Publications

Tieu, L., Križ, M. & Chemla, E. (2019). Children's Acquisition of Homogeneity in Plural Definite Descriptions. Frontiers in Psychology, . doi:10.3389/fpsyg.2019.02329

Cremers, A., Tieu, L. & Chemla, E. (2017). Children's exhaustive readings of embedded questions. Language Acquisition: A Journal of Developmental Linguistics, 24, 343-360. doi:10.1080/10489223.2016.1176173

Palminteri, S. (2023). Choice-confirmation bias and gradual perseveration in human reinforcement learning. Behavioral neuroscience, 137(1), 78-88. doi:10.1037/bne0000541

Chambon, V., Thero, H., Vidal, M., Vandendriessche, C., Haggard, P. & Palminteri, S. (2020). Choosing and learning: outcome valence differentially affects learning from free versus forced choices. Nature Human Behaviour, .

Versteegh, M., Kuhn, J., Synnaeve, G., Ravaux, L., Chemla, E., Cäsar, C., Fuller, J., Murphy, D., Schel, A. & Dunbar, E. (2016). Classification and automatic transcription of primate calls. The Journal of the Acoustical Society of America, 140(1), EL26. doi:10.1121/1.4954887

Tieu, L., Pasternak , R., Schlenker, P. & Chemla, E. (2018). Co-speech gesture projection: Evidence from inferential judgments. Glossa: a journal of general linguistics , 3(1), 109. doi:10.5334/gjgl.580

Tieu, L., Pasternak , R., Schlenker, P. & Chemla, E. (2017). Co-speech gesture projection: Evidence from truth-value judgment and picture selection tasks. Glossa, 2, 102. doi:10.5334/gjgl.334

Dupoux, E. (2018). Cognitive Science in the era of Artificial Intelligence: A roadmap for reverse-engineering the infant language-learner. Cognition, 173, 43-59. doi:10.1016/j.cognition.2017.11.008

Hansen , N. & Chemla, E. (2017). Color Adjectives, Standards, and Thresholds: An Experimental Investigation. Linguistics \& Philosophy, 40, 239-278

Carbajal, J., Chartofylaka, L., Hamilton, M., Fiévet, A. & Peperkamp, S. (2020). Compensation for Phonological Assimilation in Bilingual Children. Language Learning and Development, 16, 141-160. doi:10.1080/15475441.2020.1717955

Buccola, B., Dautriche, I. & Chemla, E. (2018). Competition and symmetry in an artificial word learning task. Frontiers in Psychology, 9, 2176. doi:10.3389/fpsyg.2018.02176

Zuraw, K., Lin, I. , Yang, M. & Peperkamp, S. (2020). Competition between whole-word and decomposed representations of English prefixed words. Morphology . doi:10.1007/s11525-020-09354-6

Sun, Y., Giavazzi, M., Adda-Decker, M., Barbosa, L., Kouider, S., Bachoud-Levi, A., Jacquemot, C. & Peperkamp, S. (2015). Complex linguistic rules modulate early auditory brain responses. Brain and language, 149, 55-65. doi:10.1016/j.bandl.2015.06.009

Findling, C., Skvortsova , V., Dromnelle, R. , Palminteri, S. & Wyart, V. (2019). Computational noise in reward-guided learning drives behavioral variability in volatile environments. Nature Neuroscience , 22, 2066–2077. doi:10.1101/439885

Buccola, B. & Chemla, E. (2021). Conceptual alternatives. Linguist and Philos . doi:10.1007/s10988-021-09327-w

Buccola, B., Križ, M. & Chemla, E. (2022). Conceptual Alternatives: Competition in Language and Beyond. Linguistics and Philosophy, 45(2 ), 265–291. doi:10.1007/s10988-021-09327-w

Palminteri, S., Lefebvre, G., Kilford, E. & Blakemore, S. (2017). Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing. PLoS computational biology, 13(8), e1005684. doi:10.1371/journal.pcbi.1005684

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

Enguehard, É. & Chemla, E. (2021). Connectedness as a Constraint on Exhaustification . Linguistics and Philosophy, 44(1), 79–112. doi:10.1007/s10988-019-09286-3

Chemla, E., Buccola, B. & Dautriche, I. (2019). Connecting content and logical words. Journal of Semantics, ffz001. doi:10.1093/jos/ffz001

Fort, M., Martin, A. & Peperkamp, S. (2015). Consonants are more important than vowels in the bouba-kiki effect. Language and speech, 58(Pt 2), 247-66. doi:10.1177/0023830914534951

Chemla, E., Dautriche, I., Buccola, B. & Fagot, J. (2019). Constraints on the lexicons of human languages have cognitive roots present in baboons ( Papio papio ) Proceedings of the National Academy of Sciences of the United States of America , 116(30), 14926-14930. doi:10.1073/pnas.1907023116

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

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

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

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

Strickland, B. & Chemla, E. (2018). Cross-linguistic regularities and learner biases reflect "core" mechanics. PloS one, 13(1), e0184132. doi:10.1371/journal.pone.0184132

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