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RJ Antonello

@rjantonello.bsky.social
62 followers 79 following 8 posts

Postdoc in the Mesgarani Lab. Studying how we can use AI to understand language processing in the brain.

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Reposted by RJ Antonello
Erica Busch @elbusch.bsky.social · 27/07/2026
🧠 New preprint! How does the brain build specialized, efficient representations as we grow up? We used manifold learning to track the "intrinsic dimensionality" (ID) of brain activity in ~800 participants (aged 3mo–53yrs), as they performed naturalistic tasks and rested/slept.
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Lenny van Dyck @levandyck.bsky.social · 16/07/2026
Excited to share that our paper is now out in #JNeurosci! We propose a multidimensional framework of high-level visual cortex that reconciles a longstanding debate. Thanks to @kathadobs.bsky.social, @martinhebart.bsky.social, and everyone else for the great discussions along the way. More to come 🧠🌈
doi.org
Multidimensional feature tuning in category-selective areas of human visual cortex
Two prominent accounts describe the functional organization of human high-level visual cortex. A categorical view emphasizes category-selective areas, while a dimensional view highlights continuous fe...
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RJ Antonello @rjantonello.bsky.social · 06/05/2026
How can manifold theory help us understand why representations learned by AI models🤖 are aligned to the brain🧠? We expanded our UniReps Best Short Paper on this topic into a full paper at @icmlconf! Now extended to ECoG and with new brain-tuning results! Check it out👇
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Floris de Lange @predictivebrain.bsky.social · 28/04/2026
And a nice summary by Richard Antonello can be found here: elifesciences.org/articles/111...
elifesciences.org
Language Models: Does the brain really know what word is coming next?
Apparent neural encoding of future words may arise from the statistical structure of language itself, rather than from predictive computations in the brain.
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Subha Nawer Pushpita @pushpita1729.bsky.social · 07/11/2025
Excited to share our work on mechanisms of naturalistic audiovisual processing in the human brain 🧠🎬!! www.biorxiv.org/content/10.1...
biorxiv.org
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Victoria Bosch @initself.bsky.social · 03/11/2025
Introducing CorText: a framework that fuses brain data directly into a large language model, allowing for interactive neural readout using natural language. tl;dr: you can now chat with a brain scan 🧠💬 1/n
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Linyang He @linyanghe.bsky.social · 30/10/2025
🧠 New at #NeurIPS2025! 🎵 We're far from the shallow now🎵 TL;DR: We introduce the first "reasoning embedding" and uncover its unique spatio-temporal pattern in the brain. 🔗 arxiv.org/abs/2510.228...
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Anna (Anya) Ivanova @neuranna.bsky.social · 29/09/2025
As our lab started to build encoding 🧠 models, we were trying to figure out best practices in the field. So @neurotaha.bsky.social built a library to easily compare design choices & model features across datasets! We hope it will be useful to the community & plan to keep expanding it! 1/
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RJ Antonello @rjantonello.bsky.social · 18/08/2025
In our new paper, we explore how we can build encoding models that are both powerful and understandable. Our model uses an LLM to answer 35 questions about a sentence's content. The answers linearly contribute to our prediction of how the brain will respond to that sentence. 1/6
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Alexander Huth @alexanderhuth.bsky.social · 01/08/2025
New paper with @mujianing.bsky.social & @prestonlab.bsky.social! We propose a simple model for human memory of narratives: we uniformly sample incoming information at a constant rate. This explains behavioral data much better than variable-rate sampling triggered by event segmentation or surprisal.
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Mark Lescroart @neuromdl.bsky.social · 12/06/2025
🚨Paper alert!🚨 TL;DR first: We used a pre-trained deep neural network to model fMRI data and to generate images predicted to elicit a large response for each many different parts of the brain. We aggregate these into an awesome interactive brain viewer: piecesofmind.psyc.unr.edu/activation_m...
piecesofmind.psyc.unr.edu
Cortex Feature Visualization
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Greta Tuckute @gretatuckute.bsky.social · 23/05/2025
What are the organizing dimensions of language processing? We show that voxel responses during comprehension are organized along 2 main axes: processing difficulty & meaning abstractness—revealing an interpretable, topographic representational basis for language processing shared across individuals
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bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 11/03/2025
Stimulus dependencies---rather than next-word prediction---can explain pre-onset brain encoding during natural listening www.biorxiv.org/content/10.1101/202…
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Nancy Kanwisher @nancykanwisher.bsky.social · 26/03/2025
I’m hiring a full-time lab tech for two years starting May/June. Strong coding skills required, ML a plus. Our research on the human brain uses fMRI, ANNs, intracranial recording, and behavior. A great stepping stone to grad school. Apply here: careers.peopleclick.com/careerscp/cl... ......
careers.peopleclick.com
Technical Associate I, Kanwisher Lab
MIT - Technical Associate I, Kanwisher Lab - Cambridge MA 02139
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Badr AlKhamissi @bkhmsi.bsky.social · 05/03/2025
🚨 New Preprint!! LLMs trained on next-word prediction (NWP) show high alignment with brain recordings. But what drives this alignment—linguistic structure or world knowledge? And how does this alignment evolve during training? Our new paper explores these questions. 👇🧵
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Ev Fedorenko @evfedorenko.bsky.social · 27/12/2024
Just in time for the holidays! Some cool new evidence from @eghbal_hosseini for the idea of universal representations shared by high-performing ANNs and brains in two domains: language and vision! Go Eghbal!
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RJ Antonello @rjantonello.bsky.social · 08/12/2023
Really excited to be at NeurIPS this week presenting our new encoding model scaling laws work! Be sure to check out our poster (#402) on Tuesday afternoon and our new code and model release, and feel free to DM me to chat!
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