Boris Gutkin

Theoretical Neuroscience Group

Leading Research Fellow:Institute of Cognitive Neuroscience / Centre for Cognition & Decision Making

Boris Gutkin has been at HSE University since 2013.

Education and Degrees

1999
PhD
University of Pittsburgh
1992
Master's
North Carolina State University

Student Term / Thesis Papers

Master
A. Kuptsova «Biologically-Inspired Neurocomputational Model of Semantic Dementia». Institute of Cognitive Neuroscience, 2020
A. Zamani mozafarabadi «Robustness of Persistent Firing in a Minimal Recurrent Network of Working Memory». Faculty of Social Sciences, 2017
J. Rawski «Homeostasis in Harmonic Grammar». Faculty of Social Sciences, 2016

Full list of of student term / thesis papers

Courses (2019/2020)

Advanced Computational Neuroscience (Master’s programme; Institute of Cognitive Neuroscience; 2 year, 1, 2 module)Eng
Past Courses

Courses (2015/2016)

Computational Neuroscience (Master’s programme; Faculty of Social Sciences; 2 year, 1, 2 module)Eng

Grants

Current:

NSF Grant: Oscillations in Working Memory: coordinator (18Ml Rubles)

PSL* (Paris) Structural grant: coordinator/ PI (value 100 K Euros)

CRCNS-ANR “GABA”/ NIH (NIAAA) RO1: France coordinator/PI (total value 600 K Euros)

ANR Blanc “Cerebcomp” : co-PI, team leader (total value 140 K Euros)

Completed:

ANR Blanc “Neurobot” 2010-2014: team leader/ co-PI (value 100K)

BION Tempus EACEA: France training site leader (total value 1,100 K Euros)

ENP Collaborative Grant (PI): value 200K Euros

NeuroIC 2010 Collaborative Grant (PI): value 24K

ANR 2009 MNP “Dopanic” Team Leader (co-PI): value 120K

NERF Grant 2009, 2010: value 120K

EU MEXT BIND (project coordinator, 2006-2010) value 1,100 K Euros

Alliance UK-France collaboration award (2006-7 and 2010-2012)

EU BACS Integrated Project (work-package deputy leader, 2007-2010), value 300 K Euros

ANR Blanc 2005 “Cognitive” Team Leader value 30 K Euros

NIH/NIDDK SBIR grants (co-PI) “Interactive tools for diabetic children” 1997-1999 value:190 K USD

IBRO award, NATO award, NSF(USA) award for Les Houches 2003; 25 K Euros

NSF Bioinformatics Graduate Fellowship 1999-2002 value: 150 K USD

Publications

2013⁶

Article Fontolan L., Krupa M., Hyafil A., Gutkin B. Analytical insights on theta-gamma coupled neural oscillators // Journal of Mathematical Neuroscience. 2013. Vol. 3. No. 1
Article Dipoppa M., Gutkin B. Correlations in background activity control persistent state stability and allow execution of working memory tasks // Front Comput Neurosci. 2013. Vol. 7. No. 139
Article Keramati M., Gutkin B. Drug dominated dopamine circuits spiral addicts into a cognitive behavioral conflict. // Plos One. 2013. Vol. 8. No. 4
Article Graupner M., Maex R., Gutkin B. Endogenous cholinergic inputs and local circuit mechanisms govern the phasic mesolimbic dopamine response to nicotine // PLoS Computational Biology. 2013. Vol. 9. No. 8
Article Dipoppa M., Gutkin B. 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. 2013. Vol. 110. No. 31. P. 12828-33.
Article Cazé R. D., Humphries M., Gutkin B. Passive Dendrites Enable Single Neurons to Compute Linearly Non-separable Functions // PLoS Computational Biology. 2013. Vol. 9. No. 2

