Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes
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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-03-01
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| Series: | Frontiers in Cellular Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fncel.2021.631485/full |
| _version_ | 1818329938341658624 |
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| author | Susanna Yu. Gordleeva Susanna Yu. Gordleeva Yuliya A. Tsybina Mikhail I. Krivonosov Mikhail V. Ivanchenko Alexey A. Zaikin Alexey A. Zaikin Alexey A. Zaikin Victor B. Kazantsev Victor B. Kazantsev Victor B. Kazantsev Alexander N. Gorban Alexander N. Gorban |
| author_facet | Susanna Yu. Gordleeva Susanna Yu. Gordleeva Yuliya A. Tsybina Mikhail I. Krivonosov Mikhail V. Ivanchenko Alexey A. Zaikin Alexey A. Zaikin Alexey A. Zaikin Victor B. Kazantsev Victor B. Kazantsev Victor B. Kazantsev Alexander N. Gorban Alexander N. Gorban |
| author_sort | Susanna Yu. Gordleeva |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T12:56:00Z |
| format | Article |
| id | doaj.art-9d0436a35a6f4f769f6ed4073396890f |
| institution | Directory Open Access Journal |
| issn | 1662-5102 |
| language | English |
| last_indexed | 2024-12-13T12:56:00Z |
| publishDate | 2021-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cellular Neuroscience |
| spelling | doaj.art-9d0436a35a6f4f769f6ed4073396890f2022-12-21T23:45:11ZengFrontiers Media S.A.Frontiers in Cellular Neuroscience1662-51022021-03-011510.3389/fncel.2021.631485631485Modeling Working Memory in a Spiking Neuron Network Accompanied by AstrocytesSusanna Yu. Gordleeva0Susanna Yu. Gordleeva1Yuliya A. Tsybina2Mikhail I. Krivonosov3Mikhail V. Ivanchenko4Alexey A. Zaikin5Alexey A. Zaikin6Alexey A. Zaikin7Victor B. Kazantsev8Victor B. Kazantsev9Victor B. Kazantsev10Alexander N. Gorban11Alexander N. Gorban12Scientific and Educational Mathematical Center “Mathematics of Future Technology,” Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, RussiaNeuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, Innopolis, RussiaScientific and Educational Mathematical Center “Mathematics of Future Technology,” Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, RussiaScientific and Educational Mathematical Center “Mathematics of Future Technology,” Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, RussiaScientific and Educational Mathematical Center “Mathematics of Future Technology,” Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, RussiaScientific and Educational Mathematical Center “Mathematics of Future Technology,” Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, RussiaCenter for Analysis of Complex Systems, Sechenov First Moscow State Medical University, Sechenov University, Moscow, RussiaInstitute for Women's Health and Department of Mathematics, University College London, London, United KingdomScientific and Educational Mathematical Center “Mathematics of Future Technology,” Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, RussiaNeuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, Innopolis, RussiaNeuroscience Research Institute, Samara State Medical University, Samara, RussiaScientific and Educational Mathematical Center “Mathematics of Future Technology,” Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, RussiaDepartment of Mathematics, University of Leicester, Leicester, United KingdomWe 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.https://www.frontiersin.org/articles/10.3389/fncel.2021.631485/fullspiking neural networkastrocyteneuron-astrocyte interactionworking memorydelayed activity |
| spellingShingle | Susanna Yu. Gordleeva Susanna Yu. Gordleeva Yuliya A. Tsybina Mikhail I. Krivonosov Mikhail V. Ivanchenko Alexey A. Zaikin Alexey A. Zaikin Alexey A. Zaikin Victor B. Kazantsev Victor B. Kazantsev Victor B. Kazantsev Alexander N. Gorban Alexander N. Gorban Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes Frontiers in Cellular Neuroscience spiking neural network astrocyte neuron-astrocyte interaction working memory delayed activity |
| title | Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes |
| title_full | Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes |
| title_fullStr | Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes |
| title_full_unstemmed | Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes |
| title_short | Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes |
| title_sort | modeling working memory in a spiking neuron network accompanied by astrocytes |
| topic | spiking neural network astrocyte neuron-astrocyte interaction working memory delayed activity |
| url | https://www.frontiersin.org/articles/10.3389/fncel.2021.631485/full |
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