Characterizing complex networks using entropy-degree diagrams: unveiling changes in functional brain connectivity induced by Ayahuasca

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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.contributor.funderDeutsche Forschungsgemeinschaften
dc.contributor.funderCoordenação de Aperfeiçoamento de Pessoal de Nível Superioren
dc.contributor.funderConselho Nacional de Desenvolvimento Científico e Tecnológicoen
dc.date.accessioned2020-04-28T11:46:09Z
dc.date.available2020-04-28T11:46:09Z
dc.date.issued2019-01-30
dc.date.updated2020-04-28T07:58:36Z
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.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.articleid128en
dc.identifier.citationViol, A., Palhano-Fontes, F., Onias, H., de Araujo, D. B., Hövell, P. and Viswanathan, G. M. (2019) 'Characterizing Complex Networks Using Entropy-Degree Diagrams: Unveiling Changes in Functional Brain Connectivity Induced by Ayahuasca', Entropy, 21, 128 (12 pp). doi: 10.3390/e21020128en
dc.identifier.doi10.3390/e21020128en
dc.identifier.endpage12en
dc.identifier.issn1099-4300
dc.identifier.issued2en
dc.identifier.journaltitleEntropyen
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/9882
dc.identifier.volume21en
dc.language.isoenen
dc.publisherMDPIen
dc.rights© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectEntropyen
dc.subjectFunctional brain networksen
dc.subjectPsychedelic stateen
dc.subjectAyahuascaen
dc.subjectComplex networksen
dc.titleCharacterizing complex networks using entropy-degree diagrams: unveiling changes in functional brain connectivity induced by Ayahuascaen
dc.typeArticle (peer-reviewed)en
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