Publications

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

Evans, M. , Locke, S. & Landy, M. (2022). Prospective and Retrospective Cues for Sensorimotor Confidence in a Reaching Task. , 22(3552). doi:10.1167/jov.22.14.3552

Hosseinizaveh, N. & Mamassian, P. (2022). The effect of confidence on visual perceptual learning. Journal of Vision, 22(14). doi:10.1167/jov.22.14.3950

Jeckeln, G., Mamassian, P. & O'Toole, A. (2022). People can evaluate the correctness of their face-identification decisions using comparative confidence judgments. , 22, 3341. doi:10.1167/jov.22.14.3341

Klever, L. , Mamassian, P. & Billino, J. (2022). Age-related differences in visual confidence are driven by individual differences in cognitive control capacities. Scientific Reports , 12(6016). doi:10.1038/s41598-022-09939-7

Kurzawski, J., Lunghi, C., Biagi, L., Tosetti, M., Maria Concetta, M. & Binda, P. (2022). Short-term plasticity in the human visual thalamus. eLife, 11. doi:10.7554/eLife.74565

Locke, S., Goettker, A. , Gegenfurtner, K. & Mamassian, P. (2022). Sensorimotor confidence for tracking eye movements. journal of Vision, 22(3500). doi:10.1167/jov.22.14.3500

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

Mamassian, P. (2022). Reverse motion from reversed time perception? Journal of Vision, 22, 4095. doi:10.1167/jov.22.14.4095

Mamassian, P. (2022). Uncertain perceptual confidence. Nature Human Behaviour, 6, 179-180. doi:10.1038/s41562-021-01248-9

Meso, A., Gekas, N., Mamassian, P. & Masson, G. (2022). Speed Estimation for Visual Tracking Emerges Dynamically from Nonlinear Frequency Interactions. eNeuro, 13(9), 3. doi:10.1523/ENEURO.0511-21.2022

Neri, P. (2022). Deep networks may capture biological behavior for shallow, but not deep, empirical characterizations Author links open overlay panel. Neural Networks, 152, 244-266. doi:10.1016/j.neunet.2022.04.023

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

Rahnev, D., Balsdon, T., Charles, L., de Gardelle, V., Denison, R., Desender, K., Faivre, N., Filevich, E., Fleming, S., Jehee, J., Lau, H., Lee, A., Locke, S., Mamassian, P., Odegaard, B., Peters, M., Reyes, G., Rouault, M., Sackur, J., Samaha, J., Sergent, C., Sherman, M., Siedlecka, M., Soto, D., Vlassova, A. & Zylberberg, A. (2022). Consensus goals for the field of visual metacognition. Perspectives on Psychological Science, . doi:10.1177/17456916221075615

Recanati, F. (2022). Understanding Force Cancellation. Inquiry: An Interdisciplinary Journal of Philosophy , . doi:10.1080/0020174X.2022.2075920

Recht, S. , Mamassian, P. & de Gardelle, V. (2022). Metacognition tracks sensitivity following involuntary shifts of visual attention. Psychon Bull Rev. doi:10.3758/s13423-022-02212-y

Recht, S. , Jovanovic, L. , Mamassian, P. & Balsdon, T. (2022). Confidence at the limits of human nested cognition. Neuroscience of consciousness, 2022(1), niac014. doi:10.1093/nc/niac014

Schaffhauser, T., de Cheveigné, A., Boubenec, Y. & Mamassian, P. (2022). EEG evoked activity suggests amodal evidence integration in multisensory decision-making. Journal of vision, 22(3963). doi:10.1167/jov.22.14.3963

Schweitzer, R. , Watson, T. , Balsdon, T. & Rolfs, M. (2022). The sources of peri-saccadic mislocalization: Evidence from the perception of intra-saccadic motion streaks. Journal of vision, 22, 3997. doi:10.1167/jov.22.14.3897

Vacher, J. , Coen-Cagli, R. & Mamassian, P. (2022). Unifying Different Psychometric Methods : Theory and Experiment. Journal of Vision, 22, 3879. doi:10.1167/jov.22.14.3879

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

Wexler, M., Mamassian, P. & Schütz, A. (2022). Structure of visual biases revealed by individual differences. Vision Research, 195, 108014. doi:10.1016/j.visres.2022.108014

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

Balsdon, T., Mamassian, P. & Wyart, V. (2021). Neural signatures of confidence after the completion of a perceptual decision. Journal of Vision, 21(9). doi:10.1167/jov.21.9.2518

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

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

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., 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