1/ New preprint with @dyamins.bsky.social + team! Ventral visual representations within areas evolve over the course of the response along the same hierarchical complexity axis that distinguishes the visual areas, potentially driven by local recurrence.

I'm proud to say we are releasing LAION-fMRI, a densely sampled 7T fMRI dataset of natural images, with very broad stimulus sampling for testing countless hypotheses and for deeply exploring brain representations. The dataset is now available at laion-fmri.hebartlab.com What does LAION-fMRI offer? 🧵

1/X Our new method, the Inter-Animal Transform Class (IATC), is a principled way to compare neural network models to the brain. It's the first to ensure both accurate brain activity predictions and specific identification of neural mechanisms. Preprint: arxiv.org/abs/2510.02523

Excited to share that our paper is now out in Neuron @cp-neuron.bsky.social (dlvr.it/TM9zJ8). Our perception isn't a perfect mirror of the world. It's often biased by our expectations and beliefs. How do these biases unfold over time, and what shapes their trajectory? A summary thread. (1/13)

Yeah. I see a lot of "if chatGPT coded all of it, how do you know it's right?" - but for me the more important thing is "if chatGPT coded all of it, how did you learn anything???"

starting to get the "NIH grants are a crapshoot" refrain

I really like this review paper by Justin Gardner: www.nature.com/articles/s41... I keep coming back to it whenever I’m writing about models of perception. I especially like this quote; it took me a while to fully wrap my head around it, but I think it touches on something quite fundamental. 🧠📈

"I published my paper on biorxiv and now I'm hoping to get it advertised in Nature" This may seem like a diss, but 'is the exposure you get from Nature worth 10k?' has a different answer than 'is it worth paying 10k to publish a PDF online?' (which was always a strawman)

A starter pack with people who research visual sensation, perception, cognition, and memory. Also, a curated feed just for vision science content.

Check out the following starter packs for suggestions on who to follow: Cognitive neuroscience: bsky.app/starter-pack... Neural engineering & computational neuroscience: bsky.app/starter-pack... Affective science: bsky.app/starter-pack... Women in neuroscience: bsky.app/starter-pack...