Publications

Bavard, S., Lebreton, M., Khamassi, M., Coricelli, G. & Palminteri, S. (2018). Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences. Nature Communications, 9(4503)

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

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

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, .

Chambon, V., Thero, H., Vidal, M., Vandendriessche, H., Haggard, P. & Palminteri, S. (2020). Information about action outcomes differentially affects learning from self-determined versus imposed choices. Nature Human Behaviour . doi:10.1038/s41562-020-0919-5

Chambon, V., Domenech, P., Jacquet, P., Barbalat, G., Bouton, S., Pacherie, E., Koechlin, E. & Farrer, C. (2017). Neural coding of prior expectations in hierarchical intention inference. Scientific reports, 7(1), 1278. doi:10.1038/s41598-017-01414-y

Correa, C. , Noorman, S. , Jiang, J. , Palminteri, S., Cohen, M. , Lebreton, M. & van Gaal, S. (2018). How the level of reward awareness changes the computational and electrophysiological signatures of reinforcement learning. Journal of Neuroscience , 0457-18. doi:10.1523/JNEUROSCI.0457-18.2018

Domenech, P., Rheims, S. & Koechlin, E. (2020 ). Neural Mechanisms resolving Exploitation-Exploration dilemmas in the prefrontal cortex. Science, .

Duverne, S. & Koechlin, E. (2017). Rewards and Cognitive Control in the Human Prefrontal Cortex. Cerebral cortex (New York, N.Y. : 1991), 27(10), 5024-5039. doi:10.1093/cercor/bhx210

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

Findling, C., Chopin, N. & Koechlin, E. (2020). Imprecise neural computations as a source of adaptive behaviour in volatile environments. Nature Human Behaviour , . doi:10.1038/s41562-020-00971-z

Fontanesi , L., Palminteri, S. & Lebreton, M. (2019). Decomposing the effects of context valence and feedback information on speed and accuracy during reinforcement learning: A meta-analytical approach using diffusion decision modeling. Cognitive Affective Behavioral Neuroscience, 1-13. doi:10.3758/s13415-019-00723-1

Giavazzi, M., Daland, R., Palminteri, S., Peperkamp, S., Brugières, P., Jacquemot, C., Schramm, C., Cleret de Langavant, L. & Bachoud-Levi, A. (2018 ). The role of the striatum in linguistic selection: Evidence from Huntington’s disease and computational modeling. Cortex, 109, 189-204. doi:10.1016/j.cortex.2018.08.031

Hertz, U., Palminteri, S., Brunetti, S., Olesen, C., Frith, C. & Bahrami, B. (2017). Neural computations underpinning the strategic management of influence in advice giving. Nature communications, 8(1), 2191. doi:10.1038/s41467-017-02314-5

Koechlin, E. (2020). Human Decision-Making beyond the Rational Decision Theory. Trends in Cognitive Sciences, 24(1), 4-6. doi:10.1016/j.tics.2019.11.001

Lebreton, M., Bacily , K., Palminteri, S. & Engelmann, J. (2019). Contextual influence on confidence judgments in human reinforcement learning. PLoS Comput Biol, 15(4), e1006973. doi:10.1371/journal.pcbi.1006973

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., Nioche, A., Bourgeois-Gironde, S. & Palminteri, S. (2018). Contrasting temporal difference and opportunity cost reinforcement learning in an empirical money-emergence paradigm. PNAS, 115(49), E11446-E11454. doi:10.1073/pnas.1813197115

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

Lussange, J., Lazarevich, I. , Bourgeois-Gironde, S., Palminteri, S. & Gutkin, B. (2020). Modelling Stock Markets by Multi-agent Reinforcement Learning. Computational Economics, ., 1-35. doi:10.1007/s10614-020-10038-w

Mansouri, F., Koechlin, E., Rosa, M. & Buckley, M. (2017). Managing competing goals - a key role for the frontopolar cortex. Nature reviews. Neuroscience, 18(11), 645-657. doi:10.1038/nrn.2017.111

Najar, A., Sigaud, O. & Chetouani , M. (2020). Interactively shaping robot behaviour with unlabeled human instructions. Auton Agent Multi-Agent Syst, 34(35). doi:10.1007/s10458-020-09459-6

Najar, A., Bonnet, E., Bahador, B. & Palminteri, S. (2020). The actions of others act as a pseudo-reward to drive imitation in the context of social reinforcement learning. PLoS Biology, 18 (12), e3001028. doi:10.1371/journal.pbio.3001028

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

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

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

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

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

Pischedda, D. , Palminteri, S. & Giorgio, C. (2020). The role of counterfactual information on outcome value coding in mPFC and cingulate cortex: from an absolute to an adaptive neural code. . The Journal of Neuroscience, 40 (16), 3268-3277. doi:10.1523/JNEUROSCI.1712-19.2020

Romagnoni, A. , Colonnese, M. , Touboul, J. & Gutkin, B. (2020). Progressive alignment of inhibitory and excitatory delay may drive a rapid developmental switch in cortical network dynamics. J. of Neurophysiology, 123(5), 1583-1599. doi:10.1152/jn.00402.2019