2014⁹

Article Krupa M., Gielen S., Gutkin B. Adaptation and shunting inhibition leads to pyramidal/interneuron gamma with sparse firing of pyramidal cells. // Journal of Computational Neuroscience. 2014. Vol. 37. No. 2. P. 357-376. doi
Article Tolu S., Eddine F., Marti F., David F., Graupner M., Pons S., Baudonat M., Besson M., Reperant C., Zembegs J., Pages C., Caboche J., Gutkin B., Gardier A., Changeux J., Faure P., Maskos U. Co-activation of VTA DA and GABA neurons mediates nicotine reinforcement // Molecular Psychiatry. 2014. Vol. 18. No. 3. P. 382-393.
Preprint Keramati M., Gutkin B. Collecting reward to defend homeostasis: A homeostatic reinforcement learning theory / Cold Spring Harbor Laboratory. Series 005140 "Biorxiv". 2014.
Preprint Gutkin B., Keramati M. Collecting reward to defend homeostasis: A homeostatic reinforcement learning theory / Cold Spring Harbor Laboratory. Series код не известен, зарубежная публикация "the preprint server for biology". 2014. doi (in press)
Article Keramati M., Gutkin B. Homeostatic reinforcement learning for integrating reward collection and physiological stability. // eLife. 2014. Vol. 2. No. 3
Preprint Oster A., Faure P., Gutkin B. Mechanisms for multiple activity modes of VTA dopamine neurons / Cold Spring Harbor Laboratory. Series http://dx.doi.org/ "BioRxiv". 2014. No. 10.1101/008920.
Article Maex R., Budygin E., Grinevich V., Bencherif M., Gutkin B. Receptor activation and desensitization as mechanisms for a7 regulation of dopamine response to nicotine // ACS Chemical Neuroscience. 2014. Vol. 15. No. 5(10). P. 1032-40. (in press)
Article Zeldenrust F., Gutkin B. Spike Frequency Adaptation // Scholarpedia. 2014. Vol. 9. No. 2. P. 30643.
Article Maex R., Grinevich V., Grinevich V., Budygin E., Bencherif M., Gutkin B. Understanding the role α7 nicotinic receptors play in dopamine efflux in nucleus accumbens // ACS Chem Neurosci. 2014. Vol. 15. No. 5. P. 1032-1040.

2015⁸

Article McDonnell M., Iannella N., To M., Tuckwell H., Jost J., Gutkin B., Ward L. A review of methods for identifying stochastic resonance in simulations of single neuron models // Network: Computation in Neural Systems. 2015. Vol. 26. No. 2. P. 35-71. doi
Article Morozova E., Myroshnychenko M., Rooy M. E., Gutkin B., Lapish C., Kuzntesov A. A role of local VTA GABAergic neurons in mediating dopamine neuron response to nicotine // BMC Neuroscience. 2015. Vol. 16. No. 1. P. 137. doi
Preprint Gutkin B., Keramati M., Girardeau P., Durand A., Ahmed S. An integrated homeostatic reinforcement learning theory of motivation explains the transition to cocaine addiction / Cold Spring Harbor Laboratory. Series код неизвестен, зарубежная публикация "the preprint server for biology". 2015. doi (in press)
Article Tran-Van-Minh A., Cazé R. D., Abrahamsson T., Cathala L., Gutkin B., DiGregorio D. A. Contribution of sublinear and supralinear dendritic integration to neuronal computations // Frontiers in Cellular Neuroscience. 2015. Vol. 9. No. March, Article number 67 doi
Article Oster A., Faure P., Gutkin B. Mechanisms for multiple activity modes of VTA dopamine neurons // Frontiers in Computational Neuroscience. 2015. Vol. 9. No. JULY, Article number 95 doi
Article Gutkin B., Hyafil A., Giraud A., Fontolan L. Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions // Trends in Neuroscience and Education. 2015. Vol. 38. No. 11. P. 725-740. doi
Preprint Gutkin B., Chalk M., Deneve S. Neural oscillations as a signature of efficient coding in the presence of synaptic delays / Cold Spring Harbor Laboratory. Series Код не известен, зарубежная публикация "the preprint server for biology". 2015. doi (in press)
Article Hyafil A., Fontolan L., Kabdebon C., Gutkin B., Giraud A. Speech encoding by coupled cortical theta and gamma oscillations // eLife. 2015. No. 4. P. 1-45. doi

