Publications

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

Sidarus, N., Palminteri, S. & Chambon, V. (2018). Trading off the cost of conflict against expected rewards. Plos Computational Biology, 42809. doi:10.1371/journal.pcbi.1007326

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

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

Domenech, P., Redouté, J., Koechlin, E. & Dreher, J. (2018). The Neuro-Computational Architecture of Value-Based Selection in the Human Brain. Cerebral cortex (New York, N.Y. : 1991), 28(2), 585-601. doi:10.1093/cercor/bhw396

Palminteri, S., Wyart, V. & Koechlin, E. (2017). The Importance of Falsification in Computational Cognitive Modeling. Trends in Cognitive Sciences, 21(6), 425-433. doi:10.1016/j.tics.2017.03.011

Andrade, K., Guieysse, T., Medani, T., Koechlin, E., Pantazis, D. & Dubois, B. (2023). The dual-path hypothesis for the emergence of anosognosia in Alzheimer's disease. Frontiers in neurology, 14. doi:10.3389/fneur.2023.1239057

Maex, R. & Gutkin, B. (2017). Temporal integration and 1/f power scaling in a circuit model of cerebellar interneurons. Journal of neurophysiology, 118(1), 471-485. doi:10.1152/jn.00789.2016

Bouchacourt, F., Palminteri, S., Koechlin, E. & Ostojic, S. (2020). Temporal Chunking as a Mechanism for Unsupervised Learning of Task-Sets. eLife, 9, e50469. doi:10.7554/eLife.50469

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

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

Lussange, J., Vrizzi, S., Bourgeois-Gironde, S., Palminteri, S. & Gutkin, B. (2022). Stock Price Formation: Precepts from a Multi-Agent Reinforcement Learning Model. Comput Econ. doi:10.1007/s10614-022-10249-3

Lazarevich, I. , Prokin, I., Gutkin, B. & Kazantsev, V. (2023). Spikebench: An open benchmark for spike train time-series classification. PLoS computational biology, 19(1), e1010792. doi:10.1371/journal.pcbi.1010792

Muller, L., Brette, R. & Gutkin, B. (2011). Spike-timing dependent plasticity and feed-forward input oscillations produce precise and invariant spike phase-locking. Frontiers in Computational Neuroscience, 15(5), 45. doi:10.3389/fncom.2011.00045

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

Jacquot, A., Eskenazi, T., Sales{-}wuillemin, E., Montalan, B., Proust, J., Grèzes, J. & Conty, L. (2015). Source Unreliability Decreases but Does Not Cancel the Impact of Social Information on Metacognitive Evaluations . Frontiers in Psychology, 6. doi:10.3389/fpsyg.2015.01385

Gurnani, H. & Cayco Gajic, A. (2023). Signatures of task learning in neural representations. Signatures of task learning in neural representations, Current Opinion in Neurobiology,, 83, 102759. doi:10.1016/j.conb.2023.102759

Chalk, M., Masset, P., Denève, S. & Gutkin, B. (2017). Sensory noise predicts divisive reshaping of receptive fields. PLoS computational biology, 13(6), e1005582. doi:10.1371/journal.pcbi.1005582

Novikov, N. & Gutkin, B. (2020). Role of synaptic nonlinearity in persistent firing rate shifts caused by external periodic forcing. PHYSICAL REVIEW E, 101(5), 052408. doi:10.1103/PhysRevE.101.052408

Novikov, N. & Gutkin, B. (2016). Robustness of persistent spiking to partial synchronization in a minimal model of synaptically driven self-sustained activity. Physical review. E, 94(5-1), 052313. doi:10.1103/PhysRevE.94.052313

Dogonasheva, O., Kasatkin, D., Gutkin, B. & Zakharov, D. (2021). Robust universal approach to identify travelling chimeras and synchronized clusters in spiking networks. Chaos, Solitons & Fractals, 153(1), 111541. doi:10.1016/j.chaos.2021.111541

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

Buchin, A., Chizhov, A., Huberfeld, G., Miles, R. & Gutkin, B. (2016). Reduced Efficacy of the KCC2 Cotransporter Promotes Epileptic Oscillations in a Subiculum Network Model. The Journal of Neuroscience, 36(46), 11619--11633. doi:10.1523/JNEUROSCI.4228-15.2016

Completo Guerreiro, I., Gu, Z., Yakel, J. & Gutkin, B. (2022). Recurring Cholinergic Inputs Induce Local Hippocampal Plasticity through Feedforward Disinhibition. eNeuro. doi:10.1523/ENEURO.0389-21.2022

Maex, R., Budygin, E., Grinevich, V., Bencherif, M. & Gutkin, B. (2014). Receptor activation and desensitization as mechanisms for a7 regulation of dopamine response to nicotine. Chemical Neuroscience , 15(10), 1032-40. doi:10.1021/cn500126t

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

Romagnoni, A. , Colonnese, M. , Touboul, J. & Gutkin, B. (2020). Progressive alignment of inhibitory and excitatory delay may drive a rapid developmental switch in cortical network dynamics. J. of Neurophysiology, 123(5), 1583-1599. doi:10.1152/jn.00402.2019

Rouault, M., Drugowitsch, J. & Koechlin, E. (2019). Prefrontal mechanisms combining rewards and beliefs in human decision-making. Nature Communications, 10, 301. doi:10.1038/s41467-018-08121-w

Koechlin, E. (2018). Prefrontal function and cognitive control: from action to language. Current Opinion in Behavioral Sciences, 21, 106-111. doi:10.1016/j.cobeha.2018.03.008

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