New preprint! 🧠👀🤖 Behavioral and brain responses to language reflect different levels of linguistic representation w/ @whylikethis.bsky.social , @evfedorenko.bsky.social , and @rplevy.bsky.social (1/10)

Hiring postdocs @EPFL: please reach out and/or apply to the AI Center fellowship www.epfl.ch/research/fun.... My #NeuroAI group is excited about testing and building models of brain and behavior, from sensory through language to cognition, and from healthy to dysfunction (treatment)! 🧠🤖🧪

EPFL AI Center and Swiss AI Initiative Postdoctoral Fellowships

The 3rd call is now open with a submission deadline on 9 November 2026 17:00 (CET).

epfl.ch

📣 New study out today! We show that the brain's language network stays remarkably stable with age — same topography, lateralization, selectivity and connectivity as in younger adults — while the domain-general multiple demand network showed altered activity patterns. www.nature.com/articles/s41...

Preserved topography, lateralization, selectivity, and functional connectivity of the language network in older brains - Nature Communications

Here, the authors show that aging affects brain networks differently, with neural changes mirroring the preservation or decline of the cognitive functions they support. The multiple demand network exh...

nature.com

3/ We tested this hypothesis in an individual (EG) missing most of her left temporal lobe—which is critical for language—likely from birth. @gretatuckute.bsky.social has a beautiful paper characterizing her reorganized neocortical language network doi.org/10.1016/j.ne...!

Excited to share our new preprint on how the cerebellum specializes for language even in the absence of contralateral neocortical inputs, with @aniladmello.bsky.social and our collaborators @evfedorenko.bsky.social, @gretatuckute.bsky.social, @hopekean.bsky.social! www.biorxiv.org/content/10.6... 1/

Hello world! 👋 We’re Minds, Machines, and Brains (MMB) 👤🤖🧠 a new open access journal from @mitpress.bsky.social exploring the principles of intelligence and cognition across natural and artificial minds. Submissions open this Fall! 🔗 direct.mit.edu/mmb

CCN time--come say hi! @cogcompneuro.bsky.social

I've posted a preprint of a philosophical paper I've written on the relationships between understanding, prediction, and compression, based on a talk I gave at SPAN 2025. Now in press at Synthese. philarchive.org/archive/POLUPA

I have always believed that ideas from basic systems neuroscience could eventually help people. But for years that felt more like hope than reality. But look! This is one of the most personally satisfying papers my lab has produced because we’re getting there. www.biorxiv.org/content/10.6... 🧪🧵 1/

Daria Kryvosheieva is presenting our work on syntactic agreement in LLMs--across diverse agreement phenomena and across 57 languages--at #ACL2026 tomorrow! July 6, 9.10am PST, Oral Session D @aclmeeting.bsky.social

Greta Tuckute@gretatuckute.bsky.social · 9mo ago

How do LLMs process syntax? Do different syntactic phenomena recruit the same model units, or do they recruit distinct model components? And do different languages rely on similar units to process the same syntactic phenomenon? Check out our new preprint (to appear at ACL 2026)! shorturl.at/QWU81

MIT researchers are studying the brain's language network — and their recent findings are surprising. @evfedorenko.bsky.social @coltoncasto.bsky.social @benlipkin.bsky.social news.mit.edu/2026/brain-l...

The brain’s language network is more extensive than previously thought

Using functional magnetic resonance imaging (fMRI) data from more than 700 people, MIT researchers identified 17 brain regions outside of the canonical language-processing centers that are also involv...

news.mit.edu

—— Open Mind is MIT Press’s Diamond Open Access Cognitive Science journal. We now have our first Impact Factor: 2.9 as of June 2026 Submit your papers to Open Mind direct.mit.edu/opmi

However, different regions differ in how strongly they rely on these features. For example, frontal regions tend to be more strongly predicted by surprisal than SAE/LM-based “content” features.

We validate our model framework by asking if we can recover existing interpretations of brain responses to language. We use our models to predict voxels that have shown tuning to either processing difficulty or meaning abstractness.

It is not easy to characterize the features represented by human language cortex. This work is a step toward doing so. Using small, interpretable feature sets, we explain language-network responses and show a shared feature basis across brain regions, with graded variation across individuals.

Michael Lepori@michael-lepori.bsky.social · 3mo ago

🚨New preprint!🚨 We know that LM representations can be used to predict brain responses to language. But what *features* of these representations underlie this alignment? We use SAEs to find out!

The #KempnerInstitute is hiring! 👇 ⏰ Application deadlines approaching: • June 1: Kempner AI Fellows (post BS/MS) • June 8: Postdoctoral AI Researchers (post PhD) Learn more and apply: bit.ly/439R2Gp #AI #NeuroAI

New paper in Imaging Neuroscience by Greta Tuckute, Evelina Fedorenko, et al: A 3.5-minute-long reading-based fMRI localizer for the language network doi.org/10.1162/IMAG...

