Neuronal synchronization enhanced by neuron–astrocyte interaction

Pankratova, Evgeniya V.; Kalyakulina, Alena; Stasenko, Sergey V.; Gordleeva, Susanna; Lazarevich, Ivan; Kazantsev, Victor B.

doi:10.1007/s11071-019-05004-7

Cited by 47 publications

(16 citation statements)

References 59 publications

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“…As pyramidal neurons generate the spike, glutamate is released from the presynaptic terminal into the synaptic cleft ( Figures 3B,D ). The amount of glutamate, G , that was diffused from the synaptic cleft and reached the astrocytic process can be described by the following equation (Gordleeva et al, 2012 ; Pankratova et al, 2019 ):…”

Section: Methodsmentioning

confidence: 99%

Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes

Gordleeva

Tsybina

Krivonosov

et al. 2021

Front. Cell. Neurosci.

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We propose a novel biologically plausible computational model of working memory (WM) implemented by a spiking neuron network (SNN) interacting with a network of astrocytes. The SNN is modeled by synaptically coupled Izhikevich neurons with a non-specific architecture connection topology. Astrocytes generating calcium signals are connected by local gap junction diffusive couplings and interact with neurons via chemicals diffused in the extracellular space. Calcium elevations occur in response to the increased concentration of the neurotransmitter released by spiking neurons when a group of them fire coherently. In turn, gliotransmitters are released by activated astrocytes modulating the strength of the synaptic connections in the corresponding neuronal group. Input information is encoded as two-dimensional patterns of short applied current pulses stimulating neurons. The output is taken from frequencies of transient discharges of corresponding neurons. We show how a set of information patterns with quite significant overlapping areas can be uploaded into the neuron-astrocyte network and stored for several seconds. Information retrieval is organized by the application of a cue pattern representing one from the memory set distorted by noise. We found that successful retrieval with the level of the correlation between the recalled pattern and ideal pattern exceeding 90% is possible for the multi-item WM task. Having analyzed the dynamical mechanism of WM formation, we discovered that astrocytes operating at a time scale of a dozen of seconds can successfully store traces of neuronal activations corresponding to information patterns. In the retrieval stage, the astrocytic network selectively modulates synaptic connections in the SNN leading to successful recall. Information and dynamical characteristics of the proposed WM model agrees with classical concepts and other WM models.

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Section: Methodsmentioning

confidence: 99%

Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes

Gordleeva

Tsybina

Krivonosov

et al. 2021

Front. Cell. Neurosci.

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“…The spiking activity of neurons leads to the release of the neurotransmitter glutamate G from the presynaptic terminal into the synaptic gap. The amount of G that reached the astrocyte is described by the following equation: [72][73][74]:…”

Section: Astrocytic Networkmentioning

confidence: 99%

Astrocytes mediate analogous memory in a multi-layer neuron–astrocyte network

Tsybina

Kastalskiy

Krivonosov

et al. 2022

Neural Comput & Applic

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Modeling the neuronal processes underlying short-term working memory remains the focus of many theoretical studies in neuroscience. In this paper, we propose a mathematical model of a spiking neural network (SNN) which simulates the way a fragment of information is maintained as a robust activity pattern for several seconds and the way it completely disappears if no other stimuli are fed to the system. Such short-term memory traces are preserved due to the activation of astrocytes accompanying the SNN. The astrocytes exhibit calcium transients at a time scale of seconds. These transients further modulate the efficiency of synaptic transmission and, hence, the firing rate of neighboring neurons at diverse timescales through gliotransmitter release. We demonstrate how such transients continuously encode frequencies of neuronal discharges and provide robust short-term storage of analogous information. This kind of short-term memory can store relevant information for seconds and then completely forget it to avoid overlapping with forthcoming patterns. The SNN is inter-connected with the astrocytic layer by local inter-cellular diffusive connections. The astrocytes are activated only when the neighboring neurons fire synchronously, e.g., when an information pattern is loaded. For illustration, we took grayscale photographs of people’s faces where the shades of gray correspond to the level of applied current which stimulates the neurons. The astrocyte feedback modulates (facilitates) synaptic transmission by varying the frequency of neuronal firing. We show how arbitrary patterns can be loaded, then stored for a certain interval of time, and retrieved if the appropriate clue pattern is applied to the input.

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“…which is exactly equivalent to (18) for any s 1 . We emphasize that hereinafter expressions containing (22). The same applies when the approximate expression for I 0 (•) (35) is used.…”

Section: Expressing the "Whole Minus Sum" Informationmentioning

confidence: 99%

“…Our recent study [ 19 ] addressed the role of astrocytic regulation of neurotransmission [ 20 , 21 , 22 ] in generating positive II via small networks of brain cells—neurons and astrocytes. Empirical “whole minus sum” II, as defined in [ 13 ], was calculated in [ 19 ] from the time series produced by a biologically realistic model of neuro-astrocytic networks.…”

Section: Introductionmentioning

confidence: 99%

Integrated Information in the Spiking–Bursting Stochastic Model

Kanakov

Gordleeva

Zaikin

2020

Entropy

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Integrated information has been recently suggested as a possible measure to identify a necessary condition for a system to display conscious features. Recently, we have shown that astrocytes contribute to the generation of integrated information through the complex behavior of neuron–astrocyte networks. Still, it remained unclear which underlying mechanisms governing the complex behavior of a neuron–astrocyte network are essential to generating positive integrated information. This study presents an analytic consideration of this question based on exact and asymptotic expressions for integrated information in terms of exactly known probability distributions for a reduced mathematical model (discrete-time, discrete-state stochastic model) reflecting the main features of the “spiking–bursting” dynamics of a neuron–astrocyte network. The analysis was performed in terms of the empirical “whole minus sum” version of integrated information in comparison to the “decoder based” version. The “whole minus sum” information may change sign, and an interpretation of this transition in terms of “net synergy” is available in the literature. This motivated our particular interest in the sign of the “whole minus sum” information in our analytical considerations. The behaviors of the “whole minus sum” and “decoder based” information measures are found to bear a lot of similarity—they have mutual asymptotic convergence as time-uncorrelated activity increases, and the sign transition of the “whole minus sum” information is associated with a rapid growth in the “decoder based” information. The study aims at creating a theoretical framework for using the spiking–bursting model as an analytically tractable reference point for applying integrated information concepts to systems exhibiting similar bursting behavior. The model can also be of interest as a new discrete-state test bench for different formulations of integrated information.

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Neuronal synchronization enhanced by neuron–astrocyte interaction

Cited by 47 publications

References 59 publications

Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes

Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes

Astrocytes mediate analogous memory in a multi-layer neuron–astrocyte network

Integrated Information in the Spiking–Bursting Stochastic Model

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