Boris S. Gutkin

According to our database1, Boris S. Gutkin authored at least 48 papers between 1996 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 




Dynamical manifold dimensionality as characterization measure of chimera states in bursting neuronal networks.
CoRR, 2023

A framework for macroscopic phase-resetting curves for generalised spiking neural networks.
PLoS Comput. Biol., 2022

Phase response approaches to neural activity models with distributed delay.
Biol. Cybern., 2022

Efficient and robust coding in heterogeneous recurrent networks.
PLoS Comput. Biol., 2021

Continuous Homeostatic Reinforcement Learning for Self-Regulated Autonomous Agents.
CoRR, 2021

Concomitance of inverse stochastic resonance and stochastic resonance in a minimal bistable spiking neural circuit.
Commun. Nonlinear Sci. Numer. Simul., 2020

Modeling dopaminergic modulation of clustered gamma rhythms.
Commun. Nonlinear Sci. Numer. Simul., 2020

Learning and Cognition in Financial Markets: A Paradigm Shift for Agent-Based Models.
Proceedings of the Intelligent Systems and Applications, 2020

Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits.
PLoS Comput. Biol., 2019

Generalized Cross-Frequency Decomposition: A Method for the Extraction of Neuronal Components Coupled at Different Frequencies.
Frontiers Neuroinformatics, 2018

Sensory noise predicts divisive reshaping of receptive fields.
PLoS Comput. Biol., 2017

Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series.
Frontiers Comput. Neurosci., 2017

Dopamine Neurons Change the Type of Excitability in Response to Stimuli.
PLoS Comput. Biol., 2016

Inverse Stochastic Resonance in Cerebellar Purkinje Cells.
PLoS Comput. Biol., 2016

Synergy of AMPA and NMDA Receptor Currents in Dopaminergic Neurons: A Modeling Study.
Frontiers Comput. Neurosci., 2016

Mechanisms for multiple activity modes of VTA dopamine neurons.
Frontiers Comput. Neurosci., 2015

Dopaminergic Cell Models.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

Theta-Neuron Model.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

Spike frequency adaptation.
Scholarpedia, 2014

Adaptation and shunting inhibition leads to pyramidal/interneuron gamma with sparse firing of pyramidal cells.
J. Comput. Neurosci., 2014

Endogenous Cholinergic Inputs and Local Circuit Mechanisms Govern the Phasic Mesolimbic Dopamine Response to Nicotine.
PLoS Comput. Biol., 2013

Passive Dendrites Enable Single Neurons to Compute Linearly Non-separable Functions.
PLoS Comput. Biol., 2013

Correlations in background activity control persistent state stability and allow execution of working memory tasks.
Frontiers Comput. Neurosci., 2013

Splay States in Finite Pulse-Coupled Networks of Excitable Neurons.
SIAM J. Appl. Dyn. Syst., 2012

Spiking and saturating dendrites differentially expand single neuron computation capacity.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Spike-Timing Dependent Plasticity and Feed-Forward Input Oscillations Produce Precise and Invariant Spike Phase-Locking.
Frontiers Comput. Neurosci., 2011

A Reinforcement Learning Theory for Homeostatic Regulation.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

The Role of Ongoing Dendritic Oscillations in Single-Neuron Dynamics.
PLoS Comput. Biol., 2009

The effects of cholinergic neuromodulation on neuronal phase-response curves of modeled cortical neurons.
J. Comput. Neurosci., 2009

Computational disease modeling - fact or fiction?
BMC Syst. Biol., 2009

Random perturbations of spiking activity in a pair of coupled neurons.
Theory Biosci., 2008

Synchrony of Neuronal Oscillations Controlled by GABAergic Reversal Potentials.
Neural Comput., 2007

Dopamine modulation in the basal ganglia locks the gate to working memory.
J. Comput. Neurosci., 2006

Phase Dependent Sign Changes of GABAergic Synaptic Input Explored <i>In-Silicio</i> and <i>In-Vitro</i>.
J. Comput. Neurosci., 2005

Guest Editorial.
J. Comput. Neurosci., 2005

Study on the role of GABAergic synapses in synchronization.
Neurocomputing, 2005

Noise delays onset of sustained firing in a minimal model of persistent activity.
Neurocomputing, 2004

Spike Generating Dynamics and the Conditions for Spike-Time Precision in Cortical Neurons.
J. Comput. Neurosci., 2003

Dopamine Modulation in a Basal Ganglio-cortical Network Implements Saliency-based Gating of Working Memory.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Multiple Bumps in a Neuronal Model of Working Memory.
SIAM J. Appl. Math., 2002

The Effects of Spike Frequency Adaptation and Negative Feedback on the Synchronization of Neural Oscillators.
Neural Comput., 2001

Turning On and Off with Excitation: The Role of Spike-Timing Asynchrony and Synchrony in Sustained Neural Activity.
J. Comput. Neurosci., 2001

Layer 3 patchy recurrent excitatory connections may determine the spatial organization of sustained activity in the primate prefrontal cortex.
Neurocomputing, 2000

Conditions for noise reduction and stable encoding of spatial structure by cortical neural networks.
Biol. Cybern., 2000

A minimal model for metabotropic modulation of fast synaptic transmission and firing properties in bullfrog sympathetic B neurons.
Neurocomputing, 1999

Effects of dopaminergic modulation of persistent sodium currents on the excitability of prefrontal cortical neurons: A computational study.
Neurocomputing, 1999

Dynamics of Membrane Excitability Determine Inter-Spike Interval Variability: A Link Between Spike Generation Mechanisms and Cortical Spike Train Statistics.
Neural Comput., 1998

Stable encoding of spatial structure by a recurrent neural network in the presence of noisy data.
Proceedings of International Conference on Neural Networks (ICNN'96), 1996