9 ms·

An adult fruit fly brain has been mapped

594 points by teleforce 2y ago

fennecfoxy 2y ago
Interesting, with all of the BS around LLM training sucking up other peoples' content that something like the economist can base an article off a paper without adding too much more in the way of unique content, just fluff and still lock down access to the content.
tonetegeatinst 2y ago
Datahoarder question but can I download the map of the fly?
- elevatedastalt 2y ago
  [flagged]
  - hackboyfly 2y ago
    [flagged]
- ijxjdffnkkpp 2y ago
  I think that releasing the map on torrent would be a useful idea as well. This fly could end up like the lobsters in Accelerando. In that book the mapped animal is lobsters and they get first mover advantage on some post-scarcity type things. Getting them to the Internet would be a good first step, IMO.
  - rbanffy 2y ago
    I, for one, welcome our new fruit fly overlords.
- dekhn 2y ago
  See the FAQ: https://codex.flywire.ai/faq https://codex.flywire.ai/faq which leads to the API for access: https://codex.flywire.ai/api/download https://codex.flywire.ai/api/download You'd need to inspect the paper, the supplementals, and the website closely to determine exactly which files are interesting.
  - deleted 2y ago
    [deleted]
- andbberger 2y ago
  the raw data will be on the order of PBs
  - rmorey 2y ago
    the EM dataset for this connectome, FAFB, is only a few hundred TB. as a rule of thumb volume electron microscopy datasets are on the order of 1 PB / cubic millimeter, and the fly brain is much smaller than 1 mm3
    - andbberger 2y ago
      a few hundred TB is on the order PBs
      - rmorey 2y ago
        I meant like 100-200
- j6m8 2y ago
  raw data is O(petabytes) (single-digit); synapse-neuron graph will be probably order 100GB. But you also want morphology and locations, since it's not enough to just say "X connects to Y" if you want to know about dynamics! i'm not hosting this dataset specifically, but check out https://bossdb.org/ https://bossdb.org/. my disclaimer and also my brag is that this is my job and research area :) if you're looking for a copy, let's talk! there are easy ways and hard ways :)
mjburgess 2y ago
It was my understanding that all this connectome-based research was largely a deadend, because it doesnt capture dynamics, nor a vast array of interactions. if you've ever seen neurones being grown (go search YT), you'll see it's a massive gelatinous structure which is highly plastic and highly dynamic. Even in the simplest brains (eg., of elgans), you get 10^x exponential growth in number of neurones and their connections as it grows.
- dekhn 2y ago
  This is done agaist an adult so all the neurons have already grown. connectome isn't a dead end but it doesn't solve all known problems. It's like making a static map which you can then use to inspect all those cars driving around (the dynamics) and crashing (the interactions). [edit: I forgot to mention that neuron growth in adults (across many species) is still a controversial topic; see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554932/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554932/ for some commentary on the challenge in fly; https://en.wikipedia.org/wiki/Adult_neurogenesis https://en.wikipedia.org/wiki/Adult_neurogenesis for commentary on the larger problem ]
- caseyy 2y ago
  Giving scientists access to the connectome snapshot alone is very exciting. The first step to understanding why something is and how it came to be is seeing what it is. There are systems at play that form the brain into what it is and we don’t know much about them. The individual neurons — we have a better understanding of, but not the emergent systems. Now that many more scientists will know what the target for these systems is — what is the brain they shape, we can start to understand the control and feedback loops that result in this snapshot state of the brain. And that’s why it’s not a dead end. Just because it doesn’t immediately give some sort of a consumer product, doesn’t mean it’s not a step forward.
- westurner 2y ago
  From https://news.ycombinator.com/item?id=35877402#35886145 https://news.ycombinator.com/item?id=35877402#35886145 : > So, to run the same [fMRI, NIRS,] stimulus response activation observation/burn-in again weeks or months later with the same subjects is likely necessary given Representational drift And isn't there n-ary entanglement?
ChumpGPT 2y ago
http://archive.today/vBUjt http://archive.today/vBUjt
- purplejacket 2y ago
  Thanks
fabiensanglard 2y ago
What does it mean "mapped". Does it mean we know what each nerve/axon does?
- CobrastanJorji 2y ago
  It's my (layman) understanding that it's more or less a wiring diagram. Synapse #8217492 connects neuron #27472 and neuron #27865. It's a graph with 140,000 nodes (neurons) and 54.5 million edges (synapses). And then some labels for them like neurotransmitter type, which class of brain operations they're associated with, its size and position in 3D, etc. They have a cool website that lets you browse the data: https://codex.flywire.ai/ https://codex.flywire.ai/
  - mont_tag 2y ago
    Is the data such that it can be modeled in software?
    - dekhn 2y ago
      Yes. One example: https://www.biorxiv.org/content/10.1101/2024.03.11.584515v1 https://www.biorxiv.org/content/10.1101/2024.03.11.584515v1
    - GoblinSlayer 2y ago
      https://github.com/Flowx08/Celegans-simulation https://github.com/Flowx08/Celegans-simulation
    - tsimionescu 2y ago
      Depends what you mean by "modeled". You can probably create a visualization of it, but the data doesn't include any information about the dynamics of the system, how the neurons behave. So, you can't "simulate a brain" to any extent with this data, if that's what you were thinking.
- generuso 2y ago
  Unfortunately, not. We get the graph of the connections, but there are tons of essential parameters that are not captured. Such as the synaptic weights, the complex non-linear dynamics of the real neurons, their intricate modulation by various chemicals, etc. For example, after the connectome of the worm were finished, despite it being quite small, for many years it proved to be impossible to simulate the dynamics, because of so many unknown parameters. This was one of the criticisms that the opponents of connectomics have always brought up. "You spend a lot of money that could have been used for other research, but in the end you do not get a true insight into how the brain really works." For the researchers who thought that knowing all the connections was important, it was an uphill battle to overcome such attitudes. But one has to start somewhere -- like a genome, the connectome is not the whole story, but it is a very important part of it, on which many other advances can be built up.
droideqa 2y ago
There is this interesting past post: Whole-brain connectome of the fruit fly (2023) https://news.ycombinator.com/item?id=36568609 https://news.ycombinator.com/item?id=36568609
- dang 2y ago
  Thanks! Macroexpanded: Whole-brain connectome of the fruit fly - https://news.ycombinator.com/item?id=36568609 https://news.ycombinator.com/item?id=36568609 - July 2023 (94 comments) The connectome of an insect brain by Winding et al. - https://news.ycombinator.com/item?id=35112234 https://news.ycombinator.com/item?id=35112234 - March 2023 (1 comment) Map of an Insect’s Brain - https://news.ycombinator.com/item?id=35111371 https://news.ycombinator.com/item?id=35111371 - March 2023 (119 comments) The Connectome of an Insect Brain - https://news.ycombinator.com/item?id=35094565 https://news.ycombinator.com/item?id=35094565 - March 2023 (1 comment) The first wiring map of an insect's brain hints at incredible complexity - https://news.ycombinator.com/item?id=35089298 https://news.ycombinator.com/item?id=35089298 - March 2023 (5 comments) Fruit Fly Brain Map - https://news.ycombinator.com/item?id=29672565 https://news.ycombinator.com/item?id=29672565 - Dec 2021 (1 comment) Structure of Fruit Fly Brain (2018) - https://news.ycombinator.com/item?id=26474430 https://news.ycombinator.com/item?id=26474430 - March 2021 (7 comments) Google publishes largest ever high-resolution map of brain connectivity - https://news.ycombinator.com/item?id=22124888 https://news.ycombinator.com/item?id=22124888 - Jan 2020 (1 comment) Explore the the adult fruit fly brain - https://news.ycombinator.com/item?id=20015218 https://news.ycombinator.com/item?id=20015218 - May 2019 (1 comment) To detect new odors, fruit fly brains improve on a well-known computer algorithm - https://news.ycombinator.com/item?id=18656016 https://news.ycombinator.com/item?id=18656016 - Dec 2018 (1 comment) A Complete Electron Microscopy Volume of the Brain of Adult Fruit Fly - https://news.ycombinator.com/item?id=17590910 https://news.ycombinator.com/item?id=17590910 - July 2018 (50 comments) Fruit Fly Brain Hackathon 2017 – Brain Circuit, Memory and Computation - https://news.ycombinator.com/item?id=13692166 https://news.ycombinator.com/item?id=13692166 - Feb 2017 (13 comments) Neurokernel: Emulating the Fruit Fly Brain - https://news.ycombinator.com/item?id=9284802 https://news.ycombinator.com/item?id=9284802 - March 2015 (8 comments) An open source platform for emulating the fruit fly brain - https://news.ycombinator.com/item?id=8377600 https://news.ycombinator.com/item?id=8377600 - Sept 2014 (17 comments) Maybe also throw in: Six Nobel prizes – what’s the fascination with the fruit fly? - https://news.ycombinator.com/item?id=15463522 https://news.ycombinator.com/item?id=15463522 - Oct 2017 (16 comments) Fruit fly nervous system: new solution to fundamental computer network problem - https://news.ycombinator.com/item?id=2103668 https://news.ycombinator.com/item?id=2103668 - Jan 2011 (13 comments)
