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Publications

Autres  

Lussange, J., Belianin, A., Bourgeois-Gironde, S. & Gutkin, B. (2017). A bright future for financial agent-based models. arXiv preprint arXiv:1801.08222

Autres  

Vacher, J. , Mamassian, P. & Coen-Cagli, R. (2018). An Ideal Observer Model to Probe Human Visual Segmentation of Natural Images. arXiv

Autres  
Autres  

Neri, P. (2018). Classification images as descriptive statistics. "Journal of Mathematical Psychology", "82"("1), "26–37"

Autres  

Martinez-Saito, M. , Konovalov, R. , Piradov, M. , Shestakova, A. , Gutkin, B. & Klucharev, V. (2018). Action in auctions: neural and computational mechanisms of bidding behavior. BioRxiv, 464925. doi:10.1101/464925

Autres  

Lazarevich, I. , Gutkin, B. & Prokin, I. (2018). Neural activity classification with machine learning models trained on interspike interval series data. arxiv , 1810.03855

Chapitre d'ouvrage  

Graupner, M. & Gutkin, B. (2012). Dynamical Approaches to understanding cholinergic control of nicotine action pathways in the dopaminergic reward circuits. Computational Neuroscience of Drug Addiction (Springer ed.).Ahmed and Gutkin (eds.)

Chapitre d'ouvrage  

Caze, R., Humphries, M. & Gutkin, B. (2013). Dendrites enhance both single neuron and network computation. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Chapitre d'ouvrage  

Remme, M., Lengyel, M. & Gutkin, B. (2014). Phase Response Methods in Dendritic Dynamics. In Schultheiss et al (eds) (Eds.), Phase Response Cruves in NeuroscienceSpringer

Chapitre d'ouvrage  

Remme, M., Lengyel, M. & Gutkin, B. (2015). Trade-off between dendritic democracy and independence in neurons with intrinsic subthreshold membrane potential oscillatio. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Chapitre d'ouvrage  

Kuznetsov, A. & Gutkin, B. (2015). Dopaminergic cell Models. The Encyclopedia of Computational Neuroscience (pp. 2958-2965).

Chapitre d'ouvrage  

Gutkin, B. (2015). Theta-neurons. In Springer Verlag (Eds.), Encyclopedia of Comptutational Neuroscience (pp. 1034-1042).

Chapitre d'ouvrage  

Dumont, G., Maex, R. & Gutkin, B. (2018). Dopaminergic Neurons in the Ventral Tegmental Area and Their Dysregulation in Nicotine Addiction. In Alan Anticevic and John D. Murray (Eds.), Computational Psychiatry: Mathematical Modeling of Mental Illness (pp. 47-84). doi:10.1016/B978-0-12-809825-7.00003-1

Chapitre d'ouvrage  

Mamassian, P., Landy, M., Maloney, L., Rao, R., Olshausen, B. & Lewicki, M. (2002). Bayesian modelling of visual perception. In R. Rao, B. Olshausen & M. Lewicki (Eds.), Probabilistic Models of the Brain: Perception and Neural Function (pp. 13-36). Cambridge, MA: MIT Press

Chapitre d'ouvrage  

Ramus, F., Peperkamp, S., Christophe, A., Jacquemot, C., Kouider, S. & Dupoux, E. (2010). A Psycholinguistic Perspective on the Acquisition of Phonology. In C. Fougeron (Eds.), Laboratory Phonology (Vol. 10 ).De Gruyter Mouton

Chapitre d'ouvrage  

Ramus, F. & Szenkovits, G. (2011). Understanding the nature of the phonological deficit. (pp. 153-169). doi:10.4324/9780203838006

Chapitre d'ouvrage  

Ramus, F. (2013). A neurological model of dyslexia and other domain-specific developmental disorders with an associated sensorimotor syndrome. (pp. 75-102). doi:10.4324/9780203774915

Ouvrage  

Gutkin, B. & Ahmed, S. (2012). Computational Neuroscience of Drug Addiction.

Acte de conférence non expertisé  

Caze, R., Humphries, M., Gutkin, B. & Schultz, S. (2013). A difficult classification for neurons without dendrites. In Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on, San Diego, CA, USA, IEEE, 215-218. doi:10.1109/NER.2013.6695910

Acte de conférence expertisé  

Mamassian, P. & Vemuri, B. (1993). ISOPHOTES ON A SMOOTH SURFACE RELATED TO SCENE GEOMETRY. , Vol. 2031: In Geometric Methods in Computer Vision II, 124-133. doi:10.1117/12.146619

Acte de conférence expertisé  

Caze, R., Humphries, M. & Gutkin, B. (2012). Spiking and saturating dendrites differentially expand single neuron computation capacity. , Vol. 13: In Twenty First Annual Computational Neuroscience Meeting: CNS*2012, Decatur, GA, USA.

Acte de conférence expertisé  

Lussange, J., Belianin, A., Bourgeois-Gironde, S. & Gutkin, B. (2020). Learning and Cognition in Financial Markets: A Paradigm Shift for Agent-Based Models. In Arai K., Kapoor S., Bhatia R. (Eds.), Vol. 1252: In IntelliSys 2020. Advances in Intelligent Systems and Computing, 241-255. doi:10.1007/978-3-030-55190-2_19

Article dans une revue nationale  

Ramus, F. (2005). Aux origines cognitives, neurobiologiques et génétiques de la dyslexie. ANAE - Approche Neuropsychologique des Apprentissages chez l'Enfant, 17, 247-253

Article dans une revue nationale  

Ramus, F. (2008). Génétique de la dyslexie développementale. ANAE - Approche Neuropsychologique des Apprentissages chez l'Enfant, 20, 9-14

Article dans une revue nationale  

Ramus, F. (2011). Quel pouvoir prédictif de la génétique et des neurosciences, et quels problmes? Medecine et Droit, 2011(106), 51-58. doi:10.1016/j.meddro.2010.10.010

Article dans une revue nationale  

Ramus, F. (2012). Les troubles spécifiques de la lecture. Information Grammaticale, 133, 34-40