The hippocampus is not a library, it is a simulation engine.

HPC is known for storing maps of the environment but not so known for generating planned trajectories.

This paper proposes that recurrence in CA3 is crucial for planning.

A🧵with my toy model and notes:

#neuroskyence #compneuro #NeuroAI

How do brain areas control each other? 🧠🎛️

✨In our NeurIPS 2025 Spotlight paper, we introduce a data-driven framework to answer this question using deep learning, nonlinear control, and differential geometry.🧵⬇️

My paper is out!
Computational modeling of error patterns during reward-based learning show evidence that habit learning (value free!) supplements working memory in 7 human data sets.
rdcu.be/eQjLN

I'm very excited about this work led by @nbalamur.bsky.social Inspired by the classic "Spot the ball ⚽" task, we develop a benchmark for visual social inference. We find that human participants perform much better than vision-language models.

Try it here: v0-new-project-9b5vt6k9ugb.vercel.app

Today in Nature Machine Intelligence, Kazuki Irie & I discuss 4 classic challenges for neural nets — systematic generalization, catastrophic forgetting, few-shot learning, & reasoning. We argue there is a unifying fix: the right incentives & practice. rdcu.be/eLRmg

When does new learning interfere with existing knowledge in people and ANNs? Great to have this out today in @nathumbehav.nature.com

Work with @summerfieldlab.bsky.social, @tsonj.bsky.social, Lukas Braun and Jan Grohn
www.nature.com/articles/s41...

Very cool study showing that "apparent" asymmetric update in reinforcement learning can emerge from Bayes optimal principles by Prakhar Godara in @pnas.org

www.pnas.org/doi/abs/10.1...

Very excited to share that our work (together with co-first author Shanka Subhra Mondal and @neuroai.bsky.social ) on a brain-inspired architecture for planning with LLMs is now out in Nature Communications! www.nature.com/articles/s41... (thread below)

Thrilled to see our TinyRNN paper in @nature! We show how tiny RNNs predict choices of individual subjects accurately while staying fully interpretable. This approach can transform how we model cognitive processes in both healthy and disordered decisions. doi.org/10.1038/s415...

Epic recordings of model-based and model-free learning signals from Kennerley lab (Bruno Miranda). Now at @elife.bsky.social

doi.org/10.7554/eLif...

getting this paper published was a bit painful but I am proud of it: www.nature.com/articles/s41.... We use deep RL to find mechanisms that help (real) people sustain the commons. Well done to Raphael Koster and Miruna Pislar (not on BlueSky). non-paywalled version on arxiv.

Applications for the global Google PhD Fellowship Program are open! Fellowships directly support graduate students doing exceptional and innovative research in computer science and related fields as they pursue their PhD. Learn more and apply by May 15 at goo.gle/phdfellowship.

We are looking for two PhD students at our institute in Munich.

Both postions are open-topic, so anything between cognitive science and machine learning is possible.

More information: hcai-munich.com/PhDHCAI.pdf

Feel free to share broadly!

New preprint with Aly Dayan Eliza Kosoy Yuqing Du.I really love this study, play and exploration, comparing free exploration of children adults and agents w entropy, empowerment and info gain as rewards. Plus kids private speech increases exploration.

arxiv.org/abs/2503.23631

Can LLMs be used to discover interpretable models of human and animal behavior?🤔

Turns out: yes!

Thrilled to share our latest preprint where we used FunSearch to automatically discover symbolic cognitive models of behavior.
1/12