2016¹¹

Article Morozova E., Myroshnychenko M., di Volo M., Zakharov D., Lapish C., Gutkin B., Kuznetsov A. Contribution of synchronized GABAergic neurons to dopaminergic neuron firing and bursting // Journal of Neurophysiology. 2016. Vol. 116. No. 4. P. 1900-1923. doi
Article Dipoppa M., Szwed M., Gutkin B. Controlling working memory operations by selective gating: The roles of oscillations and synchrony // Advances in Cognitive Psychology. 2016. No. 12(4). P. 209-232. doi
Article Morozova E. O., Zakharov D., Gutkin B., Lapish C. C., Kuznetsov A. Dopamine Neurons Change the Type of Excitability in Response to Stimuli // PLoS Computational Biology. 2016 doi
Article Morozova E., Zakharov D., Gutkin B., Lapish C., Kuznetsov A. Dopamine neurons change the type of excitability in response to stimuli // PLoS Computational Biology. 2016. Vol. 12. No. 12. P. e1005233-1-e1005233-36. doi
Article Gutkin B., Canavier C., Evans R., Oster A., Pissadaki E., Drion G., Kuznetsov A. Implications of cellular models of dopamine neurons for disease. // Journal of Neurophysiology. 2016 doi
Article Gutkin B., Roth A., Buchin A., Hausser M. Inverse Stochastic Resonance in Cerebellar Purkinje Cells // PLoS Computational Biology. 2016 doi
Article Gutkin B., Chalk M., Deneve S. Neural oscillations as a signature of efficient coding in the presence of synaptic delays // eLife. 2016. Vol. 7. No. 6. P. 1-11. doi
Article Buchin A., Chizov A., Huberfeld G., Miles R., Gutkin B. Reduced efficacy of the KCC2 cotransporter promotes epileptic oscillations in a subiculum network model // Journal of Neuroscience. 2016. Vol. 36. No. 46. P. 11619-11633. doi
Article Novikov N., Gutkin B. Robustness of persistent spiking to partial synchronization in a minimal model of synaptically driven self-sustained activity // Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. 2016. Vol. 94. No. 5. P. 052313-1-052313-13. doi
Article Gutkin B., Lapish C., Kuznetsov A., Zakharov D. Synergy of AMPA and NMDA Receptor Currents in Dopaminergic Neurons: A Modeling Study. // Frontiers in Computational Neuroscience. 2016. Vol. 10. No. 48 doi
Article Zakharov D., Lapish C., Gutkin B., Kuznetsov A. Synergy of AMPA and NMDA Receptor Currents in Dopaminergic Neurons: A Modeling Study. // Frontiers in Computational Neuroscience. 2016. Vol. 10. No. 48. P. 1-11. doi

2017⁸

Article Bobashev G., Holloway J., Solano E., Gutkin B. A Control Theory Model of Smoking // Methods Reports. 2017. Vol. июнь. P. 1-20. doi
Article Keramati M., Durand A., Girardeau P., Gutkin B., Ahmed S. Cocaine addiction as a homeostatic reinforcement learning disorder // Psychological Review. 2017. Vol. 124. No. 2. P. 130-153. doi
Article Gutkin B., Zeldenrust F., de Knecht S., Wadman W., Deneve S. Estimating the information extracted by a single spiking neuron from a continuous input time series // Frontiers in Computational Neuroscience. 2017. No. 11. P. 1-15. doi
Article Keramati M., Ahmed S., Gutkin B. Misdeed of the need: towards computational accounts of transition to addiction. // Current Opinion in Neurobiology. 2017. Vol. 8. No. 46. P. 142-153. (in press)
Article 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. Nicotine reverses hypofrontality in animal models of addiction and schizophrenia // Nature Medicine. 2017. No. 23. P. 347-354. doi
Article Koukouli F., Rooy M. E., 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. Nicotine reverses hypofrontality in animal models of addiction and schizophrenia // Nature Medicine. 2017. Vol. 23. No. 3. P. 347. doi
Article Gutkin B., Chalk M., Masset P., Deneve S. Sensory noise predicts divisive reshaping of receptive fields // PLoS Computational Biology. 2017. Vol. 13. No. 6. P. 1-16. doi
Article Gutkin B., Maex R. Temporal integration and 1/f power scaling in a circuit model of cerebellar interneurons // Journal of Neurophysiology. 2017. Vol. 118. No. 1. P. 471-485. doi

2018⁵

Article Buchin A., Kerr C., Huberfeld G., Miles R., Gutkin B. Adaptation and inhibition control pathological synchronization in a model of focal epileptic seizure // eNeuro. 2018. Vol. 0019-18. P. 1-14. doi
Article Gutkin B., di Volo M., Morozova E., Kuznetsov A., Lapish C. Dynamical ventral tegmental area circuit mechanisms of alcohol‐dependent dopamine release // European Journal of Neuroscience. 2018 doi
Article Volk D., Дубинин И. В., Myasnikova A., Gutkin B., Nikulin V. Generalized Cross-Frequency Decomposition: A Method for the Extraction of Neuronal Components Coupled at Different Frequencies // Frontiers in Neuroinformatics. 2018. Vol. 12. No. 72 doi
Article Zakharov D., Gutkin B., Krupa M., Kuznetsov A. High-frequency forced oscillations in neuronlike elements // Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. 2018. Vol. 97. No. 6. P. 062211-1-062211-5. doi
Article Новиков Н. А., Гуткин Б. С. РОЛЬ БЕТА- И ГАММА-РИТМОВ В РЕАЛИЗАЦИИ ФУНКЦИИ рабочей памяти // Психология. Журнал Высшей школы экономики. 2018. Т. 15. № 1. С. 174-182. doi

