    - xyproto 4y ago
      It could be simulated slowly at first.
      - coldtea 4y ago
        That requires we know how each node behaves and the kind of inputs it has, which we're very very far off from...
      - lossolo 4y ago
        To simulate something you need to first know how it works and know all the relevant interactions, this is something that we currently do not understand. Neurons are not equivalent of neural networks we use in computers, they are A LOT more complex with whole groups firing the same time and chemicals regulating neurons all the time and whole topology is plastic, it works in a way we can't model or simulate currently. People hugely overestimate our knowledge about brains.
        epgui 4y ago
        I'm a biochemist, and I somewhat disagree with this take. Yes, it's true that modelling just a single cell's interactions with its environments is beyond our capacity. But here we're talking about simulating how a brain reacts to signals at a higher level of abstraction: we're studying an "emergent" phenomenon. We don't need to model molecular interactions, and we absolutely can model this using artificial neural networks. This doesn't mean we'll be able to completely accurately model its behaviour, but we should get a lot closer than many HN commenters seem to believe. Biological neurons don't have magical properties, they just have more side-effects.
  - margorczynski 4y ago
    Wasn't there success in replicating how the neuron modulates a signal with electronics? If we can reproduce the out given any in then that's interchangeable from a system perspective?
- Groxx 4y ago
  For some more context / concrete links: there are ongoing efforts to simulate the C. elegans worm, e.g. https://openworm.org/ https://openworm.org/ , which has ~300 neurons. The actual precision of this model is: nobody knows, because nobody knows precisely what neurons do / what they react to. We know some of it but definitely not all. But, simulating what we do know, you get quite worm-like behavior, despite whatever flaws exist. To get a more perfect simulation, we'd need more perfect knowledge of the chemistry and physics, and lots and lots more computing power. It's something that's continually improving, but a lot of shortcuts have to be made to make it even remotely calculable. That'll always be the case, physics is simply too complicated to both efficiently and accurately simulate.
  - cyberax 4y ago
    OpenWorm is a bad model. To give a computer analogy, you're simulating highly optimized low-level code for Apple ][. That uses all the little hardware-specific tricks and timings to work. A fruit fly brain is a better model to simulate in this regard. It's much more "generic", so there's a hope that we can recapture high-level behavior from it more easily.
    - tsimionescu 4y ago
      > A fruit fly brain is a better model to simulate in this regard. It's much more "generic", so there's a hope that we can recapture high-level behavior from it more easily. This is a completely baseless assumption. It is also moot, since simulating even 300 neurons is beyond our current computational power; simulating 3000 is not going to be possible in the foreseeable future.
      - cutemonster 4y ago
        What makes stimulating 300 that computationally heavy? (Doesn't sound like many?, but I've read that one single neuron needed 100 or so nodes in a deep neural net to simulate. But 300*100 also doesn't sound like many (nodes)?) Edit: some explanations here: https://news.ycombinator.com/item?id=35113498 https://news.ycombinator.com/item?id=35113498 (in this discussion)
- neurohdmi 4y ago
  The first thing you said is correct. To do a proper simulation you would need to gather functional properties of the various cell classes and their synaptic connection, which this study didn't do. (Maybe you can find that information from other lab, I'm not familiar with fly models?) However we definitely have the computational ability to do simulations a fly network. Look at some of the modeling done by the Blue Brain Project or Allen Institute for Brain Science - they do simulations of rat and mice models with hundreds-of-thousands to millions of neurons and exponentially more synapses. 3000 neurons is not that many. If you stuck to non-compartmental point models a 3,000 neuron simulation could probably be ran on a moderately high-end laptop. But as said before, the physical connectome is only part of the information you'd need do any worthwhile simulations.
  - bombolo 4y ago
    But, do we know that they actually model completely accurately?
    - Groxx 4y ago
