English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/186464
Share/Impact:
Statistics
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

Title

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

AuthorsDel Ferraro, Gino; Abad, Diana; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C.; Holodny, Andrei; Canals Gamoneda, Santiago; Makse, Hernán A.
Issue Date3-Aug-2018
PublisherSpringer Nature
CitationNature Communications 9: 3156 (2018)
AbstractGlobal integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.
DescriptionCorrection to: Nature Communications https://doi.org/10.1038/s41467-018-04718-3; published online: 11 June 2018.
Publisher version (URL)https://doi.org/10.1038/s41467-018-05686-4
URIhttp://hdl.handle.net/10261/186464
DOI10.1038/s41467-018-05686-4
E-ISSN2041-1723
ReferencesDel Ferraro, Gino; Abad, Diana; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C.; Holodny, Andrei; Canals Gamoneda, Santiago; Makse, Hernán A. Finding influential nodes for integration in brain networks using optimal percolation theory. https://doi.org/10.1038/s41467-018-04718-3 http://hdl.handle.net/10261/186461
Appears in Collections:(IN) Artículos
Files in This Item:
File Description SizeFormat 
brain_networks_publisher_correction.pdf313,9 kBAdobe PDFView/Open
Show full item record
Review this work
 

Related articles:


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.