Just out! Expectations modulate stimulus-evoked recurrent, but not feedforward, processing, and this is attention-dependent. NMDA-dependent feedback specifically supports perceptual integration (illusory contours), rather than mediating expectations (base rate). www.jneurosci.org/content/46/1...

New preprint! w/ @mheilbron.bsky.social We found that, even during simple natural scene viewing, human visual cortex predicts—hierarchically in central vision and at higher levels peripherally—reconciling classical predictive coding with recent evidence from animal models and AI (e.g. JEPA) (1/10)

To this theoretical physicist, time is not a basic ingredient of reality.

An optical illusion with nine simple dots reveals a surprising amount about the eye and brain

What are the systems in neuroscience that we really have something that we can call “explanation” at all relevant levels, other than reflexive feed-forward like circuits. Here are a few that I would argue are getting there. Obviously not complete explanations but genuinely satisfying.

For nearly two decades resting-state fMRI has ruled supreme. And resting-state is suprisingly powerful. But we can do so much better by using broad batteries of tasks with the right design. Here a double-punch delivered by two papers from @carobellum.bsky.social and @basselarafat.bsky.social!

We've posted a new fMRI study of semantic relations (has-part, is-a, made-of, etc.), a key aspect of language. We find that relations are represented in the same brain regions as are other semantic concepts, though voxels tend to be selective for only one relation or another. doi.org/10.64898/202...

📢 PhD position in the NeuroAI of Language Why can LLMs predict brain activity so well? We're hiring a PhD student to find out -- AI interpretability meets neuroimaging Deadline March 20 Please RT 🙏 👇 mpi.nl/career-education/vacancies/vacancy/fully-funded-4-year-phd-position-neuroai-language

A new generation of engineered immune cell destroys cancer cells in mice as effectively as conventional CAR-T-cell therapies without suppressing the immune system go.nature.com/4agA7Fl

Interesting convergence: The trick that made predictive self-supervised vision models work seems to be what the brain was doing all along w/ @predictivebrain.bsky.social: visual cortex is most sensitive to high-level prediction errors -- even in V1 Now published: journals.plos.org/ploscompbiol...

What is the brain for? Active inference is widely discussed as a unifying framework for understanding brain function, yet its empirical status remains debated. Our review identifies core predictions across the action-perception cycle and evaluates their empirical support: osf.io/preprints/ps...

I have a PhD opening for my #VIDI BrainShorts project 📽️🧠🤖! Are you or do you know an ambitious, recent (or almost) MSc graduate with a background in NeuroAI and interest in large-scale data collection and video perception? Check out our vacancy! (deadline Feb 15). werkenbij.uva.nl/en/vacancies...

real-life Necker cubes - can you see them?

This paper had a pretty shocking headline result (40% of voxels!), so I dug into it, and I think it is wrong. Essentially: they compare two noisy measures and find that about 40% of voxels have different sign between the two. I think this is just noise!

🚨Preprint: Semantic Tuning of Single Neurons in the Human Medial Temporal Lobe 1/8: How do human neurons encode meaning? In this work, led by Katharina Karkowski, we recorded hundreds of human MTL neurons to study semantic coding in the human brain: doi.org/10.1101/2025...

Sleep dependent consolidation and replay that doesn’t require the hippocampus? Very beautiful work by Marcus Stephenson-Jones’ lab on sleep driven sequential skill consolidation in the striatum. www.biorxiv.org/content/10.1...

New Perspective from myself, Sarah Heilbronner and @myoo.bsky.social . “Rethinking the centrality of brain areas in understanding functional organization” in Nature Neuroscience. 🧵 rdcu.be/eVZ1A

At #NVP, I presented fMRI work with @predictivebrain.bsky.social and @mheilbron.bsky.social on "Implicit physics prediction of object dynamics". We study predictions derived from the brain's intuitive physics model to probe prediction based on real-world structure—learned through lifelong exposure.

1/6 New preprint 🚀 How does the cortex learn to represent things and how they move without reconstructing sensory stimuli? We developed a circuit-centric recurrent predictive learning (RPL) model based on JEPAs. 🔗 doi.org/10.1101/2025... Led by @atenagm.bsky.social @mshalvagal.bsky.social

New today in @Nature: your visual cortex contains touch-based body maps. bit.ly/VisualBodyMaps Your brain transforms what you see into first-person, body-referenced codes: A previously unknown bridge between vision and touch.

Spoke at #CCN2025 about my work with @mheilbron.bsky.social on "A hierarchy of spatial predictions across human visual cortex during natural vision". (Full preprint and recording coming soon)

On Friday, during a contributed talk (and a poster), @wiegerscheurer will present the project he spearheaded: “A hierarchy of spatial predictions across human visual cortex during natural vision” 

(Full preprint soon) t.ly/fTJqy

🚨PhD position alert!🚨 Joint PhD position with @fedemar.bsky.social @predictivebrain.bsky.social and Sonja Kotz, to investigate the neurobiological underpinnings of perceptual decisions vacancies.maastrichtuniversity.nl/job/Maastric... Please share and if you have questions, send me a message!

New preprint, w/ @predictivebrain.bsky.social ! we've found that visual cortex, even when just viewing natural scenes, predicts *higher-level* visual features The aligns with developments in ML, but challenges some assumptions about early sensory cortex www.biorxiv.org/content/10.1...

I am so happy—this is the first 1st author paper I have written, since the cancer diagnosis of my late wife seven years ago. 📑 PAPER ALERT: "Beyond binding: from modular to natural vision" in Trends in Cognitive Sciences (2025) sciencedirect.com/science/arti...

In @elife.bsky.social: Stimulus dependencies—rather than next-word prediction—can explain pre-onset brain encoding during natural listening doi.org/10.7554/eLif...