821 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Institut du CerveauFR17 papers
- Centre National de la Recherche ScientifiqueFR13 papers
- InsermFR12 papers
- Sorbonne UniversitéFR12 papers
- Pitié-Salpêtrière HospitalFR8 papers
- Institut national de recherche en sciences et technologies du numériqueFR7 papers
- Assistance Publique – Hôpitaux de ParisFR5 papers
- Institut des Sciences MoléculairesFR4 papers
- Centre de Recherche des CordeliersFR3 papers
- Université Pierre-et-Marie-CurieFR3 papers
- Santa Fe InstituteUS2 papers
- Sorbonne Paris CitéFR2 papers
17 papers
Multiscale modeling of brain network organization
Charley Presigny, Fabrizio De Vico Fallani
A complete understanding of the brain requires an integrated description of the numerous scales of neural organization. It means studying the interplay of genes, synapses, and even…
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder
Clément Chadebec, Elina Thibeau-Sutre, Ninon Burgos +1
In this paper, we propose a new method to perform data augmentation in a reliable way in the High Dimensional Low Sample Size (HDLSS) setting using a geometry-based variational aut…
Improving J-divergence of brain connectivity states by graph Laplacian denoising
Tiziana Cattai, Gaetano Scarano, Marie-Constance Corsi +3
Functional connectivity (FC) can be represented as a network, and is frequently used to better understand the neural underpinnings of complex tasks such as motor imagery (MI) detec…
Geometry-Aware Hamiltonian Variational Auto-Encoder
Clément Chadebec, Clément Mantoux, Stéphanie Allassonnière
Variational auto-encoders (VAEs) have proven to be a well suited tool for performing dimensionality reduction by extracting latent variables lying in a potentially much smaller dim…
BCI learning induces core-periphery reorganization in M/EEG multiplex brain networks
Marie-Constance Corsi, Mario Chavez, Denis Schwartz +6
Brain-computer interfaces (BCIs) constitute a promising tool for communication and control. However, mastering non-invasive closed-loop systems remains a learned skill that is diff…
Inferring epistasis from genomic data with comparable mutation and outcrossing rate
Hong-Li Zeng, Eugenio Mauri, Vito Dichio +3
We consider a population evolving due to mutation, selection and recombination, where selection includes single-locus terms (additive fitness) and two-loci terms (pairwise epistati…
Gaussian Graphical Model exploration and selection in high dimension low sample size setting
Thomas Lartigue, Simona Bottani, Stephanie Baron +3
Gaussian Graphical Models (GGM) are often used to describe the conditional correlations between the components of a random vector. In this article, we compare two families of GGM i…
Temporal connection signatures of human brain networks after stroke
Catalina Obando, Charlotte Rosso, Joshua Siegel +2
Plasticity after stroke is a complex phenomenon initiated by the functional reorganization of the brain, especially in the perilesional tissue. At macroscales, the reestablishment…
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation
Junhao Wen, Elina Thibeau-Sutre, Mauricio Diaz-Melo +7
Over 30 papers have proposed to use convolutional neural network (CNN) for AD classification from anatomical MRI. However, the classification performance is difficult to compare ac…
Reproducible evaluation of classification methods in Alzheimer's disease: framework and application to MRI and PET data
Jorge Samper-González, Ninon Burgos, Simona Bottani +13
A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of AD. However, they are difficult to reproduce because…
Converting Alzheimer s disease map into a heavyweight ontology: a formal network to integrate data
Vincent Henry, Ivan Moszer, Olivier Dameron +3
Alzheimer s disease (AD) pathophysiology is still imperfectly understood and current paradigms have not led to curative outcome. Omics technologies offer great promises for improvi…
Network neuroscience for optimizing brain-computer interfaces
Fabrizio De Vico Fallani, Danielle S. Bassett
Human-machine interactions are being increasingly explored to create alternative ways of communication and to improve our daily life. Based on a classification of the user's intent…
Integrating EEG and MEG signals to improve motor imagery classification in brain-computer interfaces
Marie-Constance Corsi, Mario Chavez, Denis Schwartz +4
We propose a fusion approach that combines features from simultaneously recorded electroencephalographic (EEG) and magnetoencephalographic (MEG) signals to improve classification p…
Loss of brain inter-frequency hubs in Alzheimer's disease
Jeremy Guillon, Yohan Attal, Olivier Colliot +5
Alzheimer's disease (AD) causes alterations of brain network structure and function. The latter consists of connectivity changes between oscillatory processes at different frequenc…
Robust imaging of hippocampal inner structure at 7T: in vivo acquisition protocol and methodological choices
Linda Marrakchi-Kacem, Alexandre Vignaud, Julien Sein +8
OBJECTIVE:Motion-robust multi-slab imaging of hippocampal inner structure in vivo at 7T.MATERIALS AND METHODS:Motion is a crucial issue for ultra-high resolution imaging, such as c…
A topological criterion for filtering information in complex brain networks
Fabrizio De Vico Fallani, Vito Latora, Mario Chavez
In many biological systems, the network of interactions between the elements can only be inferred from experimental measurements. In neuroscience, non-invasive imaging tools are ex…
Riemannian geometry applied to detection of respiratory states from EEG signals: the basis for a brain-ventilator interface
X Navarro-Sune, A. L. Hudson, F. De Vico Fallani +6
During mechanical ventilation, patient-ventilator disharmony is frequently observed and may result in increased breathing effort, compromising the patient's comfort and recovery. T…