Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function

What determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical ex...

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Main Authors: Aurore Thibaut, Marcel Simis, Linamara Rizzo Battistella, Chiara Fanciullacci, Federica Bertolucci, Rodrigo Huerta-Gutierrez, Carmelo Chisari, Felipe Fregni
Format: Article
Language:English
Published: Frontiers Media S.A. 2017-05-01
Series:Frontiers in Neurology
Subjects:
EEG
Online Access:http://journal.frontiersin.org/article/10.3389/fneur.2017.00187/full
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spelling doaj-0c473333af1d4fd3ba9174cf905315602020-11-24T23:47:49ZengFrontiers Media S.A.Frontiers in Neurology1664-22952017-05-01810.3389/fneur.2017.00187261298Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor FunctionAurore Thibaut0Marcel Simis1Linamara Rizzo Battistella2Chiara Fanciullacci3Federica Bertolucci4Rodrigo Huerta-Gutierrez5Rodrigo Huerta-Gutierrez6Carmelo Chisari7Felipe Fregni8Neuromodulation Center, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USAInstitute of Physical and Rehabilitation Medicine, University of Sao Paulo Medical School, Sao Paulo, BrazilInstitute of Physical and Rehabilitation Medicine, University of Sao Paulo Medical School, Sao Paulo, BrazilUnit of Neurorehabilitation, University Hospital of Pisa, Pisa, ItalyUnit of Neurorehabilitation, University Hospital of Pisa, Pisa, ItalyNeuromodulation Center, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USAFaculty of Medicine, National Autonomous University of Mexico, Mexico City, MexicoUnit of Neurorehabilitation, University Hospital of Pisa, Pisa, ItalyNeuromodulation Center, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USAWhat determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical excitability (transcranial magnetic stimulation—TMS) and brain oscillations (electroencephalography—EEG). In this cross-sectional study, 55 subjects with chronic stroke (62 ± 14 yo, 17 women, 32 ± 42 months post-stroke) were recruited in two sites. We analyzed TMS measures (i.e., motor threshold—MT—of the affected and unaffected sides) and EEG variables (i.e., power spectrum in different frequency bands and different brain regions of the affected and unaffected hemispheres) and their correlation with motor impairment as measured by Fugl-Meyer. Multiple univariate and multivariate linear regression analyses were performed to identify the predictors of good motor function. A significant interaction effect of MT in the affected hemisphere and power in beta bandwidth over the central region for both affected and unaffected hemispheres was found. We identified that motor function positively correlates with beta rhythm over the central region of the unaffected hemisphere, while it negatively correlates with beta rhythm in the affected hemisphere. Our results suggest that cortical activity in the affected and unaffected hemisphere measured by EEG provides new insights on the association between high-frequency rhythms and motor impairment, highlighting the role of an excess of beta in the affected central cortical region in poor motor function in stroke recovery.http://journal.frontiersin.org/article/10.3389/fneur.2017.00187/fullstrokemotor functionrecoveryEEGbeta oscillationsbiomarker
collection DOAJ
language English
format Article
sources DOAJ
author Aurore Thibaut
Marcel Simis
Linamara Rizzo Battistella
Chiara Fanciullacci
Federica Bertolucci
Rodrigo Huerta-Gutierrez
Rodrigo Huerta-Gutierrez
Carmelo Chisari
Felipe Fregni
spellingShingle Aurore Thibaut
Marcel Simis
Linamara Rizzo Battistella
Chiara Fanciullacci
Federica Bertolucci
Rodrigo Huerta-Gutierrez
Rodrigo Huerta-Gutierrez
Carmelo Chisari
Felipe Fregni
Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function
Frontiers in Neurology
stroke
motor function
recovery
EEG
beta oscillations
biomarker
author_facet Aurore Thibaut
Marcel Simis
Linamara Rizzo Battistella
Chiara Fanciullacci
Federica Bertolucci
Rodrigo Huerta-Gutierrez
Rodrigo Huerta-Gutierrez
Carmelo Chisari
Felipe Fregni
author_sort Aurore Thibaut
title Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function
title_short Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function
title_full Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function
title_fullStr Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function
title_full_unstemmed Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function
title_sort using brain oscillations and corticospinal excitability to understand and predict post-stroke motor function
publisher Frontiers Media S.A.
series Frontiers in Neurology
issn 1664-2295
publishDate 2017-05-01
description What determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical excitability (transcranial magnetic stimulation—TMS) and brain oscillations (electroencephalography—EEG). In this cross-sectional study, 55 subjects with chronic stroke (62 ± 14 yo, 17 women, 32 ± 42 months post-stroke) were recruited in two sites. We analyzed TMS measures (i.e., motor threshold—MT—of the affected and unaffected sides) and EEG variables (i.e., power spectrum in different frequency bands and different brain regions of the affected and unaffected hemispheres) and their correlation with motor impairment as measured by Fugl-Meyer. Multiple univariate and multivariate linear regression analyses were performed to identify the predictors of good motor function. A significant interaction effect of MT in the affected hemisphere and power in beta bandwidth over the central region for both affected and unaffected hemispheres was found. We identified that motor function positively correlates with beta rhythm over the central region of the unaffected hemisphere, while it negatively correlates with beta rhythm in the affected hemisphere. Our results suggest that cortical activity in the affected and unaffected hemisphere measured by EEG provides new insights on the association between high-frequency rhythms and motor impairment, highlighting the role of an excess of beta in the affected central cortical region in poor motor function in stroke recovery.
topic stroke
motor function
recovery
EEG
beta oscillations
biomarker
url http://journal.frontiersin.org/article/10.3389/fneur.2017.00187/full
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