Search Results for author: Bertrand Thirion

Found 49 papers, 23 papers with code

Variable Importance in High-Dimensional Settings Requires Grouping

1 code implementation18 Dec 2023 Ahmad Chamma, Bertrand Thirion, Denis A. Engemann

Furthermore, as handling groups with high cardinality (such as a set of observations of a given modality) are both time-consuming and resource-intensive, we also introduce a new stacking approach extending the DNN architecture with sub-linear layers adapted to the group structure.

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

no code implementations11 Sep 2023 Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff, Yoni K. Ashar, Tibor Auer, Sylvain Baillet, Shashank Bansal, Leandro Beltrachini, Christian G. Benar, Giacomo Bertazzoli, Suyash Bhogawar, Ross W. Blair, Marta Bortoletto, Mathieu Boudreau, Teon L. Brooks, Vince D. Calhoun, Filippo Maria Castelli, Patricia Clement, Alexander L Cohen, Julien Cohen-Adad, Sasha D'Ambrosio, Gilles de Hollander, María de la iglesia-Vayá, Alejandro de la Vega, Arnaud Delorme, Orrin Devinsky, Dejan Draschkow, Eugene Paul Duff, Elizabeth Dupre, Eric Earl, Oscar Esteban, Franklin W. Feingold, Guillaume Flandin, anthony galassi, Giuseppe Gallitto, Melanie Ganz, Rémi Gau, James Gholam, Satrajit S. Ghosh, Alessio Giacomel, Ashley G Gillman, Padraig Gleeson, Alexandre Gramfort, Samuel Guay, Giacomo Guidali, Yaroslav O. Halchenko, Daniel A. Handwerker, Nell Hardcastle, Peer Herholz, Dora Hermes, Christopher J. Honey, Robert B. Innis, Horea-Ioan Ioanas, Andrew Jahn, Agah Karakuzu, David B. Keator, Gregory Kiar, Balint Kincses, Angela R. Laird, Jonathan C. Lau, Alberto Lazari, Jon Haitz Legarreta, Adam Li, Xiangrui Li, Bradley C. Love, Hanzhang Lu, Camille Maumet, Giacomo Mazzamuto, Steven L. Meisler, Mark Mikkelsen, Henk Mutsaerts, Thomas E. Nichols, Aki Nikolaidis, Gustav Nilsonne, Guiomar Niso, Martin Norgaard, Thomas W Okell, Robert Oostenveld, Eduard Ort, Patrick J. Park, Mateusz Pawlik, Cyril R. Pernet, Franco Pestilli, Jan Petr, Christophe Phillips, Jean-Baptiste Poline, Luca Pollonini, Pradeep Reddy Raamana, Petra Ritter, Gaia Rizzo, Kay A. Robbins, Alexander P. Rockhill, Christine Rogers, Ariel Rokem, Chris Rorden, Alexandre Routier, Jose Manuel Saborit-Torres, Taylor Salo, Michael Schirner, Robert E. Smith, Tamas Spisak, Julia Sprenger, Nicole C. Swann, Martin Szinte, Sylvain Takerkart, Bertrand Thirion, Adam G. Thomas, Sajjad Torabian, Gael Varoquaux, Bradley Voytek, Julius Welzel, Martin Wilson, Tal Yarkoni, Krzysztof J. Gorgolewski

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities.

Probing Brain Context-Sensitivity with Masked-Attention Generation

no code implementations23 May 2023 Alexandre Pasquiou, Yair Lakretz, Bertrand Thirion, Christophe Pallier

Two fundamental questions in neurolinguistics concerns the brain regions that integrate information beyond the lexical level, and the size of their window of integration.

Word Embeddings

Information-Restricted Neural Language Models Reveal Different Brain Regions' Sensitivity to Semantics, Syntax and Context

1 code implementation28 Feb 2023 Alexandre Pasquiou, Yair Lakretz, Bertrand Thirion, Christophe Pallier

A fundamental question in neurolinguistics concerns the brain regions involved in syntactic and semantic processing during speech comprehension, both at the lexical (word processing) and supra-lexical levels (sentence and discourse processing).

