887 citations
- Centre National de la Recherche ScientifiqueFR81 papers
- Sorbonne UniversitéFR79 papers
- InsermFR75 papers
- Pitié-Salpêtrière HospitalFR52 papers
- Assistance Publique – Hôpitaux de ParisFR43 papers
- Institut national de recherche en sciences et technologies du numériqueFR25 papers
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- ARAMIS: Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain sain et pathologiqueFR17 papers
- Université Paris CitéFR11 papers
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- Allen Institute for Brain ScienceUS8 papers
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11 papers · 1 filter
Multiplex core-periphery organization of the human connectome
Federico Battiston, Jeremy Guillon, Mario Chavez +2
The behavior of many complex systems is determined by a core of densely interconnected units. While many methods are available to identify the core of a network when connections be…
Parallel transport in shape analysis: a scalable numerical scheme
Maxime Louis, Alexandre Bône, Benjamin Charlier +1
The analysis of manifold-valued data requires efficient tools from Riemannian geometry to cope with the computational complexity at stake. This complexity arises from the always-in…
Prediction of the progression of subcortical brain structures in Alzheimer's disease from baseline
Alexandre Bône, Maxime Louis, Alexandre Routier +5
We propose a method to predict the subject-specific longitudinal progression of brain structures extracted from baseline MRI, and evaluate its performance on Alzheimer's disease da…
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…
Multilevel Modeling with Structured Penalties for Classification from Imaging Genetics data
Pascal Lu, Olivier Colliot
In this paper, we propose a framework for automatic classification of patients from multimodal genetic and brain imaging data by optimally combining them. Additive models with unad…
Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks
Igor Koval, Jean-Baptiste Schiratti, Alexandre Routier +4
We introduce a mixed-effects model to learn spatiotempo-ral patterns on a network by considering longitudinal measures distributed on a fixed graph. The data come from repeated obs…