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Neuroimaging of Human Balance Control: A Systematic Review

This review examined 83 articles using neuroimaging modalities to investigate the neural correlates underlying static and dynamic human balance control, with aims to support future mobile neuroimaging research in the balance control domain. Furthermore, this review analyzed the mobility of the neuro...

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Autores principales: Wittenberg, Ellen, Thompson, Jessica, Nam, Chang S., Franz, Jason R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385364/
https://www.ncbi.nlm.nih.gov/pubmed/28443007
http://dx.doi.org/10.3389/fnhum.2017.00170
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author Wittenberg, Ellen
Thompson, Jessica
Nam, Chang S.
Franz, Jason R.
author_facet Wittenberg, Ellen
Thompson, Jessica
Nam, Chang S.
Franz, Jason R.
author_sort Wittenberg, Ellen
collection PubMed
description This review examined 83 articles using neuroimaging modalities to investigate the neural correlates underlying static and dynamic human balance control, with aims to support future mobile neuroimaging research in the balance control domain. Furthermore, this review analyzed the mobility of the neuroimaging hardware and research paradigms as well as the analytical methodology to identify and remove movement artifact in the acquired brain signal. We found that the majority of static balance control tasks utilized mechanical perturbations to invoke feet-in-place responses (27 out of 38 studies), while cognitive dual-task conditions were commonly used to challenge balance in dynamic balance control tasks (20 out of 32 studies). While frequency analysis and event related potential characteristics supported enhanced brain activation during static balance control, that in dynamic balance control studies was supported by spatial and frequency analysis. Twenty-three of the 50 studies utilizing EEG utilized independent component analysis to remove movement artifacts from the acquired brain signals. Lastly, only eight studies used truly mobile neuroimaging hardware systems. This review provides evidence to support an increase in brain activation in balance control tasks, regardless of mechanical, cognitive, or sensory challenges. Furthermore, the current body of literature demonstrates the use of advanced signal processing methodologies to analyze brain activity during movement. However, the static nature of neuroimaging hardware and conventional balance control paradigms prevent full mobility and limit our knowledge of neural mechanisms underlying balance control.
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spelling pubmed-53853642017-04-25 Neuroimaging of Human Balance Control: A Systematic Review Wittenberg, Ellen Thompson, Jessica Nam, Chang S. Franz, Jason R. Front Hum Neurosci Neuroscience This review examined 83 articles using neuroimaging modalities to investigate the neural correlates underlying static and dynamic human balance control, with aims to support future mobile neuroimaging research in the balance control domain. Furthermore, this review analyzed the mobility of the neuroimaging hardware and research paradigms as well as the analytical methodology to identify and remove movement artifact in the acquired brain signal. We found that the majority of static balance control tasks utilized mechanical perturbations to invoke feet-in-place responses (27 out of 38 studies), while cognitive dual-task conditions were commonly used to challenge balance in dynamic balance control tasks (20 out of 32 studies). While frequency analysis and event related potential characteristics supported enhanced brain activation during static balance control, that in dynamic balance control studies was supported by spatial and frequency analysis. Twenty-three of the 50 studies utilizing EEG utilized independent component analysis to remove movement artifacts from the acquired brain signals. Lastly, only eight studies used truly mobile neuroimaging hardware systems. This review provides evidence to support an increase in brain activation in balance control tasks, regardless of mechanical, cognitive, or sensory challenges. Furthermore, the current body of literature demonstrates the use of advanced signal processing methodologies to analyze brain activity during movement. However, the static nature of neuroimaging hardware and conventional balance control paradigms prevent full mobility and limit our knowledge of neural mechanisms underlying balance control. Frontiers Media S.A. 2017-04-10 /pmc/articles/PMC5385364/ /pubmed/28443007 http://dx.doi.org/10.3389/fnhum.2017.00170 Text en Copyright © 2017 Wittenberg, Thompson, Nam and Franz. 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) or licensor 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
Wittenberg, Ellen
Thompson, Jessica
Nam, Chang S.
Franz, Jason R.
Neuroimaging of Human Balance Control: A Systematic Review
title Neuroimaging of Human Balance Control: A Systematic Review
title_full Neuroimaging of Human Balance Control: A Systematic Review
title_fullStr Neuroimaging of Human Balance Control: A Systematic Review
title_full_unstemmed Neuroimaging of Human Balance Control: A Systematic Review
title_short Neuroimaging of Human Balance Control: A Systematic Review
title_sort neuroimaging of human balance control: a systematic review
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385364/
https://www.ncbi.nlm.nih.gov/pubmed/28443007
http://dx.doi.org/10.3389/fnhum.2017.00170
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