Language Modelling Sentence

Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps

no code implementations7 Jul 2022 Alexandre Pasquiou, Yair Lakretz, John Hale, Bertrand Thirion, Christophe Pallier

Neural Language Models (NLMs) have made tremendous advances during the last years, achieving impressive performance on various linguistic tasks.

Language Modelling

A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension

no code implementations29 May 2022 Binh T. Nguyen, Bertrand Thirion, Sylvain Arlot

Identifying the relevant variables for a classification model with correct confidence levels is a central but difficult task in high-dimension.

regression Test +1

Shared Independent Component Analysis for Multi-Subject Neuroimaging

1 code implementation NeurIPS 2021 Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvärinen

While ShICA-J is based on second-order statistics, we further propose to leverage non-Gaussianity of the components using a maximum-likelihood method, ShICA-ML, that is both more accurate and more costly.


Functional Magnetic Resonance Imaging data augmentation through conditional ICA

2 code implementations11 Jul 2021 Badr Tajini, Hugo Richard, Bertrand Thirion

Advances in computational cognitive neuroimaging research are related to the availability of large amounts of labeled brain imaging data, but such data are scarce and expensive to generate.

Brain Decoding Data Augmentation

Spatially relaxed inference on high-dimensional linear models

1 code implementation4 Jun 2021 Jérôme-Alexis Chevalier, Tuan-Binh Nguyen, Bertrand Thirion, Joseph Salmon

This calls for a reformulation of the statistical inference problem, that takes into account the underlying spatial structure: if covariates are locally correlated, it is acceptable to detect them up to a given spatial uncertainty.

Constrained Clustering Vocal Bursts Intensity Prediction

Adaptive Multi-View ICA: Estimation of noise levels for optimal inference

no code implementations22 Feb 2021 Hugo Richard, Pierre Ablin, Aapo Hyvärinen, Alexandre Gramfort, Bertrand Thirion

By contrast, we propose Adaptive multiView ICA (AVICA), a noisy ICA model where each view is a linear mixture of shared independent sources with additive noise on the sources.


An empirical evaluation of functional alignment using inter-subject decoding

1 code implementation8 Dec 2020 Thomas Bazeille, Elizabeth Dupre, Jean-Baptise Poline, Bertrand Thirion

Taking inter-subject decoding accuracy as a quantification of inter-subject similarity, our results support the use of functional alignment to improve inter-subject comparisons in the face of variable structure-function organization.

Computational Efficiency

Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso

no code implementations NeurIPS 2020 Jerome-Alexis Chevalier, Joseph Salmon, Alexandre Gramfort, Bertrand Thirion

To deal with this, we adapt the desparsified Lasso estimator ---an estimator tailored for high dimensional linear model that asymptotically follows a Gaussian distribution under sparsity and moderate feature correlation assumptions--- to temporal data corrupted with autocorrelated noise.

Constrained Clustering EEG +3

Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso

1 code implementation29 Sep 2020 Jérôme-Alexis Chevalier, Alexandre Gramfort, Joseph Salmon, Bertrand Thirion

To deal with this, we adapt the desparsified Lasso estimator -- an estimator tailored for high dimensional linear model that asymptotically follows a Gaussian distribution under sparsity and moderate feature correlation assumptions -- to temporal data corrupted with autocorrelated noise.

Constrained Clustering EEG +3

Modeling Shared Responses in Neuroimaging Studies through MultiView ICA

1 code implementation NeurIPS 2020 Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin

Group studies involving large cohorts of subjects are important to draw general conclusions about brain functional organization.


Fine-grain atlases of functional modes for fMRI analysis

no code implementations5 Mar 2020 Kamalaker Dadi, Gaël Varoquaux, Antonia Machlouzarides-Shalit, Krzysztof J. Gorgolewski, Demian Wassermann, Bertrand Thirion, Arthur Mensch

We demonstrate the benefits of extracting reduced signals on our fine-grain atlases for many classic functional data analysis pipelines: stimuli decoding from 12, 334 brain responses, standard GLM analysis of fMRI across sessions and individuals, extraction of resting-state functional-connectomes biomarkers for 2, 500 individuals, data compression and meta-analysis over more than 15, 000 statistical maps.

