Publication overview

Most representative publications

Networks

  • De Vico Fallani F, Richiardi J, Chavez M, Achard S. Graph analysis of functional brain networks: practical issues in translational neuroscience. Philosophical Transactions of the Royal Society B: Biological Sciences 369:1653, 20130521–20130521, 2014. PDF Paper in PDF
  • De Vico Fallani F, Latora V, Chavez, M. A Topological Criterion for Filtering Information in Complex Brain Networks. PLOS Computational Biology, 13(1), e1005305, 2017.PDF Paper in PDF
  • De Vico Fallani F, Corazzol M, Sternberg JR, Wyart C, Chavez M. Hierarchy of neural organization in the embryonic spinal cord: Granger-causality graph analysis of in vivo calcium imaging data. IEEE Transactions on Neural Systems and Rehabilitation Engineering 23(3):333-341, 2014. PDF Paper in PDF
  • Obando C, De Vico Fallani F. A statistical model for brain networks inferred from large-scale electrophysiological signals. Journal of the Royal Society Interface (Accepted for Publication), 2017. PDF Paper in PDF
  • De Vico Fallani F, Nicosia V, Latora V, Chavez M. Non-parametric resampling of random walks for spectral networks clustering. Physical Review E 89, 012802, 2013. PDF Paper in PDF
  • Guillon J, Attal Y, Colliot O, La Corte V, Dubois B, Schwartz D, Chavez M, De Vico Fallani F Loss of brain inter-frequency hubs in Alzheimer’s disease. In Scientific Reports 7;10879. 2017.PDF Paper in PDF
  • Corsi M-C, Chavez M, Schwartz D, George N, Hugueville L, Kahn A E, Dupont S, Bassett D S, De Vico Fallani F,
    Functional disconnection of associative cortical areas predicts performance during BCI training, NeuroImage, 209: 116500, 2020. PDF Paper in PDF

Longitudinal

  • Schiratti J-B, Allassonniere S, Colliot O, Durrleman S. Learning spatiotemporal trajectories from manifold-valued longitudinal data. In Advances in Neural Information Processing Systems pp. 2395–2403, 2015. PDF Paper in PDF
  • Schiratti J-B, Allassonniere S, Colliot O, Durrleman S.A Bayesian mixed-efects model to learn trajectories of changes from repeated manifold-valued observations. In Journal of Machine Learning Research (JMLR) 18(1), 4840-4872. 2017. PDF Paper in PDF
  • Koval I, Schiratti JB, Routier A, Bacci M, Colliot M, Allassonnière S, Durrleman S. Spatiotemporal propagation of the cortical atrophy: population and individual patterns. In Frontiers in Neurology 9, 2018. PDF Paper in PDF

Morphometry

  • Durrleman S, Pennec X, Trouvé A, Braga J, Gerig G, Ayache N. Toward a comprehensive framework for the spatiotemporal statistical analysis of longitudinal shape data. International Journal of Computer Vision 103(1):22-59, 2013. PDF Paper in PDF
  • Durrleman S, Prastawa M, Charon N, Korenberg JR, Joshi S, Gerig G, Trouvé A. Morphometry of anatomical shape complexes with dense deformations and sparse parameters. NeuroImage 101:35–49, 2014. PDF Paper in PDF
  • Gori P, Colliot O, Marrakchi-Kacem L, Worbe Y, Poupon, C, Hartmann A, Ayache N, Durrleman S. A Bayesian framework for joint morphometry of surface and curve meshes in multi-object complexes. Medical Image Analysis , 35, 458-474, 2017.PDF Paper in PDF
  • Louis M, Charlier B, Jusselin P, Susovan P, Durrleman S. A fanning scheme for the parallel transport along geodesicson Riemmanian manifolds. In SIAM journal on Numerical Analysis 2017. 56(4), 256-2584PDF Paper in PDF
  • Bone A, Colliot O, Durrleman SLearning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms. In Computer Vision and Pattern Recognition (CVPR) 9271-9280, 2018. PDF Paper in PDF

