2024-03-28T17:52:55Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1864642021-12-27T16:32:15Zcom_10261_133com_10261_1col_10261_386
2019-07-22T09:03:04Z
urn:hdl:10261/186464
Publisher Correction: Finding influential nodes for integration in brain networks using optimal percolation theory
Del 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.
National Science Foundation (US)
National Institutes of Health (US)
Ministerio de Economía y Competitividad (España)
European Commission
Ministerio de Educación, Cultura y Deporte (España)
Correction to: Nature Communications https://doi.org/10.1038/s41467-018-04718-3; published online: 11 June 2018.
Global 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.
2019-07-22T09:03:04Z
2019-07-22T09:03:04Z
2018-08-03
artículo
Nature Communications 9: 3156 (2018)
http://hdl.handle.net/10261/186464
10.1038/s41467-018-05686-4
2041-1723
http://dx.doi.org/10.13039/501100003329
http://dx.doi.org/10.13039/100000002
http://dx.doi.org/10.13039/501100003176
http://dx.doi.org/10.13039/501100000780
http://dx.doi.org/10.13039/100000001
30076304
eng
Publisher's version
Del 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
https://doi.org/10.1038/s41467-018-05686-4
Sí
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/BFU2015-64380-C2-1-R
info:eu-repo/grantAgreement/EC/H2020/668863
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/SEV-2013-0317
http://creativecommons.org/licenses/by/4.0/
openAccess
Springer Nature