[HN Gopher] An adult fruit fly brain has been mapped
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       An adult fruit fly brain has been mapped
        
       Author : teleforce
       Score  : 226 points
       Date   : 2024-10-02 16:16 UTC (6 hours ago)
        
 (HTM) web link (www.economist.com)
 (TXT) w3m dump (www.economist.com)
        
       | tonetegeatinst wrote:
       | Datahoarder question but can I download the map of the fly?
        
         | ijxjdffnkkpp wrote:
         | 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.
        
         | dekhn wrote:
         | See the FAQ: https://codex.flywire.ai/faq which leads to the
         | API for access: 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.
        
       | mjburgess wrote:
       | 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 wrote:
         | 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/ for some
         | commentary on the challenge in fly;
         | https://en.wikipedia.org/wiki/Adult_neurogenesis for commentary
         | on the larger problem ]
        
         | caseyy wrote:
         | 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 wrote:
         | From 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?
        
         | tgbugs wrote:
         | You don't get the dynamics from connectomes, but you absolutely
         | need them. So it isn't that they are a dead end, it is that the
         | dynamics by themselves are also insufficient and the connectome
         | is insufficient, you need both. Further, if you want to
         | actually be able to have anything to attach the dynamics to,
         | you need the cellular anatomy, so connectomes are absolutely
         | necessary. The fact that connectomes are insufficient does not
         | mean that such research is a dead end, but rather that the
         | prerequisites for understanding the nervous system are vastly
         | more complex and demanding than some might have hoped.
        
         | bhouston wrote:
         | It is useful.
         | 
         | It is like getting a static map of the country's roads with no
         | cars on it.
         | 
         | You can not make it come alive with cars (activity), but you
         | can infer where people need to drive but you don't know when
         | and why they drive or what they are doing, but it is a major
         | clue.
        
           | criddell wrote:
           | > It is like getting a static map of the country's roads with
           | no cars on it.
           | 
           | I was thinking it was more like giving somebody iPhone
           | schematics and die shots of all the chips and then asking
           | them to figure out how Portrait Mode works in the Camera app.
        
             | bhouston wrote:
             | Yup, it is similar to that as well. It is a part of the
             | puzzle definitely, but not at all the whole picture.
        
         | rkp8000 wrote:
         | Connectome-adjacent neuroscientist here. Definitely not a dead
         | end! But also definitely not the whole picture.
         | 
         | One of the main open questions in neuroscience right now is how
         | network structure, dynamics, and function are related in the
         | brain. Connectomes provide tremendous insight into structure,
         | but as mentioned this does not generically solve either the
         | dynamics or function problem. For example, for many of these
         | neurons we don't have a good understanding of their input-
         | output relationship, and the nature of this relationship can
         | strongly affect the dynamics that emerge in a highly connected
         | network. Individual variability across connectomes, and how
         | connectomes change over development are also a significant
         | issue, but at least for the fly it's thought that many of the
         | basic structures are pretty conserved across adult animals,
         | even if many of the details could differ.
         | 
         | Modulo these caveats, knowing the physical network structure of
         | the brain does still impose huge constraints on what kinds of
         | models we should be using for gaining insight into dynamics and
         | function. For example, there are well known areas (the
         | "mushroom bodies") with specific feed-forward connectivity
         | patterns that are very different from a random recurrent
         | network. Further, there are at least some areas in the fly
         | brain where we think there are indeed quite clean structure-
         | function relationships, e.g. in the central complex of the fly
         | brain, which contains a physical ring of neurons and is thought
         | to support a "bump" of activity that acts as a sort of compass
         | that helps flies navigate via a ring-attractor-like dynamical
         | system. Thus, even though it has many missing pieces, a wiring
         | diagram like this can be tremendously useful for generating
         | hypotheses to guide more targeted experiments and theoretical
         | studies.
        
           | Animats wrote:
           | How's Open Worm coming along? The connectome of C. Elegans
           | has been known for years, and Open Worm tries to simulate it.
           | [1] Not with enormous success.
           | 
           | [1] https://openworm.org/assets/OpenWormPoster_Celegans_Glasg
           | ow_...
        