qafy 2y ago
"human brains could follow" feels like a few jumps ahead? a fruit fly has on the order of 100k neurons, a human brain has on the order of 100 billion neurons. that's 6 orders of magnitude larger. that's like saying "A map of San Francisco has been completed, the entire solar system could follow!"
- IshKebab 2y ago
  Well assuming the same density it's "only" 100 times bigger in linear dimensions. Doesn't sound quite as crazy...
  - twojacobtwo 2y ago
    Isn't that just saying "if you take the cube root of the number, it's a smaller number"? I don't mean to be facetious - I'm struggling to to see what other consideration this helps with.
    - svara 2y ago
      The physical process of cutting. We're physically sectioning 3 dimensional blocks of tissue.
- cloudripper 2y ago
  I thought it was intended as more of a pun on questionable displays of human intelligence.
- BurningFrog 2y ago
  The method used seems like it would work as well on bigger brains. The amount of data may mean we have to wait for Moore's Law to keep improving things for a while though.
  - tsimionescu 2y ago
    The method used required 3 million manual human corrections. Even if Moore's Law actually still meant anything for compute power, this is still many orders of magnitude from scaling to a human brain.
baanist 2y ago
Are all fruit fry brains the same? Does anyone know what has actually been mapped and why it would generalize from one fruit fly to the next?
- dekhn 2y ago
  I don't think that drosophila are eutelic (https://en.wikipedia.org/wiki/Eutely https://en.wikipedia.org/wiki/Eutely) so no two flies have precisely the same cells at precisely the same locations (that's true for c. elegans, whose connectome is probably the best studied). The large-scale architecture will be roughly the same between any two individuals. You would likely need some sort of mapping (like an embedding) to generalize. It's definitely an active area of research.
- BurningFrog 2y ago
  The article describes it as slicing the fly brain into very thin slices, which are imaged by an electron microscope. Then you analyze the slice images and determine the neurons and their connection. This is the hard part, and the breakthrough is an AI based method. Pretty sure they've only mapped one brain so far.
  - LeifCarrotson 2y ago
    Fortunately, the whole chain of slicing, imaging, and analysis are now at least partially automated, so in theory you can repeat the process with nothing more than some time on the equipment and a bit of compute. In practice, I suspect there's a fair bit of grad student manual labor that keeps the pipeline flowing...
    - roywiggins 2y ago
      They crowdsourced three million manual corrections to the AI output, yeah.
      - int_19h 2y ago
        That sounds like a great training set then.
swayvil 2y ago
Simulated too? I assume that if you can map it then you can simulate it. Am I correct?
- glial 2y ago
  I doubt that's been done yet but I'd be surprised if it didn't happen soon using something like NEURON [1]. It would be telling to see how similar the simulation is to the living organism, since there is a lot going on inside the brain in addition to the neuron spiking. [1] https://nrn.readthedocs.io/en/8.2.6/ https://nrn.readthedocs.io/en/8.2.6/
- meindnoch 2y ago
  Simulating it would require many orders of magnitude more compute. Biological neurons are not just a sigmoid function.
  - roywiggins 2y ago
    > In one paper, for example, researchers used the connectome to create a computer model of the entire fruit-fly brain, including all the connections between neurons. They tested it by activating neurons that they knew either sense sweet or bitter tastes. These neurons then launched a cascade of signals through the virtual fly’s brain, ultimately triggering motor neurons tied to the fly’s proboscis — the equivalent of the mammalian tongue. When the sweet circuit was activated, a signal for extending the proboscis was transmitted, as if the insect was preparing to feed; when the bitter circuit was activated, this signal was inhibited. To validate these findings, the team activated the same neurons in a real fruit fly. The researchers learnt that the simulation was more than 90% accurate at predicting which neurons would respond and therefore how the fly would behave. https://www.nature.com/articles/d41586-024-03190-y https://www.nature.com/articles/d41586-024-03190-y
- jknoepfler 2y ago
  If I understand what you're asking for correctly, then no, not in any meaningful sense. This is the gross structural anatomy of a dead brain, which is a small but important step towards understanding dynamics. Inference from structure to dynamics in a brain is several orders of magnitude less plausible than inferring from a record of local weather reports to simulating actual weather patterns. Maybe a better analogy would be inferring from Grey's Anatomy to the regulatory dynamics of proteins at the cellular level in vivo (although I think that might actually be easier?)
worik 2y ago
Quite a leap, fruit fly to human....
PaulKeeble 2y ago
Going to need a significant improvement in the software to get it to map a human. The fruit flu has 140,000 neurons and 54.5 million synapses and the AI that mapped it required a post process with humans checking it all with 3 million edits and they still have to identify every neuron type. A human brain has about 86 billion neurons and quite likely many trillions of synapses and that is likely an underestimate. That 3 million edits will turn into 3 million * 10^6 at least manual edits, that doesn't seem feasible. The error rate on the fruit flu would have to come down into the single digits to be usable to map a human brain. So an improvement from about 6% of synapses to 0.000006%. That is one heck of a jump in improvement for an AI.
- sieabahlpark 2y ago
  [dead]
- keybored 2y ago
  Cartographers have mapped Scotland. [random scribe muses that] The whole world could be next.
  - pepve 2y ago
    Did a rough calculation, it would be more like Edinburgh. There's easily a century between the earliest accurate map of Edinburgh and the earliest accurate map of the world. And even at present, the accuracy of maps of Edinburgh is much greater than the accuracy of maps of the world. So yeah, the whole world could be next. But the person you're replying to has a point when they say significant improvements are needed.
    - xandrius 2y ago
      We did map a handful of brains yet, the more we do the better we will get at it. I don't understand all this rushing and skepticism when such amazing science is being done. It's not like some AI company marking claims to sell a product, it's some researchers trying to accomplish something. Yes, they should (and probably will) do it better but that's not the goal here. If 3 million manual edits are still doable then it's ok. And when the manual step is not feasible, a jump in the tech will be required.
deleted 2y ago
[deleted]
willcipriano 2y ago
50 years from now I am dying in a hospital bed, the nurse informs me that my consciousness will be uploaded to a computer with all the other brains, a digital heaven if you will. Get there and its full of flies.
- inglor_cz 2y ago
  Well, the big question is if a human is "just" a mega-fly when it comes to brain structure.
- dekhn 2y ago
  No, beetles (JBS Haldane said god has an "inordinate fondness for beetles")
  - phyzome 2y ago
    That may be so, but scientists have an inordinate fondness for flies.
- AStonesThrow 2y ago
