ENS - Ecole Normale Supérieure
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Publications

Non-reviewed conference proceeding  

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

Book chapter  

Pressnitzer, D., Agus, T., Kang, H. , Graves, J. & Andrillon, T. (2021). Apprentissage de motifs sonores. In S. Samson, B. Tillmann, C. Jourdan, V. Brun (Eds.), Audition et Cognition Montpellier: Sauramps Medical

Book chapter  

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

Non-reviewed conference proceeding  

Zakharov, D., Dogonasheva, O. & Gutkin, B. (2021). Bistability of globally synchronous and chimera states in a ring of phase oscillators coupled by a cosine kernel. In 2021 5th Scientific School Dynamics of Complex Networks and their Applications (DCNA), 211-214. doi:10.1109/DCNA53427.2021.9586968

Non-reviewed conference proceeding  

Dogonasheva, O., Gutkin, B. & Zakharov, D. (2021). Calculation of travelling chimera speeds for dynamical systems with ring topologies. In 5th Scientific School Dynamics of Complex Networks and their Applications (DCNA), 61-64. doi:10.1109/DCNA53427.2021.9586903

Non-reviewed conference proceeding  

Radushev, D. , Dogonasheva, O., Gutkin, B. & Zakharov, D. (2023). Chimera states in a ring of non-locally connected interneurons. In 7th Scientific School Dynamics of Complex Networks and their Applications (DCNA), Kaliningrad, Russian Federation, 229-232. doi:10.1109/DCNA59899.2023.10290318

Non-reviewed conference proceeding  
Book chapter  

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

Non-reviewed conference proceeding  

Caucheteux, C. , Gramfort, A. & King, J. (2021). Disentangling syntax and semantics in the brain with deep networks. , Vol. 139: In International Conference on Machine Learning, PMLR, 1336-1348.

Non-reviewed conference proceeding  

Dubreuil, A., Valente, A., Mastrogiuseppe, F. & Ostojic, S. (2019). Disentangling the roles of dimensionality and cell classes in neural computation. In NeurIPS Workshop.

Book chapter  

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

Book chapter  

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

Book chapter  

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.)

Book chapter  
Book chapter  

Lussange, J., Belianin, A., Bourgeois-Gironde, S. & Gutkin, B. (2021). Learning and Cognition in Financial Markets: A Paradigm Shift for Agent-Based Models. Advances in Intelligent Systems and Computing (Vol. 1252, pp. 241-255). doi:10.1007/978-3-030-55190-2_19

Non-reviewed conference proceeding  

Zuk, N. , Di Liberto, G. & Lalor, E. (2019). Linear-nonlinear Bernoulli modeling for quantifying temporal coding of phonemes in brain responses to continuous speech. In 2019 Conference on Cognitive Computational Neuroscience, Berlin, Germany.

Book chapter  

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

Non-reviewed conference proceeding  

Erdmann, A. , Joseph Wrisley, D., Allen, B. , Brown, C. , Cohen-Bodenes, S., Elsner, M. , Feng, Y. , D Joseph, B. , Joyeux-Prunel, B. & de Marneffe, M. (2019). Practical, Efficient, and Customizable Active Learning for Named Entity Recognition in the Digital Humanities. In Proceedings of the 2019 Conference of the North, 2223-2234. doi:10.18653/v1/N19-1231

Non-reviewed conference proceeding  

Zakharov, D., Dogonasheva, O. & Gutkin, B. (2020). Role of Pyramidal Cell M-current in Weak Pyramidal/Interneuronal Gamma Cluster Formation. In 2020 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR), Innopolis, Russia, IEEE. doi:10.1109/DCNAIR50402.2020.9216942

Non-reviewed conference proceeding  

Thoret, E., Andrillon, T., Gauriau, C., Léger, D. & Pressnitzer, D. (2020). Sleep deprivation impacts speech spectro-temporal modulations. In e-FA2020 (e- Forum Acusticum 2020 ), Lyon, France.

Book chapter  

Shamma, S. (2020). Temporal Coherence Principle in Scene Analysis. The Senses: A Comprehensive Reference (Second Edition) (Vol. 2, pp. 777-790).Elsevier. doi:10.1016/B978-0-12-809324-5.24252-1

Book chapter  

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

Non-reviewed conference proceeding  

Millet, J., Caucheteux, C. , Boubenec, Y., Gramfort, A., Dunbar, E., Pallier, C. & King, J. (2022). Toward a realistic model of speech processing in the brain with self-supervised learning. , Vol. 35: In 36th Conference on Neural Information Processing Systems, 33428-33443.

Book chapter  

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

Non-reviewed conference proceeding