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Prediction of regional functional impairment following experimental stroke via connectome analysis

Recent advances in functional connectivity suggest that shared neuronal activation patterns define brain networks linking anatomically separate brain regions. We sought to investigate how cortical stroke disrupts multiple brain regions in processing spatial information. We conducted a connectome inv...

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Autores principales: Schmitt, O., Badurek, S., Liu, W., Wang, Y., Rabiller, G., Kanoke, A., Eipert, P., Liu, J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5390322/
https://www.ncbi.nlm.nih.gov/pubmed/28406178
http://dx.doi.org/10.1038/srep46316
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author Schmitt, O.
Badurek, S.
Liu, W.
Wang, Y.
Rabiller, G.
Kanoke, A.
Eipert, P.
Liu, J.
author_facet Schmitt, O.
Badurek, S.
Liu, W.
Wang, Y.
Rabiller, G.
Kanoke, A.
Eipert, P.
Liu, J.
author_sort Schmitt, O.
collection PubMed
description Recent advances in functional connectivity suggest that shared neuronal activation patterns define brain networks linking anatomically separate brain regions. We sought to investigate how cortical stroke disrupts multiple brain regions in processing spatial information. We conducted a connectome investigation at the mesoscale-level using the neuroVIISAS-framework, enabling the analysis of directed and weighted connectivity in bilateral hemispheres of cortical and subcortical brain regions. We found that spatial-exploration induced brain activation mapped by Fos, a proxy of neuronal activity, was differentially affected by stroke in a region-specific manner. The extent of hypoactivation following spatial exploration is inversely correlated with the spatial distance between the region of interest and region damaged by stroke, in particular within the parietal association and the primary somatosensory cortex, suggesting that the closer a region is to a stroke lesion, the more it would be affected during functional activation. Connectome modelling with 43 network parameters failed to reliably predict regions of hypoactivation in stroke rats exploring a novel environment, despite a modest correlation found for the centrality and hubness parameters in the home-caged animals. Further investigation in the inhibitory versus excitatory neuronal networks and microcircuit connectivity is warranted to improve the accuracy of predictability in post-stroke functional impairment.
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spelling pubmed-53903222017-04-14 Prediction of regional functional impairment following experimental stroke via connectome analysis Schmitt, O. Badurek, S. Liu, W. Wang, Y. Rabiller, G. Kanoke, A. Eipert, P. Liu, J. Sci Rep Article Recent advances in functional connectivity suggest that shared neuronal activation patterns define brain networks linking anatomically separate brain regions. We sought to investigate how cortical stroke disrupts multiple brain regions in processing spatial information. We conducted a connectome investigation at the mesoscale-level using the neuroVIISAS-framework, enabling the analysis of directed and weighted connectivity in bilateral hemispheres of cortical and subcortical brain regions. We found that spatial-exploration induced brain activation mapped by Fos, a proxy of neuronal activity, was differentially affected by stroke in a region-specific manner. The extent of hypoactivation following spatial exploration is inversely correlated with the spatial distance between the region of interest and region damaged by stroke, in particular within the parietal association and the primary somatosensory cortex, suggesting that the closer a region is to a stroke lesion, the more it would be affected during functional activation. Connectome modelling with 43 network parameters failed to reliably predict regions of hypoactivation in stroke rats exploring a novel environment, despite a modest correlation found for the centrality and hubness parameters in the home-caged animals. Further investigation in the inhibitory versus excitatory neuronal networks and microcircuit connectivity is warranted to improve the accuracy of predictability in post-stroke functional impairment. Nature Publishing Group 2017-04-13 /pmc/articles/PMC5390322/ /pubmed/28406178 http://dx.doi.org/10.1038/srep46316 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Schmitt, O.
Badurek, S.
Liu, W.
Wang, Y.
Rabiller, G.
Kanoke, A.
Eipert, P.
Liu, J.
Prediction of regional functional impairment following experimental stroke via connectome analysis
title Prediction of regional functional impairment following experimental stroke via connectome analysis
title_full Prediction of regional functional impairment following experimental stroke via connectome analysis
title_fullStr Prediction of regional functional impairment following experimental stroke via connectome analysis
title_full_unstemmed Prediction of regional functional impairment following experimental stroke via connectome analysis
title_short Prediction of regional functional impairment following experimental stroke via connectome analysis
title_sort prediction of regional functional impairment following experimental stroke via connectome analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5390322/
https://www.ncbi.nlm.nih.gov/pubmed/28406178
http://dx.doi.org/10.1038/srep46316
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