Publications

Schütz, A. & Mamassian, P. (2016). Early, local motion signals generate directional preferences in depth ordering of transparent motion. Journal of vision, 16(10), 24. doi:10.1167/16.10.24

Schmale, R., Seidl, A. & Cristia, A. (2015). Mechanisms underlying accent accommodation in early word learning: evidence for general expansion. Developmental Science, 18(4), 664-670. doi:10.1111/desc.12244

Schmale, R., Cristia, A. & Seidl, A. (2012). Toddlers recognize words in an unfamiliar accent after brief exposure. Developmental Science, 15(6), 732-738. doi:10.1111/j.1467-7687.2012.01175.x

Schaffhauser, T., Boubenec, Y. & Mamassian, P. (2019). Temporal binding across senses facilitates change detection within senses. Journal of vision, 19(10), 19a-19a. doi:10.1167/19.10.19a

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

Recht, S. , Mamassian, P. & de Gardelle, V. (2018). Confidence blinks before attention. Journal of Vision, 18(10), 1112. doi:10.1167/18.10.1112

Recht, S. , de Gardelle, V. & Mamassian, P. (2021). Metacognitive blindness in temporal selection during the deployment of spatial attention. Cognition, 216, 104864. doi:10.1016/j.cognition.2021.104864

Recht, S. , de Gardelle, V. & Mamassian, P. (2019). Metacognitive estimates of time during spatial orienting of attention. Journal of vision, 19(10), 214c-214c. doi:10.1167/19.10.214c

Recht, S. , Mamassian, P. & de Gardelle, V. (2019). Temporal attention causes systematic biases in visual confidence. Scientific Reports, 9(1), 11622. doi:10.1038/s41598-019-48063-x

Recht, S. , Mamassian, P. & de Gardelle, V. (2018). When temporal attention lacks confidence. bioRxiv, 496232

Räsänen, O., Seshadri, S., Lavechin, M., Cristia, A. & Casillas , M. (2021). ALICE: An open-source tool for automatic measurement of phoneme, syllable, and word counts from child-centered daylong recordings. Behav Res, 53, 818–835. doi:10.3758/s13428-020-01460-x

Räsänen, O., Seshadri, S., Karadayi, J., Riebling , E., Bunce , J., Cristia, A., Metze, F., Bergelson, E. & Soderstrom, M. (2019). Automatic word count estimation from daylong child-centered recordings in various language environments using language-independent syllabification of speech. Speech Communication, 113, 63-80. doi:10.1016/j.specom.2019.08.005

Rahnev, D., Desender, K., Lee, A., Adler, W., Aguilar-Lleyda, D., Akdoğan, B., Arbuzova, P., Atlas, L., Balcı, F., Bang, J., Bègue, I., Birney, D., Brady, T., Calder-Travis, J., Chetverikov, A., Clark, T., Davranche, K., Denison, R., Dildine, T., Double, K., Duyan, Y., Faivre, N., Fallow, K., Filevich, E., Gajdos, T., Gallagher, R., de Gardelle, V., Gherman, S., Haddara, N., Hainguerlot, M., Hsu, T., Hu, X., Iturrate, I., Jaquiery, M., Kantner, J., Koculak, M., Konishi, M., Koß, C., Kvam, P., Kwok, S., Lebreton, M., Lempert, K., Ming Lo, C., Luo, L., Maniscalco, B., Martin, A., Massoni, S., Matthews, J., Mazancieux, A., Merfeld, D., O'Hora, D., Palser, E., Paulewicz, B., Pereira, M., Peters, C., Philiastides, M., Pfuhl, G., Prieto, F., Rausch, M., Recht, S. , Reyes, G., Rouault, M., Sackur, J., Sadeghi, S., Samaha, J., Seow, T., Shekhar, M., Sherman, M., Siedlecka, M., Skóra, Z., Song, C., Soto, D., Sun, S., Van Boxtel, J., Wang, S., Weidemann, C., Weindel, G., Wierzchoń, M., Xu, X., Ye, Q., Yeon, J., Zou, F. & Zylberberg, A. (2020). The Confidence Database. Nature Human Behaviour, 4, 317–325. doi:10.1038/s41562-019-0813-1