      We can model some aspects essentially completely - that's basically what this map covers, the "obvious" physical connections. Simplified forms of this can probably be simulated very very quickly. Sometimes that's sufficient. It's not the complete picture though, normally that brain would be in an ever-changing soup of chemicals, which definitely impact behavior... somehow. Simulating that, and even knowing what might be relevant to simulate, will never be complete. Only incrementally better than previous attempts.
    - neurohdmi 4y ago
      If you're lucky, the system you're trying to simulate has good in-vivo recordings. That way you can compare the in-silco models directly to the real ones using either firing rates, LFPs, or other neuronal dynamic. Unfortunately, most of the time that isn't the case. Trying to simulate a 3000 cells and 500K connections of the fly brain is not a computational problem, it's a knowledge one. If you can find functional properties to build a spiking/rates model, and data to compare it too; then it would be feasible (although a lot of work) to build and run simulations on the model. But without that extra info, and only using the physical connectome, there would be very little reason to try to do so.
- stevenjgarner 4y ago
  Synapses of neurons change over time due to synaptic plasticity. This process is responsible for allowing learning and memory. Synaptic plasticity occurs through a combination of changes in the number of synapses and the strength of those synapses. So these brain maps are like a single frame still image frozen in time taken from a video of the changing connectome.
notfed 4y ago
This article is fluffy. The original research is titled: "A searchable image resource of Drosophila GAL4-driver expression patterns with single neuron resolution. eLife, 2023; 12 DOI: 10.7554/eLife.80660"
gptgpp 4y ago
Man... I just find neural connectomes so depressing. It's like looking at the copper wiring on the motherboard, or the pins of the CPU, when what you really want is the logic from the networked gates (transistors). Yet it seems we are many, many decades away from being able to extract that in any comprehensible or definitive way. I need to stop reading neuroscience articles. There's always big proclamations, Like "the neural circuitry behind arithmetic has been discovered!" then you dig into the meat and it's mostly guesswork and hypothesis based on correlated activity and connectivity, no logic to be seen. This paper did blow my mind though, I hope to see more creative stuff like it: https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627322008066%3Fshowall%3Dtrue https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6?_... pdf here: https://www.cell.com/action/showPdf?pii=S0896-6273%2822%2900806-6 https://www.cell.com/action/showPdf?pii=S0896-6273%2822%2900...
- seesawtron 4y ago
  You should read about the immense criticism this paper attracted after its publication. It was published on the same journal since publishers like a bit of controversy ;) [0] https://www.sciencedirect.com/science/article/abs/pii/S0896627323001137 https://www.sciencedirect.com/science/article/abs/pii/S08966...
  - gptgpp 4y ago
    There's a pdf here if anyone else is interested: https://www.yorku.ca/science/research/schalljd/wp-content/uploads/sites/654/2023/03/Balci-et-al-Monosov-Procyk-2023-NEURON-Response-to-claims-of-sentience-in-a-dish.pdf https://www.yorku.ca/science/research/schalljd/wp-content/up... Yeah all that criticism doesn't go into any detail about actual methodological flaws or issues with the results... It just complains about language and is pretty sanctimonious for such weak and generic citations. Like, those are the sort of citations I'd give as an undergrad and trying to pad a paper to make it seem more authoritative and well established than it is lol. Were any of the criticisms NOT centered around their irresponsible use of language and about the actual methodology and results? How they cultured different neurons to play pong is pretty amazing by itself to me.
moffkalast 4y ago
Not sure if they're at that stage yet, but it's definitely possible and been done before for the elegans worm https://github.com/topics/c-elegans https://github.com/topics/c-elegans They even got a web sim working by now it looks like https://heyseth.github.io/worm-sim/ https://heyseth.github.io/worm-sim/
ar9av 4y ago
The level of detail in insect brain simulations varies, and it may be challenging to simulate it to the level of reacting to visual stimuli. Neural interfaces have been successful in controlling robots, but real-time processing and precision remain a challenge.
abecedarius 4y ago
Good overview of what that sort of thing would take and what was known and unknown: https://www.fhi.ox.ac.uk/brain-emulation-roadmap-report.pdf https://www.fhi.ox.ac.uk/brain-emulation-roadmap-report.pdf (2008. Of course there's been related work since, but I don't know of any attempt to review all the newer stuff together.)

