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Dynamical and Coupling Structure of Pulse-Coupled Networks in Maximum Entropy Analysis

Maximum entropy principle (MEP) analysis with few non-zero effective interactions successfully characterizes the distribution of dynamical states of pulse-coupled networks in many fields, e.g., in neuroscience. To better understand the underlying mechanism, we found a relation between the dynamical...

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Detalles Bibliográficos
Autores principales: Xu, Zhi-Qin John, Zhou, Douglas, Cai, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514185/
https://www.ncbi.nlm.nih.gov/pubmed/33266793
http://dx.doi.org/10.3390/e21010076
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author Xu, Zhi-Qin John
Zhou, Douglas
Cai, David
author_facet Xu, Zhi-Qin John
Zhou, Douglas
Cai, David
author_sort Xu, Zhi-Qin John
collection PubMed
description Maximum entropy principle (MEP) analysis with few non-zero effective interactions successfully characterizes the distribution of dynamical states of pulse-coupled networks in many fields, e.g., in neuroscience. To better understand the underlying mechanism, we found a relation between the dynamical structure, i.e., effective interactions in MEP analysis, and the anatomical coupling structure of pulse-coupled networks and it helps to understand how a sparse coupling structure could lead to a sparse coding by effective interactions. This relation quantitatively displays how the dynamical structure is closely related to the anatomical coupling structure.
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spelling pubmed-75141852020-11-09 Dynamical and Coupling Structure of Pulse-Coupled Networks in Maximum Entropy Analysis Xu, Zhi-Qin John Zhou, Douglas Cai, David Entropy (Basel) Article Maximum entropy principle (MEP) analysis with few non-zero effective interactions successfully characterizes the distribution of dynamical states of pulse-coupled networks in many fields, e.g., in neuroscience. To better understand the underlying mechanism, we found a relation between the dynamical structure, i.e., effective interactions in MEP analysis, and the anatomical coupling structure of pulse-coupled networks and it helps to understand how a sparse coupling structure could lead to a sparse coding by effective interactions. This relation quantitatively displays how the dynamical structure is closely related to the anatomical coupling structure. MDPI 2019-01-16 /pmc/articles/PMC7514185/ /pubmed/33266793 http://dx.doi.org/10.3390/e21010076 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xu, Zhi-Qin John
Zhou, Douglas
Cai, David
Dynamical and Coupling Structure of Pulse-Coupled Networks in Maximum Entropy Analysis
title Dynamical and Coupling Structure of Pulse-Coupled Networks in Maximum Entropy Analysis
title_full Dynamical and Coupling Structure of Pulse-Coupled Networks in Maximum Entropy Analysis
title_fullStr Dynamical and Coupling Structure of Pulse-Coupled Networks in Maximum Entropy Analysis
title_full_unstemmed Dynamical and Coupling Structure of Pulse-Coupled Networks in Maximum Entropy Analysis
title_short Dynamical and Coupling Structure of Pulse-Coupled Networks in Maximum Entropy Analysis
title_sort dynamical and coupling structure of pulse-coupled networks in maximum entropy analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514185/
https://www.ncbi.nlm.nih.gov/pubmed/33266793
http://dx.doi.org/10.3390/e21010076
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