  Yeah but you can earn CPU cycles and egress bandwidth by sending bug reports Keeps your virtual landlord happy... Landlord of the Flies, if you will.
- akomtu 2y ago
  heaven? not so fast. how about solving captchas at 100x speed for 100 years to aid the development of some ai vision project?
deleted 2y ago
[deleted]
dmitrysergeyev 2y ago
https://archive.is/vBUjt https://archive.is/vBUjt
_giorgio_ 2y ago
Is this correct? It this like knowing only this: which neuron is connected to which neuron But you don't know: the values of the weights (the value of the neuron, or the parameters) the activation functions what circuit do neurons implement (fully connected? CNN?)
- charlescurt123 2y ago
  I believe they do know this. However the real challenge would be: 1. bring this mapping into a AI framework for inferencing 2. We don't know the "OS" on how it runs. Just randomly triggering a neuron probably wouldn't work as there is a lot of other factors that trigger neurons.
- andbberger 2y ago
  > which neuron is connected to which neuron yes. and you can get VERY roughly connection strengths by synapse count but that's as far as you can go
- drdeca 2y ago
  I don’t think the last one is right. Fully connected and CNN are part of “what neuron is connected to what neuron” (though in the case of CNN, a number of corresponding “neurons” have equal weights going to/from them ). Also, “activation function” isn’t exactly the right thing for real biological neurons. They aren’t just functions of the current input or the like. Their behavior depends on their recent history. Some will like, by themselves iirc, periodically fire. Others will fire if enough input is sent within some amount of time (in some models of some of them there’s like, some accumulations of signal when receiving inputs, which gradually decays/leaks, and it fires (and depletes) if enough is accumulated). But yes, the idea is that “what is connected to what” is obtained, but not more specific things about how the ones that are connected are connected (how the behavior of one relates to the behavior of the ones it is connected to).
adrian_b 2y ago
The paper published in Nature, which is open access: https://www.nature.com/articles/s41586-024-07558-y https://www.nature.com/articles/s41586-024-07558-y
dmvdoug 2y ago
Paging mjg59, Matthew Garrett, Matthew Garrett to the white courtesy phone.
holtkam2 2y ago
What hard steps exist between mapping the physical structure of the brain and simulating a running one via software?
- aithrowawaycomm 2y ago
  Knowing what the individual neurons actually do. The connectome is like an electrical schematic but you don't even know which components are resistors, inductors, etc (let alone the resistances and inductances). The connectome for the C. elegans nematode was mapped in the 1980s and the OpenWorm project has successfully simulated all non-neuronal cells. But they are very far from simulating the brain abd it will take decades of experimental work to understand C. elegans's brain - it's very difficult to observe a living brain in the required molecular detail.
  - s1artibartfast 2y ago
    I think it's even more complex. The neurons are like individual raspberry pi. They have both complex logic and physical memory.
    - notahacker 2y ago
      Yeah, I think it's close to "what steps exist between observing the network topology of the internet and being able to emulate a Google search query?" There's plenty of value to knowing where the datacentres are and which regions are active under which circumstances, but none of that is telling you what the internet is thinking...
  - nonameiguess 2y ago
    I'm frankly not sure it will ever be possible. Forget about observing the inside of a running neuron. In spite of how confidently people on the Internet will tell you their body fat percentage, in reality we can't even accurately measure that without killing you first.
    - aithrowawaycomm 2y ago
beefman 2y ago
Better source: https://www.nature.com/articles/d41586-024-03190-y https://www.nature.com/articles/d41586-024-03190-y
janalsncm 2y ago
Do we have an accurate model of a single neuron or very small group of neurons? I understand the reality may be chaotic, but I would hope to have a simulation such that it mirrors the evolution of neurons to a reasonable extent.
- RaftPeople 2y ago
  > Do we have an accurate model of a single neuron No. Many unknowns and even more being discovered regularly (e.g. tunneling nanotubes connecting neurons dynamically)
Jun8 2y ago
My (maybe very ignorant) question is: can this connectome be used to “run” simulations of a virtual fruit fly, a la MMAcevedo?
- fhdsgbbcaA 2y ago
  Microsoft Fly Simulator (tm).
- andbberger 2y ago
  no. turaga and co have some work where they constrain model network topologies with the connectome and train on visual data. this is imo a very silly line of research and they come to some very wrong conclusions about what neurons do what with it. but that's the closest to what you're asking for
- mr_toad 2y ago
  It’s a neural network without weights. And it doesn’t have a body. Figuring out the behaviour of the neurons could take decades, although I have no doubt that people will eventually. And simulating a whole fruit fly body seems like it’s going to be out of reach for a very long time.
  - hwillis 2y ago
    > It’s a neural network without weights. It has approximate weights. Neuron connection strength is determined by the number of synapses (1-100s, sometimes 1000s), the type of synapse neurotransmitter, and the number of receptors. The connectome has 1 and 2 and is only missing 3. The number of receptors may not even be that important- the fact that the number of synapses is important may well mean the number of receptors is unreliable. Neurons also don't transmit scalars to each other. The synapse is stimulate by frequency of action potentials much more than strength. > And it doesn’t have a body. It does have nervous connections outside the brain. That behavior is not as complex. > Figuring out the behaviour of the neurons could take decades Neurons are not that complex in terms of matching in->out behavior. Since spiking is frequency-based, you can verify it quite well by ensuring the frequency of spikes in->out matches; you can even measure single neurons with implanted electrodes. You don't need so much precision to see individual spikes, since the size of the spikes does not matter much at all. Long term potentiation also makes measuring individual neuron strength even less important- if you model potentiation correctly, then over time you'll converge accurately as understimulated connections weaken and vice versa. The real issue is we have barely any clue how potentiation works and can't model it well at all. It's very important to brain behavior and most of the interesting things brains do. Its kind of an issue.
Lonestar1440 2y ago
A big reason for my imminent-AGI Skepticism is the fact that our understanding of the currently existing, Biological intelligence is so, so shallow. We're here at "Systems level sketch of a fruit fly brain". It's incredible work! But as other comments detail, there is far more to the function of a fly brain than this "map". It's quite a long way from "Deep understanding of a Human Brain, to the point where we can begin engineering a replica". Maybe we'll get lucky, and find that "Neural Network" techniques really are a pathway to Intelligence in a broad sense. But without some mechanistic understanding of Biological Intelligence, it seems no better than betting on the Numbers in roulette.
- tomrod 2y ago
  I think we've already done this with a certain flatworm.
- deleted 2y ago
  [deleted]
- perryizgr8 2y ago
  I don't think you need to fully understand how the brain works to be able to create AGI. Did the invention of the wheel/cart/car require us to fully understand how we walk? Did we need to fully understand how fish swim before we could make a boat? The only caveat would be that the AGI we build would be entirely unlike human minds. In the sane way a car going 100 kph is different from a running person.
  - tim333 2y ago
    It's surprising in a way how similar some generative AI seems to be to human parts of human minds like the dream like images produced some times and the reasoning in o1 being kind of human like.
- israrkhan 2y ago
  AGI does not need to be based on biological intelligence. it is analogous to human will to fly, and our models were birds, but eventually we came up with something else (airplanes), that are much better at flying than birds (in some regards), and much there is nothing in nature so big, that can fly (nothing that we know of). IMO AGI could be similar.. despite its dissimilarities with biological brains, if it looks like a duck, quacks like a duck, swims like a duck, then it probably is duck (and perhaps better than duck in some ways).
