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Multiscale Topological Properties Of Functional Brain Networks During Motor Imagery After Stroke

Authors :
Fallani, Fabrizio De Vico
Pichiorri, Floriana
Morone, Giovanni
Molinari, Marco
Babiloni, Fabio
Cincotti, Febo
Mattia, Donatella
Publication Year :
2013

Abstract

In recent years, network analyses have been used to evaluate brain reorganization following stroke. However, many studies have often focused on single topological scales, leading to an incomplete model of how focal brain lesions affect multiple network properties simultaneously and how changes on smaller scales influence those on larger scales. In an EEG-based experiment on the performance of hand motor imagery (MI) in 20 patients with unilateral stroke, we observed that the anatomic lesion affects the functional brain network on multiple levels. In the beta (13-30 Hz) frequency band, the MI of the affected hand (Ahand) elicited a significantly lower smallworldness and local efficiency (Eloc) versus the unaffected hand (Uhand). Notably, the abnormal reduction in Eloc significantly depended on the increase in interhemispheric connectivity, which was in turn determined primarily by the rise in regional connectivity in the parieto-occipital sites of the affected hemisphere. Further, in contrast to the Uhand MI, in which significantly high connectivity was observed for the contralateral sensorimotor regions of the unaffected hemisphere, the regions that increased in connection during the Ahand MI lay in the frontal and parietal regions of the contralaterally affected hemisphere. Finally, the overall sensorimotor function of our patients, as measured by Fugl-Meyer Assessment (FMA) index, was significantly predicted by the connectivity of their affected hemisphere. These results increase our understanding of stroke-induced alterations in functional brain networks.<br />Comment: Neuroimage, accepted manuscript (unedited version) available online 19-June-2013

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1306.5262
Document Type :
Working Paper
Full Text :
https://doi.org/10.1016/j.neuroimage.2013.06.039