PloS One

<article class="align-center media media--type-link media--view-mode-default"><div class="field field--name-field-media-entity-link field--type-link field--label-hidden field__item"><a href="https://doi.org/10.1371/journal.pone.0084612" target="_blank">9, e84612</a></div>
 
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Biological motion coding in the brain: extracting local properties from visually-driven EEG functional networks

Biological motion coding in the brain: extracting local properties from visually-driven EEG functional networks - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0084612

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.

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Biological motion coding in the brain: extracting local properties from visually-driven EEG functional networks

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