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Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes

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journal contribution
posted on 2021-10-01, 14:52 authored by Susanna Yu Gordleeva, Yuliya A Tsybina, Mikhail I Krivonosov, Mikhail V Ivanchenko, Alexey A Zaikin, Victor B Kazantsev, Alexander N Gorban
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.

Funding

Ministry of Science and Higher Education of the Russian Federation (project no. 075-15-2020-808). MRC Grant no. MR/R02524X/1.

History

Citation

Front. Cell. Neurosci. 2021, 15: 631485.

Author affiliation

Department of Mathematics

Version

  • VoR (Version of Record)

Published in

Frontiers in Cellular Neuroscience

Volume

15

Pagination

631485

Publisher

Frontiers Media

issn

1662-5102

eissn

1662-5102

Acceptance date

2021-03-04

Copyright date

2021

Available date

2021-03-31

Language

English

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