Publications

Eising, E. , Mirza-Schreiber, N. , de Zeeuw, E. , ..., .., Ramus, F. & (Et Al), . (2022). Genome-wide analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people. PNAS, 19(35), e2202764119. doi:10.1073/pnas.2202764119

Valente, A., Ostojic, S. & Pillow, J. (2022). Probing the Relationship Between Latent Linear Dynamical Systems and Low-Rank Recurrent Neural Network Models. Neural Computation, 1-22. doi:10.1162/neco_a_01522

Williams, C., Peyre, H., Toro, R. & Ramus, F. (2022). Comparing brain asymmetries independently of brain size. NeuroImage, 254, 119118. doi:10.1016/j.neuroimage.2022.119118

Ramus, F., Di Folco , C. , Guez, A. & Peyre, H. (2021). Epidémiologie des troubles de la lecture en France : une comparaison du DSM-5 et de la CIM-11. Approche neuropsychologique des apprentissages chez l'enfant, 175, 639-649

Lizarazu, M., Scotto Di Covella, L., van Wassenhove, V. , Rivière, D., Mizzi, R. , Lehongre, K., Hertz-Pannier, L. & Ramus, F. (2021). Neural entrainment to speech and nonspeech in dyslexia: conceptual replication and extension of previous investigations. Cortex, 137, 160-178. doi:10.1016/j.cortex.2020.12.024

Gialluisi, A., Andlauer, T., Mirza-Schreiber, N., Moll, K., Becker, J., Hoffmann, P., Ludwig, K., Czamara, D., Pourcain, B. , Honbolygó, F., Tóth, D., Csépe, V., Huguet, G., Chaix, Y., Iannuzzi, S., Démonet, J., Morris, A., Hulslander, J., Willcutt, E., Defries, J., Olson, R., Smith, S., Pennington, B., Vaessen, A., Maurer, U., Lyytinen, H., Peyrard-Janvid, M., Leppänen, P., Brandeis, D., Bonte, M., Stein, J., Talcott, J., Fauchereau, F., Wilcke, A., Kirsten, H., Müller, B., Francks, C., Bourgeron, T., Monaco, A., Ramus, F., Landerl, K., Kere, J., Scerri, T., Paracchini, S., Fisher, S., Schumacher, J., Nöthen, M., Müller-Myhsok, B. & Schulte-Körne, G. (2021). Genome-wide association study reveals new insights into the heritability and genetic correlates of developmental dyslexia. Molecular Psychiatry, 26 (7), 3004-3017. doi:10.1038/s41380-020-00898-x

Guez, A., Peyre, H., Williams, C., Labouret, G. & Ramus, F. (2021). The epidemiology of cognitive development. Cognition, 213, 104690. doi:10.1016/j.cognition.2021.104690

Ramus, F. & Peyre, H. (2021). Can the Prevalence of ADHD Really be 0.3%? Journal of Attention Disorders, 25(10), 1351‑1351. doi:1d0o.i1.o1r7g/71/01.1018770/150487205049782609286892

Latimier, A., Peyre, H. & Ramus, F. (2020). A Meta-Analytic Review of the Benefit of Spacing out Retrieval Practice Episodes on Retention. Educational Psychology Review, 33(3), 959-987. doi:10.1007/s10648-020-09572-8

Williams, C., Peyre, H., Toro, R. & Ramus, F. (2021). Neuroanatomical norms in the UK Biobank: The impact of allometric scaling, sex, and age. Human Brain Mapping, 42(14), 4623-4642. doi:10.1002/hbm.25572

Di Folco , C. , Guez, A., Peyre, H. & Ramus, F. (2021). Epidemiology of reading disability: A comparison of DSM-5 and ICD-11 criteria. Scientific Studies of Reading, NA. doi:10.1080/10888438.2021.1998067

Liu , T., De Schotten, M. , Altarelli, I., Ramus, F. & Zhao, J. (2021). Maladaptive compensation of right fusiform gyrus in developmental dyslexia: A hub-based white matter network analysis. Cortex, 145, 57‑66. doi:10.1016/j.cortex.2021.07.016

Liu, S. , Wei, W. , Chen, Y. , Peyre, H. & Zhao, J. (2021). Visual–Spatial Ability Predicts Academic Achievement Through Arithmetic and Reading Abilities. Front. Psychol. doi:10.3389/fpsyg.2020.591308