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.

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · 4mo ago

A hierarchical computational motif unifies neural dynamics across the ventral visual stream https://www.biorxiv.org/content/10.64898/2026.05.18.726101v1

Congratulations to @olaozpal.bsky.social & big team on new paper: large sample of children reveals the early origins of left-lateralization in language processing. Nice profile in MIT news: news.mit.edu/2026/languag...

Language development in the brain

The brain’s capacity to use and understand language expands rapidly in the first years of life. But by age 4, language processing is already handled by the left side of the brain, as in adults, accord...

news.mit.edu

So excited about this new work—check it out and go see Jane’s talk on Sunday if you’re at #VSS2026!

jane-yang.bsky.social@jane-yang.bsky.social · 4mo ago

Children acquire object category representations from their everyday experiences in the first few years of life. What do the inputs to this learning process actually look like? New preprint! arxiv.org/abs/2605.14990

New peer-reviewed paper w/ @mheilbron.bsky.social, @predictivebrain.bsky.social & Jakub Szewczyk! Pre-onset brain encoding has been taken as evidence that brains–like LLMs–predict upcoming words. We show that the same signatures arise in systems that cannot predict. (elifesciences.org) (1/8)

MIT researchers have developed automated pipeline that generates child-friendly audiovisual stimuli in minutes instead of weeks. Bianca Santi, Halie Olson @halieolson.bsky.social, others coauthored a paper in Developmental Cognitive Neuroscience describing the project. sqi.mit.edu/news/audiovi...

A Faster Way to Create Research Videos for Children

MIT researchers develop automated pipeline that generates child-friendly audiovisual stimuli in minutes instead of weeks

sqi.mit.edu

I always assumed that brain function had to line up with cytoarchitectonics. It turns out I was wrong. Human cortex, especially PFC, is tiled by chains of functional patches that subdivide and interlink architectonic areas into parallel processing streams. www.biorxiv.org/content/10.6...

Huge shoutout to my amazing co-authors on Mixture of Cognitive Reasoners: @cndesabbata.bsky.social, @gretatuckute.bsky.social, @eric-zemingchen.bsky.social, @mschrimpf.bsky.social, and @abosselut.bsky.social! Link: cognitive-reasoners.epfl.ch Poster below👇

The Cognitive Tools Lab at Stanford (cogtoolslab.github.io) is recruiting two new research staff members to join in AY 26-27. Full-Time Lab Manager: forms.gle/UVwfx5wbY9Km.... IRiSS Predoc Researcher: iriss.stanford.edu/predoc/2026-.... Please share widely in your networks, thank you!!

Another line of response pointed to what current LM research lacks: multilingualism, multimodality, audio, interaction, communication, smaller-scale learning, learning trajectories that match children. We're sympathetic. But we see these not as fundamental limitations but as a research program.

Richard @futrell.bsky.social and I have posted our response to the commentaries on our BBS target article "How Linguistics Learned to Stop Worrying and Love the Language Models." The response is: "You Can't Fight in Here! This is BBS!" arxiv.org/abs/2604.09501

You Can't Fight in Here! This is BBS!

Norm, the formal theoretical linguist, and Claudette, the computational language scientist, have a lovely time discussing whether modern language models can inform important questions in the language ...

arxiv.org

Recent news on automating developmental neuroscience studies, facilitating LLM "brainstorming" sessions, and studying how language is implemented in biological and artificial systems. @evfedorenko.bsky.social @gretatuckute.bsky.social @halieolson.bsky.social sqi.mit.edu/news/recent-...

Recent news from SQI: April 2026

From automating developmental neuroscience studies to facilitating LLM "brainstorming" sessions, this spring, the MIT Siegel Family Quest for Intelligence supported research across neuroscience, AI, a...

sqi.mit.edu

Check out @smonsays.bsky.social's work on detecting LLMs in experiments based on their lack of human memory constraints

Simon Schug@smonsays.bsky.social · 5mo ago

LLM agents are a serious problem for online experiments. It is very easy to use them and very hard to spot them. What can researchers do? With @brendenlake.bsky.social, we suggest detecting LLMs based on their lack of human cognitive constraints in our #CogSci2026 paper: arxiv.org/abs/2604.00016

Idan Blank (UCLA, psych) makes the complex intuitive if you want to learn how LLMs work, watch👇 newly posted to YouTube (no ads) www.youtube.com/watch?v=cGMn...

How Transformers Work: A Detailed, Conceptual Explanation (No Coding / Math)

YouTube video by IbanDlank

youtu.be