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09/14/2023
Statistically Valid Variable Importance Assessment through Conditional Permutations
Variable importance assessment has become a crucial step in machine-lear...
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02/28/2023
Information-Restricted Neural Language Models Reveal Different Brain Regions' Sensitivity to Semantics, Syntax and Context
A fundamental question in neurolinguistics concerns the brain regions in...
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08/29/2022
FDP control in multivariate linear models using the bootstrap
In this article we develop a method for performing post hoc inference of...
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07/07/2022
Neural Language Models are not Born Equal to Fit Brain Data, but Training Helps
Neural Language Models (NLMs) have made tremendous advances during the l...
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06/19/2022
Aligning individual brains with Fused Unbalanced Gromov-Wasserstein
Individual brains vary in both anatomy and functional organization, even...
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05/29/2022
A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension
Identifying the relevant variables for a classification model with corre...
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04/22/2022
Notip: Non-parametric True Discovery Proportion estimation for brain imaging
Cluster-level inference procedures are widely used for brain mapping. Th...
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10/12/2021
Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction
High-quality data accumulation is now becoming ubiquitous in the health ...
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06/04/2021
Spatially relaxed inference on high-dimensional linear models
We consider the inference problem for high-dimensional linear models, wh...
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09/29/2020
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified multi-task Lasso
Detecting where and when brain regions activate in a cognitive task or i...
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03/05/2020
Fine-grain atlases of functional modes for fMRI analysis
Population imaging markedly increased the size of functional-imaging dat...
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02/21/2020
Aggregation of Multiple Knockoffs
We develop an extension of the Knockoff Inference procedure, introduced ...
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02/21/2020
NeuroQuery: comprehensive meta-analysis of human brain mapping
Reaching a global view of brain organization requires assembling evidenc...
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10/03/2019
Multi-subject MEG/EEG source imaging with sparse multi-task regression
Magnetoencephalography and electroencephalography (M/EEG) are non-invasi...
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09/27/2019
Fast shared response model for fMRI data
The shared response model provides a simple but effective framework toan...
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03/12/2019
ECKO: Ensemble of Clustered Knockoffs for multivariate inference on fMRI data
Continuous improvement in medical imaging techniques allows the acquisit...
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02/13/2019
Group level MEG/EEG source imaging via optimal transport: minimum Wasserstein estimates
Magnetoencephalography (MEG) and electroencephalogra-phy (EEG) are non-i...
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09/17/2018
Approximate message-passing for convex optimization with non-separable penalties
We introduce an iterative optimization scheme for convex objectives cons...
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09/17/2018
Extracting Universal Representations of Cognition across Brain-Imaging Studies
The size of publicly available data in cognitive neuro-imaging has incre...
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09/07/2018
Optimizing deep video representation to match brain activity
The comparison of observed brain activity with the statistics generated ...
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07/31/2018
Using Feature Grouping as a Stochastic Regularizer for High-Dimensional Noisy Data
The use of complex models --with many parameters-- is challenging with h...
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06/15/2018
Statistical Inference with Ensemble of Clustered Desparsified Lasso
Medical imaging involves high-dimensional data, yet their acquisition is...
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06/04/2018
Text to brain: predicting the spatial distribution of neuroimaging observations from text reports
Despite the digital nature of magnetic resonance imaging, the resulting ...
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10/31/2017
Learning Neural Representations of Human Cognition across Many fMRI Studies
Cognitive neuroscience is enjoying rapid increase in extensive public br...
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01/19/2017
Stochastic Subsampling for Factorizing Huge Matrices
We present a matrix-factorization algorithm that scales to input matrice...
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11/18/2016
Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example
Resting-state functional Magnetic Resonance Imaging (R-fMRI) holds the p...
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09/15/2016
Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signals
-In this work, we revisit fast dimension reduction approaches, as with r...
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06/21/2016
Social-sparsity brain decoders: faster spatial sparsity
Spatially-sparse predictors are good models for brain decoding: they giv...
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06/16/2016
Assessing and tuning brain decoders: cross-validation, caveats, and guidelines
Decoding, ie prediction from brain images or signals, calls for empirica...
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05/03/2016
Dictionary Learning for Massive Matrix Factorization
Sparse matrix factorization is a popular tool to obtain interpretable da...
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02/08/2016
Compressed Online Dictionary Learning for Fast fMRI Decomposition
We present a method for fast resting-state fMRI spatial decomposi-tions ...
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11/16/2015
Fast clustering for scalable statistical analysis on structured images
The use of brain images as markers for diseases or behavioral difference...
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12/12/2014
Region segmentation for sparse decompositions: better brain parcellations from rest fMRI
Functional Magnetic Resonance Images acquired during resting-state provi...
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12/12/2014
Machine Learning for Neuroimaging with Scikit-Learn
Statistical machine learning methods are increasingly used for neuroimag...
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11/15/2013
Mapping cognitive ontologies to and from the brain
Imaging neuroscience links brain activation maps to behavior and cogniti...
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08/10/2013
Second order scattering descriptors predict fMRI activity due to visual textures
Second layer scattering descriptors are known to provide good classifica...
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09/24/2012
Improving accuracy and power with transfer learning using a meta-analytic database
Typical cohorts in brain imaging studies are not large enough for system...
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09/07/2012
On spatial selectivity and prediction across conditions with fMRI
Researchers in functional neuroimaging mostly use activation coordinates...
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07/16/2012
Learning to rank from medical imaging data
Medical images can be used to predict a clinical score coding for the se...
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07/15/2012
Improved brain pattern recovery through ranking approaches
Inferring the functional specificity of brain regions from functional Ma...
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06/27/2012
Small-sample Brain Mapping: Sparse Recovery on Spatially Correlated Designs with Randomization and Clustering
Functional neuroimaging can measure the brain?s response to an external ...
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05/02/2011
Multi-scale Mining of fMRI data with Hierarchical Structured Sparsity
Inverse inference, or "brain reading", is a recent paradigm for analyzin...
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04/28/2011
A supervised clustering approach for fMRI-based inference of brain states
We propose a method that combines signals from many brain regions observ...
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02/05/2011
Total variation regularization for fMRI-based prediction of behaviour
While medical imaging typically provides massive amounts of data, the ex...
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08/30/2010
Brain covariance selection: better individual functional connectivity models using population prior
Spontaneous brain activity, as observed in functional neuroimaging, has ...
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11/24/2009