Evidence map›Paper›PMID 31597125›Full record

ArticleJournal of neural engineering2019

An exploration of neural dynamics of motor imagery for people with amyotrophic lateral sclerosis.

Sarah M Hosni, R J Deligani, A Zisk, J McLinden, S B Borgheai, Y Shahriari

Abstract read
In one paragraph

Article in Journal of neural engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Enhancing Communication for People in Late-Stage ALS Using an fNIRS-Based BCI System.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2020
    Article
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

6 authors.

Sarah M HosniDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States of America.
R J DeliganiDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States of America.
A ZiskInterdisciplinary Neuroscience Program, University of Rhode Island, Kingston, RI, United States of America.ORCID 0000-0003-2266-4855
J McLindenDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States of America.
S B BorgheaiDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States of America.ORCID 0000-0002-3164-6440
Y ShahriariDepartment of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States of America.ORCID 0000-0003-1640-0749

Funding

Training CoreP20GM103430 · NIGMS · UNIVERSITY OF RHODE ISLAND · PI Bongsup P Cho · 2012 to 2026
$63.6M
Training and DisseminationP41EB018783 · NIBIB · WADSWORTH CENTER · PI Theresa M. Vaughan · 2014 to 2026
$15.4M
NIBIB NIH HHS P41 EB018783NIGMS NIH HHS P20 GM103430
6 · The paper itself

Abstract

objectiveStudies of the neuropathological effects of amyotrophic lateral sclerosis (ALS) on the underlying motor system have investigated abnormalities in the magnitude and timing of the event-related desynchronization (ERD) and synchronization (ERS) during motor execution (ME). However, the spatio-spectral-temporal dynamics of these sensorimotor oscillations during motor imagery (MI) have not been fully explored for these patients. This study explores the neural dynamics of sensorimotor oscillations for ALS patients during MI by quantifying ERD/ERS features in frequency, time, and space. APPROACH: Electroencephalogram (EEG) data were recorded from six patients with ALS and 11 age-matched healthy controls (HC) while performing a MI task. ERD/ERS features were extracted using wavelet-based time-frequency analysis and compared between the two groups to quantify the abnormal neural dynamics of ALS in terms of both time and frequency. Topographic correlation analysis was conducted to compare the localization of MI activity between groups and to identify subject-specific frequencies in the µ and β frequency bands. MAIN

resultsOverall, reduced and delayed ERD was observed for ALS patients, particularly during right-hand MI. ERD features were also correlated with ALS clinical scores, specifically disease duration, bulbar, and cognitive functions. SIGNIFICANCE: The analyses in this study quantify abnormalities in the magnitude and timing of sensorimotor oscillations for ALS patients during MI tasks. Our findings reveal notable differences between MI and existing results on ME in ALS. The observed alterations are speculated to reflect disruptions in the underlying cortical networks involved in MI functions. Quantifying the neural dynamics of MI plays an important role in the study of EEG-based cortical markers for ALS.

Indexed as

Brain-Computer InterfacesAdultAgedAmyotrophic Lateral SclerosisElectroencephalographyFemaleHumansImaginationMaleMiddle AgedMotor CortexPhotic StimulationPsychomotor Performance

Identifiers

PMID31597125
PMCPMC7158070

What OpenQuestion holds

Textmetadata
LicenceTDM
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.