New paper with @rjantonello.bsky.social @csinva.bsky.social, Suna Guo, Gavin Mischler, Jianfeng Gao, & Nima Mesgarani: We use LLMs to generate VERY interpretable embeddings where each dimension corresponds to a scientific theory, & then use these embeddings to predict fMRI and ECoG. It WORKS!

🚨 New Preprint 🚨

Targeting intracranial electrical stimulation (ES) to network regions defined within individuals causes network-level effects

By Cyr et al.

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Q: Can we use individualized network maps from precision fMRI to modulate a targeted network via intracranial ES?

A: Yes!

🧵:

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.

Super excited to share our new article: “Dissociable cortical regions represent things and stuff in the human brain” with @nancykanwisher.bsky.social, @rtpramod.bsky.social and @joshtenenbaum.bsky.social

Video abstract: www.youtube.com/watch?v=B0XR...

Paper: authors.elsevier.com/a/1lWxv3QW8S...

Check out Zaid's open "Podcast" ECoG dataset for natural language comprehension (w/ Hasson Lab). The paper is now out at Scientific Data (nature.com/articles/s41...) and the data are available on OpenNeuro (openneuro.org/datasets/ds0...).

**ecstatic** to share our @iclr-conf.bsky.social paper: sparse components distinguish visual pathways & their alignment to neural networks, with @nancykanwisher.bsky.social and meenakshi khosla (openreview.net/forum?id=IqH...)

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"With precision fMRI, we identify cerebellar regions that respond to language across modalities, one supporting semantic processing, the other three integrating info from diverse neocortical regions." Elegant work by @evfedorenko.bsky.social lab, with 🧵 from lead author @coltoncasto.bsky.social. 🧪

More broadly, our work reveals that cerebellar language regions are remarkably *functionally diverse* (likely supporting distinct functions; cf. a universal transformation), and we argue that domain-specific inquiry is critical for advancing cerebellar research.
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Based on these findings, we propose that these 4 regions constitute components of the *extended language network*, and we join a growing number of researchers calling for the inclusion of the cerebellum in theories of neural language processing.
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Finally, all cerebellar language regions, but esp. LangCereb3, were similar to LANG in their response profiles and showed strong functional correlations during naturalistic cognition (Expt. 4, n=85).
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We also found that responses in LangCereb3 were modulated by many of the same linguistic properties as LANG (Expt. 3c, n=5). Interestingly, responses in LangCereb3 were not strongly modulated by surprisal.
10/n

…than LANG. This suggests that LangCereb3 processes sentence-level meanings, plausibly inherited from LANG.
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What might the language-selective cerebellar region contribute to language? Using a paradigm that decomposes language processing into its component processes (Expts. 3a-b, n=100), we found that LangCereb3 was less sensitive to lexical access and syntactic structure building…
8/n

The other three regions exhibited mixed-selective response profiles, responding strongly to language, but also to at least one of the non-linguistic conditions in our battery. These regions may integrate information across diverse neocortical systems.
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One cerebellar language region—LangCereb3, spanning Crus I/II/VIIb—responded selectively to language (mirroring the selectivity of LANG), suggesting that the computations it supports are specifically linguistic in nature.
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We then evaluated the selectivity of these regions for language relative to diverse non-linguistic conditions: motor/articulation tasks, demanding executive tasks, musical stimuli, social/communicative visual stimuli, and semantically meaningful visual stimuli (Expts. 2a-f, n=732).
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Using precision fMRI and a within-participant localization approach, we identified *4* regions of the cerebellum that respond reliably to language across modalities (written and spoken; Expts. 1a-b, n=754).
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Here we test 1️⃣ whether the cerebellum is selectively engaged in language (over perceptual, motor, and general cognitive processing), 2️⃣ what linguistic computations it supports, and 3️⃣ its role in language processing relative to the neocortical language network (LANG).
3/n

The cerebellum has long captivated the neuroscientific community as a computationally powerful, cytoarchitecturally uniform, and evolutionarily expanded neural structure, but its contributions to language and cognition have remained elusive.
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New paper! 🧠 **The cerebellar components of the human language network**

with: @hsmall.bsky.social @moshepoliak.bsky.social @gretatuckute.bsky.social @benlipkin.bsky.social @awolna.bsky.social @aniladmello.bsky.social and @evfedorenko.bsky.social

www.biorxiv.org/content/10.1...

1/n 🧵

Excited to share new work on the language system!

Using a large fMRI dataset (n=772) we comprehensively search for language-selective regions across the brain. w/
Aaron Wright, @benlipkin.bsky.social, and @evfedorenko.bsky.social

Link to the preprint: biorxiv.org/content/10.1...
Thread below!👇🧵