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Database of 25 validated coil models for electric field simulations for TMS

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BACKGROUND: The effects of transcranial magnetic stimulation (TMS) on brain activity depend on the design of the stimulation coil. A wide range of coils from different vendors are currently used with different stimulation properties. This decreases the comparability of study results.

OBJECTIVE: To systematically compare widely used commercial TMS coils concerning their focality, stimulation depth and efficacy. To provide validated models and data of these coils for accurate simulations of the induced electric fields.

METHODS: We reconstructed the magnetic vector potential of 25 commercially available TMS coils of different vendors from measurements of their magnetic fields. Most coils had a figure-of-eight configuration. We employed the reconstructed magnetic vector potential in simulations of the electric field in a spherical head model. We estimated the motor thresholds of the coil-stimulator combinations using the calculated fields, the pulse waveforms and a leaky integrator model of the neural membrane.

RESULTS: Our results confirm a previously reported systematic trade-off between focality and relative depth of stimulation. However, neither the peak field strength in the "cortex" of the sphere model nor the estimated motor thresholds were strongly related to the two former measures and need to be additionally determined.

CONCLUSION: Our comprehensive coil characterization facilitates objective comparisons of coils of different sizes and from different vendors. The models and auxiliary data will be made available for electric field simulations in SimNIBS. Our work will support TMS users making an informed selection of a suited coil for a specific application and will help to reduce uncertainty regarding the TMS-induced electric field in the brain target region.

TidsskriftBrain Stimulation
Udgave nummer3
Sider (fra-til)697-706
Antal sider10
StatusUdgivet - 1 maj 2022

Bibliografisk note

Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

ID: 77845770