I've been editing this article about "brain mapping" and... connectomics, and I'm just stunned by how quickly the cost estimates to map, say, a mouse brain have plummeted in just the last couple years. It actually seems feasible that we could map the entire human brain -- all 86 billion neurons, and their connections -- in this lifetime. In the 1970s, Sydney Brenner started mapping all the connections between neurons in C. elegans. His team sliced the worm into thin pieces, took photos using an electron microscope, and manually traced and reconstructed each synapse for 302 neurons total. This project took more than a decade of work, and it cost about $16,500 to reconstruct each neuron. Scaling this up to a human brain boggles the mind. Electron microscopy remained the norm in connectomics for decades, because it was the only option available to see synapses at a resolution high enough to be able to trace their paths. Each electron microscope costs several hundreds of thousands of dollars, though, and you need lots of them to map even a mouse brain in a reasonable timeframe. In 2023, the Wellcome Trust released a report estimating how long, and how expensive, it would be to map the mouse connectome (~70M neurons). They estimated that imaging alone would cost $200-300M, and that proofreading (or ensuring that traces between neurons are correct) would cost $7-21 BILLION. (A human can only manually trace about 1 mm of neuron per hour.) Also, the images would occupy about 500 petabytes of data, and getting those data would require 20 electron microscopes running in parallel for about 5 years, continuously. They estimated the whole project would take about 17 years of work. This is, understandably, insane. But now it seems like there's an actual path toward mapping the full mouse brain in about five years for ~$100M dollars. There have been three major breakthroughs in the last year or so: 1/ Expansion microscopy, first developed in 2015, showed that it's possible to "enlarge" the brain by about 5x using a swellable polymer. But an improved method increases this number to >20x expansion, meaning we can now expand brains and image neurons much more easily using cheap light microscopes, rather than expensive electron ones. 2/ E11 Bio (a nonprofit research org) developed protein barcodes that get delivered into brain tissue; each neuron gets a unique combination of barcodes. These cells are then stained with colorful antibodies, which stick to a matching protein barcode, causing each neuron to light up in a distinct color. This makes tracing neurons so much easier. 3/ Google Research released PATHFINDER this May, an AI-based neuron tracing tool that can proofread about 67,200 cubic microns of brain tissue per hour, with very high accuracy. It works on electron micrographs, but something similar could be presumably be developed for the E11 / colorful tag approach. This is an extremely exciting time for neuroscience. (C. elegans connectome below.)show more

E11 Bio is excited to unveil PRISM technology for... mapping brain wiring with simple light microscopes. Today, brain mapping in humans and other mammals is bottlenecked by accurate neuron tracing. PRISM uses molecular ID codes and AI to help neurons trace themselves. We discovered a new cell barcoding approach exceeding comparable methods by more than 750x. This is the heart of PRISM. We integrated this capability with microscopy and AI image analysis to automatically trace neurons at high resolution and annotate them with molecular features. This is a key advance towards economically viable brain mapping - 95% of costs stem from neuron tracing. It is also an important step towards democratizing neuron tracing for everyday neuroscience. Solving these problems is critical for curing brain disorders, building safer and human-like AI, and even simulating brain function. In our first pilot study, we acquired a unique dataset in mouse hippocampus. Barcodes improved the accuracy of tracing genetically labelled neurons by 8x – with a clear path to 100x or more. They also permit tracing across spatial gaps – essential for mitigating tissue section loss in whole-brain scaling. Using molecular annotation, we uncover an intriguing feature of synaptic organization, demonstrating how PRISM can be used for systematic discovery 🧵show more