Liu, C. , Tabea, S., M Davies, N. , Peyre, H., Lim, K. , Barker, E. , Llewellyn, C. , Dudbridge, F. & Pingault, J. (2021). Are there causal relationships between attention-deficit/hyperactivity disorder and body mass index? Evidence from multiple genetically informed designs. International Journal of Epidemiology, 50(2). doi:10.1093/ije/dyaa214

Kuchibhotla, K., Hindmarsh Sten, T., Papadoyannis, E., Elnozahy, S. , Fogelson, K. , Kumar, R., Boubenec, Y., Holland, P., Ostojic, S. & Froemke, R. (2020). Dissociating task acquisition from expression during learning reveals latent knowledge. Nature communications, 10(1), 2151. doi:10.1038/s41467-019-10089-0

Williams, C., Peyre, H., Toro, R. & Ramus, F. (2021). Sex differences in the brain are not reduced to differences in body size. Neuroscience & Biobehavioral Reviews, 130, 509-511. doi:10.1016/j.neubiorev.2021.09.015

Bernard, A., Bredeche, N. & Andre, J. (2020). Indirect genetic effects allow escape from the inefficient equilibrium in a coordination game. Evolution Letters, 4(3), 257-265. doi:10.1002/evl3.155

Beiran, M., Dubreuil, A., Valente, A., Mastrogiuseppe, F. & Ostojic, S. (2021). Shaping dynamics with multiple populations in low-rank recurrent networks. Neural Computation, 33(6), 1572-1615. doi:10.1162/neco_a_01381 Article history

Giulio, B., Thomas, D., Brice, B. & Ostojic, S. (2021). Network dynamics underlying OFF responses in the auditory cortex. eLife, 10, e53151. doi:10.7554/eLife.53151

Oswald, A. & Ostojic, S. (2020). Curating more diverse scientific conferences. Nat Rev Neurosci, 21, 589-590. doi:10.1038/s41583-020-0373-4

Bouchacourt, F., Palminteri, S., Koechlin, E. & Ostojic, S. (2020). Temporal Chunking as a Mechanism for Unsupervised Learning of Task-Sets. eLife, 9, e50469. doi:10.7554/eLife.50469

Bondanelli, G. & Ostojic, S. (2020). Coding with transient trajectories in recurrent neural networks. PLoS Computational Biology, 16 (2), e1007655. doi:10.1371/journal.pcbi.1007655

Schuessler, F. , Dubreuil, A., Mastrogiuseppe, F., Ostojic, S. & Barak, O. (2020). Dynamics of random recurrent networks with correlated low-rank structure. Phys. Rev. Research, 2(1), 013111. doi:10.1103/PhysRevResearch.2.013111

Lourenço, J. , De Stasi, A., Deleuze, C. , Bigot, M. , Pazienti, A. , Aguirre, A. , Giugliano, M., Ostojic, S. & Bacci, A. (2020). Modulation of Coordinated Activity across Cortical Layers by Plasticity of Inhibitory Synapses. Cell reports, 30(3), 630-641.e5. doi:10.1016/j.celrep.2019.12.052

Zeldenrust, F., De Knecht, S., Wadman, W., Denève, S. & Gutkin, B. (2017). Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series. Frontiers in computational neuroscience, 11, 49. doi:10.3389/fncom.2017.00049

Jardri, R. & Denève, S. (2017). [Jumping-to-conclusions in schizophrenia is mediated by circular inference]. Medecine sciences : M/S, 33(11), 933-935. doi:10.1051/medsci/20173311006

Leptourgos, P., Denève, S. & Jardri, R. (2017). Can circular inference relate the neuropathological and behavioral aspects of schizophrenia? Current opinion in neurobiology, 46, 154-161. doi:10.1016/j.conb.2017.08.012

Denève, S., Alemi, A. & Bourdoukan, R. (2017). The Brain as an Efficient and Robust Adaptive Learner. Neuron, 94(5), 969-977. doi:10.1016/j.neuron.2017.05.016

Jardri, R., Duverne, S., Litvinova, A. & Denève, S. (2017). Experimental evidence for circular inference in schizophrenia. Nature communications, 8, 14218. doi:10.1038/ncomms14218

Koren, V. & Denève, S. (2017). Computational Account of Spontaneous Activity as a Signature of Predictive Coding. PLoS computational biology, 13(1), e1005355. doi:10.1371/journal.pcbi.1005355