Turing instability mechanism of short-memory formation in multilayer FitzHugh-Nagumo network
IntroductionThe study of brain function has been favored by scientists, but the mechanism of short-term memory formation has yet to be precise.Research problemSince the formation of short-term memories depends on neuronal activity, we try to explain the mechanism from the neuron level in this paper....
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Psychiatry |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1083015/full |
| _version_ | 1797859725639942144 |
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| author | Junjie Wang Jianwei Shen |
| author_facet | Junjie Wang Jianwei Shen |
| author_sort | Junjie Wang |
| collection | DOAJ |
| description | IntroductionThe study of brain function has been favored by scientists, but the mechanism of short-term memory formation has yet to be precise.Research problemSince the formation of short-term memories depends on neuronal activity, we try to explain the mechanism from the neuron level in this paper.Research contents and methodsDue to the modular structures of the brain, we analyze the pattern properties of the FitzHugh-Nagumo model (FHN) on a multilayer network (coupled by a random network). The conditions of short-term memory formation in the multilayer FHN model are obtained. Then the time delay is introduced to more closely match patterns of brain activity. The properties of periodic solutions are obtained by the central manifold theorem.ConclusionWhen the diffusion coeffcient, noise intensity np, and network connection probability p reach a specific range, the brain forms a relatively vague memory. It is found that network and time delay can induce complex cluster dynamics. And the synchrony increases with the increase of p. That is, short-term memory becomes clearer. |
| first_indexed | 2024-04-09T21:34:15Z |
| format | Article |
| id | doaj.art-f09432f19ee245eaad12b3f770414714 |
| institution | Directory Open Access Journal |
| issn | 1664-0640 |
| language | English |
| last_indexed | 2024-04-09T21:34:15Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj.art-f09432f19ee245eaad12b3f7704147142023-03-27T05:50:52ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402023-03-011410.3389/fpsyt.2023.10830151083015Turing instability mechanism of short-memory formation in multilayer FitzHugh-Nagumo networkJunjie Wang0Jianwei Shen1School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, ChinaSchool of Mathematics and Statistics, North China University of Water Resources and Electric Power, Zhengzhou, ChinaIntroductionThe study of brain function has been favored by scientists, but the mechanism of short-term memory formation has yet to be precise.Research problemSince the formation of short-term memories depends on neuronal activity, we try to explain the mechanism from the neuron level in this paper.Research contents and methodsDue to the modular structures of the brain, we analyze the pattern properties of the FitzHugh-Nagumo model (FHN) on a multilayer network (coupled by a random network). The conditions of short-term memory formation in the multilayer FHN model are obtained. Then the time delay is introduced to more closely match patterns of brain activity. The properties of periodic solutions are obtained by the central manifold theorem.ConclusionWhen the diffusion coeffcient, noise intensity np, and network connection probability p reach a specific range, the brain forms a relatively vague memory. It is found that network and time delay can induce complex cluster dynamics. And the synchrony increases with the increase of p. That is, short-term memory becomes clearer.https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1083015/fullFHN modelshort-term memorymultilayer networkTuring patterndelayHopf bifurcation |
| spellingShingle | Junjie Wang Jianwei Shen Turing instability mechanism of short-memory formation in multilayer FitzHugh-Nagumo network Frontiers in Psychiatry FHN model short-term memory multilayer network Turing pattern delay Hopf bifurcation |
| title | Turing instability mechanism of short-memory formation in multilayer FitzHugh-Nagumo network |
| title_full | Turing instability mechanism of short-memory formation in multilayer FitzHugh-Nagumo network |
| title_fullStr | Turing instability mechanism of short-memory formation in multilayer FitzHugh-Nagumo network |
| title_full_unstemmed | Turing instability mechanism of short-memory formation in multilayer FitzHugh-Nagumo network |
| title_short | Turing instability mechanism of short-memory formation in multilayer FitzHugh-Nagumo network |
| title_sort | turing instability mechanism of short memory formation in multilayer fitzhugh nagumo network |
| topic | FHN model short-term memory multilayer network Turing pattern delay Hopf bifurcation |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1083015/full |
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