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dc.creatorDeco, Gustavo-
dc.creatorTagliazucchi, Enzo Rodolfo-
dc.creatorLaufs, Helmut-
dc.creatorSanjuán, Ana-
dc.creatorKringelbach, Morten L.-
dc.date2018-08-15T18:23:39Z-
dc.date2018-08-15T18:23:39Z-
dc.date2017-09-
dc.date2018-08-10T17:47:38Z-
dc.date.accessioned2019-04-29T15:48:34Z-
dc.date.available2019-04-29T15:48:34Z-
dc.date.issued2017-09-
dc.identifierDeco, Gustavo; Tagliazucchi, Enzo Rodolfo; Laufs, Helmut; Sanjuán, Ana; Kringelbach, Morten L.; Novel intrinsic ignition method measuring local-global integration characterizes wakefulness and deep sleep; Society for Neuroscience; eNeuro; 4; 5; 9-2017; 1-12-
dc.identifier2373-2822-
dc.identifierhttp://hdl.handle.net/11336/55681-
dc.identifierCONICET Digital-
dc.identifierCONICET-
dc.identifier.urihttp://rodna.bn.gov.ar:8080/jspui/handle/bnmm/302616-
dc.descriptionA precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states.-
dc.descriptionFil: Deco, Gustavo. Universitat Pompeu Fabra; España-
dc.descriptionFil: Tagliazucchi, Enzo Rodolfo. Goethe Universitat Frankfurt; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina-
dc.descriptionFil: Laufs, Helmut. Goethe Universitat Frankfurt; Alemania-
dc.descriptionFil: Sanjuán, Ana. Universitat Pompeu Fabra; España-
dc.descriptionFil: Kringelbach, Morten L.. University of Oxford; Reino Unido. Institut D?études Avancées de Paris; . University Aarhus; Dinamarca-
dc.formatapplication/pdf-
dc.formatapplication/pdf-
dc.languageeng-
dc.publisherSociety for Neuroscience-
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1523/ENEURO.0106-17.2017-
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/-
dc.sourcereponame:CONICET Digital (CONICET)-
dc.sourceinstname:Consejo Nacional de Investigaciones Científicas y Técnicas-
dc.sourceinstacron:CONICET-
dc.source.urihttp://hdl.handle.net/11336/65338-
dc.subjectIGNITION-
dc.subjectINTEGRATION-
dc.subjectMETASTABILITY-
dc.subjectNEUROIMAGING-
dc.subjectWHOLE-BRAIN MODELING-
dc.subjectAstronomía-
dc.subjectCiencias Físicas-
dc.subjectCIENCIAS NATURALES Y EXACTAS-
dc.subjectOtras Ciencias Biológicas-
dc.subjectCiencias Biológicas-
dc.subjectCIENCIAS NATURALES Y EXACTAS-
dc.titleNovel intrinsic ignition method measuring local-global integration characterizes wakefulness and deep sleep-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.typeinfo:ar-repo/semantics/articulo-
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