Evidence map›Paper›PMID 26529119›Full record

ArticleJournal of neural engineering2015

Effects of training pre-movement sensorimotor rhythms on behavioral performance.

Dennis J McFarland, William A Sarnacki, Jonathan R Wolpaw

Registry-linked trialAbstract read
In one paragraph

Article in Journal of neural engineering, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05345301 (Electroencephalographic Correlates of Glove-stretch Therapy Post-stroke), which is not on this map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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.

NCT05345301 nacompletednot on this mapstarted 2022, after this paper: background citation

Electroencephalographic Correlates of Glove-stretch Therapy Post-stroke

TypeinterventionalSponsorShirley Ryan AbilityLabRan2022 to 2022Enrolled10ConditionsStrokeArmsEvent related desynchronization measurement
3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Article
  6. Enhancing neurorehabilitation by targeting beneficial plasticity.Frontiers in rehabilitation sciences · 2023
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Modulation of Beta Bursts in the Subthalamic Nucleus Predicts Motor Performance.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018
    Article
  12. Article
  13. Article
  14. EEG-Based Brain-Computer Interfaces.Current opinion in biomedical engineering · 2017
    Article
  15. Sensorimotor rhythm neurofeedback as adjunct therapy for Parkinson's disease.Annals of clinical and translational neurology · 2017
    Article
  16. Article
  17. Article
  18. Therapeutic Applications of BCI Technologies.Brain computer interfaces (Abingdon, England) · 2017
    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

3 authors.

Dennis J McFarlandNational Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, PO box509, Empire State Plaza, Albany, NY 12201-0509, USA.
William A Sarnacki
Jonathan R Wolpaw

Funding

Training and DisseminationP41EB018783 · NIBIB · WADSWORTH CENTER · PI Theresa M. Vaughan · 2014 to 2026
$15.4M
GENERAL PURPOSE BRAIN-COMPUTER INTERFACE(BCI)SYSTEMR01EB000856 · NIBIB · WADSWORTH CENTER · PI SCHALK, GERWIN, WOLPAW, JONATHAN RICKEL · 2002 to 2012
$9.3M
EEG-BASED BRAIN-COMPUTER INTERFACER01HD030146 · NICHD · WADSWORTH CENTER · PI WOLPAW, JONATHAN RICKEL · 1992 to 2003
$1.5M
NIBIB NIH HHS 1P41EB018783NIBIB NIH HHS EB00856NIBIB NIH HHS P41 EB018783NIBIB NIH HHS R01 EB000856NICHD NIH HHS HD30146NICHD NIH HHS R01 HD030146
6 · The paper itself

Abstract

objectiveBrain-computer interface (BCI) technology might contribute to rehabilitation of motor function. This speculation is based on the premise that modifying the electroencephalographic (EEG) activity will modify behavior, a proposition for which there is limited empirical data. The present study asked whether learned modulation of pre-movement sensorimotor rhythm (SMR) activity can affect motor performance in normal human subjects. APPROACH: Eight individuals first performed a joystick-based cursor-movement task with variable warning periods. Targets appeared randomly on a video monitor and subjects moved the cursor to the target and pressed a select button within 2 s. SMR features in the pre-movement EEG that correlated with performance speed and accuracy were identified. The subjects then learned to increase or decrease these features to control a two-target BCI task. Following successful BCI training, they were asked to increase or decrease SMR amplitude in order to initiate the joystick task. MAIN

resultsAfter BCI training, pre-movement SMR amplitude was correlated with performance in subjects with initial poor performance: lower amplitude was associated with faster and more accurate movement. The beneficial effect on performance of lower SMR amplitude was greater in subjects with lower initial performance levels. SIGNIFICANCE: These results indicate that BCI-based SMR training can affect a standard motor behavior. They provide a rationale for studies that integrate such training into rehabilitation protocols and examine its capacity to enhance restoration of useful motor function.

Indexed as

Brain-Computer InterfacesAdultElectroencephalographyFemaleHumansMaleMiddle AgedMovementPhotic StimulationPsychomotor PerformanceSensorimotor Cortex

Identifiers

PMID26529119
PMCPMC4843806

What OpenQuestion holds

Textmetadata
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Registered trials

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.