Publications

Zhang, D., Gao, M., Xu, D., Shi, W., Gutkin, B., Steffensen, S., Lukas, R. & Wu, J. (2012). Impact of prefrontal cortex in nicotine-induced excitation of ventral tegmental area dopamine neurons in anesthetized rats. Journal of Neuroscience, 32(36), 12366-12375. doi:10.1523/JNEUROSCI.5411-11.2012

Zeldenrust, F., De Knecht, S., Wadman, W., Denève, S. & Gutkin, B. (2017). Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series. Frontiers in computational neuroscience, 11, 49. doi:10.3389/fncom.2017.00049

Zeldenrust, F., Gutkin, B. & Denève, S. (2021). Efficient and robust coding in heterogeneous recurrent networks. Plos Computational Biology, 17(4), e1008673. doi:10.1371/journal.pcbi.1008673

Zahle , J., Kaldis , B., Bouvier, A., Roth, P., Montuschi , E., Bohman, J., Turner, S., Wylie, A. & Zamora-Bonilla, J. (2014). Special Issue: Selected Papers From the ENPOSS Meeting, Venice 3-4 September 2013. Philosophy of the Social Sciences, 44(1 )

Zahle , J., Bouvier, A., Kaldis , B., Uebel, T. & Zamora-Bonilla, J. (2013). Special Issue: Papers From the Inaugural Meeting of ENPOSS (European Network for the Philosophy of the Social Sciences), University of Copenhagen, September 21-23, 2012. Philosophy of the Social Sciences, 43(3 )

Ylikoski, P., Bouvier, A., Kaldis , B., Montuschi , E., Zahle , J. & Zamora-Bonilla, J. (2017). Selected Papers from the 5th ENPOSS Meeting, Helsinki, 24-26 August, 2016. Special issue of Philosophy of the Social Sciences.

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

Wexler, M., Duyck, M. & Mamassian, P. (2015). Persistent states in vision break universality and time invariance. Proceedings of the National Academy of Sciences of the United States of America, 112(48), 14990-14995. doi:10.1073/pnas.1508847112

Van Der Groen, O., Van Der Burg, E., Lunghi, C. & Alais, D. (2013). Touch Influences Visual Perception with a Tight Orientation-Tuning. Plos One, 8(11). doi:10.1371/journal.pone.0079558

Vacher, J. , Mamassian, P. & Coen-Cagli, R. (2020). Measuring and Modeling Human Probabilistic Segmentation Maps. Journal of Vision, 20(11), 260. doi:10.1167/jov.20.11.260

Vacher, J. , Davila, A., Kohn, A. & Coen-Cagli, R. (2020). Texture Interpolation for Probing Visual Perception. Advances in Neural Information Processing Systems (Spotlight – top 5%)

Vacher, J. , Mamassian, P. & Coen-Cagli, R. (2019). An Ideal Observer Model for Grouping and Contour Integration in Natural Images. Vision, 48, 88-88

Mamassian, P. & Coen-Cagli, R. (2018). An Ideal Observer Model to Probe Human Visual Segmentation of Natural Images. arXiv

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

Toscani, M. , Mamassian, P. & Valsecchi, M. (2021). Underconfidence in peripheral vision. Journal of Vision, 21(2). doi:10.1167/jov.21.6.2

Toscani, M. , Gegenfurtner, K. , Mamassian, P. & Valsecchi, M. (2019). Under-confidence in peripheral vision. Journal of Vision, 19(10), 67c. doi:10.1167/19.10.67c

Tolu, S., Eddine, R., Marti, F., David, V., Graupner, M., Pons, S., Baudonnat, M., Husson, M., Besson, M., Reperant, C., Zemdegs, J., Pagès, C., Hay, Y., Lambolez, B., Caboche, J., Gutkin, B., Gardier, A., Changeux, J., Faure, P. & Maskos, U. (2013). Co-activation of VTA da and GABA neurons mediates nicotine reinforcement. Molecular Psychiatry, 18(3), 382-393. doi:10.1038/mp.2012.83

Stefanini, F. , A. Kheirbek, M. , Kushnir, L., C. Jimenez, J. , H. Jennings, J. , D. Stuber, G. , Hen, R. & Fusi, S. (2018). A distributed neural code in the dentate gyrus and in CA1. . doi:10.1101/292953

Simeone, O. , Rajendran, B. , Gruning, A. , Eleftheriou, E. , Davies, M. , Denève, S. & Huang, G. (2019). Learning Algorithms and Signal Processing for Brain-Inspired Computing. IEEE Signal Processing Magazine, 36(6), 12-15. doi:10.1109/MSP.2019.2935557

Schweitzer, R. , Watson, T. , Balsdon, T. & Rolfs, M. (2018). From retinal to world-centered perception of intra-saccadic motion streaks: Evidence for high-fidelity eye position information during saccades. , 18(10), 1285

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

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

Remme, M., Lengyel, M. & Gutkin, B. (2015). Trade-off between dendritic democracy and independence in neurons with intrinsic subthreshold membrane potential oscillatio. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Remme, M., Lengyel, M. & Gutkin, B. (2014). Phase Response Methods in Dendritic Dynamics. In Schultheiss et al (eds) (Eds.), Phase Response Cruves in NeuroscienceSpringer

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

Recanatesi, S., Farrell, M., Lajoie, G., Denève, S., Rigotti, M. & Shea-Brown, E. (2018). Signatures and mechanisms of low-dimensional neural predictive manifolds. bioRxiv. doi:10.1101/471987