yyyk 4y ago

>Is it simulated to the level where you could give it some visual stimulus and observe the actions it is trying to take? No way. First, this mapping doesn't tell us how the synapses are regulated - if we could 'run' this the weights would stay fixed forever and that's not how a brain works. Second, there must be some neurons dedicated to chemical management, and they'd go haywire unless you found a way to deal with them. It's possible the hardware/software is so intertwined it can't be separated. Or maybe it's just complex, regardless the mapping is of limited use here. Third, you're assuming that the synapses/axons are the only thing that matters. It may well be this is true, but having other processes being involved has not yet been entirely ruled out. If they are, the mapping is incomplete. Lastly, we don't have the computational ability just yet to simulate even the mapping itself.

BurningFrog 4y ago
Another approach is to try emulating different models of neurons/synapses/etc, and find models that act similarity to the real organism. Investing the search space, to invent a name, can sometimes be very powerful.
falcor84 4y ago
>Lastly, we don't have the computational ability just yet to simulate even the mapping itself. Could you please explain why not? 548,000 synapses sounds entirely feasible to me.
- yyyk 4y ago
  Neurons and synapses are incredibly complex. Think you're emulating over 3,000 heterogeneous cores with over half a million links while communication must be low-latency-ish. A third of the links seem to join other links and we don't even know what that does. If there's computation there we'll need even more cores.
  - xyproto 4y ago
    It could be simulated slowly at first.
    - coldtea 4y ago
      That requires we know how each node behaves and the kind of inputs it has, which we're very very far off from...
    - lossolo 4y ago
      To simulate something you need to first know how it works and know all the relevant interactions, this is something that we currently do not understand. Neurons are not equivalent of neural networks we use in computers, they are A LOT more complex with whole groups firing the same time and chemicals regulating neurons all the time and whole topology is plastic, it works in a way we can't model or simulate currently. People hugely overestimate our knowledge about brains.
      - epgui 4y ago
        I'm a biochemist, and I somewhat disagree with this take. Yes, it's true that modelling just a single cell's interactions with its environments is beyond our capacity. But here we're talking about simulating how a brain reacts to signals at a higher level of abstraction: we're studying an "emergent" phenomenon. We don't need to model molecular interactions, and we absolutely can model this using artificial neural networks. This doesn't mean we'll be able to completely accurately model its behaviour, but we should get a lot closer than many HN commenters seem to believe. Biological neurons don't have magical properties, they just have more side-effects.
- margorczynski 4y ago
  Wasn't there success in replicating how the neuron modulates a signal with electronics? If we can reproduce the out given any in then that's interchangeable from a system perspective?
Groxx 4y ago
For some more context / concrete links: there are ongoing efforts to simulate the C. elegans worm, e.g. https://openworm.org/ https://openworm.org/ , which has ~300 neurons. The actual precision of this model is: nobody knows, because nobody knows precisely what neurons do / what they react to. We know some of it but definitely not all. But, simulating what we do know, you get quite worm-like behavior, despite whatever flaws exist. To get a more perfect simulation, we'd need more perfect knowledge of the chemistry and physics, and lots and lots more computing power. It's something that's continually improving, but a lot of shortcuts have to be made to make it even remotely calculable. That'll always be the case, physics is simply too complicated to both efficiently and accurately simulate.
- cyberax 4y ago
  OpenWorm is a bad model. To give a computer analogy, you're simulating highly optimized low-level code for Apple ][. That uses all the little hardware-specific tricks and timings to work. A fruit fly brain is a better model to simulate in this regard. It's much more "generic", so there's a hope that we can recapture high-level behavior from it more easily.
  - tsimionescu 4y ago
    > A fruit fly brain is a better model to simulate in this regard. It's much more "generic", so there's a hope that we can recapture high-level behavior from it more easily. This is a completely baseless assumption. It is also moot, since simulating even 300 neurons is beyond our current computational power; simulating 3000 is not going to be possible in the foreseeable future.
    - cutemonster 4y ago
      What makes stimulating 300 that computationally heavy? (Doesn't sound like many?, but I've read that one single neuron needed 100 or so nodes in a deep neural net to simulate. But 300*100 also doesn't sound like many (nodes)?) Edit: some explanations here: https://news.ycombinator.com/item?id=35113498 https://news.ycombinator.com/item?id=35113498 (in this discussion)
neurohdmi 4y ago
The first thing you said is correct. To do a proper simulation you would need to gather functional properties of the various cell classes and their synaptic connection, which this study didn't do. (Maybe you can find that information from other lab, I'm not familiar with fly models?) However we definitely have the computational ability to do simulations a fly network. Look at some of the modeling done by the Blue Brain Project or Allen Institute for Brain Science - they do simulations of rat and mice models with hundreds-of-thousands to millions of neurons and exponentially more synapses. 3000 neurons is not that many. If you stuck to non-compartmental point models a 3,000 neuron simulation could probably be ran on a moderately high-end laptop. But as said before, the physical connectome is only part of the information you'd need do any worthwhile simulations.
- bombolo 4y ago
  But, do we know that they actually model completely accurately?
  - Groxx 4y ago
    We can model some aspects essentially completely - that's basically what this map covers, the "obvious" physical connections. Simplified forms of this can probably be simulated very very quickly. Sometimes that's sufficient. It's not the complete picture though, normally that brain would be in an ever-changing soup of chemicals, which definitely impact behavior... somehow. Simulating that, and even knowing what might be relevant to simulate, will never be complete. Only incrementally better than previous attempts.
  - neurohdmi 4y ago
    If you're lucky, the system you're trying to simulate has good in-vivo recordings. That way you can compare the in-silco models directly to the real ones using either firing rates, LFPs, or other neuronal dynamic. Unfortunately, most of the time that isn't the case. Trying to simulate a 3000 cells and 500K connections of the fly brain is not a computational problem, it's a knowledge one. If you can find functional properties to build a spiking/rates model, and data to compare it too; then it would be feasible (although a lot of work) to build and run simulations on the model. But without that extra info, and only using the physical connectome, there would be very little reason to try to do so.
stevenjgarner 4y ago
Synapses of neurons change over time due to synaptic plasticity. This process is responsible for allowing learning and memory. Synaptic plasticity occurs through a combination of changes in the number of synapses and the strength of those synapses. So these brain maps are like a single frame still image frozen in time taken from a video of the changing connectome.

