Ruimin Gao

A left frontal-temporal network selectively supports language comprehension and production. Are computations in this language network driven primarily by bottom-up input, or by top-down task demands? 🧵👇 biorxiv.org/content/10.648…

We’re hiring a new Lab Manager! I’ve loved working in this lab — super supportive environment and meaningful work in AI + cognitive neuroscience Highly recommend for anyone looking to gain research experience before grad school!

The last chapter of my PhD (expanded) is finally out as a preprint! “Semantic reasoning takes place largely outside the language network” 🧠🧐 biorxiv.org/content/10.648… What is semantic reasoning? Read on! 🧵👇

@ev_fedorenko @neuranna @HopeKean 7/ Practical implications: Language localizers using the sentences>nonwords contrast are robust to task variation. But if your localizer includes an active task, ensure the control condition is at least as difficult as the critical one, or you’ll mix language and MD networks.

@ev_fedorenko @neuranna @HopeKean 6/ Conclusion: The language network is primarily input-driven. Although modestly modulated by task demands, its response profile and activation pattern remain stable across tasks. Task demands, however, engage the MD network.

A left frontal-temporal network selectively supports language comprehension and production. Are computations in this language network driven primarily by bottom-up input, or by top-down task demands? 🧵👇 biorxiv.org/content/10.648…

A fun collaborative project! We leverage TunedLens (~linear decoding of tokens) to explore how LLMs' internal representations change from layer to layer. 1/

It's been more than a year, but the EWoK (Elements of World Knowledge) paper is finally out in TACL! tl;dr: language models learn basic social concepts way easier than physical and spatial concepts. direct.mit.edu/tacl/article/d…

🚨 Paper alert: To appear in the DBM Neurips Workshop LITcoder: A General-Purpose Library for Building and Comparing Encoding Models 📄 arxiv: arxiv.org/abs/2509.09152… 🔗 project: litcoder-brain.github.io

Many thanks to the volunteer organizers and presenters for making the CCN watch party at Georgia Tech a success! And thanks attendees for coming&engaging in discussions! @V1o6ynne @NeuroTaha @alishdipani @jwilldecker @EyasAyesh @Ruimin_G Elliot Huang @PsychBoyH Eslam Abdelaleem

Looking forward to #cogsci2025 ! Find us throughout the conference

P.S. If you’re a Matlab user, you can try using the spm_ss toolbox developed by Alfonso (which we here adapted for Python+BIDS) github.com/alfnie/spm_ss

Many thanks to @ev_fedorenko & Alfonso Nieto-Castañon for developing these methods in Fedorenko et al (2010) and in subsequent works! journals.physiology.org/doi/full/10.11…

Excited to introduce funROI: A Python package for functional ROI analyses of fMRI data! funroi.readthedocs.io/en/latest/ #fMRI #Neuroimaging #Python #OpenScience Work w @neuranna 🧵👇