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20th International Conference on Mathematical Modeling and Supercomputer Technologies, MMST 2020

作者： Sinitsina, Maria S. Gordleeva, Susanna Yu. Kazantsev, Victor B. Pankratova, Evgeniya V. Department of Applied Mathematics Institute of Information Technologies Mathematics and Mechanics Lobachevsky State University of Nizhni Novgorod 23 Gagarin Avenue Nizhny Novgorod603950 Russia Neurotechnology Department Lobachevsky State University of Nizhni Novgorod 23 Gagarin Avenue Nizhny Novgorod603950 Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University 1 Universitetskaya Street Innopolis420500 Russia Neuroscience Research Institute Samara State Medical University 89 Chapaevskaya Street Samara443099 Russia

ISBN: (纸本)9783030787585

Recent experimental data show that neural network dynamics significantly depends on the properties of an active nonlinear environment in the brain. Chemical activity of astrocytes is one of the main factor modifying the excitability of the neuronal membrane and regulating the efficiency of signal transmission between neurons. It is known that astrocytes can demonstrate both spontaneous changes in calcium concentration and calcium signals caused by neuronal activity. We focus on spontaneous calcium concentration dynamics in astrocytes. Nonlinear differential equations describing molecular t between neuronsransport in the astrocytes are investigated. Particularly, within the frame of Lavrentovich-Hemkin mathematical model for calcium dynamics, the bifurcation mechanisms of spontaneous calcium concentration change are determined. We show that both soft (emergence of small-amplitude oscillations via supercritical Andronov-Hopf bifurcation) and hard (instantaneous emergence of large-amplitude oscillations via fold limit cycle bifurcation) ways for oscillations emergence can be realized in the astrocyte dynamics. © 2021, Springer Nature Switzerland AG.

关键词： Dynamics

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Chimera-like state in ensemble of bistable neurons

Chimera-like state in ensemble of bistable neurons

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Nonlinearity, Information and robotics, (NIR) International Conference

作者： Andrey Andreev Nikita Frolov Natalija Alexandrova Marija Chaban Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Faculty of Information Technologies Saratov State University Saratov Russia

ISBN: (数字)9781728187631

ISBN: (纸本)9781728187648

We investigate the nonlinear dynamics of a neural network. As a model of a neuron, we use Hodgkin-Huxley mathematical model. We choose the neuron's parameters corresponding to a bistable region in which both fixed point and limit cycle are coexisting. We discover that depending on external current and coupling strength we can achieve a chimera-like state when one part of the neurons is in the resting state, while the other one is in the oscillatory regime in a certain area of coupling strength and external current amplitude.

关键词： Couplings Neurons Limit-cycles Nonlinear dynamical systems Mathematical model Biological neural networks Robots

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Post-stroke rehabilitation with the help of brain-computer interface 3

Post-stroke rehabilitation with the help of brain-computer i...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Kiselev, Anton R. Maksimenko, Vladimir A. Shukovskiy, Nikolay Pisarchik, Alexander N. Pitsik, Elena Hramov, Alexander E. Saratov State Medical University Saratov Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Biomedical Technology Technical University of Madrid Madrid Spain

ISBN: (纸本)9781728124704

We considered a group of 50 patients with lateral paresis in the acute period after the first stroke. The EEG recordings in the group of post-stroke patients displayed fundamentally different brain dynamics during real movements of a conventionally healthy hand and a hand with decreased muscle strength. While for the conventionally healthy hand the brain activity in the sensory zone is quite close to the dynamics observed in the control group, for the paretic hand there is pathological activity associated with increased activity in low frequency ranges (up to 12 Hz). Meanwhile, the brain activity during imaginary motion is similar for both hands and hence to the dynamics in the control group of conditionally healthy subjects. The obtained results can be used in rehabilitation techniques based on imaginary motor activity with the help of brain-computer interface. © 2019 IEEE.

关键词： Brain computer interface

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Influence of the sensory information ambiguity on the brain state during the decision-making task 3

Influence of the sensory information ambiguity on the brain ...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Kuc, Alexander Nedaivozov, Vladimir Patent and License Department Saratov State Technical University Saratov Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

The process of visual information classification includes different states of brain activity, such as sensory processing and decision-making. The stage of sensory processing is usually short and occurs in the occipital and parietal areas of the brain, while the decision-making stage is more pronounced over time and includes the parietal and frontal areas. In the current paper, we consider the brain activity during the classification task using ambiguous visual stimuli with varying degrees of ambiguity. We show that with increasing ambiguity of the visual stimulus, the brain engages neuronal populations in the distributed cortical regions in 15-30 Hz frequency band, including the frontal area at the early stages of information processing. © 2019 IEEE.

关键词： Decision making

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Spatio-temporal cortical activity during a visual task accomplishing 3

Spatio-temporal cortical activity during a visual task accom...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Kuc, Alexander Maksimenko, Vladimir Patent and License Department Saratov State Technical University Saratov Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

It is known that neuronal populations of cortical brain network are involved in the processes, related to accomplishing of different tasks, e.g. processing of sensory information and making decisions. Each particular type of tasks is characterized by the specific features of neuronal activity both in time-frequency and spatio-temporal domains. These features of neuronal activity reflect the structure of electrical activity signals (EEG) registered from the head surface via noninvasive electrodes. EEG signals are composed of the different rhythms of neuronal activity. While some studies relate these rhythms to the particular basic brain functions, other studies demonstrate that specific scenarios of EEG rhythms dynamics can be associated with accomplishing of cognitive task and affect human behavioral performance. With this in mind we analyze the spatio-temporal dynamics of alpha and beta rhythms of cortical activity during processing visual task and relate the features of rhythms dynamics to human's behavioral performance. © 2019 IEEE.

