Publications

Riad, R., Titeux, H., Lemoine, L., Montillot, J., Sliwinski, A., Hamet Bagnou, J., Cao, X., Bachoud-Levi, A. & Dupoux, E. (2022). A comparison study on patient-psychologist voice diarization. In Ninth Workshop on Speech and Language Processing for Assistive Technologies (SLPAT-2022), Dublin, Ireland: Association for Computational Linguistics, 30-36. doi:10.18653/v1/2022.slpat-1.4

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

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

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

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.

Jacquemot, C. (2019). Coupling language and executive functions for premanifest and early Huntington’s Disease follow up. , Vol. 24: In Spraak- en Taalpathologie, 77-79.

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.)

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

Bachoud-Levi, A. (2017). From open to large-scale randomized cell transplantation trials in Huntington's disease: Lessons from the multicentric intracerebral grafting in Huntington's disease trial (MIG-HD) and previous pilot studies. Prog Brain Res. (Vol. 230, pp. 227-261). doi:10.1016/bs.pbr.2016.12.011

Fenelon, G. (2019). Hallucinations visuelles. In Hélène Amievia, Antoinette Prouteau, Olivier Martinaud (Eds.), Neuropsychologie en psychiatrie

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

Poli, M. , Dupoux, E. & Riad, R. (2023). Introducing Topography in Convolutional Neural Networks. In CASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 1-5. doi:10.1109/ICASSP49357.2023.10096671

Jacquemot, C. (2017). Le langage fait l’homme et l’homme fait le langage. Paris: Sciences Humaines Editions

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

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