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dc.creatorTadić, Bosiljka
dc.creatorAnđelković, Miroslav
dc.creatorBoshkoska, Biljana Mileva
dc.creatorLevnajic, Zoran
dc.date.accessioned2018-03-01T17:15:28Z
dc.date.available2018-03-01T17:15:28Z
dc.date.issued2016
dc.identifier.issn1932-6203 (print)
dc.identifier.urihttp://vinar.vin.bg.ac.rs/handle/123456789/1322
dc.description.abstractHuman behaviour in various circumstances mirrors the corresponding brain connectivity patterns, which are suitably represented by functional brain networks. While the objective analysis of these networks by graph theory tools deepened our understanding of brain functions, the multi-brain structures and connections underlying human social behaviour remain largely unexplored. In this study, we analyse the aggregate graph that maps coordination of EEG signals previously recorded during spoken communications in two groups of six listeners and two speakers. Applying an innovative approach based on the algebraic topology of graphs, we analyse higher-order topological complexes consisting of mutually interwoven cliques of a high order to which the identified functional connections organise. Our results reveal that the topological quantifiers provide new suitable measures for differences in the brain activity patterns and inter-brain synchronisation between speakers and listeners. Moreover, the higher topological complexity correlates with the listeners concentration to the story, confirmed by self-rating, and closeness to the speakers brain activity pattern, which is measured by network-to-network distance. The connectivity structures of the frontal and parietal lobe consistently constitute distinct clusters, which extend across the listeners group. Formally, the topology quantifiers of the multi-brain communities exceed the sum of those of the participating individuals and also reflect the listeners rated attributes of the speaker and the narrated subject. In the broader context, the presented study exposes the relevance of higher topological structures ( besides standard graph measures) for characterising functional brain networks under different stimuli.en
dc.relationinfo:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/174014/RS//
dc.relationResearch Agency of the Republic of Slovenia [P1-0044, P1-0388, P1-0383, J1-5454, L2-7663], European Cooperation in Science and Technology [KNOWeSCAPE TD1210], Horizon [COSMOS 642563]
dc.rightsopenAccessen
dc.sourcePLoS Oneen
dc.titleAlgebraic Topology of Multi-Brain Connectivity Networks Reveals Dissimilarity in Functional Patterns during Spoken Communicationsen
dc.typearticleen
dcterms.abstractБосхкоска, Биљана Милева; Aнђелковић Мирослав; Левнајиц, Зоран; Тадиц, Босиљка;
dc.citation.volume11
dc.citation.issue11
dc.identifier.wos000388889500033
dc.identifier.doi10.1371/journal.pone.0166787
dc.citation.otherArticle Number: e0166787
dc.citation.rankM21
dc.identifier.pmid27880802
dc.identifier.scopus2-s2.0-84996482954
dc.identifier.fulltexthttp://vinar.rcub.bg.ac.rs/bitstream/handle/123456789/1322/journal.pone.0166787.pdf


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