Publications

Maex, R. & Gutkin, B. (2017). Temporal integration and 1/f power scaling in a circuit model of cerebellar interneurons. Journal of neurophysiology, 118(1), 471-485. doi:10.1152/jn.00789.2016

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

Najar, A., Bonnet, E., Bahador, B. & Palminteri, S. (2020). The actions of others act as a pseudo-reward to drive imitation in the context of social reinforcement learning. PLoS Biology, 18 (12), e3001028. doi:10.1371/journal.pbio.3001028

Palminteri, S., Kilford, E., Coricelli, G. & Blakemore, S. (2016). The Computational Development of Reinforcement Learning during Adolescence. PLoS Computational Biology, 12(6). doi:10.1371/journal.pcbi.1004953

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

Garcia, B., Cerrotti, F. & Palminteri, S. (2021). The description–experience gap: a challenge for the neuroeconomics of decision-making under uncertainty. Phil. Trans. R. Soc. B, 376, 20190665. doi:10.1098/rstb.2019.0665

Garcia, B., Cerrotti, F. & Palminteri, S. (2021). The description-experience gap: a challenge for the neuroeconomics of decision-making under uncertainty. Philosophical transactions of the royal society B, 376(1819). doi:10.1098/rstb.2019.0665

Pischedda, D. , Palminteri, S. & Giorgio, C. (2020). The effect of counterfactual information on outcome value coding in medial prefrontal and cingulate cortex: from an absolute to a relative neural code. Journal of Neuroscience, 40(16), 3268-3277. doi:10.1523/JNEUROSCI.1712-19.2020

Patron, E., Mennella, R., Messerotti Benvenuti, S. & Thayer, J. (2018). The frontal cortex is a heart-brake: Reduction in delta oscillations is associated with heart rate deceleration. NeuroImage, 188, 403-410. doi:10.1016/j.neuroimage.2018.12.035

Patron, E., Mennella, R., Messerotti Benvenuti, S. & Thayer, J. (2019). The frontal cortex is a heart-brake: Reduction in delta oscillations is associated with heart rate deceleration. NeuroImage, 188, 403-410. doi:10.1016/j.neuroimage.2018.12.035

Bavard, S. & Palminteri, S. (2023). The functional form of value normalization in human reinforcement learning. eLife, 12, e83891. doi:10.7554/eLife.83891

Palminteri, S., Wyart, V. & Koechlin, E. (2017). The Importance of Falsification in Computational Cognitive Modeling. Trends in Cognitive Sciences, 21(6), 425-433. doi:10.1016/j.tics.2017.03.011

Dezecache, G., Grèzes, J. & Dahl, C. (2017). The nature and distribution of affiliative behaviour during exposure to mild threat. Royal Society open science, 4(8), 170265. doi:10.1098/rsos.170265

Gutkin, B., Tuckwell, H. & Jost, J. (2009). The Phenomenon of Inverse Stochastic Resonance. Naturwissenschaften, 96(9), 1091-7

Pischedda, D. , Palminteri, S. & Giorgio, C. (2020). The role of counterfactual information on outcome value coding in mPFC and cingulate cortex: from an absolute to an adaptive neural code. . The Journal of Neuroscience, 40 (16), 3268-3277. doi:10.1523/JNEUROSCI.1712-19.2020

Kret, M., Denollet, J., Grèzes, J. & De Gelder, B. (2011). The role of negative affectivity and social inhibition in perceiving social threat: an fMRI study. Neuropsychologia, 49(5), 1187-1193. doi:10.1016/j.neuropsychologia.2011.02.007

Remme, M., Lengyel, M. & Gutkin, B. (2009). The role of ongoing dendritic oscillations in single-neuron dynamics. PLOS Comp. Bio. , 5(9)

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

Giavazzi, M., Daland, R., Palminteri, S., Peperkamp, S., Brugières, P., Jacquemot, C., Schramm, C., Cleret de Langavant, L. & Bachoud-Levi, A. (2018 ). The role of the striatum in linguistic selection: Evidence from Huntington’s disease and computational modeling. Cortex, 109, 189-204. doi:10.1016/j.cortex.2018.08.031

Mennella, R., Sarlo, M., Messerotti Benvenuti, S., Buodo, G., Mento, G. & Palomba, D. (2017). The two faces of avoidance: Time-frequency correlates of motivational disposition in blood phobia. Psychophysiology, 54(11), 1606-1620. doi:10.1111/psyp.12904

Chevallier, C. (2019). Theory of mind and autism: Revisiting Baron-Cohen et al.’s Sally-Anne study. In A. Slater and P. Quinn (Eds.), Developmental Psychology: Revisiting the Classic Studies 2nd edition (pp. 148-163).Sage

Gutkin, B. (2015). Theta-neurons. In Springer Verlag (Eds.), Encyclopedia of Comptutational Neuroscience (pp. 1034-1042).

Pichon, S., De Gelder, B. & Grèzes, J. (2012). Threat prompts defensive brain responses independently of attentional control. Cerebral cortex (New York, N.Y. : 1991), 22(2), 274-85. doi:10.1093/cercor/bhr060

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

Collins, T. & Jacquet, P. (2018). TMS over posterior parietal cortex disrupts trans-saccadic visual stability. Brain stimulation, 11(2), 390-399. doi:10.1016/j.brs.2017.11.019

Jones, B. , DeBruine, L. , .., .., Chevallier, C. & (Et Al), . (2021). To which world regions does the valence–dominance model of social perception apply? Nat Hum Behav, 5, 159-169. doi:10.6084/m9.figshare.7611443.v1

Stein, H., Barbosa, J. & Compte, A. (2021). Towards biologically constrained attractor models of schizophrenia. Current Opinion in Neurobiology, 70, 171-181. doi:10.1016/j.conb.2021.10.013

Safra, L., Chevallier, C., Grèzes, J. & Baumard, N. (2020). Tracking historical changes in trustworthiness using machine learning analyses of facial cues in painting. Nature Communications, 11, 4728. doi:10.1038/s41467-020-18566-7

Remme, M., Lengyel, M. & Gutkin, B. (2015). Trade-off between dendritic democracy and independence in neurons with intrinsic subthreshold membrane potential oscillatio. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Sidarus, N., Palminteri, S. & Chambon, V. (2018). Trading off the cost of conflict against expected rewards. Plos Computational Biology, 42809. doi:10.1371/journal.pcbi.1007326