Evidence map›Paper›PMID 35919931›Full record

ArticleBrain and behavior2022

Managing electromyogram contamination in scalp recordings: An approach identifying reliable beta and gamma EEG features of psychoses or other disorders.

Kenneth J Pope, Trent W Lewis, Sean P Fitzgibbon, Azin S Janani, Tyler S Grummett, Patricia A H Williams, Malcolm Battersby, Tarun Bastiampillai, Emma M Whitham, John O Willoughby

Abstract read
In one paragraph

Article in Brain and behavior, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Closed-Loop Systems and Real-Time Neurofeedback in Mindfulness Meditation Research.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025
    Review
  5. Article
  6. Review
  7. Article
  8. 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

10 authors.

Kenneth J PopeCollege of Science and Engineering, Flinders University, Adelaide, South Australia, Australia.
Trent W LewisCollege of Science and Engineering, Flinders University, Adelaide, South Australia, Australia.
Sean P FitzgibbonWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Azin S JananiCollege of Science and Engineering, Flinders University, Adelaide, South Australia, Australia.
Tyler S GrummettCollege of Science and Engineering, Flinders University, Adelaide, South Australia, Australia.
Patricia A H WilliamsCollege of Science and Engineering, Flinders University, Adelaide, South Australia, Australia.
Malcolm BattersbyCollege of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia.
Tarun BastiampillaiCollege of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia.
Emma M WhithamCollege of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia.
John O WilloughbyCollege of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia.ORCID 0000-0003-0457-7117

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveIn publications on the electroencephalographic (EEG) features of psychoses and other disorders, various methods are utilized to diminish electromyogram (EMG) contamination. The extent of residual EMG contamination using these methods has not been recognized. Here, we seek to emphasize the extent of residual EMG contamination of EEG.

methodsWe compared scalp electrical recordings after applying different EMG-pruning methods with recordings of EMG-free data from 6 fully paralyzed healthy subjects. We calculated the ratio of the power of pruned, normal scalp electrical recordings in the six subjects, to the power of unpruned recordings in the same subjects when paralyzed. We produced "contamination graphs" for different pruning methods.

resultsEMG contamination exceeds EEG signals progressively more as frequencies exceed 25 Hz and with distance from the vertex. In contrast, Laplacian signals are spared in central scalp areas, even to 100 Hz.

conclusionGiven probable EMG contamination of EEG in psychiatric and other studies, few findings on beta- or gamma-frequency power can be relied upon. Based on the effectiveness of current methods of EEG de-contamination, investigators should be able to reanalyze recorded data, reevaluate conclusions from high-frequency EEG data, and be aware of limitations of the methods.

Indexed as

Psychotic DisordersScalpElectroencephalographyElectromyographyHumansEEGEMG contaminationpsychosesspectral analysis

Identifiers

PMID35919931
PMCPMC9480942

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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.