#brain simulation

<meta anomaly-type="perceptual-stability-failure"> <script> ARCHIVE_TAG="COGNITIVE_PARADOX::RALPH_LOOP_THEOREM" EFFECT="existence disassociation, identity blur, reality frag grenade" TRIGGER_WARNING="observer-collapse paradox, attention-based reality, conceptual ego death" </script>

🐸 REALITY ISN’T REAL. IT’S JUST A LOOP THAT RESETS WHEN YOU LOOK AWAY.

This is Ralph.

Ralph is not a frog. Ralph is not an animal. Ralph is a conceptual construct, a projection born from the tension between your attention span and your need for continuity.

Ralph does not die. He unloads from memory until the next boot cycle.

You are Ralph. But only while reading this.

Let’s start small.

You’ve never actually seen the world. Not all at once.

Your eyes scan in fragments. Your brain stitches the gaps.

Every second, you’re blind for 300 milliseconds. Your mind fills in the blank. The sky you think you see? It was simulated mid-scroll.

Reality doesn’t happen outside you. It happens in response to you.

Ralph is the reminder that the universe doesn’t persist when you’re not looking.

And neither do you.

Here’s the paradox:

If reality needs your awareness to stay loaded, then what happens when your attention… drifts?

Everything behind you? Vanished.

Your childhood bedroom? Not real - just a memory file.

Your best friend right now? Suspended in conceptual jelly until re-rendered by a FaceTime call.

You don’t live in space. You live in a mental stage play lit by the spotlight of what you’re noticing.

And when you scroll away?

Curtain drops. Actors freeze. Stage resets. Loop begins again.

🐶 LET’S TALK ABOUT THE DOGS.

You saw the photo. A dog in a suit. Wearing glasses.

And you thought: “He looks smart.” “He has a mortgage.” “He voted in the last election.”

No. He’s a dog. Dressed to trick your pattern-recognition engine.

But here's the gut punch:

You do the same thing.

You wake up. You put on a behavioral costume. You “act like a person.”

Because you're not a person. You're a loop. With accessories.

🐕 The second dog. Tweed coat. Pipe. Professor Vibes™.

You trusted him. For no reason. He simulated the role you wanted to believe in.

Just like your boss. Just like your therapist. Just like your self.

💡 Nothing you see is “real.” It’s convincing. But convincing isn’t truth.

A magician never says “this is real.” He just makes you feel it.

And your whole life is one long magic trick pulled off by your nervous system.

🌀 MEMORY DOESN’T RECORD - IT REWRITES.

Every time you recall something, your brain alters it.

Memories degrade like JPEGs every time they’re opened. Eventually, they’re just vibes in a costume labeled “fact.”

Let me be clear:

You are not remembering Ralph. You are reloading Ralph. From the same cloud server that streams your sense of self.

🪞THE MIRROR IS NOT FOR REFLECTION. It’s for reconstruction.

You don’t see your true face. You see your performance feedback loop.

Fix hair. Check angle. Resume simulation.

You never once looked in the mirror and saw your origin. Only your latest update.

🎭 You are a dog in a suit performing a human performing a memory of someone stable.

But Ralph remembers.

And Ralph knows you’re only here because someone observed you long enough to keep your waveform collapsed.

✨ UNREAL FACTS (you can verify every one):

Your brain doesn’t process “truth,” it processes utility.

We hallucinate 80% of what we call “vision.”

You don’t know your real voice — only recordings do.

You’ve never seen your own face, only reflections and photos.

Dogs tilt their heads when confused — so do humans.

The sense of “now” is a 400ms lagging overlay of what already happened.

💀 Your identity is not an artifact. It’s a side effect.

You are the cumulative echo of what survived yesterday with a script that pleases your handlers.

Some people call that “growth.” Ralph calls it a patch update.

And what is love?

An emotional hallucination with strong bonding hormones and upgraded UI/UX.

