41 citations · 49 across the 7 of their papers we have counts for
7 papers
Probing Brain Context-Sensitivity with Masked-Attention Generation
Alexandre Pasquiou, Yair Lakretz, Bertrand Thirion +1
Two fundamental questions in neurolinguistics concerns the brain regions that integrate information beyond the lexical level, and the size of their window of integration. To addres…
Information-Restricted Neural Language Models Reveal Different Brain Regions' Sensitivity to Semantics, Syntax and Context
Alexandre Pasquiou, Yair Lakretz, Bertrand Thirion +1
A fundamental question in neurolinguistics concerns the brain regions involved in syntactic and semantic processing during speech comprehension, both at the lexical (word processin…
Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps
Alexandre Pasquiou, Yair Lakretz, John Hale +2
Neural Language Models (NLMs) have made tremendous advances during the last years, achieving impressive performance on various linguistic tasks. Capitalizing on this, studies in ne…
Toward a realistic model of speech processing in the brain with self-supervised learning
Juliette Millet, Charlotte Caucheteux, Pierre Orhan +5
Several deep neural networks have recently been shown to generate activations similar to those of the brain in response to the same input. These algorithms, however, remain largely…
Improving accuracy and power with transfer learning using a meta-analytic database
Yannick Schwartz, Gaël Varoquaux, Christophe Pallier +3
Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investiga…
Improved brain pattern recovery through ranking approaches
Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux +3
Inferring the functional specificity of brain regions from functional Magnetic Resonance Images (fMRI) data is a challenging statistical problem. While the General Linear Model (GL…
Learning to rank from medical imaging data
Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux +3
Medical images can be used to predict a clinical score coding for the severity of a disease, a pain level or the complexity of a cognitive task. In all these cases, the predicted v…