Publications

Remme, M., Lengyel, M. & Gutkin, B. (2010). Democracy-independence trade-off in oscillating dendrites and its implications for grid cells. Neuron, 66(3), 429-437. doi:10.1016/j.neuron.2010.04.027

Le Clec'H, G., Dehaene, S., Cohen, L., Mehler, J., Dupoux, E., Poline, J., Lehericy, S., van de Moortele, P. & Le Bihan, D. (2000). Distinct cortical areas for names of numbers and body parts independent of language and input modality. Neuroimage, 12(4), 381-391

Morozova, E., Faure, P., Gutkin, B., Lapish, C. & Kuznetsov, A. (2020). Distinct Temporal Structure of Nicotinic ACh Receptor Activation Determines Responses of VTA Neurons to Endogenous ACh and Nicotine. eNeuro, 7(4). doi:10.1523/ENEURO.0418-19.2020

Christophe, A., Dupoux, E., Bertoncini, J. & Mehler, J. (1994). Do infants perceive word boundaries? An empirical study of the bootstrapping of lexical acquisition. Journal of the Acoustical Society of America, 95(3), 1570-1580. doi:10.1121/1.408544

Feldman, N., Goldwater, S., Dupoux, E. & Schatz, T. (2022). Do Infants Really Learn Phonetic Categories? . Open Mind, 5, 113-131. doi:10.1162/opmi_a_00046

Ludusan, B., Mazuka, R. & Dupoux, E. (2021). Does infant-directed speech help phonetic learning? A machine learning investigation. Cognitive Science, 45(5), e12946. doi:10.1111/cogs.12946

Gruber, A., Dayan, P., Gutkin, B. & Solla, S. (2006). Dopamine modulation in the basal ganglia locks the gate to working memory. Journal of Computational Neuroscience, 20(2), 153-166. doi:10.1007/s10827-005-5705-x

Morozova, E., Zakharov, D., Gutkin, B., Lapish, C. & Kuznetsov, A. (2016). Dopamine Neurons Change the Type of Excitability in Response to Stimuli. PLoS computational biology, 12(12), e1005233. doi:10.1371/journal.pcbi.1005233

Di Volo, M., Morozova, E., Lapish, C., Kuznetsov, A. & Gutkin, B. (2018). Dynamical ventral tegmental area circuit mechanisms of alcohol‐dependent dopamine release. European Journal of Neuroscience, Special issue article. doi:10.1111/ejn.14147

Dehaene-Lambertz, G., Dupoux, E. & Gout, A. (2000). Electrophysiological correlates of phonological processing: A cross-linguistic study. Journal of Cognitive Neuroscience, 12(4), 635-647

Gallezot, C. , Riad, R., Titeux, H., Lemoine, L., Montillot, J., Sliwinski, A., Hamet Bagnou, J., Cao, X., Youssov, K., Dupoux, E. & Bachoud-Levi, A. (2022). Emotion expression through spoken language in Huntington Disease. Cortex. doi:10.1016/j.cortex.2022.05.024

Graupner, M., Maex, R. & Gutkin, B. (2013). Endogenous Cholinergic Inputs and Local Circuit Mechanisms Govern the Phasic Mesolimbic Dopamine Response to Nicotine. PLoS Computational Biology, 9(8). doi:10.1371/journal.pcbi.1003183

Delorme, C., Salvador, A., Valabrègue, R., Roze, E., Palminteri, S., Vidailhet, M., De Wit, S., Robbins, T., Hartmann, A. & Worbe, Y. (2015). Enhanced habit formation in Gilles de la Tourette syndrome. Brain, 139(2), 605-615. doi:10.1093/brain/awv307

Dupoux, E., Kakehi, K., Hirose, Y., Pallier, C. & Mehler, J. (1999). Epenthetic vowels in Japanese: A perceptual illusion? Journal of Experimental Psychology-human Perception and Performance, 25(6), 1568-1578

