Publications

Palminteri, S. & Maël, L. (2022). The computational roots of positivity and confirmation biases in reinforcement-learning. Trends in Cognitive Sciences, 26(7), 607-621. doi:10.1016/j.tics.2022.04.005

Anlló, H., Katsumi, W., Sackur, J. & de Gardelle, V. (2022). Effects of false statements on visual perception hinge on social suggestibility. J Exp Psychol Hum Percept Perform, 48(8), 889–900. doi:10.1037/xhp0001024

Atkinson-Clement, C. , Maël, L., Patsalides, L. , De Liege, A. , Klein, Y. , Roze, E. , Deniau, E. , Andreas, H., Palminteri, S. & Yulia, W. (2022). Decision-making under risk and ambiguity in adults with Tourette syndrome. Psychological Medicine, 1-11. doi:10.1017/S0033291722002318

Valente, A., Ostojic, S. & Pillow, J. (2022). Probing the Relationship Between Latent Linear Dynamical Systems and Low-Rank Recurrent Neural Network Models. Neural Computation, 1-22. doi:10.1162/neco_a_01522

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

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

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

Dubreuil, A., Valente, A., Beiran, M., Mastrogiuseppe, F. & Ostojic, S. (2022). The role of population structure in computations through neural dynamics. Nature Neuroscience, 25, 783–794. doi:10.1038/s41593-022-01088-4

Jazayeri, M. & Ostojic, S. (2021). Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity. Current Opinion in Neurobiology, 70, 113-120. doi:10.1016/j.conb.2021.08.002

Barbosa, J., Stein, H., Zorowitz, S. , Niv, Y. , Summerfield, C., Soto-Faraco, S. & Hyafil, A. (2022). A practical guide for studying human behavior in the lab. Behavior Research Methods. doi:10.3758/s13428-022-01793-9

Joao, B., Lozano-Soldevilla, D. & Compte, A. (2021). Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories. PLOS Biology, 20(3), e3001603. doi:10.1371/journal.pbio.3001436

Stein, H., Barbosa, J. & Compte, A. (2021). Towards biologically constrained attractor models of schizophrenia. Current Opinion in Neurobiology, 70, 171-181. doi:10.1016/j.conb.2021.10.013

Barbosa, J., Babushkin, V. , Temudo, A. , Sreenivasan, K. & Compte, A. (2021). Across-Area Synchronization Supports Feature Integration in a Biophysical Network Model of Working Memory. Front. Neural Circuits. doi:10.3389/fncir.2021.716965

Bavard, S. & Palminteri, S. (2021). Why unchosen options linger in our minds. Communications Biology , 4, 1271. doi:10.1038/s42003-021-02803-w

Garcia, B., Cerrotti, F. & Palminteri, S. (2021). The description–experience gap: a challenge for the neuroeconomics of decision-making under uncertainty. Phil. Trans. R. Soc. B, 376, 20190665. doi:10.1098/rstb.2019.0665

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

Delorme, C., Salvador, A., Valabrègue, R., Roze, E., Palminteri, S., Vidailhet, M., De Wit, S., Robbins, T., Hartmann, A. & Worbe, Y. (2016). Enhanced habit formation in Gilles de la Tourette syndrome. Brain : a journal of neurology, 139(Pt 2), 605-15. doi:10.1093/brain/awv307

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

Salem-Garcia, N., Palminteri, S. & Lebreton, M. (2023). Linking confidence biases to reinforcement-learning processes. Psychological review, . doi:10.1037/rev0000424

Anlló, H., Bavard, S., Benmarrakchi, F., Bonagura, D., Cerrotti, F., Cicue, M., Gueguen, M., Guzmán, E., Kadieva, D., Kobayashi, M., Lukumon, G., Sartorio, M., Yang, J., Zinchenko, O., Bahrami, B., Silva, J., Hertz, U., Konova, A., Li, J., O'Madagain, C., Navajas, J., Reyes, G., Sarabi-Jamab, A., Shestakova, A. , Sukumaran, B., Watanabe, K. & Palminteri, S. (2023). Outcome context-dependence is not WEIRD: Comparing reinforcement- and description-based economic preferences worldwide. Research square, . doi:10.21203/rs.3.rs-2621222/v1

Azzalini, D., Buot, A., Palminteri, S. & Tallon-Baudry, C. (2021). Responses to Heartbeats in Ventromedial Prefrontal Cortex Contribute to Subjective Preference-Based Decisions. Journal of Neuroscience, 41(23), 5102-5114. doi:10.1523/JNEUROSCI.1932-20.2021

Bagur, S. , Averseng, M., Elgueda, D., David, S., Fritz, J., Yin, P., Shamma, S., Boubenec, Y. & Ostojic, S. (2018). Go/No-Go task engagement enhances population representation of target stimuli in primary auditory cortex. Nature Communications, 9, 2529 . doi:10.1038/s41467-018-04839-9

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)

Bavard, S., Rustichini, A. & Palminteri, S. (2021). Two sides of the same coin: Beneficial and detrimental consequences of range adaptation in human reinforcement learning. Science Advances, 7(14). doi:10.1126/sciadv.abe0340

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

Beiran, M., Dubreuil, A., Valente, A., Mastrogiuseppe, F. & Ostojic, S. (2021). Shaping dynamics with multiple populations in low-rank recurrent networks. Neural Computation, 33(6), 1572-1615. doi:10.1162/neco_a_01381 Article history

Bimbard, C., Ledoux, E. & Ostojic, S. (2016). Instability to a heterogeneous oscillatory state in randomly connected recurrent networks with delayed interactions. Physical review. E, 94(6-1), 062207. doi:10.1103/PhysRevE.94.062207

Blot, A., De Solages, C., Ostojic, S., Szapiro, G., Hakim, V. & Léna, C. (2016). Time-invariant feed-forward inhibition of Purkinje cells in the cerebellar cortex in vivo. The Journal of physiology, 594(10), 2729-49. doi:10.1113/JP271518

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

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