Updated work from @jessegeerts.bsky.social extending his results on transitive inference in transformers (including LLMs!) updated paper: arxiv.org/abs/2506.04289 bleeprint (what are we calling these?) below ⬇️

Update on this work! We've extended our transitive inference study to large language models 🧵

I’m excited to share my first PhD preprint!🎉 We studied how interactions between medial entorhinal cortex (MEC) and hippocampus shape theta sequences during navigation, and asked whether some “planning-like” patterns in hippocampus could arise from upstream MEC dynamics. (1/8)

With some trepidation, I'm putting this out into the world: gershmanlab.com/textbook.html It's a textbook called Computational Foundations of Cognitive Neuroscience, which I wrote for my class. My hope is that this will be a living document, continuously improved as I get feedback.

New paper led by wonder postdocs Francesca Greenstreet and @jessegeerts.bsky.social and @clopathlab.bsky.social trying to understand why –in the "what for" sense– there are multiple motor learning systems –supervised and RL-based– in the brain. Check out Jesse's 🧵 www.biorxiv.org/content/10.6...

Check out our new work on motor learning across multiple brain regions!

🧠 New year, new preprint! Why does motor learning involve multiple brain regions? We propose that the cortico-cerebellar system learns a "map" of actions where similar movements are nearby, while basal ganglia do RL in this simplified space. www.biorxiv.org/content/10.6...

Thrilled to start 2026 as faculty in Psych & CS @ualberta.bsky.social + Amii.ca Fellow! 🥳 Recruiting students to develop theories of cognition in natural & artificial systems 🤖💭🧠. Find me at #NeurIPS2025 workshops (speaking coginterp.github.io/neurips2025 & organising @dataonbrainmind.bsky.social)

What aspects of human knowledge do vision models like CLIP fail to capture, and how can we improve them? We suggest models miss key global organization; aligning them makes them more robust. Check out LukasMuttenthaler's work, finally out (in Nature!?) www.nature.com/articles/s41... + our blog! 1/3

Excited to share that the full programme for the 2025 UCL NeuroAI Annual Conference is now live! 🧠🤖 @ucl-neuroai.bsky.social Spaces are limited, so register soon: lnkd.in/ehiKrSaf Full programme here: lnkd.in/e8cV3mAZ

We are delighted to support the 2025 @ucl-neurodomain.bsky.social NeuroAI Annual Conference. Join experts in neuroscience, AI, machine learning, and related fields on Wednesday 5 November 2025 at @uclchildhealth.bsky.social Details and registration: www.ucl.ac.uk/event-ticket...

Looks like a great conference---

Really interesting work by Bakhurin and colleagues challenging the reward prediction error hypothesis of dopamine: www.nature.com/articles/s41... I love this figure which both echoes and undermines the famous figure from Schultz et al. (1997).

Remember to submit an abstract to UCL NeuroAI 2025 by Wednesday! 🧠🤖 This will be a great opportunity to present your work to the local community, and we have a fantastic line-up of keynote speakers: @ucl-neuroai.bsky.social @sainsburywellcome.bsky.social

Remember to submit an abstract to UCL NeuroAI 2025 by Wednesday! 🧠🤖 This will be a great opportunity to present your work to the local community, and we have a fantastic line-up of keynote speakers: @ucl-neuroai.bsky.social @sainsburywellcome.bsky.social

🚀 New Preprint from our team: comparing place cells across species! Disentangling methods from biology provides a roadmap for cross-species insights into spatial coding 🌍 👉 www.biorxiv.org/content/10.1...

Submission deadline extended! Submit your poster or lightning talk abstract by Wednesday 15th October 2025, 12:00pm

📢 We are very happy to announce the 2025 @ucl.ac.uk #NeuroAI Annual Conference! Join us on Wed 5 November 2025 at @uclchildhealth.bsky.social Details and registration: www.ucl.ac.uk/event-ticket... Poster and lightning talks submissions are now open, up to 8th Oct. @ucl-neurodomain.bsky.social

I’m super excited to finally put my recent work with @behrenstimb.bsky.social on bioRxiv, where we develop a new mechanistic theory of how PFC structures adaptive behaviour using attractor dynamics in space and time! www.biorxiv.org/content/10.1...

Dear colleagues, we have an open PhD position in computational neuroscience - spatial memory models and intracranial recordings - fully funded. Re-advertised, candidates are ideally available in the near future. A collab. with 4 labs. Apply here: tinyurl.com/yc84ctap

Check out our latest episode on habit formation with DrFrancesca Greenstreet ✅📝 We talk about how habits are made how they may not require reward-based learning … 🎧 open.spotify.com/episode/1gZI...

🚨New paper! We know models learn distinct in-context learning strategies, but *why*? Why generalize instead of memorize to lower loss? And why is generalization transient? Our work explains this & *predicts Transformer behavior throughout training* without its weights! 🧵 1/

Humans and animals can rapidly learn in new environments. What computations support this? We study the mechanisms of in-context reinforcement learning in transformers, and propose how episodic memory can support rapid learning. Work w/ @kanakarajanphd.bsky.social : arxiv.org/abs/2506.19686

New work on relational reasoning in transformers! TLDR: Inductive biases of In-Weight and In-Context Learning in transformers are really different for relational reasoning, and pretraining can make a big difference for in-context. Check out @jessegeerts.bsky.social's thread for more!

‘Some dopamine neurons signal default behaviors to reinforce habits’ SWC research features in @thetransmitter.bsky.social ⬇️ www.thetransmitter.org/neurobiology...

This is a nice paper which applies and refines some of the ideas we put forward in our Psych Review paper. Our model combined multiple Successor Representations which it switches between based on uncertainty. Jess's model adds reward outcomes to this process and captures splitter cells and more!

Congrats to the fantastic Jess P for her new paper! She compared how feature Vs outcome focussed agents learn to solve contextual inference problems. She found that you need a balance of both to learn these tasks - and that this mix recapitulates pfc and hippocampal activity in rodent tasks!

🧠 How do transformers learn relational reasoning? We trained small transformers on transitive inference (if A>B and B>C, then A>C) and discovered striking differences between learning paradigms. Our latest work reveals when and why AI systems generalize beyond training data 🤖

Excited to see this work out! Check it out for a novel view on habit learning and the computational role of dopamine

Impressive study in @nature from my colleague Marcus Stephenson-Jones at UCL in the @sainsburywellcome.bsky.social www.nature.com/articles/s41...