Publications

Chevallier, C. (2017). Evolutionary approaches to deprivation transform the ethics of policy making. The Behavioral and brain sciences, 40, e322. doi:10.1017/S0140525X17000929

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

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

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., 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

Chadwick, M., Metzler, H., Tijus, C., Armony, J. & Grèzes, J. (2018). Stimulus and observer characteristics jointly determine the relevance of threatening facial expressions and their interaction with attention. , 1-14. doi:10.1007/s11031-018-9730-2

Calmels, C., Pichon, S. & Grèzes, J. (2014). Can we simulate an action that we temporarily cannot perform? Neurophysiologie Clinique/Clinical Neurophysiology, 44(5), 433-445. doi:10.1016/j.neucli.2014.08.004

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

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

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

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

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

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

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

Beaurenaut, M., Dezecache, G. & Grèzes, J. (2021). Action co-representation under threat: A Social Simon study. Cognition, 215, 104829. doi:10.1016/j.cognition.2021.104829

Beaurenaut, M., Tokarski , E., Dezecache, G. & Grèzes, J. (2020). The ‘Threat of Scream’ paradigm: a tool for studying sustained physiological and subjective anxiety. Scientific Reports, 10(1), 1-11. doi:10.1038/s41598-020-68889-0

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

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)

Balsdon, T., Mamassian, P. & Wyart, V. (2021). Separable neural signatures of confidence during perceptual decisions. eLife, 10, e68491. doi:10.7554/eLife.68491

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

Balsdon, T., Wyart, V. & Mamassian, P. (2019). Graded, multidimensional representations of sensory evidence allow for dissociable performance in second-choice and confidence judgments. Journal of Vision, 19(10), 289a-289a. doi:10.1167/19.10.289a

Balsdon, T., Summersby, S., Kemp, R. & White, D. (2018). Improving face identification with specialist teams. Cognitive Research: Principles and Implications, 3(1), 25. doi:10.1186/s41235-018-0114-7

Balsdon, T. & Clifford, C. (2018). How wide is the cone of direct gaze? Royal Society open science 6, 5(8), 180249

Balsdon, T. & Clifford, C. (2018). Task Dependent Effects of Head Orientation on Perceived Gaze Direction. Frontiers in Psychology, 9, 2491. doi:10.3389/fpsyg.2018.02491

Balsdon, T. & Clifford, C. (2018). Visual processing: conscious until proven otherwise. , 5(1). doi:10.1098/rsos.171783

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

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

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.