Publications

Mell, H., Safra, L., Baumard, N. & Jacquet, P. (2017). Climate is not a good candidate to account for variations in aggression and violence across space and time. The Behavioral and brain sciences, 40, e91. doi:10.1017/S0140525X16001060

Morin, O., Jacquet, P., Vaesen, K. & Acerbi , A. (2021). Social information use and social information waste. Phil. Trans. R. Soc. B, 376, 20200052. doi:10.1098/rstb.2020.0052

Palminteri, S. & Chevallier, C. (2018). Can We Infer Inter-Individual Differences in Risk-Taking From Behavioral Tasks? Frontiers in psychology, 9, 2307. doi:10.3389/fpsyg.2018.02307

Safra, L., Sijilmassi, A. & Chevallier, C. (2021). Disease, perceived infectability and threat reactivity: A COVID-19 study. Personality and Individual Difference, 180, 110945. doi:10.1016/j.paid.2021.110945

Safra, L., Baumard, N., Wyart, V. & Chevallier, C. (2020). Social motivation is associated with increased weight granted to cooperation-related impressions in face evaluation tasks. PLoS ONE, 15(4), e0230011. doi:10.1371/journal.pone.0230011

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

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

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

Safra, L., Algan, Y., Tecu, T., Grèzes, J., Baumard, N. & Chevallier, C. (2017). Childhood harshness predicts long-lasting leader preferences. Evolution and Human Behavior, 38(5), 645-651. doi:10.1016/j.evolhumbehav.2017.05.001

Udden, J. , Martins, M. , Zuidema, W. & Tecumseh Fitch, W. (2019). Hierarchical Structure in Sequence Processing: How to Measure It and Determine Its Neural Implementation. Topics in Cognitive Science . doi:10.1111/tops.12442