Data Compression

NeuroQuery: comprehensive meta-analysis of human brain mapping

no code implementations21 Feb 2020 Jérôme Dockès, Russell Poldrack, Romain Primet, Hande Gözükan, Tal Yarkoni, Fabian Suchanek, Bertrand Thirion, Gaël Varoquaux

Reaching a global view of brain organization requires assembling evidence on widely different mental processes and mechanisms.

Aggregation of Multiple Knockoffs

2 code implementations ICML 2020 Tuan-Binh Nguyen, Jérôme-Alexis Chevalier, Bertrand Thirion, Sylvain Arlot

We develop an extension of the Knockoff Inference procedure, introduced by Barber and Candes (2015).

Multi-subject MEG/EEG source imaging with sparse multi-task regression

no code implementations3 Oct 2019 Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort

Magnetoencephalography and electroencephalography (M/EEG) are non-invasive modalities that measure the weak electromagnetic fields generated by neural activity.

EEG Electroencephalogram (EEG) +2

Fast shared response model for fMRI data

2 code implementations27 Sep 2019 Hugo Richard, Lucas Martin, Ana Luısa Pinho, Jonathan Pillow, Bertrand Thirion

The shared response model provides a simple but effective framework to analyse fMRI data of subjects exposed to naturalistic stimuli.

Group level MEG/EEG source imaging via optimal transport: minimum Wasserstein estimates

no code implementations13 Feb 2019 Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort

Inferring the location of the current sources that generated these magnetic fields is an ill-posed inverse problem known as source imaging.

EEG Electroencephalogram (EEG)

Approximate message-passing for convex optimization with non-separable penalties

2 code implementations17 Sep 2018 Andre Manoel, Florent Krzakala, Gaël Varoquaux, Bertrand Thirion, Lenka Zdeborová

We introduce an iterative optimization scheme for convex objectives consisting of a linear loss and a non-separable penalty, based on the expectation-consistent approximation and the vector approximate message-passing (VAMP) algorithm.

Extracting representations of cognition across neuroimaging studies improves brain decoding

1 code implementation17 Sep 2018 Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux

Analyzing data across studies could bring more statistical power; yet the current brain-imaging analytic framework cannot be used at scale as it requires casting all cognitive tasks in a unified theoretical framework.

Brain Decoding

Optimizing deep video representation to match brain activity

no code implementations7 Sep 2018 Hugo Richard, Ana Pinho, Bertrand Thirion, Guillaume Charpiat

The comparison of observed brain activity with the statistics generated by artificial intelligence systems is useful to probe brain functional organization under ecological conditions.

Optical Flow Estimation

Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data

1 code implementation31 Jul 2018 Sergul Aydore, Bertrand Thirion, Gael Varoquaux

In many applications where collecting data is expensive, for example neuroscience or medical imaging, the sample size is typically small compared to the feature dimension.

Clustering Denoising +2

Text to brain: predicting the spatial distribution of neuroimaging observations from text reports

no code implementations4 Jun 2018 Jérôme Dockès, Demian Wassermann, Russell Poldrack, Fabian Suchanek, Bertrand Thirion, Gaël Varoquaux

In this paper, we propose to mine brain medical publications to learn the spatial distribution associated with anatomical terms.

Stochastic Subsampling for Factorizing Huge Matrices

1 code implementation19 Jan 2017 Arthur Mensch, Julien Mairal, Bertrand Thirion, Gael Varoquaux

We present a matrix-factorization algorithm that scales to input matrices with both huge number of rows and columns.

Dictionary Learning

Learning brain regions via large-scale online structured sparse dictionary learning

no code implementations NeurIPS 2016 Elvis Dohmatob, Arthur Mensch, Gael Varoquaux, Bertrand Thirion

We propose a multivariate online dictionary-learning method for obtaining decompositions of brain images with structured and sparse components (aka atoms).

Dictionary Learning

Subsampled online matrix factorization with convergence guarantees

1 code implementation30 Nov 2016 Arthur Mensch, Julien Mairal, Gaël Varoquaux, Bertrand Thirion

We present a matrix factorization algorithm that scales to input matrices that are large in both dimensions (i. e., that contains morethan 1TB of data).

