Publications

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

Lunghi, C. & Alais, D. (2015). Congruent tactile stimulation reduces the strength of visual suppression during binocular rivalry. Scientific Reports, 5. doi:10.1038/srep09413

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

Palminteri, S. & Maël, L. (2021). Context-dependent outcome encoding in human reinforcement learning. Current Opinion in Behavioral Sciences, 41, 144-151. doi:10.1016/j.cobeha.2021.06.006

Hansmann-Roth, S., Pont, S. & Mamassian, P. (2018). Contextual effects in human gloss perception. Electronic Imaging(14), 1-7

Hansmann-Roth, S., Pont, S. & Mamassian, P. (2017). Contextual effects on real bicolored glossy surfaces. Journal of Vision, 17(2):17, 1-13. doi:10.1167/17.2.17

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

Lebreton, M., Bacily , K., Palminteri, S. & Engelmann, J. (2019). Contextual influence on confidence judgments in human reinforcement learning. PLoS Comput Biol, 15(4), e1006973. doi:10.1371/journal.pcbi.1006973

Jovanovic, L. , López‐Moliner, J. & Mamassian, P. (2021). Contrasting contributions of movement onset and duration to self‐evaluation of sensorimotor timing performance. European Journal of Neuroscience, 54(3), 5092-5111. doi:10.1111/ejn.15378

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

Tran-Van-Minh, A., Caze, R., Abrahamsson, T., Cathala, L., Gutkin, B. & Digregorio, D. (2015). Contribution of sublinear and supralinear dendritic integration to neuronal computations. Frontiers in cellular neuroscience, 9, 67. doi:10.3389/fncel.2015.00067

Morozova, E., Myroshnychenko, M., Zakharov, D., Di Volo, M., Gutkin, B., Lapish, C. & Kuznetsov, A. (2016). Contribution of synchronized GABAergic neurons to dopaminergic neuron firing and bursting. Journal of neurophysiology, 116(4), 1900-1923. doi:10.1152/jn.00232.2016

Ponsot, E., Déjardin, H. & Roncière, E. (2016). Controlling Programme Loudness in Individualized Binaural Rendering of Multi-Channel Audio Contents. , Vol. 140: In Audio Engineering Society .

Dipoppa, M., Szwed, M. & Gutkin, B. (2016). Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony. Advances in cognitive psychology, 12(4), 209-232. doi:10.5709/acp-0199-x

Dipoppa, M. & Gutkin, B. (2013). Correlations in background activity control persistent state stability and allow execution of working memory tasks. Frontiers in Computational Neuroscience, 7, 139. doi:10.3389/fncom.2013.00139

Wu, J., Gao, M., Shen, J., Shi, W., Oster, A. & Gutkin, B. (2013). Cortical control of VTA function and influence on nicotine reward. Biochemical Pharmacology, 86(8), 1173-1180. doi:10.1016/j.bcp.2013.07.013

Brumberg, J. & Gutkin, B. (2007). Cortical pyramidal cells as non-linear oscillators: Experiment and spike-generation theory. Brain Research, 1171(1), 122-137. doi:10.1016/j.brainres.2007.07.028

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

Ponsot, E., Burred, J., Belin, P. & Aucouturier, J. (2018). Cracking the social code of speech prosody using reverse correlation. Proceedings of the National Academy of Sciences of the United States of America, 115(15), 3972-3977. doi:10.1073/pnas.1716090115

Volk, D., Dubinin, I., Gutkin, B., Myasnikova, A. & Nikulin, V. (2018). Cross-Frequency Synchrony Analysis. Frontiers in Neuroinformatics , 12, 72. doi:10.3389/fninf.2018.00072

Klever, L. , Christin Beyvers, M., Fiehler, K., Mamassian, P. & Billino, J. (2023). Cross-modal metacognition: Visual and tactile confidence share a common scale. Journal of vision, 23(5), 3. doi:10.1167/jov.23.5.3

Lenglet, T. , Mirault, J. , Veyrat-Masson, M. , Funkiewiez, A. , Amador, M. , Bruneteau, G. , Le Forestier, N. , Pradat, P. , Salachas, F. , Vacher, Y. , Lacomblez, L. & Lorenceau, J. (2019). Cursive Eye-Writing With Smooth-Pursuit Eye-Movement Is Possible in Subjects With Amyotrophic Lateral Sclerosis. Front Neurosci, 13, 538. doi:10.3389/fnins.2019.00538

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

Fontanesi , L., Palminteri, S. & Lebreton, M. (2019). Decomposing the effects of context valence and feedback information on speed and accuracy during reinforcement learning: A meta-analytical approach using diffusion decision modeling. Cognitive Affective Behavioral Neuroscience, 1-13. doi:10.3758/s13415-019-00723-1

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

Remme, M., Lengyel, M. & Gutkin, B. (2010). Democracy-independence trade-off in oscillating dendrites and its implications for grid cells. Neuron, 66(3), 429-437. doi:10.1016/j.neuron.2010.04.027

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

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

Morozova, E., Faure, P., Gutkin, B., Lapish, C. & Kuznetsov, A. (2020). Distinct Temporal Structure of Nicotinic ACh Receptor Activation Determines Responses of VTA Neurons to Endogenous ACh and Nicotine. eNeuro, 7(4). doi:10.1523/ENEURO.0418-19.2020

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