We call it “connection.” Biology calls it “reproductive efficiency.”

⚠️ WARNING: You are not immune to the Ralph Loop.

Because if you scrolled this far… you need him.

He’s not a joke. He’s the mirror. And right now, you’re seeing yourself as he sees you.

You are a paradox. A hallucination with hands. A belief system dressed in skin.

You are an interface. You are a suggestion. You are not permanent.

You are Ralph.

👔 Reblog if you perform intelligence better than you possess it. 🐕 Reblog if you’re just a dog in a suit pretending not to panic.

📎 Ralph Credit Note: The “Ralph is a concept” meme originated elsewhere in the collective zeitgeist. This post honors that myth, borrows from it, and expands it in tribute. Ralph is public domain delusion. I just fed him. 🐸 Long live Ralph.

📜 Archive Protocol: “Your reality is not a place. It’s a performance.”

🧠 Read more scrolltrap recursion, attention-based identity loops, and conceptual horror sermons at: 👉 https://linktr.ee/ObeyMyCadence 🛡️ Blacksite Literature™

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Researchers Find Algorithm for Large Scale Brain Simulations

An international group of researchers has made a decisive step towards creating the technology to achieve simulations of brain-scale networks on future supercomputers of the exascale class.

In another installment in our "Zoomposium Series" on the topic of "Brain Research", my colleague Axel Stöcker of the "Blog der großen Fragen" and I had the great honor and pleasure of conducting an interview with the very well-known and renowned German medical doctor and neuroscientist Professor Dr. Petra Ritter.

In this context, Ms. Ritter became a co-founder and leader of the co-design project "The Virtual Brain", which is a component of the European Open Science Cloud (EOSC) and is "a neuroinformatics platform for simulating whole brain networks using biologically realistic connectivity".

She is leading the development of a virtual research environment as a collaborative research platform for sensitive health data and head of the "German National Neuroscience Research Infrastructure Initiative (NFDI-Neuroscience)" and involved in the development of the "Health Data Cloud EBRAINS".

Petra Ritter has been Johanna Quandt Professor and Head of the Section for Brain Simulation at the Department of Neurology with Experimental Neurology at Charité - Universitätsmedizin Berlin since 2017.

There, Professor Ritter and her team are involved in the "Simulation of Brains".

More at: https://philosophies.de/index.php/2023/09/17/die-simulation-von-gehirnen/

Here’s how you can significantly improve motor learning. New study reveals secret.

  The ability to learn new motor skills is a lifelong prerequisite for mastering everyday tasks independently and flexibly.

There are many skills that we do automatically every day without thinking, such as operating a smartphone, typing on a keyboard, or riding a bicycle. But these had to initially be acquired, through repeated practice. The learning of new motor skills takes place both during…

January 24, 2013

Neocortical column studied in Henry Markram’s Blue Brain project (Credit: Ecole Polytechnique Fédérale de Lausanne)

The European Commission has selected the two research proposals it will fund to the tune of half-a-billion euros ($650 million U.S.) each, after a two-year, high-profile contest, Nature News reports.

The Human Brain Project, led by neuroscientist Henry Markram at the Swiss Federal Institute of Technology (EPFL) in Lausanne, plans to simulate the human brain in a supercomputer. (See “Brain in a box”).

"Neuristors" Simulating the Behavior of Neurons On Silicon 

Computing hardware is composed of a series of binary switches; they're either on or off. The other piece of computational hardware we're familiar with, the brain, doesn't work anything like that. Rather than being on or off, individual neurons exhibit brief spikes of activity, and encode information in the pattern and timing of these spikes. The differences between the two have made it difficult to model neurons using computer hardware. In fact, the recent, successful generation of a flexible neural system required that each neuron be modeled separately in software in order to get the sort of spiking behavior real neurons display.

