Publications

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

Zeldenrust, F., Gutkin, B. & Denève, S. (2021). Efficient and robust coding in heterogeneous recurrent networks. Plos Computational Biology, 17(4), e1008673. doi:10.1371/journal.pcbi.1008673

Weiss, A., Chambon, V., Drugowitsch, J. & Wyart, V. (2021). Interacting with volatile environments stabilizes hidden-state inference and its brain signatures. Nature Communications, 12, 2228. doi:10.1038/s41467-021-22396-6

Ting, C. , Palminteri, S., Engelmann, J. & Lebreton, M. (2020). Robust valence-induced biases on motor response and confidence in human reinforcement learning. Cognitive, Affective, & Behavioral Neuroscience, . doi:10.3758/s13415-020-00826-0

Ting, C. , Palminteri, S., Engelmann, J. & Lebreton, M. (2019). Decreased confidence in loss-avoidance contexts is a primary meta-cognitive bias of human reinforcement learning. bioRxiv. doi:10.1101/593368

Stefanini, F. , A. Kheirbek, M. , Kushnir, L., C. Jimenez, J. , H. Jennings, J. , D. Stuber, G. , Hen, R. & Fusi, S. (2018). A distributed neural code in the dentate gyrus and in CA1. . doi:10.1101/292953

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

Simeone, O. , Rajendran, B. , Gruning, A. , Eleftheriou, E. , Davies, M. , Denève, S. & Huang, G. (2019). Learning Algorithms and Signal Processing for Brain-Inspired Computing. IEEE Signal Processing Magazine, 36(6), 12-15. doi:10.1109/MSP.2019.2935557

Sidarus, N., Palminteri, S. & Chambon, V. (2019). Cost-benefit trade-offs in decision-making and learning. PLOS Computational Biology, 15(9), e1007326. doi:10.1371/journal.pcbi.1007326

Sidarus, N., Palminteri, S. & Chambon, V. (2018). Trading off the cost of conflict against expected rewards. Plos Computational Biology, 42809. doi:10.1371/journal.pcbi.1007326

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

Safra, L., Chevallier, C. & Palminteri, S. (2019). Depressive symptoms are associated with blunted reward learning in social contexts. PLOS Computational Biology, 15(7), e1007224. doi:10.1371/journal.pcbi.1007224

Safra, L., Palminteri, S. & Chevallier, C. (2019). Social information impairs reward learning in depressive subjects: behavioral and computational characterization. Plos Computational Biology, 15(7), e1007224. doi:10.1101/378281

Recanatesi, S., Farrell, M., Lajoie, G., Denève, S., Rigotti, M. & Shea-Brown, E. (2018). Signatures and mechanisms of low-dimensional neural predictive manifolds. bioRxiv. doi:10.1101/471987

Recanatesi, S., Farrell, M., Lajoie, G., Denève, S., Rigotti, M. & Shea-Brown, E. (2021). Predictive learning as a network mechanism for extracting low-dimensional latent space representations. Nature Communications, 12(1417). doi:10.1038/s41467-021-21696-1

Rahnev, D., Desender, K., Lee, A., Adler, W., Aguilar-Lleyda, D., Akdoğan, B., Arbuzova, P., Atlas, L., Balcı, F., Bang, J., Bègue, I., Birney, D., Brady, T., Calder-Travis, J., Chetverikov, A., Clark, T., Davranche, K., Denison, R., Dildine, T., Double, K., Duyan, Y., Faivre, N., Fallow, K., Filevich, E., Gajdos, T., Gallagher, R., de Gardelle, V., Gherman, S., Haddara, N., Hainguerlot, M., Hsu, T., Hu, X., Iturrate, I., Jaquiery, M., Kantner, J., Koculak, M., Konishi, M., Koß, C., Kvam, P., Kwok, S., Lebreton, M., Lempert, K., Ming Lo, C., Luo, L., Maniscalco, B., Martin, A., Massoni, S., Matthews, J., Mazancieux, A., Merfeld, D., O'Hora, D., Palser, E., Paulewicz, B., Pereira, M., Peters, C., Philiastides, M., Pfuhl, G., Prieto, F., Rausch, M., Recht, S. , Reyes, G., Rouault, M., Sackur, J., Sadeghi, S., Samaha, J., Seow, T., Shekhar, M., Sherman, M., Siedlecka, M., Skóra, Z., Song, C., Soto, D., Sun, S., Van Boxtel, J., Wang, S., Weidemann, C., Weindel, G., Wierzchoń, M., Xu, X., Ye, Q., Yeon, J., Zou, F. & Zylberberg, A. (2020). The Confidence Database. Nature Human Behaviour, 4, 317–325. doi:10.1038/s41562-019-0813-1

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

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

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

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

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

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

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

Lussange, J., Lazarevich, I. , Bourgeois-Gironde, S., Palminteri, S. & Gutkin, B. (2020). Modelling Stock Markets by Multi-agent Reinforcement Learning. Computational Economics, 57, 113-147. doi:10.1007/s10614-020-10038-w

Lussange, J., Belianin, A., Bourgeois-Gironde, S. & Gutkin, B. (2017). A bright future for financial agent-based models. arXiv preprint arXiv:1801.08222

Leptourgos, P., Denève, S. & Jardri, R. (2017). Can circular inference relate the neuropathological and behavioral aspects of schizophrenia? Current opinion in neurobiology, 46, 154-161. doi:10.1016/j.conb.2017.08.012