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

Zamani, A. , Novikov, N. & Gutkin, B. (2020). Concomitance of inverse stochastic resonance and stochastic resonance in a minimal bistable spiking neural circuit. Communications in Nonlinear Science and Numerical Simulation, 82, 105024. doi:10.1016/j.cnsns.2019.105024

Zakharov, D., Krupa, M., Gutkin, B. & Kuznetsov, A. (2018). High-frequency forced oscillations in neuronlike elements. Physical Review E , 97(6). doi:10.1103/PhysRevE.97.062211

Zakharov, D., Lapish, C., Gutkin, B. & Kuznetsov, A. (2016). Synergy of AMPA and NMDA Receptor Currents in Dopaminergic Neurons: A Modeling Study. Frontiers in computational neuroscience, 10, 48. doi:10.3389/fncom.2016.00048

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

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

Vilarem, E., Armony, J. & Grèzes, J. (2019). Action opportunities modulate attention allocation under social threat. Emotion. doi:10.1037/emo0000598

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

Van Den Stock, J., Tamietto, M., Sorger, B., Pichon, S., Grèzes, J. & De Gelder, B. (2011). Cortico-subcortical visual, somatosensory, and motor activations for perceiving dynamic whole-body emotional expressions with and without striate cortex (V1). Proceedings of the National Academy of Sciences of the United States of America, 108(39), 16188-93. doi:10.1073/pnas.1107214108

Van Den Stock, J., Peretz, I., Grèzes, J. & De Gelder, B. (2009). Instrumental music influences recognition of emotional body language. Brain topography, 21(3-4), 216-20. doi:10.1007/s10548-009-0099-0

Van De Riet, W., Grèzes, J. & De Gelder, B. (2009). Specific and common brain regions involved in the perception of faces and bodies and the representation of their emotional expressions. Social neuroscience, 4(2), 101-20. doi:10.1080/17470910701865367

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

Udden, J. , Martins, M. , Zuidema, W. & Tecumseh Fitch, W. (2019). Hierarchical Structure in Sequence Processing: How to Measure It and Determine Its Neural Implementation. Topics in Cognitive Science . doi:10.1111/tops.12442

Tuckwell, H., Jost, J. & Gutkin, B. (2009). Inhibition and modulation of rhythmic neuronal spiking by noise. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 80(3). doi:10.1103/PhysRevE.80.031907

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

Ting, C. , Palminteri, S., Engelmann, J. & Lebreton, M. (2020). Robust valence-induced biases on motor response and confidence in human reinforcement learning. Cognitive, Affective, & Behavioral Neuroscience, . doi:10.3758/s13415-020-00826-0

Ting, C. , Palminteri, S., Engelmann, J. & Lebreton, M. (2019). Decreased confidence in loss-avoidance contexts is a primary meta-cognitive bias of human reinforcement learning. bioRxiv. doi:10.1101/593368

Tegnér, J., Compte, A., Auffray, C., An, G., Cedersund, G., Clermont, G., Gutkin, B., Oltvai, Z., Stephan, K., Thomas, R. & Villoslada, P. (2009). Computational disease modeling - Fact or fiction? BMC Systems Biology, 3. doi:10.1186/1752-0509-3-56

Stiefel, K., Gutkin, B. & Sejnowski, T. (2008). Cholinergic neuromodulation changes phase response curve shape and type in cortical pyramidal neurons. PLoS ONE, 3(12). doi:10.1371/journal.pone.0003947

Sperber, D. & Mercier, H. (2017). The Enigma of Reason .

Soussignan, R., Chadwick, M., Philip, L., Conty, L., Dezecache, G. & Grèzes, J. (2013). Self-relevance appraisal of gaze direction and dynamic facial expressions: Effects on facial electromyographic and autonomic reactions. Emotion, 13(2), 330-337. doi:10.1037/a0029892

Skvortsova , V., Palminteri, S., Buot, A., Karachi, C., Welter, M., Grabli, D. & Pessiglione, M. (2020). A Causal Role for the Pedunculopontine Nucleus in Human Instrumental Learning. Current Biology, 31(5). doi:10.1016/j.cub.2020.11.042