#HumanBrain

The Most Bizarre Neurological Conditions You Never Heard Of

peertube.gravitywell.xyz/w/dc4

2026-01-11

From PsyPost.org: How scientists are growing computers from human brain cells – and why they want to keep doing it: A new race is on to build computers using human brain tissue. Fuelled by venture capital and biotech advances, startups are blurring the line between biology and machines. dlvr.it/TQHX7L News: bit.ly/3LA2jdQ #Neuroscience #Biotech #HumanBrain #ArtificialIntelligence #Bioengineering

2025-11-12

"A spatial transcriptomic atlas of autism-associated genes identifies convergence in the developing human thalamus", Aivazidis et al. 2025
biorxiv.org/content/10.1101/20

"The developing thalamus showed the most prevalent expression of autism susceptibility genes... Within the thalamus, excitatory neurons showed the most enriched expression"

Makes a lot of good sense relative to the hyper- and hypo-sensitivity in autism: the neurons that relay sensory signals to the brain are impacted the most.

Browse the gene expression data:
stageatlas.org/

#neuroscience #autism #HumanBrain

Steve Dustcircle 🌹dustcircle
2025-10-28
Hacker Newsh4ckernews
2025-09-29

Daniel Yon Explains Why Your Brain Is a Brilliant Illusionist | Scientific American

francescoch/Getty Images

September 12, 2025

How Your Brain Constructs—And Sometimes Distorts—Your Experience of the World

 In his new book, Daniel Yon explains how our brain is constantly constructing reality

By Rachel Feltman, Fonda Mwangi & Alex Sugiura

https://playlist.megaphone.fm/?e=SAM4518074123&light=true&artwork=false

Rachel Feltman: For Scientific American’s Science Quickly, I’m Rachel Feltman.

You probably think you’re listening to my voice right now. But what if I told you that you’re actually experiencing a sophisticated hallucination?

Perception isn’t the passive process that most of us imagine it to be, with our senses simply recording reality and sending it up to our brains for processing. Instead, our brains are constantly constructing theories about what’s going on around us—and sometimes our brains get reality wrong.

Here to explain this mind-bending way of looking at, well, the mind, is Daniel Yon, an associate professor of cognitive neuroscience and director of the Uncertainty Lab at Birkbeck, University of London. Daniel is also the author of a recent book called A Trick of the Mind: How the Brain Invents Your Reality.

Thank you so much for coming on to chat with us.

Daniel Yon: Thank you for having me.

Feltman: So why don’t you start by telling me a little bit about your background and how it led you to write your latest book.

Yon: Yeah, so I’m an experimental psychologist and a cognitive neuroscientist, so that means my day job is to try and understand how your mind and brain work and how what happens inside your skull kind of makes the world that you live in.

So the motivation behind my new book, A Trick of the Mind, is that I think that the work that’s been going on in my lab and that which colleagues have been working on around the world gives us a brand-new way of thinking about how our brains work: that your brain is like a scientist. And I think this new idea …

Feltman: Hmm.

Yon: Can shed a lot of light on both the wonderful things [laughs] that your brain gets right but also the ways that our minds and brains can mislead us and get us to perceive and believe things that may not be true.

Feltman: Right. So you, you say that our brains are constantly hallucinating reality and that this is “a feature, not a bug.” Can you explain more what that means for our listeners?

Editor’s Note: Read the rest of the story, at the below link.

Continue/Read Original Article Here: Daniel Yon Explains Why Your Brain Is a Brilliant Illusionist | Scientific American

#2025 #America #Books #Brain #Education #Hallucinations #Health #Human #HumanBrain #HumanExperience #Libraries #Library #LibraryOfCongress #Memories #Perception #Reading #Research #Science #ScienceQuickly #ScientificAmerican #Technology #UnitedStates

2025-08-11

Import AI 424: LLM and human brain similarities https://importai.substack.com/p/import-ai-424-facebook-improves-ads #AI #HumanBrain (similar in some ways)

Why this matters - internal representational complexity maps to computational complexity: LLMs and brains are different - they're built on different substrates (one silicon, the other biological), and their hardware has radically different properties and constraints.
But research like this suggests that these differences may not matter for high-level cognition. What we seem to be discovering is that Al systems exhibit similar representational richness to humans, and the representations we and the machines arrive at appear to agree with one another. This is quite remarkable - we'
re not
dealing with 'stochastic parrots' here, rather we're dealing with things that have as rich an inner representation of reality as ourselves. "The robust and structured mapping between LLM embeddings and visually evoked activities paves the way for new approaches seeking to characterize complex visual information processing in the brain,
" the authors write.
2025-08-11

Import AI 424: LLM and human brain similarities importai.substack.com/p/import #AI #HumanBrain (similar in some ways)

Why this matters - internal representational complexity maps to computational complexity: LLMs and brains are different - they're built on different substrates (one silicon, the other biological), and their hardware has radically different properties and constraints.
But research like this suggests that these differences may not matter for high-level cognition. What we seem to be discovering is that Al systems exhibit similar representational richness to humans, and the representations we and the machines arrive at appear to agree with one another. This is quite remarkable - we'
re not
dealing with 'stochastic parrots' here, rather we're dealing with things that have as rich an inner representation of reality as ourselves. "The robust and structured mapping between LLM embeddings and visually evoked activities paves the way for new approaches seeking to characterize complex visual information processing in the brain,
" the authors write.
2025-07-31

How does cerebral #BloodPerfusion map onto micro-, meso- & macro-scale brain structure? @misicbata &co characterize blood perfusion in the #HumanBrain, revealing how it changes with age & in #NeurodegenerativeDisease @PLOSBiology plos.io/46AEURS

Normative blood perfusion map on lateral and medial views of the inflated and 2D flat cortical surfaces (fsLR). Borders and areal names of the multi-modal Glasser parcellation are overlaid on the flat surface. The figure highlights the non-uniform distribution of perfusion scores across the cortex, with areas that have sharp gradient compared to their underlying perfusion score levels (e.g., LIPv and MT/MST).

WRITER FUEL: How much of your brain do you need to survive? Case reports of people with atypical brains reveal the human brain's staggering ability to adapt to damage.

limfic.com/2025/07/27/writer-f

#WriterFuel #StoryIdeas #Writers #Authors #HumanBrain

2025-07-01

L'IA nous facilite la vie... mais à quel prix ?

Nouvel article choc sur l'impact cognitif de ChatGPT :
"Notre cerveau en danger ?"

⚠️ À lire avant votre prochaine requête IA !
🔗 sharemania.blog4ever.xyz/pourq

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