Optimization of the Navigated TMS Mapping Algorithm for Accurate Estimation of Cortical Muscle Representation Characteristics

Navigated transcranial magnetic stimulation (nTMS) mapping of cortical muscle representations allows noninvasive assessment of the state of a healthy or diseased motor system, and monitoring changes over time. These applications are hampered by the heterogeneity of existing mapping algorithms and th...

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Bibliographic Details
Published in:Brain sciences 2019-04, Vol.9 (4), p.88
Main Authors: Sinitsyn, Dmitry O, Chernyavskiy, Andrey Yu, Poydasheva, Alexandra G, Bakulin, Ilya S, Suponeva, Natalia A, Piradov, Michael A
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
bootstrapping
Brain research
cortical muscle representation
Data analysis
Experiments
Magnetic fields
Magnetic resonance imaging
Mapping
Methods
Morphology
Motor evoked potentials
Muscles
navigated transcranial magnetic stimulation
Sampling
Software
TMS motor mapping
Transcranial magnetic stimulation
variability
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Summary:Navigated transcranial magnetic stimulation (nTMS) mapping of cortical muscle representations allows noninvasive assessment of the state of a healthy or diseased motor system, and monitoring changes over time. These applications are hampered by the heterogeneity of existing mapping algorithms and the lack of detailed information about their accuracy. We aimed to find an optimal motor evoked potential (MEP) sampling scheme in the grid-based mapping algorithm in terms of the accuracy of muscle representation parameters. The abductor pollicis brevis (APB) muscles of eight healthy subjects were mapped three times on consecutive days using a seven-by-seven grid with ten stimuli per cell. The effect of the MEP variability on the parameter accuracy was assessed using bootstrapping. The accuracy of representation parameters increased with the number of stimuli without saturation up to at least ten stimuli per cell. The detailed sampling showed that the between-session representation area changes in the absence of interventions were significantly larger than the within-session fluctuations and thus could not be explained solely by the trial-to-trial variability of MEPs. The results demonstrate that the number of stimuli has no universally optimal value and must be chosen by balancing the accuracy requirements with the mapping time constraints in a given problem.
ISSN:2076-3425
2076-3425
DOI:10.3390/brainsci9040088