We’d love your feedback on BERG (github.com/gifale95/BERG): pretrained encoding models + a Python toolkit for generating in silico neural responses for in silico experimentation. Your input will make BERG more useful and reliable! forms.gle/pybrqcaqdso2... #NeuroAI #CompNeuro #neuroscience #AI

The Brain Encoding Response Generator (BERG) survey

Thank you for taking part in this survey aimed at (anonymously) collecting your thoughts and suggestions on a new resource called the Brain Encoding Response Generator (BERG; https://github.com/gifale...

forms.gle

CNeuroMod is now on substack, and our first post highlights a new study showing that a tiny 2M-parameter audio model can be meaningfully fine-tuned on an individual brain with benefits for downstream AI tasks. open.substack.com/pub/cneuromo...

When an audio AI Model Play 🧠 Dress-Up

This really is about fine-tuning an audio artificial network to align representations with human brain data, and seeing what happened next

open.substack.com

Our very own Isil Bilgin will share some updates on her work with Leila Wehbe and @lune-bellec.bsky.social to create brain-aligned language models by fine-tuning LLAMA-7B to produce brain-like embeddings.

Hao-Ting Wang@haotingwang.bsky.social · 9mo ago

On November 26th noon ET, @complexbrains.bsky.social will present her talk titled " Aligning Brains and Language Models: Toward a NeuroAI Framework for Brain-Grounded Language Understanding". The project combined @cneuromod.ca dataset 🧠🧑‍🤝‍🧑 and AI 🤖.

Brain–AI alignment can reveal exciting similarities in representations. Our Super Mario Bros. experiment demonstrates an important caveat: alignment can be very brittle. 1/🧵

Very much looking forward to #CCN2025! Would love to see you at our lab's talks and posters, and meet me at the panel discussion in the Algonauts session on Wednesday!

In 2019, the CNeuroMod team and 6 participants began a massive data collection journey: twice-weekly MRI scans for most of 5 years. Data collection is now complete! 1/🧵

In 2019, the CNeuroMod team and 6 participants began a massive data collection journey: twice-weekly MRI scans for most of 5 years. Data collection is now complete! 1/🧵

New CNeuroMod-THINGS open-access fMRI dataset: 4 participants · ~4 000 images (720 categories) each shown 3× (12k trials per subject)· individual functional localizers & NSD-inspired QC . Preprint: arxiv.org/abs/2507.09024 Congrats Marie St-Laurent and @martinhebart.bsky.social !!

Excited to announce the first workshop on CogInterp: Interpreting Cognition in Deep Learning Models @ NeurIPS 2025! 📣 How can we interpret the algorithms and representations underlying complex behavior in deep learning models? 🌐 coginterp.github.io/neurips2025/ 1/4

Can one hundred MRI scans be linked to hearing loss? The case of the Courtois NeuroMod project 🧠🎧👇🧵

🧠📊 Just out: a deeply sample structural brain and spine dataset from the cneuromod.ca team, now published in Imaging Neuroscience! led by Mathieu Boudreau and Julien Cohen-Adad. 📰 Paper here: lnkd.in/ewXA3dED 1/🧵