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Jean-Rémi King

@jeanremiking.bsky.social
3.3K followers 974 following 155 posts

Researcher in Neuroscience & AI CNRS, Ecole Normale Supérieure, PSL currently detached to Meta

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Reposted by Jean-Rémi King
Marcel Binz @marcelbinz.bsky.social · 18/09/2026
📢 The CORE COGNITION lab (core-cognition.github.io) is looking to hire another PhD student, working on automated scientific discovery and knowledge representation in cognitive science. Starting date: March to September 2027. 🙏 Please share widely!
core-cognition.github.io
CORE COGNITION
CORE COGNITION works towards a unified theory of human cognition, instantiated in models that simulate, predict, and explain human behavior.
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Jean-Rémi King @jeanremiking.bsky.social · 29/06/2026
📄v1 Nature Neuro: www.nature.com/articles/s41... 📑v2 Meta preprint: facebookresearch.github.io/brain2qwerty... 💻Code: github.com/facebookrese... 📊Data: huggingface.co/datasets/bcb... 📝Blog: ai.meta.com/blog/brain2q...
nature.com
Noninvasive decoding of typed sentences from human brain activity - Nature Neuroscience
Here the authors introduce Brain2Qwerty, a deep learning model that decodes typed sentences from non-invasive brain activity with character error rate down to 18%. This opens a pathway for non-invasiv...
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Jean-Rémi King @jeanremiking.bsky.social · 29/06/2026
We’re happy to announce 2 releases today: - 🧠Brain2qwerty v1 is published at @Nature Neuroscience - 🚀 Brain2Qwerty v2 is now publicly released Explore how we decode sentences from non-invasive brain recordings: facebookresearch.github.io/brain2qwerty/ Code, papers, data below:
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Jean-Rémi King @jeanremiking.bsky.social · 09/06/2026
🧠➜🖼️ Boost brain-to-image decoding (up to 68% 🚀!) by adding synthetic brain data (#TribeV2) in the training set. Our latest paper is out: arxiv.org/abs/2606.06345
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Jean-Rémi King @jeanremiking.bsky.social · 05/06/2026
We have a new postdoc position to work on Neuro AI and human intracranial recording with Pierre Bourdillon and I: Apply here: docs.google.com/forms/d/e/1F... Lab info: bourdillon-titan-lab.fr feel free to RT ;)
docs.google.com
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Jean-Rémi King @jeanremiking.bsky.social · 13/05/2026
Announcing: a new interactive online tool for a quick and simple start of encoding or encoding: 🧠 fMRI, EEG, MEG, iEEG, spikes… preprocessing 💬 text 🔊 audio ▶️ video 🏞️ image… embeddings 📦 pip install neuralset 🔍https://facebookresearch.github.io/neuroai/neuralset/index.html
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Teon ⁂ @teonbrooks.com · 06/05/2026
🧪 Excited to share some really awesome work our team, Brain & AI, just released led by Hubert Banville! Introducing NeuralBench: A Unifying Framework for Benchmarking Neuro AI @jeanremiking.bsky.social, @sdascoli.bsky.social, @jarodlevy.bsky.social, @lucyzmf.bsky.social 🧠📈🧠🤖 #cogsci #neuroai #ai
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Jean-Rémi King @jeanremiking.bsky.social · 06/05/2026
Thanks for the ping, apologies for the lack of response. Can you ask contact@digitalbrainproject.org ? They should have a precise answer to this kind of question
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Jean-Rémi King @jeanremiking.bsky.social · 30/04/2026
haha. Well for what it's worth, we had to hand-craft quite a lot of curating code to just get the public dataset into a standardized format :)
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Jean-Rémi King @jeanremiking.bsky.social · 30/04/2026
✨🧠 Tribe v2, our latest model of human brain responses to sound, sight and language can now be (partly) explored on your phone📱: ▶️demo: aidemos.atmeta.com/tribev2/ 📄paper: ai.meta.com/research/pub... 💻code: github.com/facebookrese...
