Publications

Grèzes, J. & Dezecache, G. (2014). Bases cérébrales et cognitives de la communication émotionnelle. In M. Botbol (Eds.), L'empathie au carrefour des sciences et de la cliniqueJohn Libbey Eurotext

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

Abrusan, M. & Spector, B. (2008). An Interval-Based Semantics for Degree Questions: Negative Islands and Their Obviation. In Abner, Natasha and Jason Bishop (Eds.), In Proceedings of the 27th West Coast Conference on Formal Linguistics, Cascadilla Proceedings Project, 17-26.

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

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

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

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

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

Gutkin, B. & Stiefel, K. (2014). Cholinergic Neuromodulation of Phase Response Curves. In Schultheiss et al (eds) (Eds.), Phase Response Cruves in NeuroscienceSpringer

Grèzes, J. & Dezecache, G. (2012). Communication émotionnelle: mécanismes cognitifs et cérébraux. In P. Allain, G. Aubin & D. Le Gal (Eds.), Cognition Sociale et NeuropsychologieSolal

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

Osses , A. & Varnet, L. (2021). Consonant-in-noise discrimination using an auditory model with different speech- based decision devices. In DAGA, Vienna Austria.

Batty, M., Kovarski, K. & Meaux, E. (2018). De l’exploration à la perception des visages chez les personnes avec un trouble du spectre de l’autisme. Neuropsychologie et remédiations des troubles du spectre de l’autismeEditions deboeck Supérieur

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

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.

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

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

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

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.)

Dezecache, G., Eskenazi, T. & Grèzes, J. (2016). Emotional Convergence: A Case of Contagion? In Sukhvinder D. Obhi & Emily S. Cross (Eds.), Shared Representations: Sensorimotor Foundations of Social Life (Cambridge University Press ed., pp. 417).

Koechlin, E. (2020). Executive Control and Decision-Making: a neural theory of prefrontal function. The Cognitive Neurosciences VI (pp. 451).

Chemla, E. & Spector, B. (2010 ). Experimental Detection of Embedded Implicatures. In Aloni, Maria and Bastiaanse, Harald and de Jager, Tikitu and Schulz, Katrin (Eds.), In Logic, Language and Meaning: 17th Amsterdam Colloquium, Amsterdam, The Netherlands, Springer Berlin Heidelberg, 53–62. doi:10.1007/978-3-642-14287-1_6

Koralus, P. & Mascarenhas, S. (2018). Illusory Inferences in a question-based theory of reasoning. In Turner, Ken and Horn, Laurence (Eds.), Pragmatics, Truth, and Underspecification: Towards an Atlas of Meaning (pp. 300–322). Leiden: Brill

Berthommier, F. & Lorenzi, C. (2021). Implications of Physiological Mechanisms of Amplitude Modulation Processing for Modeling Complex Sounds Analysis and Separation. (pp. 12). doi:10.1201/9781003064183

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

Grèzes, J., Dezecache, G. & Eskenazi, T. (2015). Limbic to Motor Interactions during Social Perception. In Arthur W. Toga (Eds.), Brain Mapping: An Encyclopedic Reference (pp. 1027-1030).Academic Press: Elsevier

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.

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

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

Cremers, A. & Chemla, E. (2017). Probability Judgments of Gappy Sentences. In Pistoia-Reda, Salvatore and Filippo Domaneschi (Eds.), Linguistic and Psycholinguistic Approaches on Implicatures and Presuppositions (pp. 111-150).Palgrave