Lets distinguish belief from knowledge. And lets say clearly which is which. We need to take neuroscience seriously if we are to make progress.

On a Thursday your best bet is probably Silbergold or Pracht

Congrats!! & welcome to one of the best cities ;)

Thanks to the whole team behind Mouse vs AI:
@jingpeng.bsky.social , Yuchen Hou, Joe Canzano, @spencerlaveresmith.bsky.social & @mbeyeler.bsky.social !

A special shout-out to Joe, who designed the Unity task, trained the mice, and recorded the neural data — making this benchmark possible!

Submit your model. Compete against mice.
Which model architectures solve the task, and which find brain-like solutions?
Let us uncover what it takes to build robust, biologically inspired agents!
Read the whitepaper: arxiv.org/abs/2509.14446
Explore the challenge: robustforaging.github.io

🧠 Track 2: Neural Alignment

Do task-trained agents develop brain-like internal representations?

We regress model activations onto 19k+ neurons across all mouse visual areas recorded during the same task.

This lets us test whether brain-like codes emerge naturally from behavior-driven learning.

🧭Track 1: Visual Robustness

Track 1 evaluates how well RL agents generalize to unseen visual perturbations, like different weather or lighting changes, while performing a foraging task.

Mice perform the same task in VR—enabling direct behavioral comparisons across species.

We built a naturalistic Unity world (not blocky or toy-like) and trained mice to perform a foraging task in it.

Now it’s your turn: train RL agents on the same task and submit your model!