Social-sparsity brain decoders: faster spatial sparsity

no code implementations21 Jun 2016 Gaël Varoquaux, Matthieu Kowalski, Bertrand Thirion

Spatially-sparse predictors are good models for brain decoding: they give accurate predictions and their weight maps are interpretable as they focus on a small number of regions.

Brain Decoding General Classification

Dictionary Learning for Massive Matrix Factorization

1 code implementation3 May 2016 Arthur Mensch, Julien Mairal, Bertrand Thirion, Gaël Varoquaux

Sparse matrix factorization is a popular tool to obtain interpretable data decompositions, which are also effective to perform data completion or denoising.

Collaborative Filtering Dictionary Learning +2

Compressed Online Dictionary Learning for Fast fMRI Decomposition

no code implementations8 Feb 2016 Arthur Mensch, Gaël Varoquaux, Bertrand Thirion

We present a method for fast resting-state fMRI spatial decomposi-tions of very large datasets, based on the reduction of the temporal dimension before applying dictionary learning on concatenated individual records from groups of subjects.

Dictionary Learning

Fast clustering for scalable statistical analysis on structured images

no code implementations16 Nov 2015 Bertrand Thirion, Andrés Hoyos-Idrobo, Jonas Kahn, Gael Varoquaux

The use of brain images as markers for diseases or behavioral differences is challenged by the small effects size and the ensuing lack of power, an issue that has incited researchers to rely more systematically on large cohorts.

Clustering Computational Efficiency +1

Region segmentation for sparse decompositions: better brain parcellations from rest fMRI

no code implementations12 Dec 2014 Alexandre Abraham, Elvis Dohmatob, Bertrand Thirion, Dimitris Samaras, Gael Varoquaux

Functional Magnetic Resonance Images acquired during resting-state provide information about the functional organization of the brain through measuring correlations between brain areas.

Data-driven HRF estimation for encoding and decoding models

no code implementations27 Feb 2014 Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu, Bertrand Thirion, Alexandre Gramfort

We develop a method for the joint estimation of activation and HRF using a rank constraint causing the estimated HRF to be equal across events/conditions, yet permitting it to be different across voxels.

Computational Efficiency

Mapping paradigm ontologies to and from the brain

no code implementations NeurIPS 2013 Yannick Schwartz, Bertrand Thirion, Gael Varoquaux

Imaging neuroscience links brain activation maps to behavior and cognition via correlational studies.

Mapping cognitive ontologies to and from the brain

no code implementations15 Nov 2013 Yannick Schwartz, Bertrand Thirion, Gaël Varoquaux

Imaging neuroscience links brain activation maps to behavior and cognition via correlational studies.

Second order scattering descriptors predict fMRI activity due to visual textures

no code implementations10 Aug 2013 Michael Eickenberg, Fabian Pedregosa, Senoussi Mehdi, Alexandre Gramfort, Bertrand Thirion

Second layer scattering descriptors are known to provide good classification performance on natural quasi-stationary processes such as visual textures due to their sensitivity to higher order moments and continuity with respect to small deformations.

General Classification

HRF estimation improves sensitivity of fMRI encoding and decoding models

no code implementations13 May 2013 Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion, Alexandre Gramfort

Extracting activation patterns from functional Magnetic Resonance Images (fMRI) datasets remains challenging in rapid-event designs due to the inherent delay of blood oxygen level-dependent (BOLD) signal.

Brain covariance selection: better individual functional connectivity models using population prior

no code implementations NeurIPS 2010 Gael Varoquaux, Alexandre Gramfort, Jean-Baptiste Poline, Bertrand Thirion

We describe subject-level brain functional connectivity structure as a multivariate Gaussian process and introduce a new strategy to estimate it from group data, by imposing a common structure on the graphical model in the population.

Discriminative Network Models of Schizophrenia

no code implementations NeurIPS 2009 Irina Rish, Benjamin Thyreau, Bertrand Thirion, Marion Plaze, Marie-Laure Paillere-Martinot, Catherine Martelli, Jean-Luc Martinot, Jean-Baptiste Poline, Guillermo A. Cecchi

Schizophrenia is a complex psychiatric disorder that has eluded a characterization in terms of local abnormalities of brain activity, and is hypothesized to affect the collective, ``emergent working of the brain.

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