Publications

Mamassian, P. & Zannoli, M. (2020). Sensory loss due to object formation. Vision Research, 14, 22-40. doi:10.1016/j.visres.2020.05.005

Mamassian, P. (2016). Visual Confidence. Annual Review of Vision Science, 2, 459-481. doi:10.1146/annurev-vision-111815-114630

Mamassian, P. & Landy, M. (1998). Observer biases in the 3D interpretation of line drawings. Vision Research, 38(18), 2817-2832. doi:10.1016/S0042-6989(97)00438-0

Mamassian, P., Knill, D. & Kersten, D. (1998). The perception of cast shadows. Trends in Cognitive Sciences, 2(8), 288-295. doi:10.1016/S1364-6613(98)01204-2

Mamassian, P. (1997). Prehension of objects oriented in three-dimensional space. Experimental Brain Research, 114(2), 235-245. doi:10.1007/PL00005632

Mamassian, P., Kersten, D. & Knill, D. (1996). Categorical local-shape perception. Perception, 25(1), 95-107. doi:10.1068/p250095

Mamassian, P. & Kersten, D. (1996). Illumination, shading and the perception of local orientation. Vision Research, 36(15), 2351-2367. doi:10.1016/0042-6989(95)00286-3

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

Mcdonnell, M., Iannella, N., To, M., Tuckwell, H., Jost, J., Gutkin, B. & Ward, L. (2015). A review of methods for identifying stochastic resonance in simulations of single neuron models. Network: Computation in Neural Systems, 26(2), 35-71. doi:10.3109/0954898X.2014.990064

Morisseau, T. , Branch-Smith, T. & Origgi, G. (2021). Stakes of Knowing the Truth: A Motivational Perspective on the Popularity of a Controversial Scientific Theory. Front. Psychol., 12, 3800. doi:10.3389/fpsyg.2021.708751

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

Muller, L., Brette, R. & Gutkin, B. (2011). Spike-timing dependent plasticity and feed-forward input oscillations produce precise and invariant spike phase-locking. Frontiers in Computational Neuroscience, 15(5), 45. doi:10.3389/fncom.2011.00045

Müller, B., Tsalas, N., Van Schie, H., Meinhardt, J., Proust, J., Sodian, B. & Paulus, M. (2016). Neural correlates of judgments of learning - An ERP study on metacognition. Brain research, 1652, 170-177. doi:10.1016/j.brainres.2016.10.005

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. (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

Origgi, G. (2019). Passions Sociales. Paris: PUF

Origgi, G. (2018). Politicamente corretto. Genesi, sviluppi e derive di un’ideologia Americana. Micromega

Origgi, G. (2018). La democrazia può sopravvivere a Facebook? Egualitarismo epistemico, vulnerabilità cognitiva e nuove tecnologie. Ragion pratica, 445-458. doi:10.1415/91549

Oster, A. & Gutkin, B. (2011). A reduced model of DA neuronal dynamics that displays quiescence, tonic firing and bursting. Journal of Physiology Paris, 105, 53-58. doi:10.1016/j.jphysparis.2011.07.012

Oster, A., Faure, P. & Gutkin, B. (2015). Mechanisms for multiple activity modes of VTA dopamine neurons. Frontiers in computational neuroscience, 9, 95. doi:10.3389/fncom.2015.00095

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

Paulus, M., Tsalas, N., Proust, J. & Sodian, B. (2014). Metacognitive monitoring of oneself and others: developmental changes during childhood and adolescence. Journal of experimental child psychology, 122, 153-165. doi:10.1016/j.jecp.2013.12.011

Paulus, M., Proust, J. & Sodian, B. (2013). Examining Implicit Metacognition in 3.5-Year-Old Children: An Eye-Tracking and Pupillometric Study. Frontiers in Psychology , 4, 145. doi:10.3389/fpsyg.2013.00145

Pitron, V., Alsmith, A. & de Vignemont, F. (2018). How do the body schema and the body image interact? . Consciousness and Cognition, 65, 352-358. doi:10.1016/j.concog.2018.08.007