Publications

Mamassian, P. (2020). Confidence Forced-Choice and Other Metaperceptual Tasks. , 49(6), 616-635. doi:10.1177/0301006620928010

Lunghi, C. & Alais, D. (2015). Congruent tactile stimulation reduces the strength of visual suppression during binocular rivalry. Scientific Reports, 5. doi:10.1038/srep09413

Rahnev, D., Balsdon, T., Charles, L., de Gardelle, V., Denison, R., Desender, K., Faivre, N., Filevich, E., Fleming, S., Jehee, J., Lau, H., Lee, A., Locke, S., Mamassian, P., Odegaard, B., Peters, M., Reyes, G., Rouault, M., Sackur, J., Samaha, J., Sergent, C., Sherman, M., Siedlecka, M., Soto, D., Vlassova, A. & Zylberberg, A. (2022). Consensus goals for the field of visual metacognition. Perspectives on Psychological Science, . doi:10.1177/17456916221075615

Hansmann-Roth, S., Pont, S. & Mamassian, P. (2018). Contextual effects in human gloss perception. Electronic Imaging(14), 1-7

Hansmann-Roth, S., Pont, S. & Mamassian, P. (2017). Contextual effects on real bicolored glossy surfaces. Journal of Vision, 17(2):17, 1-13. doi:10.1167/17.2.17

Jovanovic, L. , López‐Moliner, J. & Mamassian, P. (2021). Contrasting contributions of movement onset and duration to self‐evaluation of sensorimotor timing performance. European Journal of Neuroscience, 54(3), 5092-5111. doi:10.1111/ejn.15378

Tran-Van-Minh, A., Caze, R., Abrahamsson, T., Cathala, L., Gutkin, B. & Digregorio, D. (2015). Contribution of sublinear and supralinear dendritic integration to neuronal computations. Frontiers in cellular neuroscience, 9, 67. doi:10.3389/fncel.2015.00067

Morozova, E., Myroshnychenko, M., Zakharov, D., Di Volo, M., Gutkin, B., Lapish, C. & Kuznetsov, A. (2016). Contribution of synchronized GABAergic neurons to dopaminergic neuron firing and bursting. Journal of neurophysiology, 116(4), 1900-1923. doi:10.1152/jn.00232.2016

Ponsot, E., Déjardin, H. & Roncière, E. (2016). Controlling Programme Loudness in Individualized Binaural Rendering of Multi-Channel Audio Contents. , Vol. 140: In Audio Engineering Society .

Dipoppa, M., Szwed, M. & Gutkin, B. (2016). Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony. Advances in cognitive psychology, 12(4), 209-232. doi:10.5709/acp-0199-x

Dipoppa, M. & Gutkin, B. (2013). Correlations in background activity control persistent state stability and allow execution of working memory tasks. Frontiers in Computational Neuroscience, 7, 139. doi:10.3389/fncom.2013.00139

Wu, J., Gao, M., Shen, J., Shi, W., Oster, A. & Gutkin, B. (2013). Cortical control of VTA function and influence on nicotine reward. Biochemical Pharmacology, 86(8), 1173-1180. doi:10.1016/j.bcp.2013.07.013

Brumberg, J. & Gutkin, B. (2007). Cortical pyramidal cells as non-linear oscillators: Experiment and spike-generation theory. Brain Research, 1171(1), 122-137. doi:10.1016/j.brainres.2007.07.028

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

Volk, D., Dubinin, I., Gutkin, B., Myasnikova, A. & Nikulin, V. (2018). Cross-Frequency Synchrony Analysis. Frontiers in Neuroinformatics , 12, 72. doi:10.3389/fninf.2018.00072

Klever, L. , Christin Beyvers, M., Fiehler, K., Mamassian, P. & Billino, J. (2023). Cross-modal metacognition: Visual and tactile confidence share a common scale. Journal of vision, 23(5), 3. doi:10.1167/jov.23.5.3

Lenglet, T. , Mirault, J. , Veyrat-Masson, M. , Funkiewiez, A. , Amador, M. , Bruneteau, G. , Le Forestier, N. , Pradat, P. , Salachas, F. , Vacher, Y. , Lacomblez, L. & Lorenceau, J. (2019). Cursive Eye-Writing With Smooth-Pursuit Eye-Movement Is Possible in Subjects With Amyotrophic Lateral Sclerosis. Front Neurosci, 13, 538. doi:10.3389/fnins.2019.00538

Neri, P. (2022). Deep networks may capture biological behavior for shallow, but not deep, empirical characterizations Author links open overlay panel. Neural Networks, 152, 244-266. doi:10.1016/j.neunet.2022.04.023

Remme, M., Lengyel, M. & Gutkin, B. (2010). Democracy-independence trade-off in oscillating dendrites and its implications for grid cells. Neuron, 66(3), 429-437. doi:10.1016/j.neuron.2010.04.027

Caze, R., Humphries, M. & Gutkin, B. (2013). Dendrites enhance both single neuron and network computation. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Gekas, N., Mcdermott, K. & Mamassian, P. (2019). Disambiguating serial effects of multiple timescales. Journal of Vision, 19(6), 24-24. doi:10.1167/19.6.24

Morozova, E., Faure, P., Gutkin, B., Lapish, C. & Kuznetsov, A. (2020). Distinct Temporal Structure of Nicotinic ACh Receptor Activation Determines Responses of VTA Neurons to Endogenous ACh and Nicotine. eNeuro, 7(4). doi:10.1523/ENEURO.0418-19.2020

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

Gruber, A., Dayan, P., Gutkin, B. & Solla, S. (2006). Dopamine modulation in the basal ganglia locks the gate to working memory. Journal of Computational Neuroscience, 20(2), 153-166. doi:10.1007/s10827-005-5705-x

Morozova, E., Zakharov, D., Gutkin, B., Lapish, C. & Kuznetsov, A. (2016). Dopamine Neurons Change the Type of Excitability in Response to Stimuli. PLoS computational biology, 12(12), e1005233. doi:10.1371/journal.pcbi.1005233

Kuznetsov, A. & Gutkin, B. (2015). Dopaminergic cell Models. The Encyclopedia of Computational Neuroscience (pp. 2958-2965).

Dumont, G., Maex, R. & Gutkin, B. (2018). Dopaminergic Neurons in the Ventral Tegmental Area and Their Dysregulation in Nicotine Addiction. In Alan Anticevic and John D. Murray (Eds.), Computational Psychiatry: Mathematical Modeling of Mental Illness (pp. 47-84). doi:10.1016/B978-0-12-809825-7.00003-1

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

Graupner, M. & Gutkin, B. (2012). Dynamical Approaches to understanding cholinergic control of nicotine action pathways in the dopaminergic reward circuits. Computational Neuroscience of Drug Addiction (Springer ed.).Ahmed and Gutkin (eds.)

Di Volo, M., Morozova, E., Lapish, C., Kuznetsov, A. & Gutkin, B. (2018). Dynamical ventral tegmental area circuit mechanisms of alcohol‐dependent dopamine release. European Journal of Neuroscience, Special issue article. doi:10.1111/ejn.14147