166,700 fruit fly neurons just took over 3 drones,... and nobody taught them to fly. Scientists mapped the full brain of 1 real fly, every neuron and all 25 million connections, and put it online for free. Someone copied that brain 3 times and plugged each copy into a drone. No flight code, no gesture presets, no "avoid the chair" rule, just a camera feeding the fly's eyes and neurons turning into throttle. 1 drone hovers, 1 slips past a chair, 1 drops to the floor and holds. This brain spent 350 million years learning to stay in the air, and now it's back where it belongs. No GPUs, no training run, no $100B data center, just a brain smaller than a grain of salt. 1 fly gives you 3 pilots, and 1,000 flies give you a swarm. The fly is dead, but its brain just got a squadron.show more

did something similar, with a map of the brain... showing which neurons are firing in realtime and a readout of what the fly decided to doshow more

A dead fruit fly was sliced into 66 pieces.... Now its 166,700 neurons are driving robots. Nobody trained it, no dataset, no reward function, no GPU farm, just the wiring. The fly took a second to die, but copying it took 7 microscopes running nonstop for a year, shaving it 1/10,000 of a hair at a time and photographing every layer before the next cut. AI rebuilt it from the scraps, eyes to legs with the neck still attached, 124M synapses and 11,710 cell types, 44 years of human labor finished by machines. Scientists first tried this in 2008 and guessed it would take 500 people 10 years. Then the internet got the file and someone gave it a body. Camera → fly eyes → 166,700 spiking neurons → descending neurons → motors. One of those neurons is DNp01, the giant fiber, the cell that fires when your hand comes down. Push an object at the camera and the looming detectors light up, so the robot swerves. It took 0 training runs, just the same reflex that gets a fly out from under a swatter in 100 milliseconds. Then came the control test, where they kept all 138,639 neurons and shuffled where the synapses connect. The behavior died. The intelligence was never in the neurons, it was in the map. The fly is gone, but the flinch is still running.show more

You’re looking at neurons growing and connecting in real... time 🧠. A 65-hour recording of hippocampal activity in a rat brain. The hippocampus plays a crucial role in memory and learning. In this footage, neurons extend their dendrites and axons, building and reshaping connections across days. Capturing this process live offers a rare view into how neural circuits form and reorganize. Why this matters ⬇️ 1️⃣It’s a continuous, multi-day recording of living hippocampal neurons under the microscope 2️⃣You can clearly see dendritic branching and network formation 3️⃣It reveals the dynamic processes that drive brain development and plasticity Observing growth at this resolution helps researchers understand how neurons connect—and how disruptions in these processes might contribute to neurological or psychiatric conditions. Credit to Louis Romet and Dr. Christophe Leterrier for the videoshow more

THIS ROBOT HAS A DEAD FLY'S BRAIN AND IT... WALKS LIKE A FLY scientists sliced the fly into thousands of layers thinner than a virus to copy every wire in its body the fly didn't survive the map did: 166,700 neurons, from the brain all the way down to the legs so somebody built it a new body six metal legs, 18 motors, two camera eyes and a battery strapped to its back no walking code, they just wired the leg neurons into the motors and switched it on > it turned its head and looked straight at the camera > then it walked, three legs down, three legs up, the exact way a real fly does > when someone reached for it, it froze > when the hand got closer, it ran nobody taught it any of that the fly has been dead for years, and its brain still knows how to escape next on the list is a mouseshow more

A STUDENT TURNED A FRUIT FLY BRAIN INTO AN... AI AGENT AND STEERS IT WITH HER BARE HAND Google and HHMI Janelia spent 10 years mapping the nervous system of 1 male fruit fly, and on September 3 they released the whole map for free. 166,700 neurons and 24.5M synapses, every wire from eye to leg. She ran all of it as a leaky integrate-and-fire simulation and then gave it a job. The top-right panel is the brain firing live, the robot on the left is the agent it drives. A camera tracks her fingers, the movements hit the fly's sensory neurons, and whatever motor neurons fire decide what the agent does. Status: IDLE Pinch → RUNNING IMPLEMENTATION Point → SPINNING UP NEW IMPL Pull back → HEAVY LIFTING The catch: this is not a living fly but a computer model of real wiring, and she built the link between her hand and its neurons. 12 days ago this brain was a dataset Then it played DOOM Then Chrome Dino Then it walked a Strandbeest Now it works for a student. The fly died years ago, but its wiring still takes orders.show more

