Publications

Mercier, H., Yesilaltay , S. & Hacquin, A. (2022). Why do so few people share fake news? It hurts their reputation. , 24(6), 1303-1324. doi:10.1177/1461444820969893

Yesilaltay , S., Hacquin, A. & Mercier, H. (2020). Why do so few people share fake news? It hurts their reputation. New Media & Society, . doi:10.1177/1461444820969893

Ladenbauer, J. & Obermayer, K. (2019). Weak electric fields promote resonance in neuronal spiking activity: Analytical results from two-compartment cell and network models. PLOS Computational Biology, 15(4), e1006974. doi:10.1371/journal.pcbi.1006974

Mercier, H. & Boyer, P. (2021). Truth-making institutions: From divination, ordeals and oaths to judicial torture and rules of evidence. Evolution and Human Behavior, 42(3), 259-267. doi:10.1016/j.evolhumbehav.2020.11.004

Gutkin, B., Jost, J. & Tuckwell, H. (2008). Transient termination of spiking by noise in coupled neurons. EPL, 81(2). doi:10.1209/0295-5075/81/20005

Stein, H., Barbosa, J. & Compte, A. (2021). Towards biologically constrained attractor models of schizophrenia. Current Opinion in Neurobiology, 70, 171-181. doi:10.1016/j.conb.2021.10.013

Dubreuil, A., Valente, A., Beiran, M., Mastrogiuseppe, F. & Ostojic, S. (2022). The role of population structure in computations through neural dynamics. Nature Neuroscience, 25, 783–794. doi:10.1038/s41593-022-01088-4

Bai, D. & Strickland, B. (2023). The Pulfrich solidity illusion: a surprising demonstration of the visual system’s tolerance of solidity violations. Psychon Bull Rev. doi:10.3758/s13423-023-02271-9

O'Madagain, C., Kachel , G. & Strickland, B. (2019). The Origin of Pointing: Evidence for the Touch Hypothesis. Science Advances, 5(7), eaav2558. doi:10.1126/sciadv.aav2558

O'Madagain, C., Kachel , G. & Strickland, B. (2019). The origin of pointing: Evidence for the touch hypothesis. Science Advances, 5(7), eaav2558. doi:10.1126/sciadv.aav2558

Trouche, E., Prado, J. , Léone, J. , Epinat-Duclos, J. & Mercier, H. (2020). The neural bases of argumentative reasoning. Brain and Language, 208, 104827. doi:10.1016/j.bandl.2020.104827

King, J. & Wyart, V. (2021). The Human Brain Encodes a Chronicle of Visual Events at each Instant of Time thanks to the Multiplexing of Traveling Waves. Journal of Neuroscience, 41(34), 7224-7233. doi:10.1523/JNEUROSCI.2098-20.2021

Mahr, J. , Mascaro, O., Mercier, H. & Csibra, G. (2021). The effect of disagreement on children’s source memory performance. Plos One, 16(4), e0249958. doi:10.1371/journal.pone.0249958

Mercier, H. (2020). The Cultural Evolution of Oaths, Ordeals, and Lie Detectors. The Journal of Cognition and Culture, 20(3-4), 159-187. doi:10.1163/15685373-12340080

Marie, A. , Yesilaltay , S. & Strickland, B. (2020). The cognitive foundations of misinformation on science - What we know and what scientists can do about it. EMBO Rep , 21(4), e50205. doi:10.15252/embr.202050205

Denève, S., Alemi, A. & Bourdoukan, R. (2017). The Brain as an Efficient and Robust Adaptive Learner. Neuron, 94(5), 969-977. doi:10.1016/j.neuron.2017.05.016

Bai, D., Falck, A. & Strickland, B. (2021). The adult visual system resists learning continuity violations. Journal of vision, 21, 2590. doi:10.1167/jov.21.9.2590

Maex, R. & Gutkin, B. (2017). Temporal integration and 1/f power scaling in a circuit model of cerebellar interneurons. Journal of neurophysiology, 118(1), 471-485. doi:10.1152/jn.00789.2016

Bouchacourt, F., Palminteri, S., Koechlin, E. & Ostojic, S. (2020). Temporal Chunking as a Mechanism for Unsupervised Learning of Task-Sets. eLife, 9, e50469. doi:10.7554/eLife.50469

Zakharov, D., Lapish, C., Gutkin, B. & Kuznetsov, A. (2016). Synergy of AMPA and NMDA Receptor Currents in Dopaminergic Neurons: A Modeling Study. Frontiers in computational neuroscience, 10, 48. doi:10.3389/fncom.2016.00048

Jeong, H. & Gutkin, B. (2007). Synchrony of neuronal oscillations controlled by GABAergic reversal potentials. Neural Computation, 19(3), 706-729. doi:10.1162/neco.2007.19.3.706

Lussange, J., Vrizzi, S., Bourgeois-Gironde, S., Palminteri, S. & Gutkin, B. (2022). Stock Price Formation: Precepts from a Multi-Agent Reinforcement Learning Model. Comput Econ. doi:10.1007/s10614-022-10249-3

Lazarevich, I. , Prokin, I., Gutkin, B. & Kazantsev, V. (2023). Spikebench: An open benchmark for spike train time-series classification. PLoS computational biology, 19(1), e1010792. doi:10.1371/journal.pcbi.1010792

Muller, L., Brette, R. & Gutkin, B. (2011). Spike-timing dependent plasticity and feed-forward input oscillations produce precise and invariant spike phase-locking. Frontiers in Computational Neuroscience, 15(5), 45. doi:10.3389/fncom.2011.00045

Hyafil, A., Fontolan, L., Kabdebon, C., Gutkin, B. & Giraud, A. (2015). Speech encoding by coupled cortical theta and gamma oscillations. eLife, 4, 1-45. doi:10.7554/eLife.06213

Graves, J. & Oxenham, A. (2019). Spectral and temporal models of human pitch perception with mixtures of three concurrent harmonic complexes. The Journal of the Acoustical Society of America, 145(3), 1784-1784. doi:10.1121/1.5101525

Ueshima, A., Mercier, H. & Kameda, T. (2021). Social deliberation systematically shifts resource allocation decisions by focusing on the fate of the least well-off. Journal of Experimental Social Psychology, 92, 104067 . doi:10.1016/j.jesp.2020.104067

Gurnani, H. & Cayco Gajic, A. (2023). Signatures of task learning in neural representations. Signatures of task learning in neural representations, Current Opinion in Neurobiology,, 83, 102759. doi:10.1016/j.conb.2023.102759

Gurnani, H. & Cayco Gajic, A. (2023). Signatures of task learning in neural representations. Current opinion in neurobiology, 83, 102759. doi:10.1016/j.conb.2023.102759

Beiran, M., Dubreuil, A., Valente, A., Mastrogiuseppe, F. & Ostojic, S. (2021). Shaping dynamics with multiple populations in low-rank recurrent networks. Neural Computation, 33(6), 1572-1615. doi:10.1162/neco_a_01381 Article history