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Evaluation of Changes in the Motor Network Following BCI Therapy Based on Graph Theory Analysis

Despite the established effectiveness of the brain-computer interface (BCI) therapy during stroke rehabilitation (Song et al., 2014a, 2015; Young et al., 2014a,b,c, 2015; Remsik et al., 2016), little is understood about the connections between motor network reorganization and functional motor improv...

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Autores principales: Mazrooyisebdani, Mohsen, Nair, Veena A., Loh, Po-Ling, Remsik, Alexander B., Young, Brittany M., Moreno, Brittany S., Dodd, Keith C., Kang, Theresa J., William, Justin C., Prabhakaran, Vivek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6277805/
https://www.ncbi.nlm.nih.gov/pubmed/30542258
http://dx.doi.org/10.3389/fnins.2018.00861
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author Mazrooyisebdani, Mohsen
Nair, Veena A.
Loh, Po-Ling
Remsik, Alexander B.
Young, Brittany M.
Moreno, Brittany S.
Dodd, Keith C.
Kang, Theresa J.
William, Justin C.
Prabhakaran, Vivek
author_facet Mazrooyisebdani, Mohsen
Nair, Veena A.
Loh, Po-Ling
Remsik, Alexander B.
Young, Brittany M.
Moreno, Brittany S.
Dodd, Keith C.
Kang, Theresa J.
William, Justin C.
Prabhakaran, Vivek
author_sort Mazrooyisebdani, Mohsen
collection PubMed
description Despite the established effectiveness of the brain-computer interface (BCI) therapy during stroke rehabilitation (Song et al., 2014a, 2015; Young et al., 2014a,b,c, 2015; Remsik et al., 2016), little is understood about the connections between motor network reorganization and functional motor improvements. The aim of this study was to investigate changes in the network reorganization of the motor cortex during BCI therapy. Graph theoretical approaches are used on resting-state functional magnetic resonance imaging (fMRI) data acquired from stroke patients to evaluate these changes. Correlations between changes in graph measurements and behavioral measurements were also examined. Right hemisphere chronic stroke patients (average time from stroke onset = 38.23 months, standard deviation (SD) = 46.27 months, n = 13, 6 males, 10 right-handed) with upper-extremity motor deficits received interventional rehabilitation therapy using a closed-loop neurofeedback BCI device. Eyes-closed resting-state fMRI (rs-fMRI) scans, along with T-1 weighted anatomical scans on 3.0T MRI scanners were collected from these patients at four test points. Immediate therapeutic effects were investigated by comparing pre and post-therapy results. Results displayed that th average clustering coefficient of the motor network increased significantly from pre to post-therapy. Furthermore, increased regional centrality of ipsilesional primary motor area (p = 0.02) and decreases in regional centrality of contralesional thalamus (p = 0.05), basal ganglia (p = 0.05 in betweenness centrality analysis and p = 0.03 for degree centrality), and dentate nucleus (p = 0.03) were observed (uncorrected). These findings suggest an overall trend toward significance in terms of involvement of these regions. Increased centrality of primary motor area may indicate increased efficiency within its interactive network as an effect of BCI therapy. Notably, changes in centrality of the bilateral cerebellum regions have strong correlations with both clinical variables [the Action Research Arm Test (ARAT), and the Nine-Hole Peg Test (9-HPT)]
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spelling pubmed-62778052018-12-12 Evaluation of Changes in the Motor Network Following BCI Therapy Based on Graph Theory Analysis Mazrooyisebdani, Mohsen Nair, Veena A. Loh, Po-Ling Remsik, Alexander B. Young, Brittany M. Moreno, Brittany S. Dodd, Keith C. Kang, Theresa J. William, Justin C. Prabhakaran, Vivek Front Neurosci Neuroscience Despite the established effectiveness of the brain-computer interface (BCI) therapy during stroke rehabilitation (Song et al., 2014a, 2015; Young et al., 2014a,b,c, 2015; Remsik et al., 2016), little is understood about the connections between motor network reorganization and functional motor improvements. The aim of this study was to investigate changes in the network reorganization of the motor cortex during BCI therapy. Graph theoretical approaches are used on resting-state functional magnetic resonance imaging (fMRI) data acquired from stroke patients to evaluate these changes. Correlations between changes in graph measurements and behavioral measurements were also examined. Right hemisphere chronic stroke patients (average time from stroke onset = 38.23 months, standard deviation (SD) = 46.27 months, n = 13, 6 males, 10 right-handed) with upper-extremity motor deficits received interventional rehabilitation therapy using a closed-loop neurofeedback BCI device. Eyes-closed resting-state fMRI (rs-fMRI) scans, along with T-1 weighted anatomical scans on 3.0T MRI scanners were collected from these patients at four test points. Immediate therapeutic effects were investigated by comparing pre and post-therapy results. Results displayed that th average clustering coefficient of the motor network increased significantly from pre to post-therapy. Furthermore, increased regional centrality of ipsilesional primary motor area (p = 0.02) and decreases in regional centrality of contralesional thalamus (p = 0.05), basal ganglia (p = 0.05 in betweenness centrality analysis and p = 0.03 for degree centrality), and dentate nucleus (p = 0.03) were observed (uncorrected). These findings suggest an overall trend toward significance in terms of involvement of these regions. Increased centrality of primary motor area may indicate increased efficiency within its interactive network as an effect of BCI therapy. Notably, changes in centrality of the bilateral cerebellum regions have strong correlations with both clinical variables [the Action Research Arm Test (ARAT), and the Nine-Hole Peg Test (9-HPT)] Frontiers Media S.A. 2018-11-27 /pmc/articles/PMC6277805/ /pubmed/30542258 http://dx.doi.org/10.3389/fnins.2018.00861 Text en Copyright © 2018 Mazrooyisebdani, Nair, Loh, Remsik, Young, Moreno, Dodd, Kang, William and Prabhakaran. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Mazrooyisebdani, Mohsen
Nair, Veena A.
Loh, Po-Ling
Remsik, Alexander B.
Young, Brittany M.
Moreno, Brittany S.
Dodd, Keith C.
Kang, Theresa J.
William, Justin C.
Prabhakaran, Vivek
Evaluation of Changes in the Motor Network Following BCI Therapy Based on Graph Theory Analysis
title Evaluation of Changes in the Motor Network Following BCI Therapy Based on Graph Theory Analysis
title_full Evaluation of Changes in the Motor Network Following BCI Therapy Based on Graph Theory Analysis
title_fullStr Evaluation of Changes in the Motor Network Following BCI Therapy Based on Graph Theory Analysis
title_full_unstemmed Evaluation of Changes in the Motor Network Following BCI Therapy Based on Graph Theory Analysis
title_short Evaluation of Changes in the Motor Network Following BCI Therapy Based on Graph Theory Analysis
title_sort evaluation of changes in the motor network following bci therapy based on graph theory analysis
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6277805/
https://www.ncbi.nlm.nih.gov/pubmed/30542258
http://dx.doi.org/10.3389/fnins.2018.00861
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