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Reposted by Jean-Rémi King
Jarod Levy @jarodlevy.bsky.social · 21/04/2026
Our Brain&AI team is releasing NeuralSet! 🚀🚀🚀 A fast, simple, and scalable package for Neuro-AI: 📦 `pip install neuralset` 💻 Code: lnkd.in/eamwxBUY 📄 Paper: lnkd.in/epbreyDy As a PhD student working extensively with neuro recordings and AI models, I find this library to be a game-changer.
lnkd.in
neuralset - neuroai
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Reposted by Jean-Rémi King
Lucy (Mingfang) Zhang @lucyzmf.bsky.social · 21/04/2026
New package release from our amazing team 🎉🎉🎉 Using NeuralSet, you can go from a directory of downloaded data files to analysis-ready / AI-ready tensors with only a couple of lines of code Time to power up 💪
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Jean-Rémi King @jeanremiking.bsky.social · 21/04/2026
S Panchavati, A Ratouchniak, M Careil & Jérémy Rapin. 🙏 Many thanks to everyone involved and happy coding :) #Python #NeuroAI #OpenSource
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Jean-Rémi King @jeanremiking.bsky.social · 21/04/2026
Y Benchetrit @sdascoli.bsky.social, S Dahan, H Banville @teonbrooks.com K Begany, S Khanna @pierreorhan.bsky.social, A Thual @honualx.bsky.social @corentinbel.bsky.social, J Bonnaire, C Caucheteux, T Desbordes, P Diego-Simón, J Millet, ...
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Jean-Rémi King @jeanremiking.bsky.social · 21/04/2026
🙏 This package is made possible thanks to the neuroscience software stack: MNE-Python Nilearn HuggingFace OpenNeuro and many more Made possible thanks to J Raugel @jarodlevy.bsky.social, L Evanson @lucyzmf.bsky.social, @juliengadonneix.bsky.social, A Santos, S Houhamdi ...
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Jean-Rémi King @jeanremiking.bsky.social · 21/04/2026
…and more: 🎨 Decoding images from fMRI — DynaDiff: bsky.app/profile/jean... 👶 Modeling the development of language in iEEG: bsky.app/profile/jean... ⌨️ Decoding words from MEG: bsky.app/profile/jean...
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Jean-Rémi King @jeanremiking.bsky.social · 21/04/2026
NeuralSet already powers our Neuro-AI studies: 🧠🎬 Modeling fMRI responses to audio & video — Tribe v2: bsky.app/profile/sdas... 🗣️ Decomposing language processing with Utah arrays (@juliengadonneix.bsky.social): bsky.app/profile/juli... 👁️ Comparing fMRI and DINOv3: bsky.app/profile/jean...
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Jean-Rémi King @jeanremiking.bsky.social · 21/04/2026
NeuralSet fills a specific gap: the hierarchical preprocessing and data loading of all brain recordings and all modalities.
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Jean-Rémi King @jeanremiking.bsky.social · 21/04/2026
Caching and cluster dispatch come for free. Flip `infra={...}` and the same Study + Extractors run locally, reuse an on-disk cache, or fan out on SLURM — no other code change. Prototype on a laptop, scale to 100 subjects with one kwarg.
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Jean-Rémi King @jeanremiking.bsky.social · 21/04/2026
How this works: NeuralSet provides a modular pipeline: Study → Events → Transforms → Extractors → Segmenter → Batch.
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Jean-Rémi King @jeanremiking.bsky.social · 21/04/2026
<10 lines of code And get a scalable PyTorch `DataLoader` of preprocessed neural recordings and stimulus embeddings.
