Publications

Titeux, H., Riad, R., Cao, X., Hamilakis, N., Madden, K., Cristia, A., Bachoud-Levi, A. & Dupoux, E. (2020). Seshat: A tool for managing and verifying annotation campaigns of audio data. In LREC - 2th Language Resources and Evaluation Conference, Marseille, France.

Scharenborg, O., Besacier, L., Black, A., Hasegawa-Johnson, M., Metze, F., Neubig, G., Stuker, S., Godard, P., Muller, M., Ondel, L., Palaskar, S., Arthur, P., Ciannella, F., Du, M., Larsen, E., Merkx, D., Riad, R., Wang, L. & Dupoux, E. (2018). Linguistic Unit Discovery From Multi-Modal Inputs In Unwritten Languages: Summary Of The “Speaking Rosetta” Jsalt 2017 Workshop. In Jsalt 2017 Workshop.

Riad, R., Bachoud-Levi, A., Rudzicz , F. & Dupoux, E. (2020). Identification of primary and collateral tracks in stuttered speech. , Vol. Proceedings of The 12th Language Resources and Evaluation Conference: In LREC, European Language Resources Association, 1681–1688.

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

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

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

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

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

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

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

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.)

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

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

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.

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

Alemi, A., Machens, C., Denève, S. & Slotine, J. (2018). Learning nonlinear dynamics in efficient, balanced spiking networks using local plasticity rules. In Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, AAAI Press.