           | SubiculumCode wrote:
           | Very Nice. --from a Connectome-Centric neuroimager :) One
           | technique that I am pursuing right now is information
           | decomposition of timeseries to separate the mutual
           | information of two timeseries into redundant and synergistic
           | informational atoms (synnergystic here means the degree to
           | which knowing both timeseries gives you more information than
           | the individual parts give (more than sum of parts). The big
           | limitation of the method is the geometric explosion in
           | complexity of the decomposition as the number of time series
           | grow, with most analyses being limited to two or three times
           | series at a time. However, the scale of the data on which it
           | is applied is not requisite, meaning the approach can equally
           | be used on the mutual information between two regions of
           | interest in rsfMRI , or two spiking timeseries from
           | individual neurons. https://en.wikipedia.org/wiki/Partial_inf
           | ormation_decomposit...
        
         | mjfl wrote:
         | Connectome is a necessary component to understanding dynamics.
        
         | dboreham wrote:
         | You just need to supply your own training data.
        
         | ruthmarx wrote:
         | > It was my understanding that all this connectome-based
         | research was largely a deadend,
         | 
         | There's obviously something to it or implementing what we map
         | in software wouldn't give results as accurately as they do.
        
         | lawrenceyan wrote:
         | Connectomes are like a static graph of a neural network.
         | 
         | But it's the flow of information as signals pass through nodes
         | where everything actually happens.
        
       | fabiensanglard wrote:
       | What does it mean "mapped". Does it mean we know what each
       | nerve/axon does?
        
         | CobrastanJorji wrote:
         | 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/
        
           | mont_tag wrote:
           | Is the data such that it can be modeled in software?
        
             | dekhn wrote:
             | Yes. One example:
             | https://www.biorxiv.org/content/10.1101/2024.03.11.584515v1
        
             | GoblinSlayer wrote:
             | https://github.com/Flowx08/Celegans-simulation
        
             | tsimionescu wrote:
             | 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 wrote:
         | 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.
        
           | bryan0 wrote:
           | > 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.
           | 
           | Apparently they have been able to simulate dynamics with the
           | fruit fly connectome(?) [0]:
           | 
           | > 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.
           | 
           | [0]: https://www.nature.com/articles/d41586-024-03190-y
        
       | ChumpGPT wrote:
       | http://archive.today/vBUjt
        
         | purplejacket wrote:
         | Thanks
        
       | droideqa wrote:
       | There is this interesting past post:
       | 
       | Whole-brain connectome of the fruit fly (2023)
       | https://news.ycombinator.com/item?id=36568609
        
         | dang wrote:
         | Thanks! Macroexpanded:
         | 
         |  _Whole-brain connectome of the fruit fly_ -
         | 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 - March 2023 (1
         | comment)
         | 
         |  _Map of an Insect's Brain_ -
         | https://news.ycombinator.com/item?id=35111371 - March 2023 (119
         | comments)
         | 
         |  _The Connectome of an Insect Brain_ -
         | 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 - March 2023 (5
         | comments)
         | 
         |  _Fruit Fly Brain Map_ -
         | https://news.ycombinator.com/item?id=29672565 - Dec 2021 (1
         | comment)
         | 
         |  _Structure of Fruit Fly Brain (2018)_ -
         | 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 -
         | Jan 2020 (1 comment)
         | 
         |  _Explore the the adult fruit fly brain_ -
         | 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 - Dec 2018 (1
         | comment)
         | 
         |  _A Complete Electron Microscopy Volume of the Brain of Adult
         | Fruit Fly_ - 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 -
         | Feb 2017 (13 comments)
         | 
         |  _Neurokernel: Emulating the Fruit Fly Brain_ -
         | 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 - 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 - Oct
         | 2017 (16 comments)
         | 
         |  _Fruit fly nervous system: new solution to fundamental
         | computer network problem_ -
         | https://news.ycombinator.com/item?id=2103668 - Jan 2011 (13
         | comments)
        
           | idrios wrote:
           | Another for you:
           | 
           | Map of an Insect's Brain -
           | https://news.ycombinator.com/item?id=35111371 - March 2023
           | (119 comments)
        
             | dang wrote:
             | Inserted. Thank you!
        
