Publications

Schlenker, P. (2018). Gesture projection and cosuppositions. Linguistics and Philosophy, 41(3), 295–365. doi:10.1007/s10988-017-9225-8

Keramati, M. & Gutkin, B. (2014). Homeostatic reinforcement learning for integrating reward collection and physiological stability. eLife, 3. doi:10.7554/eLife.04811

Grèzes, J. & Dezecache, G. (2014). How do shared-representations and emotional processes cooperate in response to social threat signals? Neuropsychologia, 55, 105-14. doi:10.1016/j.neuropsychologia.2013.09.019

Correa, C. , Noorman, S. , Jiang, J. , Palminteri, S., Cohen, M. , Lebreton, M. & van Gaal, S. (2018). How the level of reward awareness changes the computational and electrophysiological signatures of reinforcement learning. Journal of Neuroscience , 0457-18. doi:10.1523/JNEUROSCI.0457-18.2018

Schlenker, P. (2018). Iconic pragmatics. Natural Language and Linguistic Theory, 36(3), 877–936. doi:10.1007/s11049-017-9392-x

Koralus, P. & Mascarenhas, S. (2018). Illusory Inferences in a question-based theory of reasoning. In Turner, Ken and Horn, Laurence (Eds.), Pragmatics, Truth, and Underspecification: Towards an Atlas of Meaning (pp. 300–322). Leiden: Brill

Mascarenhas, S. & Koralus, P. (2017). Illusory inferences with quantifiers. Thinking and Reasoning, 23(1), 33–48. doi:10.1080/13546783.2016.1167125

Zhang, D., Gao, M., Xu, D., Shi, W., Gutkin, B., Steffensen, S., Lukas, R. & Wu, J. (2012). Impact of prefrontal cortex in nicotine-induced excitation of ventral tegmental area dopamine neurons in anesthetized rats. Journal of Neuroscience, 32(36), 12366-12375. doi:10.1523/JNEUROSCI.5411-11.2012

Chemla, E. & Schlenker, P. (2012). Incremental Vs. Symmetric Accounts of Presupposition Projection: An Experimental Approach. Natural Language Semantics, 20(2), 177–226 . doi:10.1007/s11050-012-9080-7

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

Najar, A., Sigaud, O. & Chetouani , M. (2020). Interactively shaping robot behaviour with unlabeled human instructions. Auton Agent Multi-Agent Syst, 34(35). doi:10.1007/s10458-020-09459-6

Marty, P., Chemla, E. & Spector, B. (2013). Interpreting numerals and scalar items under memory load. Lingua, 133, 152 - 163. doi:https://doi.org/10.1016/j.lingua.2013.03.006

Krupa, M., Gielen, S. & Gutkin, B. (2014). Intrinsic and synaptic mechanisms for clustered cortical gamma. J Comput. Neurosci , 37(2), 357-76

Geraci, C. (2015). Italian Sign Language. , 473–510De Gruyter Mouton

Dezecache, G. (2013). La communication émotionnelle ou le jeu des affordances sociales. Santé Mentale, 177, 26-31

Grèzes, J., Dezecache, G. & Eskenazi, T. (2015). Limbic to Motor Interactions during Social Perception. In Arthur W. Toga (Eds.), Brain Mapping: An Encyclopedic Reference (pp. 1027-1030).Academic Press: Elsevier

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

Dipoppa, M., Krupa, M., Torcini, A. & Gutkin, B. (2012). Marginally Stable States and Quasi-periodic minor attractors in excitable pulse-coupled networks. SIADS , 63(1), 62-97

Oster, A., Faure, P. & Gutkin, B. (2015). Mechanisms for multiple activity modes of VTA dopamine neurons. Frontiers in computational neuroscience, 9, 95. doi:10.3389/fncom.2015.00095

Lussange, J., Lazarevich, I. , Bourgeois-Gironde, S., Palminteri, S. & Gutkin, B. (2020). Modelling Stock Markets by Multi-agent Reinforcement Learning. Computational Economics, 57, 113-147. doi:10.1007/s10614-020-10038-w

Caze, R., Humphries, M. & Gutkin, B. (2013). Modulation of computational capacity of neurons due to dendritic synaptic interactions. PLoS Comput. Biol., 9(2)

Geraci, C. & Cecchetto, C. (2013). Negleted cases of rightward movement. , 211–241John Benjamins Publishing Company

Hertz, U., Palminteri, S., Brunetti, S., Olesen, C., Frith, C. & Bahrami, B. (2017). Neural computations underpinning the strategic management of influence in advice giving. Nature communications, 8(1), 2191. doi:10.1038/s41467-017-02314-5

Hyafil, A., Giraud, A., Fontolan, L. & Gutkin, B. (2015). Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions. Trends in neurosciences, 38(11), 725-40. doi:10.1016/j.tins.2015.09.001

Vandendriessche, H. & Palminteri, S. (2023). Neurocognitive biases from the lab to real life. Communications biology, 6(1), 158. doi:10.1038/s42003-023-04544-4

Palminteri, S. & Cecchi, R. (2023). Objective models of subjective feelings. Neuroscience and biobehavioral reviews, 151, 105233. doi:10.1016/j.neubiorev.2023.105233

Palminteri, S. & Pessiglione, M. (2016). Opponent brain systems for reward and punishment learning: Causal evidence from drug and lesion studies in humans. Decision Neuroscience: An Integrative Perspective, 291-303. doi:10.1016/B978-0-12-805308-9.00023-3

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

Russo, L. , Farulla, G. , Pianu, D., Salgarella, A. , Controzzi, M., Cipriani, C., Oddo, C. , Geraci, C., Rosa, S. & Indaco, M. (2015). PARLOMA – A Novel Human-Robot Interaction System for Deaf-Blind Remote Communication. International Journal of Advanced Robotic Systems, 2015, 1. doi:10.5772/60416

Marty, P., Chemla, E. & Spector, B. (2015). Phantom readings: the case of modified numerals. Language, Cognition and Neuroscience, 30(4), 462-477. doi:10.1080/23273798.2014.931592