Kouider, S. & Dupoux, E. (2009). Episodic accessibility and morphological processing: Evidence from long-term auditory priming. Acta Psychologica, 130(1), 38-47. doi:10.1016/j.actpsy.2008.09.011

Zeldenrust, F., De Knecht, S., Wadman, W., Denève, S. & Gutkin, B. (2017). Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series. Frontiers in computational neuroscience, 11, 49. doi:10.3389/fncom.2017.00049

Schatz, T., Bach, F. & Dupoux, E. (2018). Evaluating automatic speech recognition systems as quantitative models of cross-lingual phonetic category perception. The Journal of the Acoustical Society of America, 143(5), EL372. doi:10.1121/1.5037615

Gutkin, B., Braun, P., Akila, M., Waltner, D. & Guhr, T. (2020). Exact local correlations in kicked chains. Phys. Rev. B, 102, 174307. doi:10.1103/PhysRevB.102.174307

Pallier, C., Dupoux, E. & Jeannin, X. (1997 ). EXPE: An expandable programming language for on-line psychological experiments. Behavior Research Methods Instruments & Computers, 29(3), 322-327

Dipoppa, M. & Gutkin, B. (2013). Flexible frequency control of cortical oscillations enables computations required for working memory. Proceedings of the National Academy of Sciences of the United States of America, 110(31), 12828-12833. doi:10.1073/pnas.1303270110

Bouton, S., Chambon, V., Tyrand, R., Guggisberg, A., Seeck, M., Karkar, S., Van De Ville, D. & Giraud, A. (2018). Focal versus distributed temporal cortex activity for speech sound category assignment. Proceedings of the National Academy of Sciences of the United States of America, . doi:10.1073/pnas.1714279115

Buon, M., Jacob, P., Margules, S., Brunet, I., Dutat, M., Cabrol, D. & Dupoux, E. (2014). Friend or foe? Early social evaluation of human interactions. PloS One, 9(2), e88612

Nguyen, T. , Kharitonov, E., Copet, J. , Adi, Y. , Hsu, W. , Elkahky, A. , Tomasello, P. , Algayres, R., Sagot, B., Mohamed, A. & Dupoux, E. (2023). Generative Spoken Dialogue Language Modeling. Transactions of the Association for Computational Linguistics, 11, 250–266. doi:10.1162/tacl_a_00545

Dunbar, E. & Dupoux, E. (2016). Geometric constraints on human speech sound inventories. Frontiers in Psychology, 7(1061). doi:10.3389/fpsyg.2016.01061

Cayco Gajic, A. & Zylberberg, A. (2021). Good decisions require more than information. Nature Neuroscience, 2', 903-904. doi:10.1038/s41593-021-00883-9

Zakharov, D., Krupa, M., Gutkin, B. & Kuznetsov, A. (2018). High-frequency forced oscillations in neuronlike elements. Physical Review E , 97(6). doi:10.1103/PhysRevE.97.062211

Gu, Z., Smith, K. , Loukatou, G., Completo Guerreiro, I., Dudek, S. , Gutkin, B., Jensen, P. & Yakel, J. (2020). Hippocampal Interneuronal α7 nAChRs Modulate Theta Oscillations in Freely Moving Mice . Cell Reports, 31(10), 107740. doi:10.1016/j.celrep.2020.107740

Hannagan, T., Dupoux, E. & Christophe, A. (2011). Holographic String Encoding. Cognitive Science, 35(1), 79-118. doi:10.1111/j.1551-6709.2010.01149.x

Keramati, M. & Gutkin, B. (2014). Homeostatic reinforcement learning for integrating reward collection and physiological stability. eLife, 3. doi:10.7554/eLife.04811

Duriez, A., Bergerot, C., J Cone, J., F Roitman, M. & Gutkin, B. (2023). Homeostatic Reinforcement Theory Accounts for Sodium Appetitive State- and Taste-Dependent Dopamine Responding. Nutrients, 15(4), 1015. doi:10.3390/nu15041015