Biological motion coding in the brain: analysis of visually driven EEG functional networks.

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 op...

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Main Authors: Daniel Fraiman, Ghislain Saunier, Eduardo F Martins, Claudia D Vargas
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24454734/pdf/?tool=EBI
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spelling doaj-ab6ae88941354533b1c60b2238f9a79f2021-03-03T20:17:05ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0191e8461210.1371/journal.pone.0084612Biological motion coding in the brain: analysis of visually driven EEG functional networks.Daniel FraimanGhislain SaunierEduardo F MartinsClaudia D VargasHerein, 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.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24454734/pdf/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Daniel Fraiman
Ghislain Saunier
Eduardo F Martins
Claudia D Vargas
spellingShingle Daniel Fraiman
Ghislain Saunier
Eduardo F Martins
Claudia D Vargas
Biological motion coding in the brain: analysis of visually driven EEG functional networks.
PLoS ONE
author_facet Daniel Fraiman
Ghislain Saunier
Eduardo F Martins
Claudia D Vargas
author_sort Daniel Fraiman
title Biological motion coding in the brain: analysis of visually driven EEG functional networks.
title_short Biological motion coding in the brain: analysis of visually driven EEG functional networks.
title_full Biological motion coding in the brain: analysis of visually driven EEG functional networks.
title_fullStr Biological motion coding in the brain: analysis of visually driven EEG functional networks.
title_full_unstemmed Biological motion coding in the brain: analysis of visually driven EEG functional networks.
title_sort biological motion coding in the brain: analysis of visually driven eeg functional networks.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description 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.
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24454734/pdf/?tool=EBI
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