2019⁵

Article Martinez-Saito M., Konovalov R., Piradov M. A., Shestakova A., Gutkin B., Klucharev V. Action in auctions: neural and computational mechanisms of bidding behaviour // European Journal of Neuroscience. 2019. Vol. 50. No. 8. P. 3327-3348. doi
Article Zamani A., Novikov N., Gutkin B. Concomitance of Inverse Stochastic Resonance and Stochastic Resonance in a minimal bistable spiking neural circuit. // Communications in Nonlinear Science and Numerical Simulation. 2019 doi (in press)
Article Deperrois N., Moiseeva V., Gutkin B. Minimal Circuit Model of Reward Prediction Error Computations and Effects of Nicotinic Modulations // Frontiers in Neural Circuits. 2019. Vol. 12. No. 116. P. 1-17. doi
Article Zakharov D., Tyutin V. V., Krupa M., Gutkin B. Modulation of synchronous gamma rhythm clusters // Cybernetics and Physics. 2019. Vol. 8. No. 3. P. 185-188. doi
Article Hulme O., Melveille T., Gutkin B. Neurocomputational Theories of Homeostatic Control // Physics of Life Reviews. 2019 doi

2020³

Article Rooy M., Novikov N., Gutkin B. Interaction between PFC neural networks ultra-slow fluctuations and brain oscillations // Izvestiya Vysshikh uchebnykh zavedeniy. Prikladnaya nelineynaya dinamika. 2020. Vol. 28. No. 1. P. 90-97. doi
Article Rooy M., Novikov N., Zakharov D., Gutkin B. Interaction between PFC neural networks ultraslow fluctuations and brain oscillations // Izvestiya Vysshikh uchebnykh zavedeniy. Prikladnaya nelineynaya dinamika. 2020. Vol. 28. No. 1. P. 90-97. doi
Article Zakharov D., Krupa M., Gutkin B. Modelling dopaminergic modulation of clustered gamma rhythms // Communications in Nonlinear Science and Numerical Simulation. 2020. Vol. 82. No. 105086. P. 1-10. doi

Employment history

Present Position

2013-present Invited Professor, Higher School of Economics, Moscow, Russia.

2009-present Director, Group for Neural Theory, Laboratoire de Neuroscience Cognitive, INSERM U960, DEC, ENS

2011- present Senior Research Scientist (Director of Research, Full Professor equivalent) CNRS, France

Positions Previously Held

2012-2014 Vice Chairman, Institut pour l’Etude de la Cognition, ENS, Paris

2004-2011 Research Scientist (CR1), CNRS, France

2005- 08 Principle Investigator and co-Leader, Group for Neural Theory, College de France and Department of Cognitive Studies, ENS, Paris.

03/2008 Invited Scientist, Okinawa Institute of Technology, Okinawa, Japan

2004-06 Research Scientist, Recepteurs et Cognition, Departement de Neuroscience, Institut Pasteur, Paris, France

2002-04 Senior Research Fellow, Gatsby Computational Neuroscience Unit,

University College London, London, UK

1999-2002 NSF Biological Informatics Fellow,

Coginition et Recepteurs, Department of Neuroscience, Institut Pasteur, Paris, France

UNIC, Institut Alfred Fessard, CNRS, France

1997-99 Vice President for Research and Development, DBAZA, Inc, Pittsburgh, PA, USA

1993-99 Graduate Research Assistant and Neural Processes in Cognition Fellow, Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, USA

1990-93 Graduate Research and Teaching Assistant, Biomathematics Graduate Program, Department of Statistics, North Carolina State University, Raleigh NC USA

1989-90 Executive Producer Assistant, Mosflim Studios and Creator Film Productions, Moscow, Russia

Sep

2019

Upcoming Neuroeconomics Symposium Aims to Share New Research and Build International Collaboration

On September 23-24, the CCCP19 Symposium ‘Cognition, Computation, Neuroeconomics and Performance’ will be held at HSE University. The goal of the symposium is to exhibit cutting edge research at the CCDM, a leading cognitive neuroscience research centre in Russia, and LNC2, a leading European research centre in neuroeconomics, cognitive neuroscience and neural theory. Ahead of CCCP19, the HSE News Service spoke with the conference organizer and several invited speakers about the plan for this symposium and the importance of their research in the field.

Mar

2017

HSE Research Teams to Receive Russian Science Foundation Grants in 2017

The Russian Science Foundation has announced winners of its latest grant competition to support basic scientific research and exploratory scientific research conducted by research teams.

Oct

2015

HSE Researchers to Create a Mathematical Model of the Brain

The HSE Centre for Cognition and Decision Making together with a group of other Russian research centres is about to begin work on creating a mathematical model of the human brain. With its help scientists will be able to study the processes which take place in the brain and brain disease. It could be used for medical purposes in the future.