Postsynaptic Potential Energy as Determinant of Synaptic Plasticity.

computational model homeostatic plasticity homo- and heterosynaptic plasticity metabolic energy synaptic plasticity

Journal

Frontiers in computational neuroscience
ISSN: 1662-5188
Titre abrégé: Front Comput Neurosci
Pays: Switzerland
ID NLM: 101477956

Informations de publication

Date de publication:
2022
Historique:
received: 29 10 2021
accepted: 13 01 2022
entrez: 7 3 2022
pubmed: 8 3 2022
medline: 8 3 2022
Statut: epublish

Résumé

Metabolic energy can be used as a unifying principle to control neuronal activity. However, whether and how metabolic energy alone can determine the outcome of synaptic plasticity remains unclear. This study proposes a computational model of synaptic plasticity that is completely determined by energy. A simple quantitative relationship between synaptic plasticity and postsynaptic potential energy is established. Synaptic weight is directly proportional to the difference between the baseline potential energy and the suprathreshold potential energy and is constrained by the maximum energy supply. Results show that the energy constraint improves the performance of synaptic plasticity and avoids setting the hard boundary of synaptic weights. With the same set of model parameters, our model can reproduce several classical experiments in homo- and heterosynaptic plasticity. The proposed model can explain the interaction mechanism of Hebbian and homeostatic plasticity at the cellular level. Homeostatic synaptic plasticity at different time scales coexists. Homeostatic plasticity operating on a long time scale is caused by heterosynaptic plasticity and, on the same time scale as Hebbian synaptic plasticity, is caused by the constraint of energy supply.

Identifiants

pubmed: 35250524
doi: 10.3389/fncom.2022.804604
pmc: PMC8891168
doi:

Types de publication

Journal Article

Langues

eng

Pagination

804604

Informations de copyright

Copyright © 2022 Chen, Xie, Wang and Zhang.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Huanwen Chen (H)

School of Automation, Central South University, Changsha, China.

Lijuan Xie (L)

Institute of Physiology and Psychology, School of Marxism, Changsha University of Science and Technology, Changsha, China.

Yijun Wang (Y)

School of Automation, Central South University, Changsha, China.

Hang Zhang (H)

School of Automation, Central South University, Changsha, China.

Classifications MeSH