[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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