Evidence map›Paper›PMID 38235854›Full record

ArticleEuropean journal of neurology2024

Electroencephalographic β-band oscillations in the sensorimotor network reflect motor symptom severity in amyotrophic lateral sclerosis.

Stefan Dukic, Antonio Fasano, Amina Coffey, Teresa Buxó, Roisin McMackin, Rangariroyashe Chipika, Mark Heverin, Peter Bede, Muthuraman Muthuraman, Madeleine Lowery and 3 more

Open access · goldAbstract read
In one paragraph

Article in European journal of neurology, 2024. 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
4.1field-weighted citation impact, top 6% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

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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

13 authors at 5 institutions in 4 countries.

Stefan DukicAcademic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland.
Antonio FasanoAcademic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland.ORCID 0000-0002-8727-9141
Amina CoffeyAcademic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland.
Teresa BuxóAcademic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland.
Roisin McMackinAcademic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland.
Rangariroyashe ChipikaAcademic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland.
Mark HeverinAcademic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland.
Peter BedeComputational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland.
Muthuraman MuthuramanNeural Engineering With Signal Analytics and Artificial Intelligence, Department of Neurology, University of Würzburg, Würzburg, Germany.
Madeleine LowerySchool of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland.
Richard G CarsonTrinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, University of Dublin, Dublin, Ireland.
Orla HardimanAcademic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland.
Bahman NasseroleslamiAcademic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland.ORCID 0000-0002-2227-2176
Trinity College Dublin · IEQueen's University Belfast · GBUniversity College Dublin · IEUniversity of Würzburg · DEUtrecht University · NL

Funding

Science Foundation Ireland 16/ERCD/3854Wellcome Trust
6 · The paper itself

Abstract

background and purposeResting-state electroencephalography (EEG) holds promise for assessing brain networks in amyotrophic lateral sclerosis (ALS). We investigated whether neural β-band oscillations in the sensorimotor network could serve as an objective quantitative measure of progressive motor impairment and functional disability in ALS patients.

methodsResting-state EEG was recorded in 18 people with ALS and 38 age- and gender-matched healthy controls. We estimated source-localized β-band spectral power in the sensorimotor cortex. Clinical evaluation included lower (LMN) and upper motor neuron scores, Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised score, fine motor function (FMF) subscore, and progression rate. Correlations between clinical scores and β-band power were analysed and corrected using a false discovery rate of q = 0.05.

resultsβ-Band power was significantly lower in people with ALS than controls (p = 0.004), and correlated with LMN score (R = -0.65, p = 0.013), FMF subscore (R = -0.53, p = 0.036), and FMF progression rate (R = 0.52, p = 0.036).

conclusionsβ-Band spectral power in the sensorimotor cortex reflects clinically evaluated motor impairment in ALS. This technology merits further investigation as a biomarker of progressive functional disability.

Indexed as

Amyotrophic Lateral SclerosisBrainBrain MappingElectroencephalographyHumansMotor Neuronsamyotrophic lateral sclerosisbiomarkerelectroencephalography

Identifiers

PMID38235854
PMCPMC11235881
OpenAlexW4390975155

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.