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Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface
Stroke is a leading cause of motor disability worldwide. Upper limb rehabilitation is particularly challenging since approximately 35% of patients recover significant hand function after 6 months of the stroke's onset. Therefore, new therapies, especially those based on brain-computer interface...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6487113/ https://www.ncbi.nlm.nih.gov/pubmed/31110515 http://dx.doi.org/10.1155/2019/7084618 |
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author | Carino-Escobar, Ruben I. Carrillo-Mora, Paul Valdés-Cristerna, Raquel Rodriguez-Barragan, Marlene A. Hernandez-Arenas, Claudia Quinzaños-Fresnedo, Jimena Galicia-Alvarado, Marlene A. Cantillo-Negrete, Jessica |
author_facet | Carino-Escobar, Ruben I. Carrillo-Mora, Paul Valdés-Cristerna, Raquel Rodriguez-Barragan, Marlene A. Hernandez-Arenas, Claudia Quinzaños-Fresnedo, Jimena Galicia-Alvarado, Marlene A. Cantillo-Negrete, Jessica |
author_sort | Carino-Escobar, Ruben I. |
collection | PubMed |
description | Stroke is a leading cause of motor disability worldwide. Upper limb rehabilitation is particularly challenging since approximately 35% of patients recover significant hand function after 6 months of the stroke's onset. Therefore, new therapies, especially those based on brain-computer interfaces (BCI) and robotic assistive devices, are currently under research. Electroencephalography (EEG) acquired brain rhythms in alpha and beta bands, during motor tasks, such as motor imagery/intention (MI), could provide insight of motor-related neural plasticity occurring during a BCI intervention. Hence, a longitudinal analysis of subacute stroke patients' brain rhythms during a BCI coupled to robotic device intervention was performed in this study. Data of 9 stroke patients were acquired across 12 sessions of the BCI intervention. Alpha and beta event-related desynchronization/synchronization (ERD/ERS) trends across sessions and their association with time since stroke onset and clinical upper extremity recovery were analyzed, using correlation and linear stepwise regression, respectively. More EEG channels presented significant ERD/ERS trends across sessions related with time since stroke onset, in beta, compared to alpha. Linear models implied a moderate relationship between alpha rhythms in frontal, temporal, and parietal areas with upper limb motor recovery and suggested a strong association between beta activity in frontal, central, and parietal regions with upper limb motor recovery. Higher association of beta with both time since stroke onset and upper limb motor recovery could be explained by beta relation with closed-loop communication between the sensorimotor cortex and the paralyzed upper limb, and alpha being probably more associated with motor learning mechanisms. The association between upper limb motor recovery and beta activations reinforces the hypothesis that broader regions of the cortex activate during movement tasks as a compensatory mechanism in stroke patients with severe motor impairment. Therefore, EEG across BCI interventions could provide valuable information for prognosis and BCI cortical activity targets. |
format | Online Article Text |
id | pubmed-6487113 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-64871132019-05-20 Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface Carino-Escobar, Ruben I. Carrillo-Mora, Paul Valdés-Cristerna, Raquel Rodriguez-Barragan, Marlene A. Hernandez-Arenas, Claudia Quinzaños-Fresnedo, Jimena Galicia-Alvarado, Marlene A. Cantillo-Negrete, Jessica Neural Plast Research Article Stroke is a leading cause of motor disability worldwide. Upper limb rehabilitation is particularly challenging since approximately 35% of patients recover significant hand function after 6 months of the stroke's onset. Therefore, new therapies, especially those based on brain-computer interfaces (BCI) and robotic assistive devices, are currently under research. Electroencephalography (EEG) acquired brain rhythms in alpha and beta bands, during motor tasks, such as motor imagery/intention (MI), could provide insight of motor-related neural plasticity occurring during a BCI intervention. Hence, a longitudinal analysis of subacute stroke patients' brain rhythms during a BCI coupled to robotic device intervention was performed in this study. Data of 9 stroke patients were acquired across 12 sessions of the BCI intervention. Alpha and beta event-related desynchronization/synchronization (ERD/ERS) trends across sessions and their association with time since stroke onset and clinical upper extremity recovery were analyzed, using correlation and linear stepwise regression, respectively. More EEG channels presented significant ERD/ERS trends across sessions related with time since stroke onset, in beta, compared to alpha. Linear models implied a moderate relationship between alpha rhythms in frontal, temporal, and parietal areas with upper limb motor recovery and suggested a strong association between beta activity in frontal, central, and parietal regions with upper limb motor recovery. Higher association of beta with both time since stroke onset and upper limb motor recovery could be explained by beta relation with closed-loop communication between the sensorimotor cortex and the paralyzed upper limb, and alpha being probably more associated with motor learning mechanisms. The association between upper limb motor recovery and beta activations reinforces the hypothesis that broader regions of the cortex activate during movement tasks as a compensatory mechanism in stroke patients with severe motor impairment. Therefore, EEG across BCI interventions could provide valuable information for prognosis and BCI cortical activity targets. Hindawi 2019-04-14 /pmc/articles/PMC6487113/ /pubmed/31110515 http://dx.doi.org/10.1155/2019/7084618 Text en Copyright © 2019 Ruben I. Carino-Escobar et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Carino-Escobar, Ruben I. Carrillo-Mora, Paul Valdés-Cristerna, Raquel Rodriguez-Barragan, Marlene A. Hernandez-Arenas, Claudia Quinzaños-Fresnedo, Jimena Galicia-Alvarado, Marlene A. Cantillo-Negrete, Jessica Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface |
title | Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface |
title_full | Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface |
title_fullStr | Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface |
title_full_unstemmed | Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface |
title_short | Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface |
title_sort | longitudinal analysis of stroke patients' brain rhythms during an intervention with a brain-computer interface |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6487113/ https://www.ncbi.nlm.nih.gov/pubmed/31110515 http://dx.doi.org/10.1155/2019/7084618 |
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