Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-8918
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dc.contributor.authorViol, Aline-
dc.contributor.authorPalhano-Fontes, Fernanda-
dc.contributor.authorOnias, Heloisa-
dc.contributor.authorde Araujo, Draulio B.-
dc.contributor.authorHövel, Philipp-
dc.contributor.authorViswanathan, Gandhi M.-
dc.date.accessioned2019-08-27T09:28:37Z-
dc.date.available2019-08-27T09:28:37Z-
dc.date.issued2019-01-30-
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/9906-
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-8918-
dc.description.abstractWith the aim of further advancing the understanding of the human brain’s functional connectivity, we propose a network metric which we term the geodesic entropy. This metric quantifies the Shannon entropy of the distance distribution to a specific node from all other nodes. It allows to characterize the influence exerted on a specific node considering statistics of the overall network structure. The measurement and characterization of this structural information has the potential to greatly improve our understanding of sustained activity and other emergent behaviors in networks. We apply this method to study how the psychedelic infusion Ayahuasca affects the functional connectivity of the human brain in resting state. We show that the geodesic entropy is able to differentiate functional networks of the human brain associated with two different states of consciousness in the awaking resting state: (i) the ordinary state and (ii) a state altered by ingestion of the Ayahuasca. The functional brain networks from subjects in the altered state have, on average, a larger geodesic entropy compared to the ordinary state. Finally, we discuss why the geodesic entropy may bring even further valuable insights into the study of the human brain and other empirical networks.en
dc.description.sponsorshipDFG, 163436311, SFB 910: Kontrolle selbstorganisierender nichtlinearer Systeme: Theoretische Methoden und Anwendungskonzepteen
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc570 Biowissenschaften; Biologiede
dc.subject.ddc003 Systemede
dc.subject.otherentropyen
dc.subject.otherfunctional brain networksen
dc.subject.otherpsychedelic stateen
dc.subject.otherAyahuascaen
dc.subject.othercomplex networksen
dc.titleCharacterizing Complex Networks Using Entropy-Degree Diagrams: Unveiling Changes in Functional Brain Connectivity Induced by Ayahuascaen
dc.typeArticleen
dc.date.updated2019-08-26T15:58:06Z-
tub.accessrights.dnbfreeen
tub.publisher.universityorinstitutionTechnische Universität Berlinen
dc.identifier.eissn1099-4300-
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.doi10.3390/e21020128en
dcterms.bibliographicCitation.journaltitleEntropyen
dcterms.bibliographicCitation.originalpublisherplaceBaselen
dcterms.bibliographicCitation.volume21en
dcterms.bibliographicCitation.originalpublishernameMDPIen
dcterms.bibliographicCitation.issue2en
dcterms.bibliographicCitation.articlenumber128en
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