Publications

Winkler, M. , Dumont, G., Schöll, E. & Gutkin, B. (2021). Phase response approaches to neural activity models with distributed delay. Bio Cybern. doi:10.1007/s00422-021-00910-9

Dumont, G., Pérez-Cervera, A. & Gutkin, B. (2022). A framework for macroscopic phase-resetting curves for generalised spiking neural networks. Plos Computational Biology. doi:10.1371/journal.pcbi.1010363

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

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

Ghambaryan, A., Gutkin, B., Klucharev, V. & Koechlin, E. (2021). Additively Combining Utilities and Beliefs: Research Gaps and Algorithmic Developments. Frontiers in Neuroscience, . doi:10.3389/fnins.2021.704728

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

Dogonasheva, O., Gutkin, B. & Zakharov, D. (2021). Multistability of coherent states in ring networks of type II neurons with asymmetrical nonlocal inhibitory connectivity. Journal of Computational Neuroscience. doi:10.1016/j.chaos.2021.111541

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

Pérez-Cervera, A. , Gutkin, B., J Thomas, P. & Lindner, B. (2023). A universal description of stochastic oscillators. Proceedings of the National Academy of Sciences of the United States of America, 120(29), e2303222120. doi:10.1073/pnas.2303222120

Dogonasheva, O., Kasatkin, D., Gutkin, B. & Zakharov, D. (2022). Multistability and evolution of chimera states in a network of type II Morris-Lecar neurons with asymmetrical nonlocal inhibitory connections. Chaos (Woodbury, N.Y.), 32(10), 101101. doi:10.1063/5.0117845

Lussange, J., Vrizzi, S., Palminteri, S. & Gutkin, B. (2024). Mesoscale effects of trader learning behaviors in financial markets: A multi-agent reinforcement learning study. PloS one, 19(4), e0301141. doi:10.1371/journal.pone.0301141

Pellegrino, A., Stein, H. & Alex Cayco-Gajic, N. (2024). Dimensionality reduction beyond neural subspaces with slice tensor component analysis. Nature neuroscience, . doi:10.1038/s41593-024-01626-2

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

D Cazé, R., Tran-Van-Minh, A., Gutkin, B. & A Digregorio, D. (2024). Demonstration that sublinear dendrites enable linearly non-separable computations. Scientific reports, 14(1), 18226. doi:10.1038/s41598-024-65866-9

Duriez, A., Bergerot, C., J Cone, J., F Roitman, M. & Gutkin, B. (2023). Homeostatic Reinforcement Theory Accounts for Sodium Appetitive State- and Taste-Dependent Dopamine Responding. Nutrients, 15(4), 1015. doi:10.3390/nu15041015

Bobashev, G., Costenbader, E. & Gutkin, B. (2007). Comprehensive mathematical modeling in drug addiction sciences. Drug and Alcohol Dependence, 89(1), 102-106. doi:10.1016/j.drugalcdep.2006.12.029

Brumberg, J. & Gutkin, B. (2007). Cortical pyramidal cells as non-linear oscillators: Experiment and spike-generation theory. Brain Research, 1171(1), 122-137. doi:10.1016/j.brainres.2007.07.028

Buchin, A., Kerr, C., Huberfeld, G., Miles, R. & Gutkin, B. (2018). Adaptation and Inhibition Control Pathological Synchronization in a Model of Focal Epileptic Seizure. eNeuro, 5(5), 0019-18. doi:10.1523/ENEURO.0019-18.2018

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

Buchin, A., Rieubland, S., Häusser, M., Gutkin, B. & Roth, A. (2016). Inverse Stochastic Resonance in Cerebellar Purkinje Cells. PLoS computational biology, 12(8), e1005000. doi:10.1371/journal.pcbi.1005000

Canavier, C., Evans, R., Oster, A., Pissadaki, E., Drion, G., Kuznetsov, A. & Gutkin, B. (2016). Implications of cellular models of dopamine neurons for disease. Journal of neurophysiology, 116(6), 2815-2830. doi:10.1152/jn.00530.2016

Cayco Gajic, A. & Zylberberg, A. (2021). Good decisions require more than information. Nature Neuroscience, 2', 903-904. doi:10.1038/s41593-021-00883-9

Caze, R., Humphries, M. & Gutkin, B. (2013). Modulation of computational capacity of neurons due to dendritic synaptic interactions. PLoS Comput. Biol., 9(2)

Caze, R., Humphries, M. & Gutkin, B. (2012). Spiking and saturating dendrites differentially expand single neuron computation capacity. , Vol. 13: In Twenty First Annual Computational Neuroscience Meeting: CNS*2012, Decatur, GA, USA.

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

Chalk, M., Gutkin, B. & Denève, S. (2016). Neural oscillations as a signature of efficient coding in the presence of synaptic delays. eLife, . doi:10.7554/eLife.13824

Delorme, C., Salvador, A., Valabrègue, R., Roze, E., Palminteri, S., Vidailhet, M., De Wit, S., Robbins, T., Hartmann, A. & Worbe, Y. (2015). Enhanced habit formation in Gilles de la Tourette syndrome. Brain, 139(2), 605-615. doi:10.1093/brain/awv307

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

Deperrois, N. & Gutkin, B. (2018). Nicotinic and Cholinergic Modulation of Reward Prediction Error Computations in the Ventral Tegmental Area: a Minimal Circuit Model. bioRxiv, 423806. doi:10.1101/423806

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