Ponsot, E., Varnet, L., Wallaert, N., Daoud, E., Shamma, S., Lorenzi, C. & Neri, P. (2021). Mechanisms of Spectrotemporal Modulation Detection for Normal- and Hearing-Impaired Listeners. Trends Hear, 25, 2331216520978029. doi:10.1177/2331216520978029

Ponsot, E., Burred, J., Belin, P. & Aucouturier, J. (2018). Reply to Knight et al.: The complexity of inferences from speech prosody should be addressed using data-driven approaches. Proceedings of the National Academy of Sciences of the United States of America, 115(27), E6104-E6105. doi:10.1073/pnas.1806857115

Ponsot, E., Susini, P. & Meunier, S. (2017). Global loudness of rising- and falling-intensity tones: How temporal profile characteristics shape overall judgments. The Journal of the Acoustical Society of America, 142(1), 256. doi:10.1121/1.4991901

Ponsot, E., Arias, P. & Aucouturier, J. (2018). Uncovering mental representations of smiled speech using reverse correlation. The Journal of the Acoustical Society of America, 143(1), EL19. doi:10.1121/1.5020989

Ponsot, E., Burred, J., Belin, P. & Aucouturier, J. (2018). Cracking the social code of speech prosody using reverse correlation. Proceedings of the National Academy of Sciences of the United States of America, 115(15), 3972-3977. doi:10.1073/pnas.1716090115

Ponsot, E., Susini, P. & Oberfeld, D. (2016). Temporal weighting of loudness: Comparison between two different psychophysical tasks. The Journal of the Acoustical Society of America, 139(1), 406-17. doi:10.1121/1.4939959

Ponsot, E., Meunier, S., Kacem, A., Chatron, J. & Susini, P. (2015). Are Rising Sounds Always Louder? Influences of Spectral Structure and Intensity-Region on Loudness Sensitivity to Intensity-Change Direction. Acta Acustica united with Acustica, 101(6). doi:10.3813/AAA.918902

Ponsot, E., Susini, P., Saint Pierre, G. & Meunier, S. (2013). Temporal loudness weights for sounds with increasing and decreasing intensity profiles. The Journal of the Acoustical Society of America, 134(4), EL321-6. doi:10.1121/1.4819184

Ponsot, E., Susini, P. & Meunier, S. (2015). A robust asymmetry in loudness between rising- and falling-intensity tones. Attention, perception & psychophysics, 77(3), 907-20. doi:10.3758/s13414-014-0824-y

Piot, L. , Havron, N. & Cristia, A. (2021). Socioeconomic status correlates with measures of Language Environment Analysis (LENA) system: A meta-analysis. . Journal of Child Language, 1-15. doi:10.1017/S0305000921000441[Opens in a new window]

Paraouty, N., Ewert, S., Wallaert, N. & Lorenzi, C. (2016). Interactions between amplitude modulation and frequency modulation processing: Effects of age and hearing loss. The Journal of the Acoustical Society of America, 140(1), 121. doi:10.1121/1.4955078

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

Otto, T. & Mamassian, P. (2017). Multisensory decisions: The test of a race model, its logic, and power. Multisensory Research, 30(1), 1-24. doi:10.1163/22134808-00002541

Ota, K. , Wu, Q. & Mamassian, P. (2020). Visual cue estimation with non-gaussian distribution. Journal of vision, 20(11). doi:10.1167/jov.20.11.1436

Norman-Haignere, S., Mcdermott, J., Kanwisher, N. & Conway, B. (2019). Divergence in the functional organization of human and macaque auditory cortex revealed by fMRI responses to harmonic tones. Nature Neuroscience , 22, 1057–1060. doi:10.1038/s41593-019-0410-7

Neri, P. (2021). Optimal templates for signal extraction by noisy ideal detectors and human observers. Journal of Computational Neuroscience, 49(1-20). doi:10.1007/s10827-020-00768-z

Neri, P. (2020). Complex visual analysis of ecologically relevant signals in Siamese fighting fish. Anim Cogn ., 23(1), 41-53. doi:10.1007/s10071-019-01313-x