An adult fruit fly brain has been mapped

The paper published in Nature, which is open access: <a href="https:&#x2F;&#x2F;www.nature.com&#x2F;articles&#x2F;s41586-024-07558-y" rel="nofollow">https:&#x2F;&#x2F;www.nature.com&#x2F;articles&#x2F;s41586-024-07558-y</a>

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Related: my favorite HN comment ever from a similar submission a year ago:<p>&gt; There&#x27;s lots of very exciting work going on around the fully mapped fruit fly connectome. For example, I&#x27;m a CTO of a stealth startup that aims to do for utilitarianism what carbon credits did for environmentalism. We are selling &#x27;utility credits&#x27; 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&#x27;ve seen a lot of interest from some pretty large industry players.<p><a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=36584130">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=36584130</a>

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&#x27;ve ever seen neurones being grown (go search YT), you&#x27;ll see it&#x27;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.

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.<p>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&#x27;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.

My undergrad research was on identifying synaptic strengths based on firing behavior of networks of simple integrate to threshold neuron models.<p>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.<p>I would be curious how well the connectome documents connection and dendrite&#x2F;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.<p>To investigate adaptation purpose &amp; behavior, it helps to understand what operational behavior has been learned.

There is this interesting past post:<p>Whole-brain connectome of the fruit fly (2023) <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=36568609">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=36568609</a>

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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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?

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

What does it mean &quot;mapped&quot;. Does it mean we know what each nerve&#x2F;axon does?

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

Is this correct?<p>It this like knowing only this:<p>which neuron is connected to which neuron<p>But you don&#x27;t know:<p>the values of the weights (the value of the neuron, or the parameters)<p>the activation functions<p>what circuit do neurons implement (fully connected? CNN?)

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?

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.

&gt; Data available for download, programmatic access and interactive browsing and have been made interoperable with other fly data resources<p>Curious what a &#x27;fly brain map&#x27; looks like - iss the download a 3D model, or a matrix with values for attributes?

If this could be done for a human, I think there is a realistic prospect of perhaps being the first human &quot;brought back to life inside a computer&quot;.<p>Sure, the connectome isn&#x27;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&#x2F;approximations for the information not captured, that person is effectively time-travelled.<p>Could be amazing for archaeologists - rather than looking at broken bits of pottery and guessing what they&#x27;re used for, you could literally just ask someone (a brain) from that time.

So, can it run Doom?

&quot;human brains could follow&quot; 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&#x27;s 6 orders of magnitude larger. that&#x27;s like saying &quot;A map of San Francisco has been completed, the entire solar system could follow!&quot;

A 3D interactive interface, which has been around for several years now: <a href="https:&#x2F;&#x2F;flycircuit.neuronlp.fruitflybrain.org&#x2F;" rel="nofollow">https:&#x2F;&#x2F;flycircuit.neuronlp.fruitflybrain.org&#x2F;</a>

Interesting stuff, but I don&#x27;t understand HOW they&#x27;ve done it.<p>There&#x27;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&#x27;s the thing I am not understanding. How do they get such images in the first place?<p>CAVE is mentioned along with electron microscopy... but I don&#x27;t understand how an electron microscope can be useful here. Obviously, it&#x27;s not TEM (which required a very flat specimen). Then, there&#x27;s SEM, but doesn&#x27;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?<p>TLDR; How is it possible to even image the way the neurons are connected in the first place? ELI5?

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.

Better source: <a href="https:&#x2F;&#x2F;www.nature.com&#x2F;articles&#x2F;d41586-024-03190-y" rel="nofollow">https:&#x2F;&#x2F;www.nature.com&#x2F;articles&#x2F;d41586-024-03190-y</a>

So can we run it on a computer now? That&#x27;s the end goal, isn&#x27;t it? Or maybe ask an LLM to look at the upload and figure out what makes it tick.

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

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

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

Does it matter ?<p>Openworm still hasn&#x27;t succeeded.

It thinks a lot about fruit.

Interesting, with all of the BS around LLM training sucking up other peoples&#x27; 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.

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

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.<p>Get there and its full of flies.

A big reason for my imminent-AGI Skepticism is the fact that our understanding of the currently existing, Biological intelligence is so, so shallow.<p>We&#x27;re here at &quot;Systems level sketch of a fruit fly brain&quot;. It&#x27;s incredible work! But as other comments detail, there is far more to the function of a fly brain than this &quot;map&quot;. It&#x27;s quite a long way from &quot;Deep understanding of a Human Brain, to the point where we can begin engineering a replica&quot;.<p>Maybe we&#x27;ll get lucky, and find that &quot;Neural Network&quot; 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.