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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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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)] |
format | Online Article Text |
id | pubmed-6277805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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