thoi234324234 2y ago
Does it matter ? Openworm still hasn't succeeded.
nomilk 2y ago
> Data available for download, programmatic access and interactive browsing and have been made interoperable with other fly data resources Curious what a 'fly brain map' looks like - iss the download a 3D model, or a matrix with values for attributes?
idlewords 2y ago
It thinks a lot about fruit.
- khazhoux 2y ago
  Can we please stop perpetuating this racist stereotype?
  - philodeon 2y ago
    The stereotype sounds way more homophobic to me than racist…
black_13 2y ago
[dead]
perryizgr8 2y ago
So can we run it on a computer now? That's the end goal, isn't it? Or maybe ask an LLM to look at the upload and figure out what makes it tick.
- okdood64 2y ago
  Why would an LLM in particular be good at this?
yuz 2y ago
So, can it run Doom?
pugworthy 2y ago
They are currently active in my kitchen. I think those thinking that AI and ML need massive compute power and electricity should take note that these little bastards can be annoying and pervasive as hell with just 100k neurons in that little head. And run off ripe bananas.
- dennis_jeeves2 2y ago
  Indeed it is miracle of evolution (or a creator if that suit you) to be so efficient.
londons_explore 2y ago
If this could be done for a human, I think there is a realistic prospect of perhaps being the first human "brought back to life inside a computer". Sure, the connectome isn't the whole story, but I think it possible that a few hundred years from now we might understand the brain sufficiently to simulate it, and then by inputting this connectome, together with guesses/approximations for the information not captured, that person is effectively time-travelled. Could be amazing for archaeologists - rather than looking at broken bits of pottery and guessing what they're used for, you could literally just ask someone (a brain) from that time.
- groestl 2y ago
  I fully agree, but at the same time it gives me Black Mirror vibes.
- londons_explore 2y ago
  On the other hand, I suspect just putting your brain in a jar filled with formaldehyde has similar chances of future humans managing to re-animate it. With a connectome, you can make hundreds of copies of the data round the world. With pickled-brain-in-a-jar you better make sure that jar is well hidden in a dusty basement for long enough to not get chucked out, but not so well hidden future generations never find it.
- codeulike 2y ago
  https://qntm.org/mmacevedo https://qntm.org/mmacevedo
- tim333 2y ago
  Long before bringing people back based on analysis of their neurons, there will be many people 'brought back' by something like an LLM acting like them similar to how a human actor sort of becomes someone. There have already been crude efforts and I guess as time goes on they will get better. (eg. the Kurzweils in 2016 https://www.pcmag.com/articles/how-ray-kurzweil-and-his-daughter-brought-a-relative-back-from-the-dead https://www.pcmag.com/articles/how-ray-kurzweil-and-his-daug...)
Nevermark 2y ago
My undergrad research was on identifying synaptic strengths based on firing behavior of networks of simple integrate to threshold neuron models. A toy model compared to real neurons but a good starting place with nice results. We could identify the solution that most robustly reproduced the firing patterns even in the presence of noise. I would be curious how well the connectome documents connection and dendrite/axon geometry, beyond connection paths. For shedding light on behavior related to connection strengths, timing, neuron firing sensitivities, etc. For the stable non-learning model as captured at scanning time. To investigate adaptation purpose & behavior, it helps to understand what operational behavior has been learned.
DrPimienta 2y ago
What wondrous secrets of knowledge await us in such a mighty neurological architecture?
awestroke 2y ago
Related: my favorite HN comment ever from a similar submission a year ago: > There's lots of very exciting work going on around the fully mapped fruit fly connectome. For example, I'm a CTO of a stealth startup that aims to do for utilitarianism what carbon credits did for environmentalism. We are selling 'utility credits' which translates directly into us simulating trillions and trillions of fruit fly brains in a state of constant orgasmic bliss, which you can then buy to offset any actions your company has undertaken that damage global happiness or well-being. We've seen a lot of interest from some pretty large industry players. https://news.ycombinator.com/item?id=36584130 https://news.ycombinator.com/item?id=36584130
- ash1794 2y ago
  Why!
  - neverrroot 2y ago
    Feel good, bragging rights, entitlement
  - rtkwe 2y ago
    It's a joke about utilitarianism which has had it's ups and downs but is a philosophy that has some pretty powerful adherents in the tech CEO world, notably the whole effective altruist crowd that SBF came out of. There's the Parable of Felix from SMBC [0] coming at it from the other angle of one incredibly happy person skewing the utility equation to do awful things. [0] https://www.smbc-comics.com/comics/20120403.gif https://www.smbc-comics.com/comics/20120403.gif
- FrustratedMonky 2y ago
  They have a branding opportunity. Karma Kredits Perhaps a co-branding opportunity with Krispy Kreme donuts? Buy a donut, and experience some Joy, which handily comes with Karma Kredits to offset that Joy. Have some KK with the KK!
  - birracerveza 2y ago
crispyambulance 2y ago
Interesting stuff, but I don't understand HOW they've done it. There's something called Connectome Annotation Versioning Engine (CAVE). Which appears to be software(?) which allows researchers to examine a dataset and annotate it in some way. Presumably the dataset consists of images of the neurons themselves and the job is to map which neurons touch which other neurons? That's the thing I am not understanding. How do they get such images in the first place? CAVE is mentioned along with electron microscopy... but I don't understand how an electron microscope can be useful here. Obviously, it's not TEM (which required a very flat specimen). Then, there's SEM, but doesn't that require a conductive sample? In both cases, any electron microscope requires a vacuum to even work, right? How can this be done with something so wet, fragile and 3 dimensional like the brain of a fruit fly? Even worse, the connections are stacked on top of each other. How can an electron microscope image below the surface? TLDR; How is it possible to even image the way the neurons are connected in the first place? ELI5?
- svara 2y ago
  You perform chemical fixation and heavy metal staining, then some form of serial sectioning. You can either image the sections themselves or serially image the block face. The sections can be imaged with TEM or SEM in high vacuum, the block face can be imaged with SEM. The resulting 3d volume can be segmented with neural networks. CAVE is for manual editing / correction on top of the automatically generated segmentation.
0xedd 2y ago
[dead]
danbruc 2y ago
Do we understand how memory works in general? If you tell me to remember the number 71, I can do that instantly with my short term memory, so I would guess that works without any changes to the brain structure and more like charging or discharging the tiny capacity in a DRAM cell or flipping the feedback loop in an SRAM cell. For long term memory on the other hand I would assume that this involves changes to the brain structure as this seems more robust but slower to do, I would have to think of 71 for quite some time in order to remember it weeks, months or years later. Do we know anything about this in good detail or is this still too hard to investigate because the relevant structures or processes are hidden in a sea of other things?
- achileas 2y ago
  We don't really know much about how memories are formed, the short-term and long-term divisions come from cognitive psychology and we don't have (from what I remember from my neuro days, which may be out of date by now but I am friends with several neuroscientists and I'm not sure it's out of date yet) a strong idea of what the biological correlates of each are, or even if they arise via different processes or what.
ignoramceisblis 2y ago
A 3D interactive interface, which has been around for several years now: https://flycircuit.neuronlp.fruitflybrain.org/ https://flycircuit.neuronlp.fruitflybrain.org/