I successfully compressed the complete fruit fly brain, including... all 139,255 neurons and their connections into approximately 43 MB. Storing the entire connectome on Bitcoin will require around 110 separate Ordinal inscriptions of up to 350 KB each, making the process expensive. To help fund this process, we are considering creating a very limited collection of digital insects, although the exact details are still being defined. Through our neural engine, the fly’s brain could potentially control these other digital insects, influencing their movements, reactions, and behavior The goal is not merely to inscribe a brain as static data, but to make it functional,using the on-chain connectome as the foundation for an autonomous digital ecosystem living entirely on Bitcoin. This remains an experiment with much still to develop, but the vision is clear: preserve the brain, activate it, and create a world where it can continue to existshow more

We Open-Sourced a Quantized Fruit-Fly oBrain on GitHub 95%... Smaller, ~98% as Accurate as the Published Connectome We quantized the entire fruit-fly nervous system that Google Research, HHMI Janelia, and collaborators published — the complete male Drosophila central nervous system, on the order of 166,000 neurons and a massive synaptic graph — and compressed it by about 95% while retaining roughly 98% of the original simulation accuracy. That is the technical claim. The more important decision is what happens next. After the oBrain team met and debated it, we made a final call: we will not keep this brain closed. We are open-sourcing it on GitHub so researchers, builders, skeptics, and anyone obsessed with biological computation can inspect the weights, the wiring, the quantization path, and the benchmarks. If a “brain” is going to live on-chain, it has to be checkable. Closed source would make that impossible. This is the same instinct that made OpenClaw🦞 a public harness instead of a private assistant, that made Hermes / Nous Research ship agent stacks in the open, and that NVIDIA keeps repeating: the strongest systems are the ones a community can attack, fork, and improve. What we actually released A quantized runtime of the published fly CNS, not a cartoon “inspired by” a fly. A size cut of ~95%, so more people can load, step, and experiment without a research cluster. Accuracy held near 98% against the reference simulation of the published connectome. Source, evaluation notes, and the path to reproduce the comparison — on GitHub, in public. Nothing inside this connectome was “trained” into being a fly. The wiring is the published map. Quantization is an engineering layer so the same graph can run cheaper, smaller, and — in our case — in environments where you can put a brain on-chain and still let outsiders verify it. Why open source, and why on-chain A biological brain map is only as useful as the number of people who can run it and try to break the claims. If we say the on-chain brain matches the Google-published fly brain, that statement is worthless unless you can: pull the code, pull the quantized artifacts, run the same probes, compare spike statistics, circuit responses, and size/accuracy tradeoffs, publish a counter-benchmark if we are wrong. That is the point of this release. Open source so the on-chain brain can be independently verified against the published connectome — and so the community can actually use it. We want people to ask hard questions: Which circuits survive quantization, and which degrade first? Do sensory-to-descending pathways still fire in the right order? How does batch simulation, GPU vs CPU, and lower precision change behavior? What does “98% accuracy” mean for a specific cell type, not just a global score? Can the compressed graph be hashed, attested, and stepped in a verifiable way on-chain without turning the science into marketing? If those questions annoy us, good. That is how a public brain should work. Who this is for Neuroscientists who already live in MaleCNS / FlyEM data. Systems people who care about sparse graphs and event-driven simulation. Quantization researchers who are tired of toy models. Crypto builders who want an on-chain object that is more than a JPEG of a neuron. Students who should not need a petabyte pipeline just to poke a looming detector and watch a giant fiber. Come read the repo. Run the reference vs quantized comparison. File issues. Propose better compressors. Port it. Wrap it. Attack the accuracy number until it is either solid or replaced by a better one. The published fly brain was already a gift to science. Keeping a compressed, runnable version locked behind a private wall would have been a waste of that gift. The brain is on GitHub. Fork it. Measure it. Make it better.show more