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Jean-Rémi King @jeanremiking.bsky.social · 21/04/2026
We're happy to release NeuralSet: a simple, fast, scalable package for Neuro-AI Supports: 🧠 fMRI, EEG, MEG, iEEG, spikes… preprocessing 💬 text 🔊 audio ▶️ video 🏞️ image… embeddings 📦 pip install neuralset 🔍 facebookresearch.github.io/neuroai/neur... 📄 kingjr.github.io/files/neural... 🧵 Details👇
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Jean-Rémi King @jeanremiking.bsky.social · 17/04/2026
Yes, the project is deliberately shooting for an ambitious target. The committee will evaluate based on scientific impact, not strictly the numbers. HTH
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Russ Poldrack @russpoldrack.org · 15/04/2026
I'm proud to be part of the Scientific Committee for the new $5M Digital Brain Project, to accelerate development of open source models of the human brain. Apply by May 15th for funding at digitalbrainproject.org
digitalbrainproject.org
Digital Brain Project
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Jean-Rémi King @jeanremiking.bsky.social · 15/04/2026
🙏 Thanks to Scientific Committee: @arthurmensch.bsky.social, AM Karmarrec, JA Sahel, L Melloni, @lune-bellec.bsky.social , @russpoldrack.org Exec Committee: A Yavchitz, E Cascardi, G. Le Hénanff, J Boyle, JR King, P Bourdillon Hopital de la Fondation Rothschild, Meta, Université de Montréal
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Jean-Rémi King @jeanremiking.bsky.social · 15/04/2026
🧠 the Digital Brain Project is now live: $5M total · up to $500k per selected team Let's open-source the modeling of the human brain brain activity! ➡️Apply on: digitalbrainproject.org
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jerrytang.bsky.social @jerrytang.bsky.social · 09/04/2026
We're excited to share our new study on decoding brain activity in participants with post-stroke aphasia! We think this is an important step towards cognitive brain-computer interfaces for patients with language disorders www.biorxiv.org/content/10.6... 1/8
biorxiv.org
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Reposted by Jean-Rémi King
Teon ⁂ @teonbrooks.com · 08/04/2026
🧪🧠📈 some very exciting work from my colleague is now out! Come check it out! 🤩🤩🤩 great work @juliengadonneix.bsky.social, @lucyzmf.bsky.social, @jeanremiking.bsky.social, and team! 🥳🥳🥳
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Jean-Rémi King @jeanremiking.bsky.social · 08/04/2026
🥳Very pleased of our latest study on the coordination of language representations in small cortical patches of the human brain 🧠:
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Jean-Rémi King @jeanremiking.bsky.social · 27/03/2026
(I’m secretely hoping this will be asked by the reviewers such that I can convince @sdascoli.bsky.social we should do it :))
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Jean-Rémi King @jeanremiking.bsky.social · 27/03/2026
no :’( we struggled with basic preprocessing and decided to drop to give it a proper chance in our next version
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Jean-Rémi King @jeanremiking.bsky.social · 26/03/2026
Our latest work, on modeling the human brain responses to sight, sound and language at scale:
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Jean-Rémi King @jeanremiking.bsky.social · 06/03/2026
Great opportunity to work in a terrific lab:
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Pierre Orhan @pierreorhan.bsky.social · 06/02/2026
Novel study: Emergence of Phonemic, Syntactic, and Semantic Representations in Neural Networks. Joint work with P. Diego supervision: Y. Lakretz, E. Chemla, Y. Boubenec, @jeanremiking.bsky.social We explore the emergence of 3 linguistic structures in Neural Networks. Arxiv: arxiv.org/abs/2601.18617
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Jean-Rémi King @jeanremiking.bsky.social · 04/12/2025
📣 Our latest brain-to-text decoding results from our Brain team is out: "Towards decoding individual words from non-invasive brain recordings" 📄 www.nature.com/articles/s41... 👥 Led by Stéphane d'Ascoli & w/ Corentin Bel, Jérémy RAPIN, Hubert Banville, Yohann Benchetrit and Christophe Pallier
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Jean-Rémi King @jeanremiking.bsky.social · 03/12/2025
Thanks to Meta and ENS for their support, all Open Sources models at HuggingFace, as well as K Armeni, JM Schoffelen for the great MEG dataset (nature.com/articles/s41...), thanks to the community and see you at @NeuripsConf !
nature.com
A 10-hour within-participant magnetoencephalography narrative dataset to test models of language comprehension - Scientific Data
Measurement(s) brain activity measurement Technology Type(s) Magnetoencephalography Factor Type(s) auditory story Sample Characteristic - Organism Homo sapien
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Jean-Rémi King @jeanremiking.bsky.social · 03/12/2025
This study strengthens a surprising phenomenon: Even though brains and LLMs differ in many ways (architecture, modality, and learning goals), they converge on similar sequence of computations. Understanding why this convergence emerges may help bridge biological and AI.