594 points by teleforce 2y ago

Interesting, with all of the BS around LLM training sucking up other peoples' content that something like the economist can base an article off a paper without adding too much more in the way of unique content, just fluff and still lock down access to the content.

tonetegeatinst 2y ago

Datahoarder question but can I download the map of the fly?

elevatedastalt 2y ago
[flagged]
- hackboyfly 2y ago
  [flagged]
ijxjdffnkkpp 2y ago
I think that releasing the map on torrent would be a useful idea as well. This fly could end up like the lobsters in Accelerando. In that book the mapped animal is lobsters and they get first mover advantage on some post-scarcity type things. Getting them to the Internet would be a good first step, IMO.
- rbanffy 2y ago
  I, for one, welcome our new fruit fly overlords.
dekhn 2y ago
See the FAQ: https://codex.flywire.ai/faq https://codex.flywire.ai/faq which leads to the API for access: https://codex.flywire.ai/api/download https://codex.flywire.ai/api/download You'd need to inspect the paper, the supplementals, and the website closely to determine exactly which files are interesting.
- deleted 2y ago
  [deleted]
andbberger 2y ago
the raw data will be on the order of PBs
- rmorey 2y ago
  the EM dataset for this connectome, FAFB, is only a few hundred TB. as a rule of thumb volume electron microscopy datasets are on the order of 1 PB / cubic millimeter, and the fly brain is much smaller than 1 mm3
  - andbberger 2y ago
    a few hundred TB is on the order PBs
    - rmorey 2y ago
      I meant like 100-200
j6m8 2y ago
raw data is O(petabytes) (single-digit); synapse-neuron graph will be probably order 100GB. But you also want morphology and locations, since it's not enough to just say "X connects to Y" if you want to know about dynamics! i'm not hosting this dataset specifically, but check out https://bossdb.org/ https://bossdb.org/. my disclaimer and also my brag is that this is my job and research area :) if you're looking for a copy, let's talk! there are easy ways and hard ways :)

mjburgess 2y ago

It was my understanding that all this connectome-based research was largely a deadend, because it doesnt capture dynamics, nor a vast array of interactions. if you've ever seen neurones being grown (go search YT), you'll see it's a massive gelatinous structure which is highly plastic and highly dynamic. Even in the simplest brains (eg., of elgans), you get 10^x exponential growth in number of neurones and their connections as it grows.

dekhn 2y ago
This is done agaist an adult so all the neurons have already grown. connectome isn't a dead end but it doesn't solve all known problems. It's like making a static map which you can then use to inspect all those cars driving around (the dynamics) and crashing (the interactions). [edit: I forgot to mention that neuron growth in adults (across many species) is still a controversial topic; see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554932/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554932/ for some commentary on the challenge in fly; https://en.wikipedia.org/wiki/Adult_neurogenesis https://en.wikipedia.org/wiki/Adult_neurogenesis for commentary on the larger problem ]
caseyy 2y ago
Giving scientists access to the connectome snapshot alone is very exciting. The first step to understanding why something is and how it came to be is seeing what it is. There are systems at play that form the brain into what it is and we don’t know much about them. The individual neurons — we have a better understanding of, but not the emergent systems. Now that many more scientists will know what the target for these systems is — what is the brain they shape, we can start to understand the control and feedback loops that result in this snapshot state of the brain. And that’s why it’s not a dead end. Just because it doesn’t immediately give some sort of a consumer product, doesn’t mean it’s not a step forward.
westurner 2y ago
From https://news.ycombinator.com/item?id=35877402#35886145 https://news.ycombinator.com/item?id=35877402#35886145 : > So, to run the same [fMRI, NIRS,] stimulus response activation observation/burn-in again weeks or months later with the same subjects is likely necessary given Representational drift And isn't there n-ary entanglement?

ChumpGPT 2y ago

http://archive.today/vBUjt http://archive.today/vBUjt

purplejacket 2y ago
Thanks

fabiensanglard 2y ago

What does it mean "mapped". Does it mean we know what each nerve/axon does?

CobrastanJorji 2y ago
It's my (layman) understanding that it's more or less a wiring diagram. Synapse #8217492 connects neuron #27472 and neuron #27865. It's a graph with 140,000 nodes (neurons) and 54.5 million edges (synapses). And then some labels for them like neurotransmitter type, which class of brain operations they're associated with, its size and position in 3D, etc. They have a cool website that lets you browse the data: https://codex.flywire.ai/ https://codex.flywire.ai/
- mont_tag 2y ago
  Is the data such that it can be modeled in software?
  - dekhn 2y ago
    Yes. One example: https://www.biorxiv.org/content/10.1101/2024.03.11.584515v1 https://www.biorxiv.org/content/10.1101/2024.03.11.584515v1
  - GoblinSlayer 2y ago
    https://github.com/Flowx08/Celegans-simulation https://github.com/Flowx08/Celegans-simulation
  - tsimionescu 2y ago
    Depends what you mean by "modeled". You can probably create a visualization of it, but the data doesn't include any information about the dynamics of the system, how the neurons behave. So, you can't "simulate a brain" to any extent with this data, if that's what you were thinking.
generuso 2y ago
Unfortunately, not. We get the graph of the connections, but there are tons of essential parameters that are not captured. Such as the synaptic weights, the complex non-linear dynamics of the real neurons, their intricate modulation by various chemicals, etc. For example, after the connectome of the worm were finished, despite it being quite small, for many years it proved to be impossible to simulate the dynamics, because of so many unknown parameters. This was one of the criticisms that the opponents of connectomics have always brought up. "You spend a lot of money that could have been used for other research, but in the end you do not get a true insight into how the brain really works." For the researchers who thought that knowing all the connections was important, it was an uphill battle to overcome such attitudes. But one has to start somewhere -- like a genome, the connectome is not the whole story, but it is a very important part of it, on which many other advances can be built up.

droideqa 2y ago

There is this interesting past post: Whole-brain connectome of the fruit fly (2023) https://news.ycombinator.com/item?id=36568609 https://news.ycombinator.com/item?id=36568609

