Publications

Denève, S., Alemi, A. & Bourdoukan, R. (2017). The Brain as an Efficient and Robust Adaptive Learner. Neuron, 94(5), 969-977. doi:10.1016/j.neuron.2017.05.016

Deperrois, N., Moiseeva, V. & Gutkin, B. (2019). Minimal Circuit Model of Reward Prediction Error Computations and Effects of Nicotinic Modulations. Frontiers in neural circuits, 12, 116. doi:10.3389/fncir.2018.00116

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

Dipoppa, M. & Gutkin, B. (2013). Flexible frequency control of cortical oscillations enables computations required for working memory. Proceedings of the National Academy of Sciences of the United States of America, 110(31), 12828-12833. doi:10.1073/pnas.1303270110

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

Dipoppa, M., Krupa, M., Torcini, A. & Gutkin, B. (2012). Marginally Stable States and Quasi-periodic minor attractors in excitable pulse-coupled networks. SIADS , 63(1), 62-97

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

Dumont, G. & Gutkin, B. (2019). Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits. PLOS Computational Biology . doi:10.1371/journal.pcbi.1007019

Dumont, G., Ermentrout, G. & Gutkin, B. (2017). Macroscopic phase-resetting curves for spiking neural networks. Physical review. E, 96, 042311. doi:10.1103/PhysRevE.96.042311

Fontolan, L., Krupa, M., Hyafil, A. & Gutkin, B. (2013). Analytical insights on theta-gamma coupled neural oscillators. Journal of Mathematical Neuroscience, 3(1), 1-20. doi:10.1186/2190-8567-3-16

Giulio, B., Thomas, D., Brice, B. & Ostojic, S. (2021). Network dynamics underlying OFF responses in the auditory cortex. eLife, 10, e53151. doi:10.7554/eLife.53151

Graupner, M., Wallisch, P. & Ostojic, S. (2019). Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate. Journal of Neuroscience , 36 (44), 11238-11258. doi:10.1523/JNEUROSCI.0104-16.2016

Graupner, M., Maex, R. & Gutkin, B. (2013). Endogenous Cholinergic Inputs and Local Circuit Mechanisms Govern the Phasic Mesolimbic Dopamine Response to Nicotine. PLoS Computational Biology, 9(8). doi:10.1371/journal.pcbi.1003183

Gu, Z., Smith, K. , Loukatou, G., Completo Guerreiro, I., Dudek, S. , Gutkin, B., Jensen, P. & Yakel, J. (2020). Hippocampal Interneuronal α7 nAChRs Modulate Theta Oscillations in Freely Moving Mice . Cell Reports, 31(10), 107740. doi:10.1016/j.celrep.2020.107740

Gutierrez, G. & Denève, S. (2018). Population adaptation in efficient balanced networks. eLife, 8, e46926. doi:10.7554/eLife.46926

Gutkin, B., Braun, P., Akila, M., Waltner, D. & Guhr, T. (2020). Exact local correlations in kicked chains. Phys. Rev. B, 102, 174307. doi:10.1103/PhysRevB.102.174307

Hyafil, A., Fontolan, L., Kabdebon, C., Gutkin, B. & Giraud, A. (2015). Speech encoding by coupled cortical theta and gamma oscillations. eLife, 4, 1-45. doi:10.7554/eLife.06213

Hyafil, A., Giraud, A., Fontolan, L. & Gutkin, B. (2015). Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions. Trends in neurosciences, 38(11), 725-40. doi:10.1016/j.tins.2015.09.001

Jardri, R. & Denève, S. (2017). [Jumping-to-conclusions in schizophrenia is mediated by circular inference]. Medecine sciences : M/S, 33(11), 933-935. doi:10.1051/medsci/20173311006

Jardri, R., Duverne, S., Litvinova, A. & Denève, S. (2017). Experimental evidence for circular inference in schizophrenia. Nature communications, 8, 14218. doi:10.1038/ncomms14218

Jardri, R., Leptourgos, P., Bouttier, V. & Denève, S. (2020). Circular Inference and Hallucinations. Biological Psychiatry, 87(9), S41-S42. doi:10.1016/j.biopsych.2020.02.131

Jedlicka, P., Deller, T., Gutkin, B. & Backus, K. (2011). Activity-dependent intracellular chloride accumulation and diffusion controls GABA(A) receptor-mediated synaptic transmission. Hippocampus, 21(8), 885-98. doi:10.1002/hipo.20804

Keramati, M. & Gutkin, B. (2014). Homeostatic reinforcement learning for integrating reward collection and physiological stability. eLife, 3. doi:10.7554/eLife.04811

Keramati, M. & Gutkin, B. (2011). A Reinforcement Learning Theory for Homeostatic Regulation. NIPS, .

Keramati, M., Durand, A., Girardeau, P., Gutkin, B. & Ahmed, S. (2017). Cocaine addiction as a homeostatic reinforcement learning disorder. Psychological review, 124(2), 130-153. doi:10.1037/rev0000046

Keramati, M., Ahmed, S. & Gutkin, B. (2017). Misdeed of the need: towards computational accounts of transition to addiction. Current opinion in neurobiology, 46, 142-153. doi:10.1016/j.conb.2017.08.014

Kim , K., Ladenbauer, J., Babo-Rebelo, M., Buot, A., Kehongre , K., Adam, C., Hasboun, D., Lambrecq , V., Navarro , V., Ostojic, S. & Tallon-Baudry, C. (2019 ). Resting-state neural firing is linked to cardiac cycle duration in the human cingulate and parahippocampal cortices. Journal of Neuroscience , 39(19), 3676-3686. doi:10.1523/JNEUROSCI.2291-18.2019

Koren, V. & Denève, S. (2017). Computational Account of Spontaneous Activity as a Signature of Predictive Coding. PLoS computational biology, 13(1), e1005355. doi:10.1371/journal.pcbi.1005355

Koukouli, F., Rooy, M., Tziotis, D., Sailor, K., O'Neill, H., Levenga, J., Witte, M., Nilges, M., Changeux, J., Hoeffer, C., Stitzel, J., Gutkin, B., Digregorio, D. & Maskos, U. (2017). Nicotine reverses hypofrontality in animal models of addiction and schizophrenia. Nature medicine, 23(3), 347-354. doi:10.1038/nm.4274

Krupa, M., Gutkin, B. & Zakharov, D. (2020). Modeling dopaminergic modulation of clustered gamma rhythms. Communications in Nonlinear Science and Numerical Simulation, 82(105086), 1-10. doi:10.1016/j.cnsns.2019.105086