no code implementations • 26 Jul 2022 • Laura Gwilliams, Graham Flick, Alec Marantz, Liina Pylkkanen, David Poeppel, Jean-Remi King
The "MEG-MASC" dataset provides a curated set of raw magnetoencephalography (MEG) recordings of 27 English speakers who listened to two hours of naturalistic stories.
no code implementations • 3 Jun 2022 • Juliette Millet, Charlotte Caucheteux, Pierre Orhan, Yves Boubenec, Alexandre Gramfort, Ewan Dunbar, Christophe Pallier, Jean-Remi King
These elements, resulting from the largest neuroimaging benchmark to date, show how self-supervised learning can account for a rich organization of speech processing in the brain, and thus delineate a path to identify the laws of language acquisition which shape the human brain.
no code implementations • 28 Nov 2021 • Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
Predictive coding theory offers a potential explanation to this discrepancy: while deep language algorithms are optimized to predict adjacent words, the human brain would be tuned to make long-range and hierarchical predictions.
1 code implementation • 3 Mar 2021 • Omar Chehab, Alexandre Defossez, Jean-Christophe Loiseau, Alexandre Gramfort, Jean-Remi King
Understanding how the brain responds to sensory inputs is challenging: brain recordings are partial, noisy, and high dimensional; they vary across sessions and subjects and they capture highly nonlinear dynamics.
no code implementations • 2 Mar 2021 • Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
The activations of language transformers like GPT-2 have been shown to linearly map onto brain activity during speech comprehension.
no code implementations • 25 Feb 2021 • Juliette Millet, Jean-Remi King
Third, learning to process phonetically-related speech inputs (i. e., Dutch vs English) leads deep nets to reach higher levels of brain-similarity than learning to process phonetically-distant speech inputs (i. e. Dutch vs Bengali).
no code implementations • 25 Sep 2019 • Jean-Remi King, Francois Charton, Maxime Oquab, David Lopez-Paz
Identifying causes from observations can be particularly challenging when i) potential factors are difficult to manipulate individually and ii) observations are complex and multi-dimensional.