Publications

Boruta, L., Peperkamp, S., Crabbe, B. & Dupoux, E. (2011 ). Testing the robustness of online word segmentation: effects of linguistic diversity and phonetic variation. In Proceedings of the 2011 Workshop on Cognitive Modeling and Computational Linguistics, ACL, Portland, Oregon, 1-9.

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.

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

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

Darcy, I., Peperkamp, S. & Dupoux, E. (2007 ). Bilinguals play by the rules. Perceptual compensation for assimilation in late L2-learners. In Cole, J. and Hualde, J. (Eds.), Laboratory Phonology 9 (pp. 411-442). Berlin: Mouton de Gruyter

Deperrois, N. & Gutkin, B. (2018). Nicotinic and Cholinergic Modulation of Reward Prediction Error Computations in the Ventral Tegmental Area: a Minimal Circuit Model. bioRxiv, 423806. doi:10.1101/423806

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

Dumont, G. & Gutkin, B. (2018). Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits. arXiv , 1812.03455

Fort, M., Weiss, A., Martin, A. & Peperkamp, S. (2013). Looking for the bouba-kiki effect in prelexical infants. In S. Ouni, F. Berthommier & A. Jesse (Eds.), In Proceedings of the 12th International Conference on Auditory-Visual Speech Processing, INRIA, 71-76.

Geffen, L., Chemla, E. & Steinert-Threlkeld, S. (2020). On the Spontaneous Emergence of Discrete and Compositional Signals. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 4794–4800. doi:10.18653/v1/2020.acl-main.433

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.)

Guevara Rukoz, A., Parlato-Oliveira, E., Yu, S., Hirose, Y., Peperkamp, S. & Dupoux, E. (2017). Predicting epenthetic vowel quality from acoustics. In INTERSPEECH-2017, 596-600.

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

Johnson, M., Christophe, A. & Dupoux, E. (2014 ). Modelling function words improves unsupervised word segmentation. In Proceedings of the 52nd Annual meeting of the ACL, 282–292. doi:10.3115/v1/P14-1027

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

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

Lev-Ari, S., Dodsworth , R., Mielke, J. & Peperkamp, S. (2019). The different roles of expectations in phonetic and lexical processing. In Proceedings of INTERSPEECH, Graz, Austria, ISCA, 2305-2309.

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

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

Martin, A. & Peperkamp, S. (2011). Speech perception and phonology. In M. van Oostendorp, C. Ewen, E. Hume & K. Rice (Eds.), Companion to Phonology. Volume IV. (pp. 2234-2256). Hoboken, N.J.: Wiley-Blackwell

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

Melnik, G. & Peperkamp, S. (2019). Online phonetic training improves L2 word recognition. In A. Goel, C. Seifert, & C. Freksa (Eds.), In Proceedings of the 41st Annual Conference of the Cognitive Science Society, Montreal, QB, Cognitive Science Society, 809-814.

Ngon, C. & Peperkamp, S. (2017). Corrigendum to "What infants know about the unsaid: Phonological categorization in the absence of auditory input" [Cognition 152 (2016) 53-60]. Cognition, 168, 385. doi:10.1016/j.cognition.2017.06.013

Novikov, N. & Gutkin, B. (2018). Role of NMDA conductance in average firing rate shifts caused by external periodic forcing. arXiv , 1812.03609

Peperkamp, S., Hegde , M. & Carbajal, J. (2019). Liquid deletion in French child-directed speech. In Proceedings of INTERSPEECH, Graz, Austria, ISCA, 3574-3578.

Peperkamp, S. & Iturralde Zurita, A. (2019). Compensation for French liquid deletion during auditory sentence processing. In Proceedings of INTERSPEECH, Graz, Austria, ISCA, 1951-1955.

Peperkamp, S. & Dupoux, E. (2002). A typological study of stress "deafness" In Gussenhoven, C. and Warner, N. (Eds.), Laboratory Phonology VII (pp. 203-240). Berlin: Mouton de Gruyter

Peperkamp, S. & Bouchon, C. (2011). The relation between perception and production in L2 phonological processing. In Proceedings of the 12th Annual Conference of the International Speech Communication Association (Interspeech 2011), 168-171.

Peperkamp, S. & Dupoux, E. (2002). Coping with phonological variation in early lexical acquisition. In I. Lasser (Eds.), The Process of Language Acquisition (pp. 359-385). Frankfurt: Peter Lang

Peperkamp, S. & Dupoux, E. (2007 ). Learning the mapping from surface to underlying representations in an artificial language. In Cole, J. and Hualde, J. (Eds.), Laboratory Phonology 9 (pp. 315-338). Berlin: Mouton de Gruyter