notfed 4y ago

This article is fluffy. The original research is titled: "A searchable image resource of Drosophila GAL4-driver expression patterns with single neuron resolution. eLife, 2023; 12 DOI: 10.7554/eLife.80660"

gptgpp 4y ago

Man... I just find neural connectomes so depressing. It's like looking at the copper wiring on the motherboard, or the pins of the CPU, when what you really want is the logic from the networked gates (transistors). Yet it seems we are many, many decades away from being able to extract that in any comprehensible or definitive way. I need to stop reading neuroscience articles. There's always big proclamations, Like "the neural circuitry behind arithmetic has been discovered!" then you dig into the meat and it's mostly guesswork and hypothesis based on correlated activity and connectivity, no logic to be seen. This paper did blow my mind though, I hope to see more creative stuff like it: https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627322008066%3Fshowall%3Dtrue https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6?_... pdf here: https://www.cell.com/action/showPdf?pii=S0896-6273%2822%2900806-6 https://www.cell.com/action/showPdf?pii=S0896-6273%2822%2900...

seesawtron 4y ago
You should read about the immense criticism this paper attracted after its publication. It was published on the same journal since publishers like a bit of controversy ;) [0] https://www.sciencedirect.com/science/article/abs/pii/S0896627323001137 https://www.sciencedirect.com/science/article/abs/pii/S08966...
- gptgpp 4y ago
  There's a pdf here if anyone else is interested: https://www.yorku.ca/science/research/schalljd/wp-content/uploads/sites/654/2023/03/Balci-et-al-Monosov-Procyk-2023-NEURON-Response-to-claims-of-sentience-in-a-dish.pdf https://www.yorku.ca/science/research/schalljd/wp-content/up... Yeah all that criticism doesn't go into any detail about actual methodological flaws or issues with the results... It just complains about language and is pretty sanctimonious for such weak and generic citations. Like, those are the sort of citations I'd give as an undergrad and trying to pad a paper to make it seem more authoritative and well established than it is lol. Were any of the criticisms NOT centered around their irresponsible use of language and about the actual methodology and results? How they cultured different neurons to play pong is pretty amazing by itself to me.

moffkalast 4y ago

Not sure if they're at that stage yet, but it's definitely possible and been done before for the elegans worm https://github.com/topics/c-elegans https://github.com/topics/c-elegans They even got a web sim working by now it looks like https://heyseth.github.io/worm-sim/ https://heyseth.github.io/worm-sim/

ar9av 4y ago

The level of detail in insect brain simulations varies, and it may be challenging to simulate it to the level of reacting to visual stimuli. Neural interfaces have been successful in controlling robots, but real-time processing and precision remain a challenge.

abecedarius 4y ago

Good overview of what that sort of thing would take and what was known and unknown: https://www.fhi.ox.ac.uk/brain-emulation-roadmap-report.pdf https://www.fhi.ox.ac.uk/brain-emulation-roadmap-report.pdf (2008. Of course there's been related work since, but I don't know of any attempt to review all the newer stuff together.)