Publications

Tallon-Baudry, C. (2021). From global to local in conscious vison: behavior & MEG. Journal of vision, 21, 63. doi:10.1167/jov.21.9.63

de Vignemont, F. (2021). Fifty Shades of Affective Colouring of Perception. Australasian Journal of Philosophy. doi:10.1080/00048402.2021.1965176

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

Jovanovic, L. & Mamassian, P. (2020). Events are perceived earlier in peripheral vision. Current Biology, 30(21), R1299-R1300. doi:10.1016/j.cub.2020.08.096

Barthelmé, S. & Mamassian, P. (2009). Evaluation of objective uncertainty in the visual system. PLoS Computational Biology, 5(9), e1000504. doi:10.1371/journal.pcbi.1000504

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

Wolpert, N., Rebollo, I. & Tallon-Baudry, C. (2020). Electrogastrography for psychophysiological research: Practical considerations, analysis pipeline, and normative data in a large sample. Psychophysiology, 57(9), e 13599. doi:10.1111/psyp.13599

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

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

Schütz, A. & Mamassian, P. (2016). Early, local motion signals generate directional preferences in depth ordering of transparent motion. Journal of vision, 16(10), 24. doi:10.1167/16.10.24

Lunghi, C. & Morrone, M., C. (2013). Early Interaction between Vision and Touch during Binocular Rivalry. Multisensory Research, 26(3), 291-306. doi:10.1163/22134808-00002411

Wyart, V., Dehaene, S. & Tallon-Baudry, C. (2012). Early dissociation between neural signatures of endogenous spatial attention and perceptual awareness during visual masking. Frontiers in Human Neuroscience, 6, 16. doi:10.3389/fnhum.2012.00016

Lo Verde, L., Morrone, M. & Lunghi, C. (2017). Early cross-modal plasticity in adults. Journal of Cognitive Neuroscience, 29(3), 520-529. doi:10.1162/jocn_a_01067

Masson, G., Gekas, N., Meso, A., Simoncini, C. & Mamassian, P. (2019). Dynamic non-linear interactions serving speed estimation inferred from channel interactions during ocular following. Joural of Vision, 19(10), 167b-167b. doi:10.1167/19.10.167b

Moustafa, A., Kéri, S., Somlai, Z., Balsdon, T., Frydecka, D., Misiak, B. & White, C. (2015). Drift diffusion model of reward and punishment learning in schizophrenia: Modeling and experimental data. Behavioural brain research, 291, 147-154. doi:10.1016/j.bbr.2015.05.024

Casati, R. (2021). Drawing problems: thought in action. Adaptive Behavior, 29(5), 441-448. doi:10.1177/1059712319861551

Casati, R. (2019). Drawing problems: thought in action. Adaptive Behavior, . doi:10.1177/1059712319861551

Latimier, A. , Riegert, A. , Ly, S. , Peyre, H., Casati, R. & Ramus, F. (2019). Does pre-testing promote better retention than post-testing? npj Science of Learning, 4(15). doi:10.1038/s41539-019-0053-1

Norman-Haignere, S., Mcdermott, J., Kanwisher, N. & Conway, B. (2019). Divergence in the functional organization of human and macaque auditory cortex revealed by fMRI responses to harmonic tones. Nature Neuroscience , 22, 1057–1060. doi:10.1038/s41593-019-0410-7

Perroy, B. , Gurchani, U. & Casati, R. (2023). Disorientation and time distortions during the metro commute: An analysis of 456 responses to a questionnaire distributed in real time on Twitter during traffic disruptions in the Paris area. Quarterly journal of experimental psychology (2006), 17470218231163702. doi:10.1177/17470218231163702

Fernandez-Velasco, P. & Casati, R. (2020). Disorientation and GIS-Informed Wilderness Search and Rescue. The Philosophy of GIS Switzerland: Springer Nature. doi:10.1007/978-3-030-16829-2_11

Gekas, N., Mcdermott, K. & Mamassian, P. (2019). Disambiguating serial effects of multiple timescales. Journal of Vision, 19(6), 24-24. doi:10.1167/19.6.24

Balsdon, T. & Clifford, C. (2017). Detecting and identifying offset gaze. Attention, perception & psychophysics, 79(7), 1993-2006. doi:10.3758/s13414-017-1347-0

Safra, L., Chevallier, C. & Palminteri, S. (2019). Depressive symptoms are associated with blunted reward learning in social contexts. PLOS Computational Biology, 15(7), e1007224. doi:10.1371/journal.pcbi.1007224

Herzallah, M., Khdour, H., Taha, A., Elmashala, A., Mousa, H., Taha, M., Ghanim, Z., Sehwail, M., Misk, A., Balsdon, T., Moustafa, A., Myers, C. & Gluck, M. (2017). Depression Reduces Accuracy While Parkinsonism Slows Response Time for Processing Positive Feedback in Patients with Parkinson's Disease with Comorbid Major Depressive Disorder Tested on a Probabilistic Category-Learning Task. Frontiers in psychiatry, 8, 84. doi:10.3389/fpsyt.2017.00084

Hernán, A., Joshua, H. & Sackur, J. (2021). Deployment dynamics of hypnotic anger modulation. Consciousness and Cognition, 91, 103118. doi:10.1016/j.concog.2021.103118

Pasquinelli, E., Farina, M. , Bedel, A. & Casati, R. (2020). Définir et éduquer l'esprit critique.

Pasquinelli, E., Farina, M. , Bedel, A. & Casati, R. (2020). Defining and educating critical thinking Report produced within the framework of Work Package 1 EEC Project -Critical Education (ANR-18-CE28-0018)

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

Ting, C. , Palminteri, S., Engelmann, J. & Lebreton, M. (2019). Decreased confidence in loss-avoidance contexts is a primary meta-cognitive bias of human reinforcement learning. bioRxiv. doi:10.1101/593368