9/ Wonderful collaboration with extremely talented colleagues: Hana Ali, @zhenqi.bsky.social , Filip Milisav, @gozziale.bsky.social , Danilo Bzdok, & @misicbata.bsky.social (& thanks to our AI neuroscience experts 🤖 of course!)
8/ The Big Picture
To sum up: AI-powered synthesis of the neuroscience literature brings together a scattered literature to identify emergent patterns across disparate subfields, modalities, and species.
Try it yourself with our GitHub repo: github.com/Hana-Ali/neu...
7/ Mapping disorder involvement ⚕️
We derive regional risk maps for 30+ brain disorders 🧠🩹. Their clustering aligns with official ICD-11 clinical classification 🩺 better than clustering maps of risk-gene expression 🧬, & recover symptom co-morbidities
6/ From shared function to shared co-activation
Regions’ LLM-derived cognitive similarity predicts functional co-activation from fMRI, and effects of direct stimulation ⚡️ better than anatomical connectivity, molecular profile, or spatial proximity - also in 🐭&🐒
5/ Conserved molecular circuits for cognition 🧬🧠
We can also extend to macaque🐒 & mouse🐭 previous human studies based on NeuroSynth (Hansen 2021 Nat Hum Behav; Luppi 2024 Nat Biomed Eng). Integration w/ species-specific gene expression 🧬 reveals a cross-species molecular circuit for cognition
4/ A functional cortical hierarchy is latent in the literature
Asking the LLMs about regions and functions one-by-one spontaneously reveals a unimodal-transmodal functional hierarchy 🧠 matching species-specific anatomical hierarchy
3/ Unlocking Cross-Species Discovery 🐒🐭
We can use the LLM-generated maps to decode brain maps from other species. We show this with 🐒 macaque working memory & the recent Neuropixel maps of 🐭 mouse neural activity during cognitive tasks, from International Brain Laboratory (doi.org/10.1038/s415...)
2/ Beyond traditional meta-analysis
LLM maps go beyond traditional meta-analysis tools: they correlate better with 🧠 circuits derived from direct causal interventions from intracranial electrical stimulation ⚡️ and Lesion Network Mapping
1/ AI-driven cognitive mapping
We use Large Language Models (GPT-4, Gemini, Llama, Mistral, DeepSeek) as neuroscience experts, to synthesise the evidence that region X is involved in function/disorder Y. We can do this for humans but also macaque 🐒 & mouse 🐭
🧠 Excited to share our latest preprint: Automated Brain Mapping with AI Experts!🤖
www.biorxiv.org/content/10.6...
Ever wanted to summarise the cognitive/systems neuroscience literature beyond MRI and PET? Ever wished we could do the same for macaque 🐒 and mouse 🐭 ? Read on! 🧵👇
Dr Andrea Luppi is one of 25 early-career researchers recognised for their outstanding scientific contributions and commitment to mentoring and community-building in neuroscience.
@thetransmitter.bsky.social
@stjohnscollege.bsky.social
www.eng.cam.ac.uk/news/dr-andr...
@loopyluppi.bsky.social & @frosas.bsky.social have written a reply. I recommend reading this as it clarifies their stance and advances the discussion:
www.nature.com/articles/s41...
I think this was a fruitful exchange. It was also a great experience to write this up w/ David in Amsterdam @ CCN2025
Just out in Nature Reviews Neuroscience! We've been studying information synergy within the brain for a few years now: here we explore how we can take this approach to the level of synergy *between* brains! 🧠🔄🧠
Thanks to @edoardochidichimo.bsky.social for making this inter-brain synergy possible!
Incredibly grateful to @misicbata.bsky.social for the nomination, and to him and my other mentors @estamatakis.bsky.social, David Menon, and Morten Kringelbach for having my back at every step of the way 🙏
Truly honored to be recognized among @thetransmitter.bsky.social's Rising Stars of Neuroscience for 2025 next to trailblazers like @valeriejsydnor.bsky.social, @lindenmp.bsky.social, @elimuller.bsky.social & more!🌟🧠Check out everyone's full contributions at www.thetransmitter.org/early-career...
