Thank you Jeremy. Have you done any breakdowns by R21 vs R01? I am wondering if we are seeing more R21s (because they are smaller and funding is tight) or more R01s (because there is a fixed gate-keeping cost to making any award, thus POs may prioritize bigger ones to get the money out)

A Brief History of Lab Notebooks How experimental recordings have changed, from the Renaissance through today.

Fascinating short history, including how "Isaac Newton’s famous Waste Book is a rare example of a physical continuity between the two cultures of notetaking: humanist and scientific."
www.asimov.press/p/lab-notebo...

Yes. Give people grace, everyone.

There is a light on the horizon.
But things are bad right now, and people are not doing well. Hold fast, take care of yourself, be kind, and if you can, keep doing something to bend the arc of history.

Really excited about our new work on aphasia! Even in fairly profound aphasia, we can recover semantic maps through visual stimuli and use them to decode language. This is a big step! Language BCIs in aphasia might be possible!

Numbers or letters?

Awesome! Q about non-local coding... I guess that you estimate place coding using standard approaches, then show that neuron responds as if mouse is elsewhere. But if the second part is true (neuron has non-local responses), how can one estimate place coding in the first place?

My main postdoc work is now published: www.nature.com/articles/s41...! We (myself, Isabel Low, Frances Cho, and @lgiocomo.bsky.social) discovered task-relevant remote representations in entorhinal cortex independent of CA1. #paperthread below! 1/13

Computational framework to predict and shape human–machine interactions in closed-loop, co-adaptive neural interfaces - Nature Machine Intelligence Madduri et al. introduce a computational framework grounded in control and game theory to model co-adaptation between users and decoders in neural interfaces. This framework enables a principled desig...

If you're interested in emerging ideas in neural interfaces, I humbly suggest my lab's latest: www.nature.com/articles/s42...

Neural interfaces create dynamic interactions between the brain & devices. This means mean we need new engineering approaches beyond typical ML to "decode" a static brain

Safest way is probably a dedicated computer on a different network with no access to your resources or accounts. But then it's not a very useful agent.

No Prompt Injection Required A malicious litellm release on PyPI compromised our machine through an MCP server's unpinned dependency. No prompt injection, no LLM trickery, just a poisoned package auto-downloaded by uvx.

So what dnu replied to you did just happen to many folks: futuresearch.ai/blog/no-prom...
I think the old wisdom still applies: anything with physical access to your computer (this includes an agent) can probably compromise anything on it

Did you do this entire project in the last few weeks since the Eon announcement, or was this already in the works? So timely!

I had a great time talking to Meenakshi about my trajectory through neuroscience!

Tune in for electric fish, imaging the hypothalamus, and trying to find a path in theory that stays relevant to the brain. Also, my early phd experiences of trying to do science when real life rears its head.

I submitted my comments! The form is short and you can do it too.

Dang, sorry to have missed it Alex, your explanations are always so lucid! Thanks for sharing

Mammals have hundreds of joints and muscles. Controlling them individually would be nearly impossible.

How does the nervous system organize such complexity into coherent actions?

Our new study explores this question through a natural behavior: jumping.

I think people on all sides of this debate think they are the one who is "thinking seriously about how these shifts impact the ways that other people teach and research" and that others are not. Nobody identifies as someone who is not doing that. Each side is emphasizing different risks.

I actually last heard about it 4 days ago in this post. But yeah, point taken
At least we have PubmedCentral (for now) and other nations' equivalents. I think that's important
I remember ~10 years ago scientists posting that journals were doomed because twitter threads (!) could replace them

Smell is very reminiscent of movie theater buttered popcorn which is now making me question what is in that popcorn

Substituting bacon grease for butter in this recipe (kare udon roux) 😬

Another throughline: models went from absurdly over-simplified to absurdly over-complicated. In parallel, we started out creating simple models to understand the brain and ended up studying complex models for their own sake

I would say that the late 2000s optogenetics honeymoon led to a focus on circuit cracking, but more recently there’s been a revival of good old record a million neurons and correlate some stuff. We need both. Reduce when possible but recognize complexity too

thank you! We had a great discussion at journal club about your work

I saw someone say "nip it in the butt" instead of "nip it in the bud" in a slack channel and I felt like I should say something but didn't

I see. Thanks! Word processing, tax prep software, and a few lab things (CAD, PCB layout, etc) are the last few legacy apps I can't quite quit. Some day!
Word 2010 was good for its day though. It's served me well for 16 years

You don't exchange documents with students or colleagues with "track changes" enabled?

I'm ready to leave Word 2010 (running in Wine on Linux). LibreOffice is too buggy for me. GDocs is missing the killer feature of "view as if all tracked changes were accepted". I work better with WYSIWYG (so not Latex). I don't want to work in the cloud. Is typora the way to go?

Q2) It seem you find representation neurons connect to PE neurons with the "wrong" sign. I think Larkum proposed architecture that also has "wrong" sign wrt predictive processing: matches between prediction and input are facilitated not cancelled. Does that match your data? doi.org/10.1016/j.ti...

Hi Anna, I've read the paper now, great work! Wanted to ask about Fig 9 (and about JEPAs generally). You point out downsides to computing PEs in the input space. But what is the value of two networks predicting each other? What keeps their representations useful and grounded in reality?

www.reddit.com/r/Programmer...

Second preprint from the lab. Collab with @dkoveal.bsky.social, with many more to come! Effort led by @xshirleyz.bsky.social with help from Brittany Addison, @ezeyulu00.bsky.social, Claire Deng (on the grad school market, better act fast, Claire’s amazing!), @ajemanuel.bsky.social, and many others!