dang 2y ago
Thanks! Macroexpanded: Whole-brain connectome of the fruit fly - https://news.ycombinator.com/item?id=36568609 https://news.ycombinator.com/item?id=36568609 - July 2023 (94 comments) The connectome of an insect brain by Winding et al. - https://news.ycombinator.com/item?id=35112234 https://news.ycombinator.com/item?id=35112234 - March 2023 (1 comment) Map of an Insect’s Brain - https://news.ycombinator.com/item?id=35111371 https://news.ycombinator.com/item?id=35111371 - March 2023 (119 comments) The Connectome of an Insect Brain - https://news.ycombinator.com/item?id=35094565 https://news.ycombinator.com/item?id=35094565 - March 2023 (1 comment) The first wiring map of an insect's brain hints at incredible complexity - https://news.ycombinator.com/item?id=35089298 https://news.ycombinator.com/item?id=35089298 - March 2023 (5 comments) Fruit Fly Brain Map - https://news.ycombinator.com/item?id=29672565 https://news.ycombinator.com/item?id=29672565 - Dec 2021 (1 comment) Structure of Fruit Fly Brain (2018) - https://news.ycombinator.com/item?id=26474430 https://news.ycombinator.com/item?id=26474430 - March 2021 (7 comments) Google publishes largest ever high-resolution map of brain connectivity - https://news.ycombinator.com/item?id=22124888 https://news.ycombinator.com/item?id=22124888 - Jan 2020 (1 comment) Explore the the adult fruit fly brain - https://news.ycombinator.com/item?id=20015218 https://news.ycombinator.com/item?id=20015218 - May 2019 (1 comment) To detect new odors, fruit fly brains improve on a well-known computer algorithm - https://news.ycombinator.com/item?id=18656016 https://news.ycombinator.com/item?id=18656016 - Dec 2018 (1 comment) A Complete Electron Microscopy Volume of the Brain of Adult Fruit Fly - https://news.ycombinator.com/item?id=17590910 https://news.ycombinator.com/item?id=17590910 - July 2018 (50 comments) Fruit Fly Brain Hackathon 2017 – Brain Circuit, Memory and Computation - https://news.ycombinator.com/item?id=13692166 https://news.ycombinator.com/item?id=13692166 - Feb 2017 (13 comments) Neurokernel: Emulating the Fruit Fly Brain - https://news.ycombinator.com/item?id=9284802 https://news.ycombinator.com/item?id=9284802 - March 2015 (8 comments) An open source platform for emulating the fruit fly brain - https://news.ycombinator.com/item?id=8377600 https://news.ycombinator.com/item?id=8377600 - Sept 2014 (17 comments) Maybe also throw in: Six Nobel prizes – what’s the fascination with the fruit fly? - https://news.ycombinator.com/item?id=15463522 https://news.ycombinator.com/item?id=15463522 - Oct 2017 (16 comments) Fruit fly nervous system: new solution to fundamental computer network problem - https://news.ycombinator.com/item?id=2103668 https://news.ycombinator.com/item?id=2103668 - Jan 2011 (13 comments)

qafy 2y ago

"human brains could follow" feels like a few jumps ahead? a fruit fly has on the order of 100k neurons, a human brain has on the order of 100 billion neurons. that's 6 orders of magnitude larger. that's like saying "A map of San Francisco has been completed, the entire solar system could follow!"

IshKebab 2y ago
Well assuming the same density it's "only" 100 times bigger in linear dimensions. Doesn't sound quite as crazy...
- twojacobtwo 2y ago
  Isn't that just saying "if you take the cube root of the number, it's a smaller number"? I don't mean to be facetious - I'm struggling to to see what other consideration this helps with.
  - svara 2y ago
    The physical process of cutting. We're physically sectioning 3 dimensional blocks of tissue.
cloudripper 2y ago
I thought it was intended as more of a pun on questionable displays of human intelligence.
BurningFrog 2y ago
The method used seems like it would work as well on bigger brains. The amount of data may mean we have to wait for Moore's Law to keep improving things for a while though.
- tsimionescu 2y ago
  The method used required 3 million manual human corrections. Even if Moore's Law actually still meant anything for compute power, this is still many orders of magnitude from scaling to a human brain.

baanist 2y ago

Are all fruit fry brains the same? Does anyone know what has actually been mapped and why it would generalize from one fruit fly to the next?

dekhn 2y ago
I don't think that drosophila are eutelic (https://en.wikipedia.org/wiki/Eutely https://en.wikipedia.org/wiki/Eutely) so no two flies have precisely the same cells at precisely the same locations (that's true for c. elegans, whose connectome is probably the best studied). The large-scale architecture will be roughly the same between any two individuals. You would likely need some sort of mapping (like an embedding) to generalize. It's definitely an active area of research.
BurningFrog 2y ago
The article describes it as slicing the fly brain into very thin slices, which are imaged by an electron microscope. Then you analyze the slice images and determine the neurons and their connection. This is the hard part, and the breakthrough is an AI based method. Pretty sure they've only mapped one brain so far.
- LeifCarrotson 2y ago
  Fortunately, the whole chain of slicing, imaging, and analysis are now at least partially automated, so in theory you can repeat the process with nothing more than some time on the equipment and a bit of compute. In practice, I suspect there's a fair bit of grad student manual labor that keeps the pipeline flowing...
  - roywiggins 2y ago
    They crowdsourced three million manual corrections to the AI output, yeah.
    - int_19h 2y ago
      That sounds like a great training set then.

swayvil 2y ago

Simulated too? I assume that if you can map it then you can simulate it. Am I correct?

glial 2y ago
I doubt that's been done yet but I'd be surprised if it didn't happen soon using something like NEURON [1]. It would be telling to see how similar the simulation is to the living organism, since there is a lot going on inside the brain in addition to the neuron spiking. [1] https://nrn.readthedocs.io/en/8.2.6/ https://nrn.readthedocs.io/en/8.2.6/
meindnoch 2y ago
Simulating it would require many orders of magnitude more compute. Biological neurons are not just a sigmoid function.
- roywiggins 2y ago
  > In one paper, for example, researchers used the connectome to create a computer model of the entire fruit-fly brain, including all the connections between neurons. They tested it by activating neurons that they knew either sense sweet or bitter tastes. These neurons then launched a cascade of signals through the virtual fly’s brain, ultimately triggering motor neurons tied to the fly’s proboscis — the equivalent of the mammalian tongue. When the sweet circuit was activated, a signal for extending the proboscis was transmitted, as if the insect was preparing to feed; when the bitter circuit was activated, this signal was inhibited. To validate these findings, the team activated the same neurons in a real fruit fly. The researchers learnt that the simulation was more than 90% accurate at predicting which neurons would respond and therefore how the fly would behave. https://www.nature.com/articles/d41586-024-03190-y https://www.nature.com/articles/d41586-024-03190-y
jknoepfler 2y ago
If I understand what you're asking for correctly, then no, not in any meaningful sense. This is the gross structural anatomy of a dead brain, which is a small but important step towards understanding dynamics. Inference from structure to dynamics in a brain is several orders of magnitude less plausible than inferring from a record of local weather reports to simulating actual weather patterns. Maybe a better analogy would be inferring from Grey's Anatomy to the regulatory dynamics of proteins at the cellular level in vivo (although I think that might actually be easier?)

worik 2y ago

Quite a leap, fruit fly to human....

PaulKeeble 2y ago

Going to need a significant improvement in the software to get it to map a human. The fruit flu has 140,000 neurons and 54.5 million synapses and the AI that mapped it required a post process with humans checking it all with 3 million edits and they still have to identify every neuron type. A human brain has about 86 billion neurons and quite likely many trillions of synapses and that is likely an underestimate. That 3 million edits will turn into 3 million * 10^6 at least manual edits, that doesn't seem feasible. The error rate on the fruit flu would have to come down into the single digits to be usable to map a human brain. So an improvement from about 6% of synapses to 0.000006%. That is one heck of a jump in improvement for an AI.

sieabahlpark 2y ago
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keybored 2y ago
Cartographers have mapped Scotland. [random scribe muses that] The whole world could be next.
- pepve 2y ago
  Did a rough calculation, it would be more like Edinburgh. There's easily a century between the earliest accurate map of Edinburgh and the earliest accurate map of the world. And even at present, the accuracy of maps of Edinburgh is much greater than the accuracy of maps of the world. So yeah, the whole world could be next. But the person you're replying to has a point when they say significant improvements are needed.
  - xandrius 2y ago
    We did map a handful of brains yet, the more we do the better we will get at it. I don't understand all this rushing and skepticism when such amazing science is being done. It's not like some AI company marking claims to sell a product, it's some researchers trying to accomplish something. Yes, they should (and probably will) do it better but that's not the goal here. If 3 million manual edits are still doable then it's ok. And when the manual step is not feasible, a jump in the tech will be required.

