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arXiv 2022年

作者： Stasenko, Sergey V. Hramov, Alexander E. Kazantsev, Victor B. Laboratory of Advanced Methods for High-dimensional Data Analysis Lobachevsky University Nizhniy Novgorod603022 Russia Neuroscience and Cognitive Technology Lab Innopolis University Innopolis420500 Russia Department of New Cardiological Informational Technologies Saratov State Medical University Saratov410012 Russia Laboratory for Neuromodeling Neuroscience Research Institute Samara State Medical University Samara443099 Russia

Coherent activations of brain neuron networks underlay many physiological functions associated with various behavioral states. These synchronous fluctuations in the electrical activity of the brain are also referred to as brain rhythms. At the cellular level, the rhythmicity can be induced by various mechanisms of intrinsic oscillations in neurons or network circulation of excitation between synaptically coupled neurons. One of the specific mechanisms concerns the activity of brain astrocytes that accompany neurons and can coherently modulate synaptic contacts of neighboring neurons, synchronizing their activity. Recent studies have shown that coronavirus infection (Covid-19), entering the central nervous system and infecting astrocytes, causes various metabolic disorders. Specifically, Covid-19 can depress the synthesis of astrocytic glutamate and GABA. It is also known that in the postcovid state, patients may suffer from symptoms of anxiety and impaired cognitive functions, which may be a consequence of disturbed brain rhythms. We propose a mathematical model of a spiking neural network accompanied by astrocytes capable to generate quasi-synchronous rhythmic bursting discharges. The model predicts that if the astrocytes are infected, and the release of glutamate is depressed, then normal burst rhythmicity suffers dramatically. Interestingly, in some cases, the failure of network coherence may be intermittent with intervals of normal rhythmicity, or the synchronization can completely disappears. © 2022, CC BY.

关键词： Neurons

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high-dimensional brain in a high-dimensionalworld: Blessing of dimensionality

arXiv

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arXiv 2020年

作者： Gorban, Alexander N. Makarov, Valery A. Tyukin, Ivan Y. Department of Mathematics University of Leicester LeicesterLE1 7RH United Kingdom Laboratory of Advanced Methods for High-Dimensional Data Analysis Lobachevsky University Nizhny Novgorod603022 Russia Instituto de Matemática Interdisciplinar Faculty of Mathematics Universidad Complutense de Madrid Avda Complutense s/n Madrid28040 Spain

high-dimensional data and high-dimensional representations of reality are inherent features of modern Artificial Intelligence systems and applications of machine learning. The well-known phenomenon of the "curse of dimensionality" states: Many problems become exponentially difficult in high dimensions. Recently, the other side of the coin, the "blessing of dimensionality", has attracted much attention. It turns out that generic high-dimensional datasets exhibit fairly simple geometric properties. Thus, there is a fundamental tradeoff between complexity and simplicity in high dimensional spaces. Here we present a brief explanatory review of recent ideas, results and hypotheses about the blessing of dimensionality and related simplifying effects relevant to machine learning and neuroscience. Copyright © 2020, The Authors. All rights reserved.

关键词： data mining

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Astrocyte control bursting mode of spiking neuron network with memristor-implemented plasticity

arXiv

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arXiv 2023年

作者： Stasenko, Sergey V. Mikhaylov, Alexey N. Fedotov, Alexander A. Smirnov, Vladimir A. Kazantsev, Victor B. Laboratory of Neurobiomorphic Technologies Moscow Institute of Physics and Technology Moscow117303 Russia Laboratory of Advanced Methods for High-Dimensional Data Analysis Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod603022 Russia Laboratory of Memristor Nanoelectronics Lobachevsky State University of Nizhny Novgorod Nizhny Novgorod603022 Russia Institute of Nanotechnologies Electronics and Electronic Equipment Engineering Southern Federal University Taganrog347922 Russia

A mathematical model of a spiking neuron network accompanied by astrocytes is considered. The network is composed of excitatory and inhibitory neurons with synaptic connections supplied by a memristor-based model of plasticity. Another mechanism for changing the synaptic connections involves astrocytic regulations using the concept of tripartite synapses. In the absence of memristor-based plasticity, the connections between these neurons drive the network dynamics into a burst mode, as observed in many experimental neurobiological studies when investigating living networks in neuronal cultures. The memristive plasticity implementing synaptic plasticity in inhibitory synapses results in a shift in network dynamics towards an asynchronous mode. Next,it is found that accounting for astrocytic regulation in glutamatergic excitatory synapses enable the restoration of’normal’ burst dynamics. The conditions and parameters of such astrocytic regulation’s impact on burst dynamics established. © 2023, CC BY.

关键词： Memristors

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