Novikov, N. & Gutkin, B. (2016). Robustness of persistent spiking to partial synchronization in a minimal model of synaptically driven self-sustained activity. Physical review. E, 94(5-1), 052313. doi:10.1103/PhysRevE.94.052313
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Oster, A. & Gutkin, B. (2011). A reduced model of DA neuronal dynamics that displays quiescence, tonic firing and bursting. Journal of Physiology Paris, 105, 53-58. doi:10.1016/j.jphysparis.2011.07.012
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Oster, A., Faure, P. & Gutkin, B. (2015). Mechanisms for multiple activity modes of VTA dopamine neurons. Frontiers in computational neuroscience, 9, 95. doi:10.3389/fncom.2015.00095
Palminteri, S. & Chevallier, C. (2018). Can We Infer Inter-Individual Differences in Risk-Taking From Behavioral Tasks? Frontiers in psychology, 9, 2307. doi:10.3389/fpsyg.2018.02307
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Palminteri, S., Wyart, V. & Koechlin, E. (2017). The Importance of Falsification in Computational Cognitive Modeling. Trends in Cognitive Sciences, 21(6), 425-433. doi:10.1016/j.tics.2017.03.011
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Palminteri, S., Lefebvre, G., Kilford, E. & Blakemore, S. (2017). Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing. PLoS computational biology, 13(8), e1005684. doi:10.1371/journal.pcbi.1005684
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Palminteri, S. & Pessiglione, M. (2016). Opponent brain systems for reward and punishment learning: Causal evidence from drug and lesion studies in humans. Decision Neuroscience: An Integrative Perspective, 291-303. doi:10.1016/B978-0-12-805308-9.00023-3
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Palminteri, S., Kilford, E., Coricelli, G. & Blakemore, S. (2016). The Computational Development of Reinforcement Learning during Adolescence. PLoS Computational Biology, 12(6). doi:10.1371/journal.pcbi.1004953
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
Chapitre d'ouvrage
Remme, M., Lengyel, M. & Gutkin, B. (2014). Phase Response Methods in Dendritic Dynamics. In Schultheiss et al (eds) (Eds.), Phase Response Cruves in NeuroscienceSpringer
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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
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Remme, M., Lengyel, M. & Gutkin, B. (2009). The role of ongoing dendritic oscillations in single-neuron dynamics. PLOS Comp. Bio. , 5(9)
Salvador, A., Worbe, Y., Delorme, C., Coricelli, G., Gaillard, R., Robbins, T., Hartmann, A. & Palminteri, S. (2017). Specific effect of a dopamine partial agonist on counterfactual learning: evidence from Gilles de la Tourette syndrome. Scientific reports, 7(1), 6292. doi:10.1038/s41598-017-06547-8
Stiefel, K., Gutkin, B. & Sejnowski, T. (2008). Cholinergic neuromodulation changes phase response curve shape and type in cortical pyramidal neurons. PLoS ONE, 3(12). doi:10.1371/journal.pone.0003947
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Stiefel, K., Gutkin, B. & Sejnowski, T. (2009). Simulation of effects of cholinergic modulation of phase response curves. J Comp Neurosci, 29(2)
Article dans une revue internationale
Tegnér, J., Compte, A., Auffray, C., An, G., Cedersund, G., Clermont, G., Gutkin, B., Oltvai, Z., Stephan, K., Thomas, R. & Villoslada, P. (2009). Computational disease modeling - Fact or fiction? BMC Systems Biology, 3. doi:10.1186/1752-0509-3-56