Publications

Jacquet, P., Roy, A., Chambon, V., Borghi, A., Salemme, R., Farnè, A. & Reilly, K. (2016). Changing ideas about others' intentions: updating prior expectations tunes activity in the human motor system. Scientific reports, 6, 26995. doi:10.1038/srep26995

Lettinga, N., Mell, H., Algan, Y., Jacquet, P. & Chevallier, C. (2021). Childhood environmental adversity is not linked to lower levels of cooperative behaviour in economic games. Evolutionary Human Sciences, 3, E29. doi:10.1017/ehs.2021.21

Safra, L., Algan, Y., Tecu, T., Grèzes, J., Baumard, N. & Chevallier, C. (2017). Childhood harshness predicts long-lasting leader preferences. Evolution and Human Behavior, 38(5), 645-651. doi:10.1016/j.evolhumbehav.2017.05.001

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, .

Jardri, R., Leptourgos, P., Bouttier, V. & Denève, S. (2020). Circular Inference and Hallucinations. Biological Psychiatry, 87(9), S41-S42. doi:10.1016/j.biopsych.2020.02.131

Leptourgos, P., Notredame, C., Jardri, R., Denève, S. & Eck, M. (2020). Circular inference in bistable perception. Journal of Vision, 20(12), 521195. doi:10.1167/jov.20.4.12

Bouttier, V., Duttagupta, S. , Denève, S. & Jardri, R. (2022). Circular inference predicts nonuniform overactivation and dysconnectivity in brain-wide connectomes. Schizophrenia Research, 245, 59-67. doi:10.1016/j.schres.2020.12.045

Chanel, G., Pichon, S., Conty, L., Berthoz, S., Chevallier, C. & Grèzes, J. (2016). Classification of autistic individuals and controls using cross-task characterization of fMRI activity. Neuroimage-Clinical, 10, 78-88. doi:10.1016/j.nicl.2015.11.010

Chanel, G., Pichon, S., Conty, L., Berthoz, S., Chevallier, C. & Grèzes, J. (2015). Classification of autistic individuals and controls using cross-task characterization of fMRI activity. NeuroImage. Clinical, 10, 78-88. doi:10.1016/j.nicl.2015.11.010

Mell, H., Safra, L., Baumard, N. & Jacquet, P. (2017). Climate is not a good candidate to account for variations in aggression and violence across space and time. The Behavioral and brain sciences, 40, e91. doi:10.1017/S0140525X16001060

Ostojic, S., Panja, D. & Nienhuis, B. (2004). Clustering in a one-dimensional inelastic lattice gas. Physical Review E, 69(4 Pt 1), 041301. doi:10.1103/PhysRevE.69.041301

Bondanelli, G. & Ostojic, S. (2020). Coding with transient trajectories in recurrent neural networks. PLoS Computational Biology, 16 (2), e1007655. doi:10.1371/journal.pcbi.1007655

Baumard, N., Safra, L., Martins, M. & Chevallier, C. (2024). Cognitive fossils: using cultural artifacts to reconstruct psychological changes throughout history. Trends in cognitive sciences, 28(2), 172-186. doi:10.1016/j.tics.2023.10.001

Chung, V., Grèzes, J. & Pacherie, E. (2023). Collective Emotion: A Framework for Experimental Research. Emotion Review, 16(1), 28-45. doi:10.1177/17540739231214533

Grèzes, J. & Dezecache, G. (2012). Communication émotionnelle: mécanismes cognitifs et cérébraux. In P. Allain, G. Aubin & D. Le Gal (Eds.), Cognition Sociale et NeuropsychologieSolal

Anlló, H., Bavard, S., Benmarrakchi, F., Bonagura, D., Cerrotti, F., Cicue, M., Gueguen, M., José Guzmán, E., Kadieva, D., Kobayashi, M., Lukumon, G., Sartorio, M., Yang, J., Zinchenko, O., Bahrami, B., Silva Concha, J., Hertz, U., B Konova, A., Li, J., O'Madagain, C., Navajas, J., Reyes, G., Sarabi-Jamab, A., Shestakova, A. , Sukumaran, B., Watanabe, K. & Palminteri, S. (2024). Comparing experience- and description-based economic preferences across 11 countries. Nature human behaviour, 8(8), 1554-1567. doi:10.1038/s41562-024-01894-9

Findling, C. & Wyart, V. (2021). Computation noise in human learning and decision-making: origin, impact, function. Current Opinion in Behavioral Sciences, 38, 124-132. doi:10.1016/j.cobeha.2021.02.018

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

Ostojic, S. & Fusi, S. (2024). Computational role of structure in neural activity and connectivity. Trends in cognitive sciences, 28(7), 677-690. doi:10.1016/j.tics.2024.03.003

Balsdon, T., Wyart, V. & Mamassian, P. (2020). Confidence controls perceptual evidence accumulation. Nature Communications, 11(1), 1753. doi:10.1038/s41467-020-15561-w

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

Leclercq, S., Szaffarczyk, S., Leptourgos, P., Yger, P., Fakhri, A., Wathelet, M., Bouttier, V., Denève, S. & Jardri, R. (2024). Conspiracy beliefs and perceptual inference in times of political uncertainty. Scientific reports, 14(1), 9001. doi:10.1038/s41598-024-59434-4

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

Vandendriessche, H., Demmou, A. , Bavard, S., Yadak, J. , Lemogne, C. , Mauras, T. & Palminteri, S. (2022). Contextual influence of reinforcement learning performance of depression: evidence for a negativity bias? Psychological Medicine, ., 1-11. doi:10.1017/S0033291722001593

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

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

Beiran, M. & Ostojic, S. (2019). Contrasting the effects of adaptation and synaptic filtering on the timescales of dynamics in recurrent networks . PLoS Computational Biology, 15(3), e1006893. doi:10.1371/journal.pcbi.1006893

Martí, D., Brunel, N. & Ostojic, S. (2018). Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks. Physical Review E, 97, 062314. doi:https://doi.org/10.1103/PhysRevE.97.062314