🚨 SCIENTISTS JUST BUILT AN ARTIFICIAL RETINA THAT RESTORES... VISION AND ADDS INFRARED SIGHT. Researchers at Yonsei University in South Korea have developed a flexible, three-layer implant that bypasses dead photoreceptors and directly stimulates healthy retinal ganglion cells. The device not only helps restore vision in cases of retinal degeneration (like retinitis pigmentosa) but also gives the eye the ability to detect near-infrared light that humans normally cannot see. The key innovation is a soft 3D array of liquid metal micropillars (gallium-indium alloy) that gently conform to the curved retina without causing damage or inflammation a major improvement over rigid electrodes used in earlier implants. Why this matters: • Retinal diseases destroy light-sensing cells, but the neurons deeper in the eye often remain healthy and capable of sending signals to the brain • The implant uses an ultrathin filter + phototransistor array to convert near-infrared light into electrical signals the ganglion cells can understand • In mouse tests, blind animals regained visual responses, while healthy mice gained infrared sensitivity on top of their normal vision • The liquid metal electrodes are soft and biocompatible, dramatically reducing the risk of scarring or tissue damage The deeper implication: This isn’t just about restoring lost vision it’s about augmenting human sight. If it reaches human trials and proves safe long-term, people with partial vision loss could keep their remaining natural sight while gaining an entirely new sensory channel (infrared). The biggest open question is how the human brain would interpret this new stream of information whether it would feel like a new color, an overlay, or something else entirely. We’re moving from “fixing blindness” to “expanding what it means to see.” How do you think gaining the ability to see infrared light would change daily life or human perception? Follow for more frontier neurotechnology and bionic vision breakthroughs.show more

🚨 SCIENTISTS ARE USING AI TO MAP A HIDDEN... “CLEANING SYSTEM” INSIDE THE HUMAN BRAIN AND IT COULD CHANGE HOW WE UNDERSTAND SLEEP, AGING, AND NEURODEGENERATIVE DISEASE. It’s called the glymphatic system a vast network of fluid channels that flushes toxic waste from the brain while you sleep. For years it was almost impossible to observe in detail. Now AI-powered imaging is revealing it like a living galaxy of microscopic rivers and pathways inside neural tissue. Why this matters: Your brain produces toxic proteins constantly. The glymphatic system is one of its primary waste-clearance mechanisms clearing the very proteins linked to Alzheimer’s, Parkinson’s, and other neurodegenerative diseases. But here’s the unsettling part: This cleaning system becomes dramatically less efficient with age, poor sleep, stress, and brain injury. Sleep may not just “rest” your mind it may literally wash your brain. The deeper implication is staggering: The brain isn’t just a computer. It’s a dynamic, living network that constantly rebuilds and cleanses itself in real time. The more we map it, the more it looks like an entire universe of connected energy flows inside our skulls. What if some neurological diseases begin when the brain can no longer properly “wash” itself at night? Follow for more frontier neuroscience and future technology.show more

Americans handed over about 253 billion dollars in credit... card interest and fees in a single year, and for millions the debt never actually shrinks. Total household debt in the United States just hit a record of about 18.8 trillion dollars. Credit cards are only a slice of that, but they are the cruelest slice, because the interest rate almost never drops below 20 percent. Here is what that does. If you carry a balance of 5,000 dollars and pay only the minimum, it can take more than 15 years to clear, and cost you more than 6,000 dollars in interest alone. You end up paying for the same purchase twice. The amount Americans pay each year just in card interest is now more than triple what it was in 2021. This is not an accident of the market. High rates and low minimum payments are built to keep you paying, slowly, for as long as possible.show more