deleted 2y ago

[deleted]

willcipriano 2y ago

50 years from now I am dying in a hospital bed, the nurse informs me that my consciousness will be uploaded to a computer with all the other brains, a digital heaven if you will. Get there and its full of flies.

inglor_cz 2y ago
Well, the big question is if a human is "just" a mega-fly when it comes to brain structure.
dekhn 2y ago
No, beetles (JBS Haldane said god has an "inordinate fondness for beetles")
- phyzome 2y ago
  That may be so, but scientists have an inordinate fondness for flies.
AStonesThrow 2y ago
Yeah but you can earn CPU cycles and egress bandwidth by sending bug reports Keeps your virtual landlord happy... Landlord of the Flies, if you will.
akomtu 2y ago
heaven? not so fast. how about solving captchas at 100x speed for 100 years to aid the development of some ai vision project?

deleted 2y ago

[deleted]

dmitrysergeyev 2y ago

https://archive.is/vBUjt https://archive.is/vBUjt

_giorgio_ 2y ago

Is this correct? It this like knowing only this: which neuron is connected to which neuron But you don't know: the values of the weights (the value of the neuron, or the parameters) the activation functions what circuit do neurons implement (fully connected? CNN?)

charlescurt123 2y ago
I believe they do know this. However the real challenge would be: 1. bring this mapping into a AI framework for inferencing 2. We don't know the "OS" on how it runs. Just randomly triggering a neuron probably wouldn't work as there is a lot of other factors that trigger neurons.
andbberger 2y ago
> which neuron is connected to which neuron yes. and you can get VERY roughly connection strengths by synapse count but that's as far as you can go
drdeca 2y ago
I don’t think the last one is right. Fully connected and CNN are part of “what neuron is connected to what neuron” (though in the case of CNN, a number of corresponding “neurons” have equal weights going to/from them ). Also, “activation function” isn’t exactly the right thing for real biological neurons. They aren’t just functions of the current input or the like. Their behavior depends on their recent history. Some will like, by themselves iirc, periodically fire. Others will fire if enough input is sent within some amount of time (in some models of some of them there’s like, some accumulations of signal when receiving inputs, which gradually decays/leaks, and it fires (and depletes) if enough is accumulated). But yes, the idea is that “what is connected to what” is obtained, but not more specific things about how the ones that are connected are connected (how the behavior of one relates to the behavior of the ones it is connected to).

adrian_b 2y ago

The paper published in Nature, which is open access: https://www.nature.com/articles/s41586-024-07558-y https://www.nature.com/articles/s41586-024-07558-y

dmvdoug 2y ago

Paging mjg59, Matthew Garrett, Matthew Garrett to the white courtesy phone.

holtkam2 2y ago

What hard steps exist between mapping the physical structure of the brain and simulating a running one via software?

aithrowawaycomm 2y ago
Knowing what the individual neurons actually do. The connectome is like an electrical schematic but you don't even know which components are resistors, inductors, etc (let alone the resistances and inductances). The connectome for the C. elegans nematode was mapped in the 1980s and the OpenWorm project has successfully simulated all non-neuronal cells. But they are very far from simulating the brain abd it will take decades of experimental work to understand C. elegans's brain - it's very difficult to observe a living brain in the required molecular detail.
- s1artibartfast 2y ago
  I think it's even more complex. The neurons are like individual raspberry pi. They have both complex logic and physical memory.
  - notahacker 2y ago
    Yeah, I think it's close to "what steps exist between observing the network topology of the internet and being able to emulate a Google search query?" There's plenty of value to knowing where the datacentres are and which regions are active under which circumstances, but none of that is telling you what the internet is thinking...
- nonameiguess 2y ago
  I'm frankly not sure it will ever be possible. Forget about observing the inside of a running neuron. In spite of how confidently people on the Internet will tell you their body fat percentage, in reality we can't even accurately measure that without killing you first.
  - aithrowawaycomm 2y ago

beefman 2y ago

Better source: https://www.nature.com/articles/d41586-024-03190-y https://www.nature.com/articles/d41586-024-03190-y

janalsncm 2y ago

Do we have an accurate model of a single neuron or very small group of neurons? I understand the reality may be chaotic, but I would hope to have a simulation such that it mirrors the evolution of neurons to a reasonable extent.

RaftPeople 2y ago
> Do we have an accurate model of a single neuron No. Many unknowns and even more being discovered regularly (e.g. tunneling nanotubes connecting neurons dynamically)

Jun8 2y ago

My (maybe very ignorant) question is: can this connectome be used to “run” simulations of a virtual fruit fly, a la MMAcevedo?

fhdsgbbcaA 2y ago
Microsoft Fly Simulator (tm).
andbberger 2y ago
no. turaga and co have some work where they constrain model network topologies with the connectome and train on visual data. this is imo a very silly line of research and they come to some very wrong conclusions about what neurons do what with it. but that's the closest to what you're asking for
mr_toad 2y ago
It’s a neural network without weights. And it doesn’t have a body. Figuring out the behaviour of the neurons could take decades, although I have no doubt that people will eventually. And simulating a whole fruit fly body seems like it’s going to be out of reach for a very long time.
- hwillis 2y ago
  > It’s a neural network without weights. It has approximate weights. Neuron connection strength is determined by the number of synapses (1-100s, sometimes 1000s), the type of synapse neurotransmitter, and the number of receptors. The connectome has 1 and 2 and is only missing 3. The number of receptors may not even be that important- the fact that the number of synapses is important may well mean the number of receptors is unreliable. Neurons also don't transmit scalars to each other. The synapse is stimulate by frequency of action potentials much more than strength. > And it doesn’t have a body. It does have nervous connections outside the brain. That behavior is not as complex. > Figuring out the behaviour of the neurons could take decades Neurons are not that complex in terms of matching in->out behavior. Since spiking is frequency-based, you can verify it quite well by ensuring the frequency of spikes in->out matches; you can even measure single neurons with implanted electrodes. You don't need so much precision to see individual spikes, since the size of the spikes does not matter much at all. Long term potentiation also makes measuring individual neuron strength even less important- if you model potentiation correctly, then over time you'll converge accurately as understimulated connections weaken and vice versa. The real issue is we have barely any clue how potentiation works and can't model it well at all. It's very important to brain behavior and most of the interesting things brains do. Its kind of an issue.

Lonestar1440 2y ago

A big reason for my imminent-AGI Skepticism is the fact that our understanding of the currently existing, Biological intelligence is so, so shallow. We're here at "Systems level sketch of a fruit fly brain". It's incredible work! But as other comments detail, there is far more to the function of a fly brain than this "map". It's quite a long way from "Deep understanding of a Human Brain, to the point where we can begin engineering a replica". Maybe we'll get lucky, and find that "Neural Network" techniques really are a pathway to Intelligence in a broad sense. But without some mechanistic understanding of Biological Intelligence, it seems no better than betting on the Numbers in roulette.

tomrod 2y ago
I think we've already done this with a certain flatworm.
deleted 2y ago
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perryizgr8 2y ago
I don't think you need to fully understand how the brain works to be able to create AGI. Did the invention of the wheel/cart/car require us to fully understand how we walk? Did we need to fully understand how fish swim before we could make a boat? The only caveat would be that the AGI we build would be entirely unlike human minds. In the sane way a car going 100 kph is different from a running person.
- tim333 2y ago
  It's surprising in a way how similar some generative AI seems to be to human parts of human minds like the dream like images produced some times and the reasoning in o1 being kind of human like.
israrkhan 2y ago
AGI does not need to be based on biological intelligence. it is analogous to human will to fly, and our models were birds, but eventually we came up with something else (airplanes), that are much better at flying than birds (in some regards), and much there is nothing in nature so big, that can fly (nothing that we know of). IMO AGI could be similar.. despite its dissimilarities with biological brains, if it looks like a duck, quacks like a duck, swims like a duck, then it probably is duck (and perhaps better than duck in some ways).

