A computational model to explore how temporal stimulation patterns affect synapse plasticity.

Plasticity-related proteins (PRPs), which are synthesized in a synapse activation-dependent manner, are shared by multiple synapses to a limited spatial extent for a specific period. In addition, stimulated synapses can utilize shared PRPs through synaptic tagging and capture (STC). In particular, t...

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Main Authors: Ryota Amano, Mitsuyuki Nakao, Kazumichi Matsumiya, Fumikazu Miwakeichi
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2022-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0275059
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author Ryota Amano
Mitsuyuki Nakao
Kazumichi Matsumiya
Fumikazu Miwakeichi
author_facet Ryota Amano
Mitsuyuki Nakao
Kazumichi Matsumiya
Fumikazu Miwakeichi
author_sort Ryota Amano
collection DOAJ
description Plasticity-related proteins (PRPs), which are synthesized in a synapse activation-dependent manner, are shared by multiple synapses to a limited spatial extent for a specific period. In addition, stimulated synapses can utilize shared PRPs through synaptic tagging and capture (STC). In particular, the phenomenon by which short-lived early long-term potentiation is transformed into long-lived late long-term potentiation using shared PRPs is called "late-associativity," which is the underlying principle of "cluster plasticity." We hypothesized that the competitive capture of PRPs by multiple synapses modulates late-associativity and affects the fate of each synapse in terms of whether it is integrated into a synapse cluster. We tested our hypothesis by developing a computational model to simulate STC, late-associativity, and the competitive capture of PRPs. The experimental results obtained using the model revealed that the number of competing synapses, timing of stimulation to each synapse, and basal PRP level in the dendritic compartment altered the effective temporal window of STC and influenced the conditions under which late-associativity occurs. Furthermore, it is suggested that the competitive capture of PRPs results in the selection of synapses to be integrated into a synapse cluster via late-associativity.
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spelling doaj.art-4e8770ce810140aba28298d1eaf2a8a22022-12-22T04:07:41ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01179e027505910.1371/journal.pone.0275059A computational model to explore how temporal stimulation patterns affect synapse plasticity.Ryota AmanoMitsuyuki NakaoKazumichi MatsumiyaFumikazu MiwakeichiPlasticity-related proteins (PRPs), which are synthesized in a synapse activation-dependent manner, are shared by multiple synapses to a limited spatial extent for a specific period. In addition, stimulated synapses can utilize shared PRPs through synaptic tagging and capture (STC). In particular, the phenomenon by which short-lived early long-term potentiation is transformed into long-lived late long-term potentiation using shared PRPs is called "late-associativity," which is the underlying principle of "cluster plasticity." We hypothesized that the competitive capture of PRPs by multiple synapses modulates late-associativity and affects the fate of each synapse in terms of whether it is integrated into a synapse cluster. We tested our hypothesis by developing a computational model to simulate STC, late-associativity, and the competitive capture of PRPs. The experimental results obtained using the model revealed that the number of competing synapses, timing of stimulation to each synapse, and basal PRP level in the dendritic compartment altered the effective temporal window of STC and influenced the conditions under which late-associativity occurs. Furthermore, it is suggested that the competitive capture of PRPs results in the selection of synapses to be integrated into a synapse cluster via late-associativity.https://doi.org/10.1371/journal.pone.0275059
spellingShingle Ryota Amano
Mitsuyuki Nakao
Kazumichi Matsumiya
Fumikazu Miwakeichi
A computational model to explore how temporal stimulation patterns affect synapse plasticity.
PLoS ONE
title A computational model to explore how temporal stimulation patterns affect synapse plasticity.
title_full A computational model to explore how temporal stimulation patterns affect synapse plasticity.
title_fullStr A computational model to explore how temporal stimulation patterns affect synapse plasticity.
title_full_unstemmed A computational model to explore how temporal stimulation patterns affect synapse plasticity.
title_short A computational model to explore how temporal stimulation patterns affect synapse plasticity.
title_sort computational model to explore how temporal stimulation patterns affect synapse plasticity
url https://doi.org/10.1371/journal.pone.0275059
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