Publications

Dautriche, I., Chemla, E. & Christophe, A. (2016). Word Learning: Homophony and the Distribution of Learning Exemplars. Language Learning and Development, 12(3), 231-251. doi:10.1080/15475441.2015.1127163

Bavard, S. & Palminteri, S. (2021). Why unchosen options linger in our minds. Communications Biology , 4, 1271. doi:10.1038/s42003-021-02803-w

Lebreton, M. & Palminteri, S. (2016). When are inter-individual brain-behavior correlations informative? bioRxiv. doi:10.1101/036772

Dautriche, I. & Chemla, E. (2016 ). What Homophones Say about Words. PLOS ONE, 11(9), 1-2. doi:10.1371/journal.pone.0162176

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

Križ, M. & Chemla, E. (). Two Methods to Find Truth-Value Gaps and Their Application to the Projection Problem of Homogeneity. Natural Language Semantics, 23(3), 205–248

Chemla, E. & Singh, R. (2017). Training and timing local scalar enrichments under global pragmatic pressures. Journal of Semantics, 34(1), 107-126. doi:10.1093/jos/ffw006

Schlenker, P., Chemla, E., Arnold, K., Lemasson, A., Ouattara, K., Keenan, S., Stephan, C., Ryder, R. & Zuberbühler, K. (2013). Towards a formal analysis of primate alarm calls. In 23rd Semantics and Linguistics Theory Conference.

Schlenker, P., Chemla, E., Cäsar, C., Zuberbühler, K. & Ryder, R. (2017). Titi semantics: Context and meaning in Titi monkey call sequences. Natural Language and Linguistic Theory, 35(1), 271-298. doi:10.1007/s11049-016-9337-9

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

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

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

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

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

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

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

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

Turnbull, R. & Peperkamp, S. (2017). The asymmetric contribution of consonants and vowels to phonological similarity: Evidence from lexical priming. The Mental Lexicon, 12, 404-430. doi:10.1075/ ml .17010.tur

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

Bouchacourt, F., Palminteri, S., Koechlin, E. & Ostojic, S. (2020). Temporal Chunking as a Mechanism for Unsupervised Learning of Task-Sets. eLife, 9, e50469. doi:10.7554/eLife.50469

Chemla, E. & Egré, P. (2019). Suszko's problem: mixed consequence and compositionality. Review of Symbolic Logic, 12(4), 736-767. doi:10.1017/S1755020318000503

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

Zuberbühler, K., Chemla, E. & Schlenker, P. (2021). Stereotyped vocalizations. Encyclopedia of Evolutionary Psychological Science (pp. 7970-7974).Springer. doi:10.1007/978-3-319-16999-6_3330-1

Salvador, A., Worbe, Y., Delorme, C., Coricelli, G., Gaillard, R., Robbins, T., Hartmann, A. & Palminteri, S. (2017). Specific effect of a dopamine partial agonist on counterfactual learning: evidence from Gilles de la Tourette syndrome. Scientific reports, 7(1), 6292. doi:10.1038/s41598-017-06547-8

Safra, L., Palminteri, S. & Chevallier, C. (2019). Social information impairs reward learning in depressive subjects: behavioral and computational characterization. Plos Computational Biology, 15(7), e1007224. doi:10.1101/378281

Marty, P. & Chemla, E. (2013). Scalar implicatures: working memory and a comparison with only. Frontiers in psychology, 4, 403. doi:10.3389/fpsyg.2013.00403

Ting, C. , Palminteri, S., Engelmann, J. & Lebreton, M. (2020). Robust valence-induced biases on motor response and confidence in human reinforcement learning. Cognitive, Affective, & Behavioral Neuroscience, . doi:10.3758/s13415-020-00826-0

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

Bavard, S., Lebreton, M., Khamassi, M., Coricelli, G. & Palminteri, S. (2018). Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences. Nature Communications, 9(4503)