Evidence map›Paper›PMID 28443007›Full record

ReviewFrontiers in human neuroscience2017

Neuroimaging of Human Balance Control: A Systematic Review.

Ellen Wittenberg, Jessica Thompson, Chang S Nam, Jason R Franz

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in human neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 6 pooled it
5.9field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

80 citing papers in PubMed, 6 syntheses or guidelines pooled it, 167 citations in OpenAlex.

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  5. Therapeutic benefits of lower limb prostheses: a systematic review.Journal of neuroengineering and rehabilitation · 2023
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20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Ellen WittenbergEdward P. Fitts Department of Industrial and Systems Engineering, North Carolina State UniversityRaleigh, NC, USA.
Jessica ThompsonJoint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State UniversityChapel Hill, NC, USA.
Chang S NamEdward P. Fitts Department of Industrial and Systems Engineering, North Carolina State UniversityRaleigh, NC, USA.
Jason R FranzJoint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State UniversityChapel Hill, NC, USA.
North Carolina State University · USUniversity of North Carolina at Chapel Hill · US

Funding

North Carolina Translational & Clinical Sciences Institute (NC TraCS)UL1TR001111 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, CAREY, TIMOTHY S · 2013 to 2017
$43.9M
NCATS NIH HHS UL1 TR001111
6 · The paper itself

Abstract

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.

Indexed as

mechanical perturbationmovement artifactssensory degradationstatic and dynamic balance controlsusceptibility to cognitive dual taskstemporal and spatial dynamics of brain activation

Identifiers

PMID28443007
PMCPMC5385364
OpenAlexW2604383662

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.