Modelling a multiplex brain network by local transfer entropy

Abstract This paper deals with the information transfer mechanisms underlying causal relations between brain regions under resting condition. fMRI images of a large set of healthy individuals from the 1000 Functional Connectomes Beijing Zang dataset have been considered and the causal information tr...

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Autores principales:	Fabrizio Parente, Alfredo Colosimo
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6c408427bbb14fa6b3bc4124bf6427f0
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spelling	oai:doaj.org-article:6c408427bbb14fa6b3bc4124bf6427f02021-12-02T16:24:22ZModelling a multiplex brain network by local transfer entropy10.1038/s41598-021-93190-z2045-2322https://doaj.org/article/6c408427bbb14fa6b3bc4124bf6427f02021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93190-zhttps://doaj.org/toc/2045-2322Abstract This paper deals with the information transfer mechanisms underlying causal relations between brain regions under resting condition. fMRI images of a large set of healthy individuals from the 1000 Functional Connectomes Beijing Zang dataset have been considered and the causal information transfer among brain regions studied using Transfer Entropy concepts. Thus, we explored the influence of a set of states in two given regions at time t (At Bt.) over the state of one of them at a following time step (Bt+1) and could observe a series of time-dependent events corresponding to four kinds of interactions, or causal rules, pointing to (de)activation and turn off mechanisms and sharing some features with positive and negative functional connectivity. The functional architecture emerging from such rules was modelled by a directional multilayer network based upon four interaction matrices and a set of indexes describing the effects of the network structure in several dynamical processes. The statistical significance of the models produced by our approach was checked within the used database of homogeneous subjects and predicts a successful extension, in due course, to detect differences among clinical conditions and cognitive states.Fabrizio ParenteAlfredo ColosimoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-23 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Fabrizio Parente Alfredo Colosimo Modelling a multiplex brain network by local transfer entropy
description	Abstract This paper deals with the information transfer mechanisms underlying causal relations between brain regions under resting condition. fMRI images of a large set of healthy individuals from the 1000 Functional Connectomes Beijing Zang dataset have been considered and the causal information transfer among brain regions studied using Transfer Entropy concepts. Thus, we explored the influence of a set of states in two given regions at time t (At Bt.) over the state of one of them at a following time step (Bt+1) and could observe a series of time-dependent events corresponding to four kinds of interactions, or causal rules, pointing to (de)activation and turn off mechanisms and sharing some features with positive and negative functional connectivity. The functional architecture emerging from such rules was modelled by a directional multilayer network based upon four interaction matrices and a set of indexes describing the effects of the network structure in several dynamical processes. The statistical significance of the models produced by our approach was checked within the used database of homogeneous subjects and predicts a successful extension, in due course, to detect differences among clinical conditions and cognitive states.
format	article
author	Fabrizio Parente Alfredo Colosimo
author_facet	Fabrizio Parente Alfredo Colosimo
author_sort	Fabrizio Parente
title	Modelling a multiplex brain network by local transfer entropy
title_short	Modelling a multiplex brain network by local transfer entropy
title_full	Modelling a multiplex brain network by local transfer entropy
title_fullStr	Modelling a multiplex brain network by local transfer entropy
title_full_unstemmed	Modelling a multiplex brain network by local transfer entropy
title_sort	modelling a multiplex brain network by local transfer entropy
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/6c408427bbb14fa6b3bc4124bf6427f0
work_keys_str_mv	AT fabrizioparente modellingamultiplexbrainnetworkbylocaltransferentropy AT alfredocolosimo modellingamultiplexbrainnetworkbylocaltransferentropy
_version_	1718384115574636544

Modelling a multiplex brain network by local transfer entropy

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