Google just gave away the full wiring diagram of... a fruit fly's brain, and a student turned it into an AI agent. Google and HHMI Janelia spent 10 years mapping the full nervous system of one male fruit fly, then released the complete map for free on September 3. 166,700 neurons. 24.5 million synapses. Every wire from eye to leg, mapped and public. She turned the wiring into a leaky integrate and fire simulation and gave it a job. A camera tracks her fingers, the movement hits the fly's sensory neurons, and whatever motor neurons fire decide what a robot does on the other side of the screen. ▪ Pinch triggers running implementation ▪ Point spins up a new implementation ▪ Pull back triggers heavy lifting Twelve days ago this brain was just a dataset. Then it played DOOM. Then Chrome Dino. Then it walked a Strandbeest. Now it works for a student. This isn't a living fly. It's a computer model of real wiring, and she built the bridge between her hand and its neurons herself. The fly died years ago. Its wiring still takes orders.show more

🚨Iranian scientists build lab-grown artificial brain from living human... neurons Iran has mastered the technology for growing nerve cells outside the human body 🔸 Living neurons create synapses and learn like a real human brain 🔸 The new technology is up to 1 million times more energy-efficient than silicon microchips 🔸 It also shows a major increase in processing speed The breakthrough puts Iran in the global race for organoid intelligenceshow more

The newest Alzheimer's treatment cost $30,000 a year, and... can cause brain hemorrhages in up to 30% of people who take it. According to Dr. David Pearlmutter, a neurologist who's spent 40+ years studying the brain. So why would anyone take it? (1/16)show more

166,000 neurons from a dead fruit fly now hunt... drones from a bedroom desk. A white drone the size of a palm lifts off the carpet, and a black 3D-printed turret on the desk swings after it, with the fly's brain working its 2 stepper motors, 1 camera and 2 barrels through a nest of rainbow wires on a breadboard. That brain sits in the top-left corner of the screen and flares every time the drone jerks. A Patriot interceptor costs about $4 million, and armies are firing them at drones worth a fraction of that. This brain is smaller than a poppy seed, and Google put it online for free 2 weeks ago. Then someone gave it a job it was built for. Most of a fly's brain exists to see motion, and this brain is male, and male flies spend their lives chasing whatever moves. The drone climbs past the ceiling fan and the crosshair climbs with it, then drops when it drops. For 18 seconds it never loses the drone. In the last shot the drone flies home to the guy holding the controller, and the crosshair follows it right onto his chest. It spent its whole life dodging swatters. Now it's the one aiming.show more

Have you seen a complete map of the neurons... in a baby fruit fly brain? Credits: Johns Hopkins University and University of Cambridge #MedTwitter #neuroscienceshow more

166,700 fruit fly neurons are flying a drone around... my bedroom. 1 camera watches my open hand and that's the whole input. The panel in the middle is the brain running live 166,700 neurons, 25 million connections, the full reconstructed map of a fruit fly's head. Camera reads the hand, the brain fires, the output becomes throttle. Open palm and it climbs, fist and it holds, drop the hand and it comes down. 4 propellers the size of a coin hanging off a nervous system that belonged to an insect. The honest part this is a computational model, not a resurrected fly, the wiring is biological, the drone is mine, I built the bridge between them. I never wrote flight logic, no PID tuning, no gesture presets, I gave the neurons somewhere to send the signal and they found the ceiling. 11 seconds in, it holds altitude on its own. The fly is dead and it's still flying.show more

Today on The Science and Experience of Energy, we... describe mysterious mitochondria-like particles that we found in blood and saliva using high-resolution electron microscopy. These particles had double membranes, and some had folds in the internal membrane—a feature that is unique to mitochondria. We don’t yet know what exactly these particles are or their purpose, but we're excited to learn more about them. The massive image database is the first of its kind—have a look if you want to see what circulates in the human blood. Thanks to NIH and Baszucki Group who've supported our work, this resource is freely available to everyone.show more