4 citations · 15 across the 13 of their papers we have counts for
5 papers · 1 filter
DANCE: Detect and Classify Events in EEG
Jarod Lévy, Hubert Banville, Jérémy Rapin +3
Event identification in continuous neural recordings is a critical task in neuroscience. Decoding in EEG is dominated by classifying windows aligned to known event onsets. However,…
NeuralBench: A Unifying Framework to Benchmark NeuroAI Models
Hubert Banville, Stéphane d'Ascoli, Simon Dahan +12
Deep learning and large public datasets have recently catalyzed the proliferation of AI models for processing brain recordings. However, systematically evaluating these models rema…
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…
Aligning brain functions boosts the decoding of visual semantics in novel subjects
Alexis Thual, Yohann Benchetrit, Felix Geilert +4
Deep learning is leading to major advances in the realm of brain decoding from functional Magnetic Resonance Imaging (fMRI). However, the large inter-subject variability in brain c…