Thanks for sharing this, Bill โ heartbreaking to see such beautiful ancient forests in danger... Truly appreciate you bringing this to light.
24.11.2025 16:45 โ ๐ 4 ๐ 0 ๐ฌ 0 ๐ 0@zrmor.bsky.social
Postdoc @fz-juelich.de working at the intersection of ML and Neuro: #ai4neuro and #neuroai | Outside the office, mountain and rock climbing ๐๏ธ๐ง๐ปโโ๏ธ https://www.linkedin.com/in/zrmor/
Thanks for sharing this, Bill โ heartbreaking to see such beautiful ancient forests in danger... Truly appreciate you bringing this to light.
24.11.2025 16:45 โ ๐ 4 ๐ 0 ๐ฌ 0 ๐ 0These are among the oldest forests on earth, but they're running up against the new world of climate change--firefighting help badly needed!
www.nytimes.com/2025/11/23/w...
For our next UCL #NeuroAI online seminar, we are happy to welcome Dr Cian OโDonell @cianodonnell.bsky.social (@ulsteruni.bsky.social)
๐๏ธWed 11 June 2025
โฐ2-3pm BST
Talk title: 'Neurobiological constraints on learning: bug or feature?'
โน๏ธ Details / registration: www.eventbrite.co.uk/e/ucl-neuroa...
Out in @natureneuro.bsky.social today ๐ฅ
Cytoarchitecture, wiring and signal flow of the human default mode network
Combining 3D histology, 7T MRI, and connectomics to explore DMN structure-function associations
Led by Casey Paquola, @themindwanders.bsky.social & a terrific team of colleagues ๐
Nature
How neurons make a memory
www.nature.com/articles/d41...
Do babies pretrain? www.cell.com/trends/cogni...
15.11.2024 04:31 โ ๐ 47 ๐ 10 ๐ฌ 3 ๐ 1This paper may be very important:
www.biorxiv.org/content/10.1...
tl;dr: if you repeatedly give an animal a stimulus sequence XXXY, then throw in the occasional XXXX, there are large responses to the Y in XXXY, but not to the final X in XXXX, even though that's statistically "unexpected".
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Findings of scientific misconduct on a monumental scale by a prominent Alzheimer's researcher
www.science.org/content/arti...
Evidence that entorhinal cortex and prefrontal cortex (in mice, sorry) work together to encode outcomes in associative learning:
www.nature.com/articles/s41...
Studying this kind of outcome monitoring is going to be critical to understand the losses at play in the brain!
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Contrastive Learning Explains the Emergence and Function of Visual Category Selectivity
kempnerinstitute.harvard.edu/research/dee...
some cool news - I've started a regular column at The Transmitter @thetransmitter.bsky.social
First column out now on that most convenient of all the fictions in neuroscience: averaging
thetransmitter.org/neural-codin...
This post led to a lot of people saying, "Well, is in-context learning really *learning*?"
I'd like to add to that confusing mix: Learning by thinking
www.cell.com/trends/cogni...
If I figure out something purely through self-reflection, is that "learning"? If not, why?
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This paper from @martinhebart.bsky.social's lab is fantanstic: www.nature.com/articles/s41...
My takeaways:
1/ Clearly, semantic categories alone aren't enough to explain object perception or the neural system behind it.
#neuroscience #VisionScience
Paper title: Aligning Machine and Human Visual Representations across Abstraction Levels
What aspects of human knowledge are vision models missing, and can we align them with human knowledge to improve their performance and robustness on cognitive and ML tasks? Excited to share this new work (arxiv.org/abs/2409.06509) by @lukasmut.bsky.social! 1/10
13.09.2024 23:04 โ ๐ 20 ๐ 7 ๐ฌ 1 ๐ 21/ Here's a critical problem that the #neuroai field is going to have to contend with:
Increasingly, it looks like neural networks converge on the same representational structures - regardless of their specific losses and architectures - as long as they're big and trained on real world data.
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