My interests focus on computational and mathematical neuroscience. My research has focused on modelling brain circuit dynamics, neuromodulation, motivated behavior, addiction, machine learning.
Field of research
My work bears on different themes in computational and mathematical neuroscience, the underlying
principle guiding my research is to use the tools of mathematical and computational analysis to build mechanistic links across scales of neuronal organization: from the dynamics of brain cells, circuits and networks to cognitive function and to bring a coherent synthesis to the multitude of collected, and at times disparate, data.
Throughout my career, I have been particularly interested in neuromodulatory processes and how they shape (and misshape) neuronal dynamics, impacting neural systems functions and cognition. I have been studying the influence of endogenous neuromodulators (e.g. Ach and DA) on neuronal dynamics and their role in cognition (working memory, decision making, learning) as well as exogenous substances that usurp and hijack brain system to produce large scale pathologies: e.g. addiction to drugs such as nicotine, cocaine, alcohol.
My research builds multi-scale mathematical models to analyze the dynamics and the functions of neural structures: from cells to circuits to cognition and behavior.
Linking single cell level to function I strive to understand the impact of neuromodulatory processes on the cellular excitability and its implication for circuit computations, such we grid cell formation
Linking the circuit level to large scale networks and cognitive function, I study the dynamics of collective behaviors that arise as a consequence of the cell dynamics: emergent synchronization, cortical signal processing/coding and the sustained activity in working memory.
Linking physiology to the behavioral level study the dynamics of motivated decision making learning and its relationship to homeostatic processes.
I am keenly interested in probing the mechanisms for brain disorders, notably the progression to addiction, schizophrenia and Alzheimer’s disease, focusing on nicotinic neuromodulation.
Publications
Rooy M, Lazarevich I, Koukouli F, Maskos U, Gutkin B.S. (2021) Cholinergic modulation of hierarchical inhibitory control over cortical resting state dynamics: Local circuit modeling of schizophrenia-related hypofrontality, Current Research in Neurobiology, 100018, ISSN 2665-945X, 10.1016/j.crneur.2021.100018
Zeldenrust F, Gutkin B, Denéve S (2021) Efficient and robust coding in heterogeneous recurrent networks. PLoS Comput Biol 17(4): e1008673. https://doi.org/10.1371/journal.pcbi.1008673
Novikov, N and Gutkin B. (2020) Role of synaptic nonlinearity in persistent firing rate shifts caused by external periodic forcing. Phys. Rev. E 101(5): 052408}, doi:10.1103/PhysRevE.101.052408.
Romagnoni A, Colonese, M, Touboul J and Gutkin B (2020) Progressive Alignment of Inhibitory and Excitatory Delay May Drive a Rapid Developmental Switch in Cortical Network Dynamics, J. Neurophys, 123(5):1583-1599. doi: 10.1152/jn.00402.2019.
Lussange, J., Lazarevich, I., Bourgeois-Gironde, S. Palminteri, S. & Gutkin, B. (2020) Modelling Stock Markets by Multi-agent Reinforcement Learning. Comput Econ. doi: 10.1007/s10614-020-10038-w
Gu Z., Smith K.G., Alexander G. M., Guerreiro I., Dudek S.M., Gutkin, B.,Jensen P. Yakkel J.L. (2020) Hippocampal interneuronal α7 nAChRs modulate theta oscillations in freely moving mice. Cell Reports 31, 107740. doi: 10.1016/j.celrep.2020.107740
Dumont G, Gutkin B (2019) Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits. PLOS Computational Biology 15(5): e1007019.
Koukouli F, Rooy M, Tziotis D, Sailor KA, O'Neill HC, Levenga J, Witte M, Nilges M, Changeux JP, Hoeffer CA, Stitzel JA, Gutkin BS, DiGregorio DA, Maskos U.. (2017) Nicotine reverses hypofrontality in animal models of addiction and schizophrenia. Nature Medicine doi: 10.1038/nm.4274.
Chalk M, Gutkin B, Denève S.(2016) Neural oscillations as a signature of efficient coding in the presence of synaptic delays, Elife. 2016 Jul 7;5. pii: e13824
Buchin A, Chizhov A, Huberfeld G, Miles R, Gutkin BS. (2016) Reduced Efficacy of the KCC2 Cotransporter Promotes Epileptic Oscillations in a Subiculum Network Model. J Neurosci. 36(46):11619-1163. doi: 0.1523/JNEUROSCI.4228-15.2016
A Hyafil, L Fontolan, AL Giraud, B Gutkin (2015) Neural cross-frequency coupling: connecting architectures, mechanisms and functions. Trends in Neurosciences 8(11):725-40.doi: 10.1016/j.tins.2015.09.001
Keramati M,Gutkin B.S. (2015) Homeostatic reinforcement learning for integrating reward collection and physiological stability eLife doi: 10.7554/eLife.04811
Dipoppa M and Gutkin B.S. (2013) Flexible frequency control of cortical oscillations enables computations required for working memory PNAS 110(31):12828-33.
Remme M, Lengyel M, Gutkin B.S. 2010 Democracy-independence trade-off in oscillating dendrites and its implications for grid cells. Neuron 66(3):429-37.
Gutkin BS, Dehaene S & Changeux J-P. 2006 Neuro-computational Hypotesis for Nicotine Addiction. PNAS 24:1106-11. doi: 10.1073/pnas.0510220103