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Jean-Rémi King @jeanremiking.bsky.social · 03/12/2025
Two more facts: 1. This temporal alignment is not explained by word predictability. 2. bidirectional models (not inferential like the brain) do not converge toward similar sequential dynamics.
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Jean-Rémi King @jeanremiking.bsky.social · 03/12/2025
However, this temporal alignment does not emerge automatically. For the same model and configuration, it seem to depend on: • Model size (larger → more brain-like) • Context length (longer context → more brain-like) Untrained models show almost no alignment.
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Jean-Rémi King @jeanremiking.bsky.social · 03/12/2025
LLMs build representations in the same order as the brain: ➡️ First layers ↔ early brain responses ➡️ Deep layers ↔ later brain responses This temporal alignment is robust (r=0.99, p<1e-6) and holds across architectures (transformers & recurrent), sizes, and training regimes.
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Jean-Rémi King @jeanremiking.bsky.social · 03/12/2025
🧠Question: How similar are the hierarchical computations between LLMs and the human brain? Approach: we compare the evolution of MEG brain recordings across time to the evolution of latent representations across layers of 17 LLMs.
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Jean-Rémi King @jeanremiking.bsky.social · 03/12/2025
🎉 Our paper has been selected for a Neurips Spotlight: “Scaling and Context Steer LLMs along the Same Computational Path as the Human Brain” 👥led by J Raugel, w/ S. Ascoli, Rapin & @valentinwyart.bsky.social 📄https://openreview.net/pdf?id=4YKlo58RcQ 📍 Hall C-E Poster #2006 🧵thread 👇
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Jean-Rémi King @jeanremiking.bsky.social · 22/10/2025
🧠How does the hierarchy of speech representations unfolds in the human brain? Our latest work, led by @lauragwilliams.bsky.social, together with Alec Marantz and @davidpoeppel.bsky.social, is now out in PNAS: www.pnas.org/doi/10.1073/...
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BrainHack Donostia @bhdonostia.bsky.social · 01/10/2025
Jean-Rémi King - The Emergence of Language in the Human Brain We’re excited to announce that @jeanremiking.bsky.social , CRNS researcher at the ENS Paris & leader of Meta’s Brain & AI team, will be sharing groundbreaking insights into how language emerges in the human brain at BHD2025!
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Basque Center on Cognition, Brain and Language (BCBL) @bcbl.bsky.social · 11/09/2025
[2/2] 📊 His research uses encoding and decoding approaches to show how modern speech and language models account for brain responses to natural speech, measured with EEG, MEG, iEEG, and fMRI, even in children aged 2 to 12. 📆 November 19–21, 2025. +info 👇 brainhack-donostia.github.io
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Jean-Rémi King @jeanremiking.bsky.social · 04/09/2025
Congrats Mariya!
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Jean-Rémi King @jeanremiking.bsky.social · 03/09/2025
Thanks to all the great researchers who contributed to this project: Joséphine Raugel, the DINOv3 team, @valentinwyart.bsky.social, FAIR and ENS as well as the open source and open data #NeuroAI communities for making this possible! 🙏
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Jean-Rémi King @jeanremiking.bsky.social · 03/09/2025
Overall, the training of DINOv3 mirror some striking aspects of brain development: late-acquired representations map onto the cortical areas with e.g. greater expansion and slower timescales, suggesting that DINOv3 spontaneously captures some of the neuro-developmental trajectory
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Jean-Rémi King @jeanremiking.bsky.social · 03/09/2025
→ Second factor: data type: Even models trained only on satellite or cellular images significantly capture brain signals — but the same model trained on standard images encodes higher all brain regions.
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Jean-Rémi King @jeanremiking.bsky.social · 03/09/2025
So what are the factors that lead DINOv3 to become brain-like? → 1st factor: Model size: bigger models become brain-like faster during training, reach higher brain-scores, especially in high-level brain regions.
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