Finding influential nodes for integration in brain networks using optimal percolation theory

Complex networks can be used to model brain networks. Here the authors identify the essential nodes in a model of a brain network and then validate these predictions by means of in vivo pharmacogenetic interventions. They find that the nucleus accumbens is a central region for brain integration.

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Autores principales:	Gino Del Ferraro, Andrea Moreno, Byungjoon Min, Flaviano Morone, Úrsula Pérez-Ramírez, Laura Pérez-Cervera, Lucas C. Parra, Andrei Holodny, Santiago Canals, Hernán A. Makse
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/2aba73d66c5a4dc486c162f42c3f7d99
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spelling	oai:doaj.org-article:2aba73d66c5a4dc486c162f42c3f7d992021-12-02T16:49:22ZFinding influential nodes for integration in brain networks using optimal percolation theory10.1038/s41467-018-04718-32041-1723https://doaj.org/article/2aba73d66c5a4dc486c162f42c3f7d992018-06-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-04718-3https://doaj.org/toc/2041-1723Complex networks can be used to model brain networks. Here the authors identify the essential nodes in a model of a brain network and then validate these predictions by means of in vivo pharmacogenetic interventions. They find that the nucleus accumbens is a central region for brain integration.Gino Del FerraroAndrea MorenoByungjoon MinFlaviano MoroneÚrsula Pérez-RamírezLaura Pérez-CerveraLucas C. ParraAndrei HolodnySantiago CanalsHernán A. MakseNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-12 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Gino Del Ferraro Andrea Moreno Byungjoon Min Flaviano Morone Úrsula Pérez-Ramírez Laura Pérez-Cervera Lucas C. Parra Andrei Holodny Santiago Canals Hernán A. Makse Finding influential nodes for integration in brain networks using optimal percolation theory
description	Complex networks can be used to model brain networks. Here the authors identify the essential nodes in a model of a brain network and then validate these predictions by means of in vivo pharmacogenetic interventions. They find that the nucleus accumbens is a central region for brain integration.
format	article
author	Gino Del Ferraro Andrea Moreno Byungjoon Min Flaviano Morone Úrsula Pérez-Ramírez Laura Pérez-Cervera Lucas C. Parra Andrei Holodny Santiago Canals Hernán A. Makse
author_facet	Gino Del Ferraro Andrea Moreno Byungjoon Min Flaviano Morone Úrsula Pérez-Ramírez Laura Pérez-Cervera Lucas C. Parra Andrei Holodny Santiago Canals Hernán A. Makse
author_sort	Gino Del Ferraro
title	Finding influential nodes for integration in brain networks using optimal percolation theory
title_short	Finding influential nodes for integration in brain networks using optimal percolation theory
title_full	Finding influential nodes for integration in brain networks using optimal percolation theory
title_fullStr	Finding influential nodes for integration in brain networks using optimal percolation theory
title_full_unstemmed	Finding influential nodes for integration in brain networks using optimal percolation theory
title_sort	finding influential nodes for integration in brain networks using optimal percolation theory
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/2aba73d66c5a4dc486c162f42c3f7d99
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Finding influential nodes for integration in brain networks using optimal percolation theory

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