6 citations · 20 across the 12 of their papers we have counts for
5 papers · 1 filter
Scaling and context steer LLMs along the same computational path as the human brain
Joséphine Raugel, Stéphane d'Ascoli, Jérémy Rapin +2
Recent studies suggest that the representations learned by large language models (LLMs) are partially aligned to those of the human brain. However, whether and why this alignment s…
TRIBE: TRImodal Brain Encoder for whole-brain fMRI response prediction
Stéphane d'Ascoli, Jérémy Rapin, Yohann Benchetrit +2
Historically, neuroscience has progressed by fragmenting into specialized domains, each focusing on isolated modalities, tasks, or brain regions. While fruitful, this approach hind…
Brain-to-Text Decoding: A Non-invasive Approach via Typing
Jarod Lévy, Mingfang Zhang, Svetlana Pinet +4
Modern neuroprostheses can now restore communication in patients who have lost the ability to speak or move. However, these invasive devices entail risks inherent to neurosurgery.…
From Thought to Action: How a Hierarchy of Neural Dynamics Supports Language Production
Mingfang Zhang, Jarod Lévy, Stéphane d'Ascoli +5
Humans effortlessly communicate their thoughts through intricate sequences of motor actions. Yet, the neural processes that coordinate language production remain largely unknown, i…
Scaling laws for decoding images from brain activity
Hubert Banville, Yohann Benchetrit, Stéphane d'Ascoli +2
Generative AI has recently propelled the decoding of images from brain activity. How do these approaches scale with the amount and type of neural recordings? Here, we systematicall…