Evidence map›Paper›PMID 31073791›Full record

ArticleBrain topography2019

Accuracy of Estimating the Area of Cortical Muscle Representations from TMS Mapping Data Using Voronoi Diagrams.

Andrey Yu Chernyavskiy, Dmitry O Sinitsyn, Alexandra G Poydasheva, Ilya S Bakulin, Natalia A Suponeva, Michael A Piradov

Abstract read
PubMed Publisher
In one paragraph

Article in Brain topography, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Andrey Yu ChernyavskiyResearch Center of Neurology, Moscow, Russia, 125367. andrey.chernyavskiy@gmail.com.ORCID http://orcid.org/0000-0001-8768-5855
Dmitry O SinitsynResearch Center of Neurology, Moscow, Russia, 125367.ORCID http://orcid.org/0000-0001-9951-9803
Alexandra G PoydashevaResearch Center of Neurology, Moscow, Russia, 125367.ORCID http://orcid.org/0000-0003-1841-1177
Ilya S BakulinResearch Center of Neurology, Moscow, Russia, 125367.ORCID http://orcid.org/0000-0003-0716-3737
Natalia A SuponevaResearch Center of Neurology, Moscow, Russia, 125367.ORCID http://orcid.org/0000-0003-3956-6362
Michael A PiradovResearch Center of Neurology, Moscow, Russia, 125367.ORCID http://orcid.org/0000-0002-6338-0392

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motor evoked potentials (MEPs) caused by transcranial magnetic stimulation (TMS) provide a possibility of noninvasively mapping cortical muscle representations for clinical and research purposes. The interpretation of such results is complicated by the high variability in MEPs and the lack of a standard optimal mapping protocol. Comparing protocols requires the determination of the accuracy of estimated representation parameters (such as the area), which is problematic without ground truth data. We addressed this problem and obtained two main results: (1) the development of a bootstrapping-based approach for estimating the within-session variability and bias of representation parameters and (2) estimations of the area and amplitude-weighted area accuracies for motor representations using this approach. The method consists in the simulation of TMS mapping results by subsampling MEPs from a single map with a large number of stimuli. We studied the extensor digitorum communis (EDC) and flexor digitorum superficialis (FDS) muscle maps of 15 healthy subjects processed using Voronoi diagrams. We calculated the (decreasing) dependency of the errors in the area and weighted area on the number of stimuli. This result can be used to choose a number of stimuli sufficient for studying the effects of a given size (e.g., the protocol with 150 stimuli leads to relative errors of 7% for the area and 11% for the weighted area in 90% of the maps). The approach is applicable to other parameters (e.g., the center of gravity) and other map processing methods, such as spline interpolation.

Indexed as

AlgorithmsMuscle, SkeletalAdultBrain MappingElectromyographyEvoked Potentials, MotorFemaleHandHealthy VolunteersHumansMaleMotor CortexTranscranial Magnetic StimulationCortical muscle representation mappingMotor cortex mappingMotor evoked potentialStatistical bootstrappingTMSVoronoi diagram

Identifiers

What OpenQuestion holds

Textmetadata
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.