Publications

Kim, S., Sodian, B. & Proust, J. (2020). 12- and 24-Month-Old Infants’ Search Behavior Under Informational Uncertainty . Frontiers in Psychology, 11. doi:10.3389/fpsyg.2020.00566

Skvortsova , V., Palminteri, S., Buot, A., Karachi, C., Welter, M., Grabli, D. & Pessiglione, M. (2020). A Causal Role for the Pedunculopontine Nucleus in Human Instrumental Learning. Current Biology, 31(5). doi:10.1016/j.cub.2020.11.042

Proust, J. (2002). A Critical Review of G. Lynn Stephens & G. Graham's When Self-Consciousness Breaks. Philosophical Psychology , 15(4), 543–550

Lunven, M., Hernandez Dominguez, K., Youssov, K., Hamet Bagnou, J., Fliss, R. , Vandendriessche, H., Bapst, B. , Morgado, G., Remy, P., Schubert, R. , Reilmann, R., Busse, M., Craufurd, D., Massart, R., Rosser, A. & Bachoud-Levi, A. (2023). A new approach to digitized cognitive monitoring: validity of the SelfCog in Huntington's disease. Brain communications, 5(2), fcad043. doi:10.1093/braincomms/fcad043

Proust, J. (2001). A Plea for Mental Acts. Synthese, 129(1), 105–128

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

Keramati, M. & Gutkin, B. (2011). A Reinforcement Learning Theory for Homeostatic Regulation. NIPS, .

Mcdonnell, M., Iannella, N., To, M., Tuckwell, H., Jost, J., Gutkin, B. & Ward, L. (2015). A review of methods for identifying stochastic resonance in simulations of single neuron models. Network: Computation in Neural Systems, 26(2), 35-71. doi:10.3109/0954898X.2014.990064

Nair, A. , B. Johnson, E. , Gregory, S. , Osborne-Crowley, K. , Zeun, P. , Scahill, R. , Lowe, J. , Papoutsi, M., Palminteri, S., Rutledge, R. , Rees, G. & Tabrizi, S. (2021). Aberrant Striatal Value Representation in Huntington's Disease Gene Carriers 25 Years Before Onset. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(9), 910-918. doi:10.1016/j.bpsc.2020.12.015

Jedlicka, P., Deller, T., Gutkin, B. & Backus, K. (2011). Activity-dependent intracellular chloride accumulation and diffusion controls GABA(A) receptor-mediated synaptic transmission. Hippocampus, 21(8), 885-98. doi:10.1002/hipo.20804

Ghambaryan, A., Gutkin, B., Klucharev, V. & Koechlin, E. (2021). Additively Combining Utilities and Beliefs: Research Gaps and Algorithmic Developments. Frontiers in Neuroscience, . doi:10.3389/fnins.2021.704728

Proust, J. (2023). Affordances from a control viewpoint. Philosophical Psychology . doi:10.1080/09515089.2023.2274489

Bouvier, A. (2002). An Epistemological Plea for Methodological Individualism and Rational Choice Theory in Cognitive Rhetoric. Philosophy of the Social Sciences, 32(1 ), 51–70

Fontolan, L., Krupa, M., Hyafil, A. & Gutkin, B. (2013). Analytical insights on theta-gamma coupled neural oscillators. Journal of Mathematical Neuroscience, 3(1), 1-20. doi:10.1186/2190-8567-3-16

Kim, S., Le Guen, O. , Sodian, B. & Proust, J. (2021). Are Children Sensitive to What They Know?: An Insight from Yucatec Mayan Children. Journal of Cognition and Culture, 21(3-4), 226-242. doi:10.1163/15685373-12340106

Lebreton, M., Bavard, S., Daunizeau, J. & Palminteri, S. (2019). Assessing inter-individual differences with task-related functional neuroimaging. Nature Human Behaviour. doi:10.1038/s41562-019-0681-8

Lefebvre, G., Lebreton, M., Meyniel, F., Bourgeois-Gironde, S. & Palminteri, S. (2017). Behavioural and neural characterization of optimistic reinforcement learning. Nature Human Behaviour , 1(4), 0067

Chambon, V., Thero, H., Findling, C. & Koechlin, E. (2018). Believing in one's power: a counterfactual heuristic for goal-directed control. bioRxiv, 498675. doi:10.1101/498675

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

Kim, S., Paulus, M., Sodian, B. & Proust, J. (2020). Children’s Prior Experiences of their Successes and Failures Modulate Belief Alignment. European Journal of Developmental Psychology, 17(5). doi:10.1080/17405629.2020.1722634

Palminteri, S. (2023). Choice-confirmation bias and gradual perseveration in human reinforcement learning. Behavioral neuroscience, 137(1), 78-88. doi:10.1037/bne0000541

Chambon, V., Thero, H., Vidal, M., Vandendriessche, C., Haggard, P. & Palminteri, S. (2020). Choosing and learning: outcome valence differentially affects learning from free versus forced choices. Nature Human Behaviour, .

Tolu, S., Eddine, R., Marti, F., David, V., Graupner, M., Pons, S., Baudonnat, M., Husson, M., Besson, M., Reperant, C., Zemdegs, J., Pagès, C., Hay, Y., Lambolez, B., Caboche, J., Gutkin, B., Gardier, A., Changeux, J., Faure, P. & Maskos, U. (2013). Co-activation of VTA da and GABA neurons mediates nicotine reinforcement. Molecular Psychiatry, 18(3), 382-393. doi:10.1038/mp.2012.83

Bouvier, A. (2007). Collective Belief, Acceptance, and Commitment in Science . Iyyun, 56, 91

Koechlin, E. (2021). Computational models of adaptive behavior and prefrontal cortex. Neuropsychopharmacology, 47, 58–71. doi:10.1038/s41386-021-01123-1

Gutkin, B. & Ahmed, S. (2012). Computational Neuroscience of Drug Addiction.

Findling, C., Skvortsova , V., Dromnelle, R. , Palminteri, S. & Wyart, V. (2019). Computational noise in reward-guided learning drives behavioral variability in volatile environments. Nature Neuroscience , 22, 2066–2077. doi:10.1101/439885

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

Chierchia, G. , Soukupová, M., Kilford, E., Griffin, C. , Leung, J. , Palminteri, S. & Blakemore, S. (2022). Confirmatory reinforcement learning changes with age during adolescence. Developmental Science, .(e13330). doi:10.1111/desc.13330

Palminteri, S. & Maël, L. (2021). Context-dependent outcome encoding in human reinforcement learning. Current Opinion in Behavioral Sciences, 41, 144-151. doi:10.1016/j.cobeha.2021.06.006