Publications

Garcia, B., Lebreton, M., Bourgeois-Gironde, S. & Palminteri, S. (2023). Experiential values are underweighted in decisions involving symbolic options. Nature human behaviour, . doi:10.1038/s41562-022-01496-3

Angeletos Chrysaitis, N. , Jardri, R., Denève, S. & Seriès, P. (2021). No increased circular inference in adults with high levels of autistic traits or autism. Plos Computational Biology, 17(9), e1009006. doi:10.1371/journal.pcbi.1009006

Leptourgos, P., Bouttier, V., Denève, S. & Jardri, R. (2022). From hallucinations to synaesthesia: A circular inference account of unimodal and multimodal erroneous percepts in clinical and drug-induced psychosis. Neuroscience & Biobehavioral Reviews, 135, 104593. doi:10.1016/j.neubiorev.2022.104593

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

Lussange, J., Vrizzi, S., Bourgeois-Gironde, S., Palminteri, S. & Gutkin, B. (2022). Stock Price Formation: Precepts from a Multi-Agent Reinforcement Learning Model. Comput Econ. doi:10.1007/s10614-022-10249-3

Alemi, A., Machens, C., Denève, S. & Slotine, J. (2018). Learning nonlinear dynamics in efficient, balanced spiking networks using local plasticity rules. In Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, AAAI Press.

Bernard, A., Bredeche, N. & Andre, J. (2020). Indirect genetic effects allow escape from the inefficient equilibrium in a coordination game. Evolution Letters, 4(3), 257-265. doi:10.1002/evl3.155

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

Brendel, W. , Bourdoukan, R., Vertechi, P. , Machens, C. & Denève, S. (2020). Learning to represent signals spike by spike. PLOS Computational Biology, 16(3), e1007692. doi:10.1371/journal.pcbi.1007692

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 , 4, 1067-1079. doi:10.1038/s41562-020-0919-5

Claidière, N., Trouche, E. & Mercier, H. (2017). Argumentation and the diffusion of counter-intuitive beliefs. Journal of experimental psychology. General, 146(7), 1052-1066. doi:10.1037/xge0000323

Denève, S., Alemi, A. & Bourdoukan, R. (2017). The Brain as an Efficient and Robust Adaptive Learner. Neuron, 94(5), 969-977. doi:10.1016/j.neuron.2017.05.016

Gutierrez, G. & Denève, S. (2018). Population adaptation in efficient balanced networks. eLife, 8, e46926. doi:10.7554/eLife.46926

Jardri, R. & Denève, S. (2017). [Jumping-to-conclusions in schizophrenia is mediated by circular inference]. Medecine sciences : M/S, 33(11), 933-935. doi:10.1051/medsci/20173311006

Jardri, R., Duverne, S., Litvinova, A. & Denève, S. (2017). Experimental evidence for circular inference in schizophrenia. Nature communications, 8, 14218. doi:10.1038/ncomms14218

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

Kim , K., Ladenbauer, J., Babo-Rebelo, M., Buot, A., Kehongre , K., Adam, C., Hasboun, D., Lambrecq , V., Navarro , V., Ostojic, S. & Tallon-Baudry, C. (2019 ). Resting-state neural firing is linked to cardiac cycle duration in the human cingulate and parahippocampal cortices. Journal of Neuroscience , 39(19), 3676-3686. doi:10.1523/JNEUROSCI.2291-18.2019

Koren, V. & Denève, S. (2017). Computational Account of Spontaneous Activity as a Signature of Predictive Coding. PLoS computational biology, 13(1), e1005355. doi:10.1371/journal.pcbi.1005355

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

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

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

Leptourgos, P., Bouttier, V., Jardri, R. & Denève, S. (2021). A functional theory of bistable perception based on dynamical circular inference. Plos Computational Biology, 16(12), e1008480. doi:10.1371/journal.pcbi.1008480

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

Martins, M. , Bianco, R. , Sammler, D. & Villringer, A. (2019). Recursion in action: An fMRI study on the generation of new hierarchical levels in motor sequences. Human Brain Mapping , 40(4). doi:10.1002/hbm.24549

Martins, M. , Krause, C. , Neville, D. , Pino, D. , Villringer, A. & Obrig, H. (2019). Recursive hierarchical embedding in vision is impaired by posterior middle temporal gyrus lesions. Brain , 142(10), 3217-3229. doi:10.1093/brain/awz242

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

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