           | mrguyorama wrote:
           | Out there question: Do you have a hand crafted database of
           | these setup or some sort of macro to take the output of the
           | search api and form it like this, or are you hand editing
           | these lists?
        
       | qafy wrote:
       | "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 wrote:
         | Well assuming the same density it's "only" 100 times bigger in
         | linear dimensions. Doesn't sound quite as crazy...
        
           | twojacobtwo wrote:
           | 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 wrote:
             | The physical process of cutting. We're physically
             | sectioning 3 dimensional blocks of tissue.
        
         | cloudripper wrote:
         | I thought it was intended as more of a pun on questionable
         | displays of human intelligence.
        
         | BurningFrog wrote:
         | 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 wrote:
           | 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.
        
         | inglor_cz wrote:
         | Given that for a map, it is the sqkm which matters, 6 orders of
         | magnitude from the map of San Francisco is a jump from 121 sqkm
         | to 121 000 000 sqkm ... which is not even all dry land on
         | Earth, much less in the Solar System.
         | 
         | Surely a daunting task, but depending on the tools used to
         | create the smaller map, possibly a realistic one. Maybe with a
         | bit of a less precision.
        
       | baanist wrote:
       | 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 wrote:
         | I don't think that drosophila are eutelic
         | (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 wrote:
         | 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 wrote:
           | 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 wrote:
             | They crowdsourced three million manual corrections to the
             | AI output, yeah.
        
       | swayvil wrote:
       | Simulated too? I assume that if you can map it then you can
       | simulate it. Am I correct?
        
         | glial wrote:
         | 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/
        
         | meindnoch wrote:
         | Simulating it would require many orders of magnitude more
         | compute. Biological neurons are not just a sigmoid function.
        
           | roywiggins wrote:
           | > 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
        
         | jknoepfler wrote:
         | 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 wrote:
       | Quite a leap, fruit fly to human....
        
       | PaulKeeble wrote:
       | 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.
        
         | keybored wrote:
         | Cartographers have mapped Scotland. [random scribe muses that]
         | The whole world could be next.
        
           | pepve wrote:
           | 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.
        
       | willcipriano wrote:
       | 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 wrote:
         | Well, the big question is if a human is "just" a mega-fly when
         | it comes to brain structure.
        
         | dekhn wrote:
         | No, beetles (JBS Haldane said god has an "inordinate fondness
         | for beetles")
        
           | phyzome wrote:
           | That may be so, but scientists have an inordinate fondness
           | for flies.
        
         | AStonesThrow wrote:
         | 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 wrote:
         | heaven? not so fast. how about solving captchas at 100x speed
         | for 100 years to aid the development of some ai vision project?
        
       | dmitrysergeyev wrote:
       | https://archive.is/vBUjt
        
       | _giorgio_ wrote:
       | 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 wrote:
         | 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.
        
       | adrian_b wrote:
       | The paper published in Nature, which is open access:
       | https://www.nature.com/articles/s41586-024-07558-y
        
       | dmvdoug wrote:
       | Paging mjg59, Matthew Garrett, Matthew Garrett to the white
       | courtesy phone.
        
       | holtkam2 wrote:
       | What hard steps exist between mapping the physical structure of
       | the brain and simulating a running one via software?
        
         | aithrowawaycomm wrote:
         | 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 wrote:
           | I think it's even more complex. The neurons are like
           | individual raspberry pi. They have both complex logic and
           | physical memory.
        
             | notahacker wrote:
             | 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 wrote:
           | 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.
        
       | beefman wrote:
       | Better source: https://www.nature.com/articles/d41586-024-03190-y
        
       | janalsncm wrote:
       | 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.
        
       | Jun8 wrote:
       | My (maybe very ignorant) question is: can this connectome be used
       | to "run" simulations of a virtual fruit fly, a la MMAcevedo?
        
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