出版商更正：使用最优渗流理论寻找大脑网络整合中的有影响力节点。

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

作者信息

Del Ferraro Gino, Moreno Andrea, Min Byungjoon, Morone Flaviano, Pérez-Ramírez Úrsula, Pérez-Cervera Laura, Parra Lucas C, Holodny Andrei, Canals Santiago, Makse Hernán A

机构信息

Levich Institute and Physics Department, City College of New York, New York, NY, 10031, USA.

Instituto de Neurociencias, CSIC and UMH, 03550, San Juan de Alicante, Spain.

出版信息

Nat Commun. 2018 Aug 3;9(1):3156. doi: 10.1038/s41467-018-05686-4.

DOI:10.1038/s41467-018-05686-4

PMID:30076304

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6076313/

Abstract

The original version of this Article contained an error in the last sentence of the first paragraph of the Introduction, which incorrectly read 'Correlation of brain activity is typically measured using functional magnetic resonance imaging (fMRI), and the correlation structure is often referred to as "fu'. The correct version states 'referred to as "functional connectivity"' in place of 'referred to as "fu'. This has been corrected in both the PDF and HTML versions of the Article.

摘要

本文的原始版本在引言第一段的最后一句话中存在错误，原句错误地表述为“大脑活动的相关性通常使用功能磁共振成像（fMRI）来测量，并且相关结构通常被称为‘fu’”。正确的表述是“被称为‘功能连接性’”，而不是“被称为‘fu’”。本文的PDF版本和HTML版本均已对此进行了更正。