thoi234324234 2y ago

Does it matter ? Openworm still hasn't succeeded.

nomilk 2y ago

> Data available for download, programmatic access and interactive browsing and have been made interoperable with other fly data resources Curious what a 'fly brain map' looks like - iss the download a 3D model, or a matrix with values for attributes?

idlewords 2y ago

It thinks a lot about fruit.

khazhoux 2y ago
Can we please stop perpetuating this racist stereotype?
- philodeon 2y ago
  The stereotype sounds way more homophobic to me than racist…

black_13 2y ago

[dead]

perryizgr8 2y ago

So can we run it on a computer now? That's the end goal, isn't it? Or maybe ask an LLM to look at the upload and figure out what makes it tick.

okdood64 2y ago
Why would an LLM in particular be good at this?

yuz 2y ago

So, can it run Doom?

pugworthy 2y ago

They are currently active in my kitchen. I think those thinking that AI and ML need massive compute power and electricity should take note that these little bastards can be annoying and pervasive as hell with just 100k neurons in that little head. And run off ripe bananas.

dennis_jeeves2 2y ago
Indeed it is miracle of evolution (or a creator if that suit you) to be so efficient.

londons_explore 2y ago

If this could be done for a human, I think there is a realistic prospect of perhaps being the first human "brought back to life inside a computer". Sure, the connectome isn't the whole story, but I think it possible that a few hundred years from now we might understand the brain sufficiently to simulate it, and then by inputting this connectome, together with guesses/approximations for the information not captured, that person is effectively time-travelled. Could be amazing for archaeologists - rather than looking at broken bits of pottery and guessing what they're used for, you could literally just ask someone (a brain) from that time.

groestl 2y ago
I fully agree, but at the same time it gives me Black Mirror vibes.
londons_explore 2y ago
On the other hand, I suspect just putting your brain in a jar filled with formaldehyde has similar chances of future humans managing to re-animate it. With a connectome, you can make hundreds of copies of the data round the world. With pickled-brain-in-a-jar you better make sure that jar is well hidden in a dusty basement for long enough to not get chucked out, but not so well hidden future generations never find it.
codeulike 2y ago
https://qntm.org/mmacevedo https://qntm.org/mmacevedo
tim333 2y ago
Long before bringing people back based on analysis of their neurons, there will be many people 'brought back' by something like an LLM acting like them similar to how a human actor sort of becomes someone. There have already been crude efforts and I guess as time goes on they will get better. (eg. the Kurzweils in 2016 https://www.pcmag.com/articles/how-ray-kurzweil-and-his-daughter-brought-a-relative-back-from-the-dead https://www.pcmag.com/articles/how-ray-kurzweil-and-his-daug...)

Nevermark 2y ago

My undergrad research was on identifying synaptic strengths based on firing behavior of networks of simple integrate to threshold neuron models. A toy model compared to real neurons but a good starting place with nice results. We could identify the solution that most robustly reproduced the firing patterns even in the presence of noise. I would be curious how well the connectome documents connection and dendrite/axon geometry, beyond connection paths. For shedding light on behavior related to connection strengths, timing, neuron firing sensitivities, etc. For the stable non-learning model as captured at scanning time. To investigate adaptation purpose & behavior, it helps to understand what operational behavior has been learned.

DrPimienta 2y ago

What wondrous secrets of knowledge await us in such a mighty neurological architecture?

awestroke 2y ago

Related: my favorite HN comment ever from a similar submission a year ago: > There's lots of very exciting work going on around the fully mapped fruit fly connectome. For example, I'm a CTO of a stealth startup that aims to do for utilitarianism what carbon credits did for environmentalism. We are selling 'utility credits' which translates directly into us simulating trillions and trillions of fruit fly brains in a state of constant orgasmic bliss, which you can then buy to offset any actions your company has undertaken that damage global happiness or well-being. We've seen a lot of interest from some pretty large industry players. https://news.ycombinator.com/item?id=36584130 https://news.ycombinator.com/item?id=36584130

ash1794 2y ago
Why!
- neverrroot 2y ago
  Feel good, bragging rights, entitlement
- rtkwe 2y ago
  It's a joke about utilitarianism which has had it's ups and downs but is a philosophy that has some pretty powerful adherents in the tech CEO world, notably the whole effective altruist crowd that SBF came out of. There's the Parable of Felix from SMBC [0] coming at it from the other angle of one incredibly happy person skewing the utility equation to do awful things. [0] https://www.smbc-comics.com/comics/20120403.gif https://www.smbc-comics.com/comics/20120403.gif
FrustratedMonky 2y ago
They have a branding opportunity. Karma Kredits Perhaps a co-branding opportunity with Krispy Kreme donuts? Buy a donut, and experience some Joy, which handily comes with Karma Kredits to offset that Joy. Have some KK with the KK!
- birracerveza 2y ago

crispyambulance 2y ago

Interesting stuff, but I don't understand HOW they've done it. There's something called Connectome Annotation Versioning Engine (CAVE). Which appears to be software(?) which allows researchers to examine a dataset and annotate it in some way. Presumably the dataset consists of images of the neurons themselves and the job is to map which neurons touch which other neurons? That's the thing I am not understanding. How do they get such images in the first place? CAVE is mentioned along with electron microscopy... but I don't understand how an electron microscope can be useful here. Obviously, it's not TEM (which required a very flat specimen). Then, there's SEM, but doesn't that require a conductive sample? In both cases, any electron microscope requires a vacuum to even work, right? How can this be done with something so wet, fragile and 3 dimensional like the brain of a fruit fly? Even worse, the connections are stacked on top of each other. How can an electron microscope image below the surface? TLDR; How is it possible to even image the way the neurons are connected in the first place? ELI5?

svara 2y ago
You perform chemical fixation and heavy metal staining, then some form of serial sectioning. You can either image the sections themselves or serially image the block face. The sections can be imaged with TEM or SEM in high vacuum, the block face can be imaged with SEM. The resulting 3d volume can be segmented with neural networks. CAVE is for manual editing / correction on top of the automatically generated segmentation.

0xedd 2y ago

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danbruc 2y ago

Do we understand how memory works in general? If you tell me to remember the number 71, I can do that instantly with my short term memory, so I would guess that works without any changes to the brain structure and more like charging or discharging the tiny capacity in a DRAM cell or flipping the feedback loop in an SRAM cell. For long term memory on the other hand I would assume that this involves changes to the brain structure as this seems more robust but slower to do, I would have to think of 71 for quite some time in order to remember it weeks, months or years later. Do we know anything about this in good detail or is this still too hard to investigate because the relevant structures or processes are hidden in a sea of other things?

achileas 2y ago
We don't really know much about how memories are formed, the short-term and long-term divisions come from cognitive psychology and we don't have (from what I remember from my neuro days, which may be out of date by now but I am friends with several neuroscientists and I'm not sure it's out of date yet) a strong idea of what the biological correlates of each are, or even if they arise via different processes or what.

ignoramceisblis 2y ago

A 3D interactive interface, which has been around for several years now: https://flycircuit.neuronlp.fruitflybrain.org/ https://flycircuit.neuronlp.fruitflybrain.org/