Machine Learning

  • Cuingnet R, Glaunès JA, Chupin M, Benali H, Colliot O. The ADNI. Spatial and anatomical regularization of SVM: a general framework for neuroimaging data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(3):682-696, 2013. PDF Paper in PDF
  • Samper-González J, Burgos N, Bottani S, Fontanella S, Lu P, Marcoux A, Routier A, Guillon J, Bacci M, Wen J, Bertrand A, Bertin H, Habert MO, Durrleman S, Evgeniou T, Colliot O. Reproducible evaluation of classification methods in Alzheimer’s disease: Framework and application to MRI and PET data. Neuroimage, 183: 504–521, 2018. PDF Paper in PDF
  • Wen J, Thibeau-Sutre E, Samper-González J, Routier A, Bottani S, Durrleman S, Burgos N, Colliot O: Convolutional Neural Networks for Classification of Alzheimer’s Disease: Overview and Reproducible Evaluation, Medical Image Analysis, 63: 101694, 2020 PDF Paper in PDF
  • Ansart A, Epelbaum S, Gagliardi G, Colliot O, Dormont D, Dubois B, Hampel H, Durrleman S. Prediction of amyloidosis from neuropsychological and MRI data for cost effective inclusion of pre-symptomatic subjects in clinical trials. In Multimodal Learning for Clinical Decision Support, 357-364. 2017. PDF Paper in PDF
  • Wei, W., Poirion, E., Bodini, B., Durrleman, S., Ayache, N., Stankoff, B., Colliot, O. Predicting PET-derived Demyelination from Multimodal MRI using Sketcher-Refiner Adversarial Training for Multiple Sclerosis, Medical Image Analysis, 58: 101546, 2019. PDF Paper in PDF

Clinical studies

  • Dubois B, Chupin M, Hampel H, Lista S, Cavedo E, Croisile B, Tisserand GL, Touchon J, Bonafe A, Ousset PJ, Ait Ameur A, Rouaud O, Ricolfi F, Vighetto A, Pasquier F, Delmaire C, Ceccaldi M, Girard N, Lehéricy S, Tonelli I, Duveau F, Colliot O, Garnero L, Sarazin M, Dormont D. Donepezil decreases annual rate of hippocampal atrophy in suspected prodromal Alzheimer’s disease. Alzheimer’s & Dementia 11(9):1041–1049, 2015. PDF Paper in PDF
  • Hamelin L, Bertoux M, Bottlaender M, Corne H, Lagarde J, Hahn V, Mangin JF, Dubois B, Chupin M, Cruz de Souza L, Colliot O, Sarazin M, Sulcal morphology as a new imaging marker for the diagnosis of early onset Alzheimer’s disease, Neurobiology of Aging, 36(11):2932-9, 2015 PDF Paper in PDF
  • Betrand A, Wen J, Rinaldi D, Houot M, Sayah S, Camuzat A, Fournier C, Fontanella S, Routier A, Couratier P, Pasquier F, Habert MO, Hannequin D, Martinaud O, Caroppo P, Levy R, Dubois B, Brice A, Durrleman S, Colliot O. Early Cognitive, Structural, and Microstructural Changes in Presymptomatic C9orf72 Carriers Younger Than 40 Years. In JAMA neurology 75(2);236-245, 2018. PDF Paper in PDF
  • Dubois B, Epelbaum S, Nyasse F, Bakardjian H, Gagliardi G, Uspenskaya O, Houot M, Lista S, Cacciamani F, Potier MC, Bertrand A, Lamari F, Benali H, Mangin JF, Colliot O, Genthon R, Habert MO, Hampel H; INSIGHT-preAD study group. Cognitive and neuroimaging features and brain β-amyloidosis in individuals at risk of Alzheimer’s disease (INSIGHT-preAD): a longitudinal observational study.. In Lancet Neurol.. 2018, Apr;17(4):335-346. PDF Paper in PDF
  • Wen J, Zhang H, Alexander DC, Durrleman S, Routier A, Rinaldi D, Jouot M, Couratier P, Hannequin D, Pasquier F, Zhang J, Colliot O, Le Ber I, Bertrand A. Neurite density is reduced in the presymptomatic phase of C9orf72 disease. In J Neurol Neurosurg Psychiatry 318994. 2018. PDF Paper in PDF

 

Full list of publications

Here is a link to our publications on the open archive HAL.

 

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