Evidence map›Paper›PMID 38487552›Full record

ArticleBrain communications2024

Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia.

Zhenghao Guo, Jean-Pierre Lin, Osvaldo Simeone, Kerry R Mills, Zoran Cvetkovic, Verity M McClelland

Open access · goldAbstract read
In one paragraph

Article in Brain communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. 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 at 2 institutions in 2 countries.

Zhenghao GuoDepartment of Engineering, King's College London, London WC2R 2LS, UK.ORCID https://orcid.org/0000-0002-1726-4251
Jean-Pierre LinChildren's Neuroscience, Evelina London Children's Hospital, Guy's & St Thomas' NHS Foundation Trust (GSTT), London SE1 7EH, UK.
Osvaldo SimeoneDepartment of Engineering, King's College London, London WC2R 2LS, UK.
Kerry R MillsDepartment of Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London SE5 9RX, UK.
Zoran CvetkovicDepartment of Engineering, King's College London, London WC2R 2LS, UK.
Verity M McClellandChildren's Neuroscience, Evelina London Children's Hospital, Guy's & St Thomas' NHS Foundation Trust (GSTT), London SE1 7EH, UK.
King's College London · GBGuy's and St Thomas' NHS Foundation Trust · GB

Funding

Medical Research Council MR/P006868/1Medical Research Council MR/W015692/1
6 · The paper itself

Abstract

Sensory processing and sensorimotor integration are abnormal in dystonia, including impaired modulation of beta-corticomuscular coherence. However, cortex-muscle interactions in either direction are rarely described, with reports limited predominantly to investigation of linear coupling, using corticomuscular coherence or Granger causality. Information-theoretic tools such as transfer entropy detect both linear and non-linear interactions between processes. This observational case-control study applies transfer entropy to determine intra- and cross-frequency cortex-muscle coupling in young people with dystonia/dystonic cerebral palsy. Fifteen children with dystonia/dystonic cerebral palsy and 13 controls, aged 12-18 years, performed a grasp task with their dominant hand. Mechanical perturbations were provided by an electromechanical tapper. Bipolar scalp EEG over contralateral sensorimotor cortex and surface EMG over first dorsal interosseous were recorded. Multi-scale wavelet transfer entropy was applied to decompose signals into functional frequency bands of oscillatory activity and to quantify intra- and cross-frequency coupling between brain and muscle. Statistical significance against the null hypothesis of zero transfer entropy was established, setting individual 95% confidence thresholds. The proportion of individuals in each group showing significant transfer entropy for each frequency combination/direction was compared using Fisher's exact test, correcting for multiple comparisons. Intra-frequency transfer entropy was detected in all participants bidirectionally in the beta (16-32 Hz) range and in most participants from EEG to EMG in the alpha (8-16 Hz) range. Cross-frequency transfer entropy across multiple frequency bands was largely similar between groups, but a specific coupling from low-frequency EMG to beta EEG was significantly reduced in dystonia [

Indexed as

cross-frequency couplingmulti-scale wavelet transfer entropyneuronal oscillationssensorimotor processingspectral analysis

Identifiers

PMID38487552
PMCPMC10939448
OpenAlexW4392153596

What OpenQuestion holds

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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.