Publications

Mamassian, P. & Vemuri, B. (1993). ISOPHOTES ON A SMOOTH SURFACE RELATED TO SCENE GEOMETRY. , Vol. 2031: In Geometric Methods in Computer Vision II, 124-133. doi:10.1117/12.146619

Mamassian, P., Landy, M., Maloney, L., Rao, R., Olshausen, B. & Lewicki, M. (2002). Bayesian modelling of visual perception. In R. Rao, B. Olshausen & M. Lewicki (Eds.), Probabilistic Models of the Brain: Perception and Neural Function (pp. 13-36). Cambridge, MA: MIT Press

Mantovan, L. & Geraci, C. (2017). The syntax of nominal modification in Italian Sign Language (LIS) Sign Language and Linguistics, 20(2), 183-220

Mantovan, L., Duarte, K., Geraci, C. & Cardinaletti, A. (2016). Access to Knowledge The Issue of Deaf Students and More. Annali di Ca' Foscari. Serie occidentale, 50, 149–164. doi:10.14277/2499-1562/AnnOc-50-16-7

Marie, A. , Yesilaltay , S. & Strickland, B. (2020). The cognitive foundations of misinformation on science - What we know and what scientists can do about it. EMBO Rep , 21(4), e50205. doi:10.15252/embr.202050205

Martin, J., Dezecache, G., Pressnitzer, D., Nuss, P., Dokic, J., Bruno, N., Pacherie, E. & Franck, N. (2014). Perceptual hysteresis as a marker of perceptual inflexibility in schizophrenia. Consciousness and cognition, 30, 62-72. doi:10.1016/j.concog.2014.07.014

Marty, P., Chemla, E. & Spector, B. (2013). Interpreting numerals and scalar items under memory load. Lingua, 133, 152 - 163. doi:https://doi.org/10.1016/j.lingua.2013.03.006

Marty, P., Chemla, E. & Spector, B. (2015). Phantom readings: the case of modified numerals. Language, Cognition and Neuroscience, 30(4), 462-477. doi:10.1080/23273798.2014.931592

Mascarenhas, S. & Koralus, P. (2017). Illusory inferences with quantifiers. Thinking and Reasoning, 23(1), 33–48. doi:10.1080/13546783.2016.1167125

Masson, G., Gekas, N., Meso, A., Simoncini, C. & Mamassian, P. (2019). Dynamic non-linear interactions serving speed estimation inferred from channel interactions during ocular following. Joural of Vision, 19(10), 167b-167b. doi:10.1167/19.10.167b

Matushansky, O. & Spector, B. (2004). Tinker, tailor, soldier, spy. In Maier, Emar and Corien Bary and Janneke Huitink (Eds.), In Proceedings of Sinn und Bedeutung 9, Maier, Emar and Corien Bary and Janneke Huitink, 241–255.

Mayr, C. & Spector, B. (2010). Not too strong! Generalizing the scope economy condition. In Prinzhorn, Martin, Viola Schmitt and Sarah Zobel (Eds.), In Proceedings of Sinn und Bedeutung 14.

Mercier, H., Dezecache, G. & Scott-Phillips, T. (2017). Strategically Communicating Minds. Current Directions in Psychological Science, 26(5), 411-416

Moustafa, A., Kéri, S., Somlai, Z., Balsdon, T., Frydecka, D., Misiak, B. & White, C. (2015). Drift diffusion model of reward and punishment learning in schizophrenia: Modeling and experimental data. Behavioural brain research, 291, 147-154. doi:10.1016/j.bbr.2015.05.024

Murez, M., Smortchkova, J. & Strickland, B. (2015). The Mental Files Theory of Singular Thought: A Psychological Perspective.

Myers, C., Sheynin, J., Balsdon, T., Luzardo, A., Beck, K., Hogarth, L., Haber, P. & Moustafa, A. (2016). Probabilistic reward- and punishment-based learning in opioid addiction: Experimental and computational data. Behavioural brain research, 296, 240-248. doi:10.1016/j.bbr.2015.09.018

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

Neri, P. (2018). The empirical characteristics of human pattern vision defy theoretically-driven expectations . PLoS Computational Biology , 14(12), e1006585. doi:10.1371/journal.pcbi.1006585

Neri, P. (2018). Classification images as descriptive statistics. "Journal of Mathematical Psychology", "82"("1), "26–37"

Neri, P. (2017). Object segmentation controls image reconstruction from natural scenes. PLoS biology, 15(8), e1002611. doi:10.1371/journal.pbio.1002611

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

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

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

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

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. & Neri, P. (2020). Inter-individual differences in spectrotemporal modulation processing despite similar audiograms : could they be used to assess supra-threshold hearing distortions? In e-Forum Acusticum 2020. doi:10.48465/fa.2020.0808

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