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[ローソン @akiko_lawson]

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[ローソン @akiko_lawson]

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[ローソン @akiko_lawson]

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[ローソン @akiko_lawson]

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[ローソン @akiko_lawson]

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[bioRxiv Neuroscience @biorxiv_neursci]

Stress drives the hippocampus to prioritize statistical prediction over episodic encoding https://t.co/dRSLvapWxU #biorxiv_neursci

[Ruben Laukkonen @RubenLaukkonen]

Lots of warranted energy around recursion in AI rn!

But what we really need to crack is the capacity for an AI to interrogate and reflect on their own world model. This is the big, beautiful kind of recursion that keeps the organism globally coherent [and curious] over time

If we crack that, I bet it scales, because you can use your own outputs (mind) as the data to reflect on ad infinitum, as well as never ending hunger for epistemic foraging...

because now you know what you do not know.

A certain baseline intelligence is needed but then it’s takeoff—this is probably what the cognitive revolution was, a turning inward that allowed us to “grasp” facets of our mind and keep them stable long enough to share them with others...

Which in turn birthed our ability to 'know' our own knowledge: epistemic agency

What you need is basically recursive self-interpretability

—a beautiful loop.

[neurosock🧠Brain Chips🦾 @neurosock]

A core function of cortex is predicting what happens next given the world's state.

This great recent paper from Oxford shows how cortical layers may use a clever delay trick to learn to predict.

A simple illustration can explain the main idea.

Here is my toy model and notes:

[Ryohei Sasaki@engineer @rsasaki0109]

[NeurIPS 2025] Official Implementation of DINO-Foresight: Looking into the Future with DINO
https://t.co/6xvidSNE6C

[Frank Nielsen @FrnkNlsn]

New Followers, a tutorial with no prerequisite in differential geometry needed!

"An Elementary Introduction to Information Geometry"
👉 https://t.co/8KEScZpX1P

[Chris Paxton @chris_j_paxton]

"Slam is the robotics version of a world model" is honestly pretty true

[Luca Ambrogioni @LucaAmb]

1/2) Have you have noticed that the forward process in a diffusion model looks a lot like the reparameterization trick in VAEs?
It turns out that there is a deep connection!

Curious? Watch our new vedio in the Generative Memory Lab channels

(link below)

[Bertoglio lab (FMC/UFSC) @bertogliolab]

Discovery of Highly Selective 5-HT2A Agonists Using Structure-Guided Design
https://t.co/EN4ufNnzjb

[bioRxiv Neuroscience @biorxiv_neursci]

A multisensory, bidirectional, valence encoder guides behavioral decisions https://t.co/n4xJRZUs4y #biorxiv_neursci

[Jesse Brown @jesseaaronbrown]

Amazing paper. All the good stuff: brain dynamics, state trajectories, embedding, links to arousal, tracking full dynamic state with a single measurement.
https://t.co/N0zbt1Ebob

[Earl K. Miller @MillerLabMIT]

Cortical networks with multiple interneuron types generate oscillatory patterns during predictive coding
https://t.co/JULROdbetO
#neuroscience

[neurosock🧠Brain Chips🦾 @neurosock]

Dopamine (DA) in the dorsolat. striatum (DLS) is a teaching signal that shapes learning.

DA in DLS ≠ RPE but = to stimulus-choice associations relevant to a learning strategy.

This can be beautifully explained as saddles in a loss landscape.

Here is my toy model and notes:

[Julio Martinez @JulioMTNeuro]

The brain's hardware evolves to make sense of events that happen in space and time. The Lateral Prefrontal Cortex has expanded that hardware in primates. Check Alex and Megan's work if you have not done so, and find what NAS are
https://t.co/i2w31Hwm3U👇

[BrainVTA @Brain_VTA]

❗️❗️❗️News︱Nature Neuroscience
👏👏👏Prof. Zhong Chen's team revealed an inhibitory neural circuit from the medial septum (MS) to the subfornical organ (SFO).
👇More
https://t.co/o1sTJLF7vb

[European Journal of Neuroscience @EJNeuroscience]

New study reveals how the brain organizes and directs its slowest activity https://t.co/fLnLAkGaXM via @medical_xpress