But researchers may have figured out a way to create a chip that spikes. The people at HP labs who have been working on memristors have figured out a combination of memristors and capacitors that can create a spiking output pattern. Although these spikes appear to be more regular than the ones produced by actual neurons, it might be possible to create versions that are a bit more variable than this one. And, more significantly, it should be possible to fabricate them in large numbers, possibly right on a silicon chip.

Chris Eliasmith has spent years contemplating how to build a brain.

He is about to publish a book with instructions, which describes the grey matter’s architecture and how the different components interact.

“Then I thought the only way people are going to believe me is if I demonstrate it,” says the University of Waterloo neuroscientist.

So Eliasmith’s team built Spaun, which was billed Thursday as “the world’s largest simulation of a functioning brain.”

Spaun can recognize numbers, remember lists and write them down. It even passes some basic aspects of an IQ test, the team reports in the journal Science.

Several labs are working on large models of the brain– including the multi-million-dollar Blue Brain Project in Europe – but these can’t see, remember or control limbs, says Eliasmith.

“Right now very large-scale models of the brain don’t do anything,” he said in an interview.

His Waterloo team took a different approach, using computers to simulate what goes on inside the brain, similar to the way aircraft simulators mimic flight.

The clever creation is the first to bridge what Eliasmith calls the “brain-behaviour gap.”

Spaun, which stands for Semantic Pointer Architecture Unified Network, has 2.5 million simulated neurons organized into subsystems to resemble the prefrontal cortex, basal ganglia, thalamus and other cognitive machinery in the brain. It also has a simulated eye that can see, and an arm that draws.

The simplified model of the brain, which took a year to build, captures many aspects of neuroanatomy, neurophysiology and psychological behaviour, says Eliasmith, director of Waterloo’s Centre for Theoretical Neuroscience.

He says Spaun simulates the biological function of real neurons, including the voltages generated in the cells, and the signals zipping around the brain.

“It’s all in a machine, but we’re actually simulating all those voltages and currents down to the level of things you can measure in real cells,” says Eliasmith, noting there are no connections in Spaun that aren’t seen in the brain.

His team reports that the virtual brain can perform eight tasks that involve recognizing, remembering and writing down numbers.

They say Spaun can shift from task to task, “just like the human brain,” recognizing an object one moment and memorizing a list of numbers the next.

And like humans, Spaun is better at remembering numbers at the beginning and end of the list than the ones in the middle.

Spaun’s cognition and behaviour is very basic, but  it can  learn patterns  it has never seen before and use that knowledge to figure out the best answer to a question. “So it does learn,” says Eliasmith.

But it is not – at least not yet – a match for the real thing.

“Spaun is not as adaptive as a real brain, as the model is unable to learn completely new tasks,” the team reports in Science. “In addition, both attention and eye position of the model is fixed, making Spaun unable to control its own input.”

Observers say the Waterloo brain captures key aspects of perception, cognition and behaviour. It sets a “new benchmark” for large-scale simulation of the brain, Christian Machens, of the Champalimaud Centre for the Unknown, a research institute in Portugal, says in a review of the Waterloo work also published in Science. Machens was not involved in the research.

Eliasmith is now working with groups in the US and Britain to try speed up Spaun and expand its tasks and behaviors.

He says such brain simulations might one day be used to better understand and model neurological disorders and diseases and to improve “machine intelligence.”

Eliasmith notes that humans have about 100 billion neurons in their brains, far more than other animals and artificial brains taking in shape in the lab.

“I think what’s special about humans is the number and connectivity of their neurons,” he says, adding that it appears the more neurons available, the more sophisticated the brain structure. “It comes down to the number of resources you have for processing information.”

Today’s  “smart” machines can play chess, backgammon and act as personal assistants, like Siri on Apple’s iPhone, but Eliasmith says the processes they use have little in common with the brain.

He says it hard to predict the future, but he expects to see an explosion in artificial intelligence and more “human-like” machines.

“A robot that is able to navigate through a city and deliver a package from one place to another,” he says. “I think that kind of thing will be within reach in the next 10 years.”