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dc.contributor.author
Fraiman Borrazás, Daniel Edmundo
dc.contributor.author
Saunier, Ghislain
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Martins, Eduardo F.
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Vargas, Claudia D.
dc.date.available
2019-10-11T18:53:21Z
dc.date.issued
2014-01
dc.identifier.citation
Fraiman Borrazás, Daniel Edmundo; Saunier, Ghislain; Martins, Eduardo F.; Vargas, Claudia D.; Biological motion coding in the brain: Analysis of visually driven EEG functional networks; Public Library of Science; Plos One; 9; 1; 1-2014; 1-9
dc.identifier.issn
1932-6203
dc.identifier.uri
http://hdl.handle.net/11336/85763
dc.description.abstract
Herein, we address the time evolution of brain functional networks computed from electroencephalographic activity driven by visual stimuli. We describe how these functional network signatures change in fast scale when confronted with point-light display stimuli depicting biological motion (BM) as opposed to scrambled motion (SM). Whereas global network measures (average path length, average clustering coefficient, and average betweenness) computed as a function of time did not discriminate between BM and SM, local node properties did. Comparing the network local measures of the BM condition with those of the SM condition, we found higher degree and betweenness values in the left frontal (F7) electrode, as well as a higher clustering coefficient in the right occipital (O2) electrode, for the SM condition. Conversely, for the BM condition, we found higher degree values in central parietal (Pz) electrode and a higher clustering coefficient in the left parietal (P3) electrode. These results are discussed in the context of the brain networks involved in encoding BM versus SM.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Public Library of Science
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
EEG functional networks
dc.subject
biological motion
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Otras Ciencias Físicas
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Ciencias Físicas
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CIENCIAS NATURALES Y EXACTAS
dc.title
Biological motion coding in the brain: Analysis of visually driven EEG functional networks
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-10-07T17:58:05Z
dc.journal.volume
9
dc.journal.number
1
dc.journal.pagination
1-9
dc.journal.pais
Estados Unidos
dc.journal.ciudad
San Francisco
dc.description.fil
Fil: Fraiman Borrazás, Daniel Edmundo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina
dc.description.fil
Fil: Saunier, Ghislain. Universidade Federal do Rio de Janeiro; Brasil
dc.description.fil
Fil: Martins, Eduardo F.. Universidade Federal do Rio de Janeiro; Brasil
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Fil: Vargas, Claudia D.. Universidade Federal do Rio de Janeiro; Brasil
dc.journal.title
Plos One
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1371/journal.pone.0084612
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0084612
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