关键词： Wavelet analysis

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Bursting activity interplay in modular neural networks in vitro 3

Bursting activity interplay in modular neural networks in vi...

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3rd International Conference "Neurotechnologies and Neurointerfaces", CNN 2021

作者： Gladkov, Arseniy Pigareva, Yana Kolpakov, Vladimir Mukhina, Irina Bukatin, Anton Kazantsev, Victor Pimashkin, Alexey Cell Technology Department Central Research Laboratory Privolzhsky Research Medical University Nizhny Novgorod Russia Neurotechnology Department Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod Russia Laboratory of Renewable Energy Sources Alferov Saint-Petersburg National Research Academic University of the Russian Academy of Sciences Saint-Petersburg Russia Laboratory of Bio and Chemosensor Microsystems Institute for Analytical Instrumentation of the RAS Saint-Petersburg Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Neurotechnology and Machine Learning Immanuel Kant Baltic Federal University Kaliningrad Russia NeurotechnologyDepartment Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod Russia

ISBN: (纸本)9781665424745

Neural networks modularity is a major challenge to study spiking pattern propagation and information processing in the brain. Sparse and heterogeneous connectivity between network modules defines spiking activity generation and interplay. Detailed study of modular network complex connectivity and dynamics is complicated by inducing retrograde or closed-loop activity. In this study, we analyzed the spiking activity of spontaneous and stimulus-induced interplay between two cultured neuronal networks (source-target) coupled with unidirectional synaptic connections, which were formed by microfluidic microchannels. Inhibition of excitatory synaptic activity in a source module abolished retrograde and closed-loop activity in the interplay. We found characteristics of electrical stimulation applied to the intermodular connections, which evoked a network-wide response in a target module. The developed approach can be applied to study synaptic plasticity in modular networks in vitro and improvement of new methods of neurointerface design. © 2021 IEEE.

关键词： Microfluidic chips

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Mean phase coherence modified for piecewise constant phase difference data 3

Mean phase coherence modified for piecewise constant phase d...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Khorev, Vladimir Department of Dynamic Modeling and Biomedical Engineering Saratov State University Saratov Russia Neuroscience and Cognitive Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

We propose a modification of the mean phase coherence method based on the statistics arrange of phase difference data. The modification aimed towards better analysis of data of coupled oscillators under influence of s... 详细信息

ISBN: (纸本)9781728124704

关键词： Synchronization Coherence Oscillators Couplings Indexes Time series analysis Delays

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Modeling of a brain neuronal network under visual stimulation 3

Modeling of a brain neuronal network under visual stimulatio...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Pisarchik, Alexander Andreev, Andrey Ivanov, Alexey Center for Biomedical Technology Technical University of Madrid Madrid Spain Neuroscience and Cognivite Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Yuri Gagarin State Technical University of Saratov Saratov Russia

ISBN: (纸本)9781728124704

We numerically simulate a network of coupled Hodgkin-Huxley neurons for modulating a processing visual perception by the brain. On a part of the network, we apply an external current of constant amplitude modulating visual information entering the brain. We analyze the influence of the external stimulus amplitude on the dynamics of the system. We discover coherent resonance phenomenon when for certain area of external stimulus amplitude both signal-to-noise ratio and characteristic correlation time are maximal. © 2019 IEEE.

关键词： Neural networks

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Model of ‘implant-host’ neural circuits in a microfluidic chip in vitro 8

Model of ‘implant-host’ neural circuits in a microfluidic ...

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8th International School and Conference "Saint Petersburg OPEN 2021" on Optoelectronics, Photonics, Engineering and Nanostructures, SPbOPEN 2021

作者： Kolpakov, V.N. Pigareva, Y.I. Gladkov, A.A. Bukatin, A.S. Kazantsev, V.B. Mukhina, I.V. Pimashkin, A.S. Neurotechnology Department Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod603950 Russia Cell Technology Department Central Research Laboratory Privolzhsky Research Medical University Nizhny Novgorod603005 Russia Laboratory of Renewable Energy Sources Alferov Saint-Petersburg National Research Academic University of the Russian Academy of Sciences Saint-Petersburg194021 Russia Laboratory of Bio and Chemosensor Microsystems Institute for Analytical Instrumentation of the RAS Saint-Petersburg198095 Russia Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University 1 Universitetskaya Str. Innopolis420500 Russia Center for Neurotechnology and Machine Learning Immanuel Kant Baltic Federal University 14 Nevsky Str. Kaliningrad236016 Russia

In this study, we developed a new model of neuronal cells plating into a developed neural network to study functional integration using microfluidic methods. The integration was modeled in a three-chamber microfluidic chip by growing two weakly coupled neuronal networks and enhancing its connectivity by plating new dissociated cells. The direction of connections was formed by the asymmetric design of the chip. Such technology can be used to develop a new type of scaffold to recover the modular structure of the network. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Microfluidics

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Erratum: "Extreme synchronization events in a Kuramoto model: The interplay between resource constraints and explosive transitions" [Chaos 31, 063103 (2021)]

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Chaos (Woodbury, N.Y.) 2021年第12期31卷 129901页

作者： Nikita Frolov Alexander Hramov Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University 420500 Innopolis The Republic of Tatarstan Russia.

This erratum corrects a mistake in the previously published paper.1

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