Where is the story in a book?

The idea of inner and outer loop is fascinating, but this model might have a competition (based on parsimony probably) from "HRRL" described here: tinyurl.com/msptrdtj but your model seems to answer the question in the linked paper: "we have to admit that we do not know how goals are computed"

Goal selection through the lens of subjective functions: arxiv.org/abs/2512.15948 I welcome any feedback on these preliminary ideas.

WTI is hiring a Research Software Engineer. Join our interdisciplinary community at Yale to collaborate with researchers on brain + behavioral data. Learn more at the link below + share this opportunity with your network! 🔗 wti.yale.edu/opportunities #KnowTogether #ScienceAtYale

Is there any evidence for anti-Hebbian plasticity during sleep? This is an old hypothesis that continues to get cited (and to appear in some computational models), yet I haven't been able to find any study that shows this. There's ample evidence of synaptic downscaling, but that's different.

This seems to fly in the face of “thou shall not assume causation from correlation” and “thou shall not assume function from form” From what I can tell, the argument is that an adaptive system (evo/bio/neuro) will learn to use any knob available, so if we see a knob we should assume it’s used?

Some really good tips here. Wish I had learned number 3 earlier, or ever for that matter 🥲 www.reddit.com/r/GradSchool...

In which @kordinglab.bsky.social argues LLMs are more like an electric motor than a drill, and starts to build a drill for scientific research. open.substack.com/pub/kording/...

0/10 Thanks for the interest in our preprint. Some takes say it negates or fully supports the “manifold hypothesis”, neither quite right. Our results show that if you only focus on the manifold capturing most of task-related variance, you could miss important dynamics that actually drive behavior.

For a while it felt like bsky was recapturing the prof involvement of science twitter but not the students (the former PhDs/postdocs of science twitter are the new-profs of bsky 😅). Lately it feels like a lot more students getting on the bus 🧪🦋🚌 🙌🙌🙌 #neuroskyence

TFW there’s a whole new podcast about Fela Kuti for the ride home 🤩🙌 open.spotify.com/episode/203S...

Sometimes I think the best we can hope for is productively wrong 😉

Where do you think this is *not* the case? (i.e. what parts of theoretical neuro today are truly new?) Where do you think this will not be the case in 20 years? (i.e if research progresses in a direction you think it should, what will be the new stuff we’re not talking about today?)

The basal forebrain plays the cortex like a piano.

around 12 years ago I had the good fortune to meet Massimo Scanziani and told him about my ongoing postdoc project that I was preparing a manuscript on, his first question was "what is the central message of your paper?" That one prompt changed the way I write papers forever

Oh man. Science Neural Circuits would be my new favorite journal.

There’s an interesting parallel here to neural network interpretability… Understanding the recipe is not the same as knowing how the cake tastes at inference.

I am really proud that eLife have published this paper. It is a very nice paper, but you need to also read the reviews to understand why! 1/n

Y’all are reading this paper in the wrong way. We love to trash dominant hypothesis, but we need to look for evidence against the manifold hypothesis elsewhere: This elegant work doesn't show neural dynamics are high D, nor that we should stop using PCA It’s quite the opposite! (thread)

There are a small number of papers that I still think about regularly 10 years after reading them and this is one of them.

1) This is a great idea. 2) I would be happy to mentor a project like this. If you want to do a project eg at the intersection of Philosophy of Science and NeuroAI, please feel free to reach out to discuss, or just put my name as a suggested mentor!

“Our findings challenge the conventional focus on low-dimensional coding subspaces as a sufficient framework for understanding neural computations, demonstrating that dimensions previously considered task-irrelevant and accounting for little variance can have a critical role in driving behavior.”

Most neuroscientists would agree that the brain is far more sophisticated than ANNs - so why would we force tools and interpretations that are too trivial to explain ANNs today, much less the brain? We wouldn't.

We're almost at the end of the year, and that means an end-of-year review! Send me your favorite NeuroAI papers of the year (preprints or published, late last year is fine too).

What are the top 3 dream experiments you'd like neurophysiologists to do, that would help your modeling the most?

Since so many people are here for #sfn25 this week, maybe a good time to mention the algorithmic “For You” feed: bsky.app/profile/did:... which shows you posts that people who liked the same things as you liked 🫧📌

Will be presenting a poster on @apeyrache.bsky.social row, Tues AM, with an update our sequential predictive learning preprint: -CA3-like (sparse lognormal) connectivity gives a hippocampus-like (orthogonalized) map -non-spatial representation! splitters, lap/time cells, action plan…we got it all🤑

“and an otherwise normal life to lead”

TFW you land in San Diego and the bsky is hopping #sfn25

Somehow clicked the "please send me piles of email spam" checkbox when registering for SfN this year and boy do I have regrets.

It’s possible to see social media, and now AI, as the new radio — the new information technology which will ruin democracies around the globe if we don’t find a way to prise off billionaires’ control of those new info channels.

A loss of trust in information is just as bad as a loss of trustworthy information.

Starting to wonder if any of us will be at sfn or if we’re all going to be hanging out in airports for the week…

I'm not saying we don't have "systems that rival human intelligence in key tasks" (though "key" is doing some heavy lifting). I'm saying that if you're going to make this your definition of AGI, you've been taking the piss all along.

Not necessarily neuroscience, but I once heard introducing+defining the MDP formalism is the “RL handshake”

My favorite part of pragmatism is when it’s like “maybe instead of worrying about shit that doesn’t matter we should worry about shit that does.” “Oh and btw we’ll learn a lot more about the shit that doesn’t in the process anyway.” 🫣

Lyrics are just a vehicle for syllables.

[2/9] We argue that instead of getting stuck on metaphysical debates (is AI conscious?), we should treat personhood as a flexible bundle of obligations (rights & responsibilities) that societies confer.

New on the Archive: Stump, David J. (2025) Lessons from Pragmatism for Philosophers of Science: Nine Teachings and a Cautionary Tale. [Preprint] https://philsci-archive.pitt.edu/27072/

Really hoping bifurcations are the new manifolds. What a time to be alive 🥲

"Because science rejects claims to truth based on authority and depends on the criticism of established ideas, it is the enemy of autocracy. Because scientific knowledge is tentative and provisional, it is the enemy of dogma. "

George Box famously said "all models are wrong, some are useful", but what he forgot to add was that usefulness doesn't just depend on the model. A model is useful *only with respect to a given target problem*

TFW you name your company “Palentir”

Come do a postdoc at the Wu Tsai Institute! WTI fellows have freedom to work with anyone at the institute, and preference is given to applicants who want to work on interdisciplinary projects with multiple faculty mentors. If you’re interested to work with me, please reach out!

Great interview touching on affordances and the utility of weasel words we all use and no one agrees what they mean (affordances, representation, computation, et al).

The best tweets are always buried in the replies.

Is this an allegory for climate change rn or what?

Bees aside, there are a bunch of gems in here about modeling… 1) “The model is a useful and indeed unescapable tool of thought - it enables us to think about the unfamiliar in terms of the familiar. There are, however, dangers in its use: it is the function of criticism to disclose these dangers.”

Science is a question-answering activity. Whenever someone tries to pose a scientific question about art, it always turns out to really be a question about something else (perception, emotion, etc). This is why many attempts to bring art and science together fall flat.

It's possible to get first order approximate understanding of RNNs performing relatively complex tasks. [1906.10720] Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics share.google/ElT686dgAUIk... But some tasks are harder than others 🤷‍♂️