Publications

Dumont, G. & Gutkin, B. (2018). Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits. arXiv , 1812.03455

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

Dumont, G., Payeur , A. & Longtin , A. (2017). A stochastic-field description of finite-size spiking neural networks. PLoS Comput Biol, 13(8), e1005691. doi:10.1371/journal.pcbi.1005691

Duverne, S. & Koechlin, E. (2017). Rewards and Cognitive Control in the Human Prefrontal Cortex. Cerebral cortex (New York, N.Y. : 1991), 27(10), 5024-5039. doi:10.1093/cercor/bhx210

Findling, C., Chopin, N. & Koechlin, E. (2021). Imprecise neural computations as a source of adaptive behaviour in volatile environments. Nature Human Behaviour , 5, 99-112. doi:10.1038/s41562-020-00971-z

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

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.)

Graupner, M., Wallisch, P. & Ostojic, S. (2016). Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate. The Journal of Neuroscience, 36(44), 11238-11258. doi:10.1523/JNEUROSCI.0104-16.2016

Graupner, M. & Gutkin, B. (2009). Modeling nicotinic neuromodulation from global functional and network levels to nAChR based mechanisms. Acta Pharmacologica Sinica, 30(6), 681-693. doi:10.1038/aps.2009.87

Graupner, M., Ahmed, S. & Gutkin, B. (2009). Modelling dynamics of addiction. Pharmacopsychiatry, 42(Suppl 1), S144-52

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

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

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

Gutkin, B. & Ahmed, S. (2012). Computational Neuroscience of Drug Addiction.

Gutkin, B. (2015). Theta-neurons. In Springer Verlag (Eds.), Encyclopedia of Comptutational Neuroscience (pp. 1034-1042).

Gutkin, B. & Ermentrout, G. (2006). Neuroscience: Spikes too kinky in the cortex? Nature, 440(7087), 999-1000. doi:10.1038/440999a

Gutkin, B., Dehaene, S. & Changeux, J. (2006). A neurocomputational hypothesis for nicotine addiction. Proceedings of the National Academy of Sciences of the United States of America, 103(4), 1106-1111. doi:10.1073/pnas.0510220103

Gutkin, B., Jost, J. & Tuckwell, H. (2008). Random perturbations of spiking activity in a pair of coupled neurons. Theory in Biosciences, 127(2), 135-139. doi:10.1007/s12064-008-0039-7

Gutkin, B., Jost, J. & Tuckwell, H. (2008). Transient termination of spiking by noise in coupled neurons. EPL, 81(2). doi:10.1209/0295-5075/81/20005

Gutkin, B., Tuckwell, H. & Jost, J. (2009). The Phenomenon of Inverse Stochastic Resonance. Naturwissenschaften, 96(9), 1091-7

Gutkin, B. & Stiefel, K. (2007). Phase-resetting curves and neuromodulation of action potential dynamics in the cortex. (Vol. 40, pp. 14-15).

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

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

Jeong, H. & Gutkin, B. (2007). Synchrony of neuronal oscillations controlled by GABAergic reversal potentials. Neural Computation, 19(3), 706-729. doi:10.1162/neco.2007.19.3.706

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, .