Ruimin Gao

Research tech @ Georgia Tech LIT Lab

[Ruimin Gao @Ruimin_G]

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?
🧵👇

https://t.co/X7g3ye51CI

[Anna Ivanova @neuranna]

Now out in Imaging Neuroscience! The language network responds robustly to sentences across tasks
https://t.co/zNXh4cWbTD

[Ruimin Gao @Ruimin_G]

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!

[Anna Ivanova @neuranna]

Language, Intelligence & Thought lab is looking for a lab manager! This is a 2-year postbac position that will allow you to gain experience in human neuroscience, cognitive science, and AI research prior to applying to PhD programs.

Express interest here: https://t.co/HMUll9bH6q

[Anna Ivanova @neuranna]

The last chapter of my PhD (expanded) is finally out as a preprint!

“Semantic reasoning takes place largely outside the language network” 🧠🧐

https://t.co/Z7cgHsvIbu

What is semantic reasoning? Read on! 🧵👇

[Ruimin Gao @Ruimin_G]

@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.

[Ruimin Gao @Ruimin_G]

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?
🧵👇

https://t.co/X7g3ye51CI

[Ruimin Gao @Ruimin_G]

@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.

[Anna Ivanova @neuranna]

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

1/

[Anna Ivanova @neuranna]

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.

https://t.co/NW78qjEx51

[Taha Binhuraib 🦉 @NeuroTaha]

🚨 Paper alert:
To appear in the DBM Neurips Workshop

LITcoder: A General-Purpose Library for Building and Comparing Encoding Models

📄 arxiv: https://t.co/jXoYcIkpsC
🔗 project: https://t.co/UHtzfGGriY

[Anna Ivanova @neuranna]

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

[Anna Ivanova @neuranna]

Looking forward to #cogsci2025 ! Find us throughout the conference

[Ruimin Gao @Ruimin_G]

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)
https://t.co/liWaPbG6lJ

[Ruimin Gao @Ruimin_G]

Excited to introduce funROI: A Python package for functional ROI analyses of fMRI data!

https://t.co/5Ch4LvyctJ

#fMRI #Neuroimaging #Python #OpenScience

Work w @neuranna

🧵👇

[Ruimin Gao @Ruimin_G]

Many thanks to @ev_fedorenko & Alfonso Nieto-Castañon for developing these methods in Fedorenko et al (2010) and in subsequent works!
https://t.co/8GoAuNomoE