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Precise motor mapping with transcranial magnetic stimulation

Nature Protocols volume 18, pages 293–318 (2023)Cite this article

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Abstract

We describe a routine to precisely localize cortical muscle representations within the primary motor cortex with transcranial magnetic stimulation (TMS) based on the functional relation between induced electric fields at the cortical level and peripheral muscle activation (motor-evoked potentials; MEPs). Besides providing insights into structure–function relationships, this routine lays the foundation for TMS dosing metrics based on subject-specific cortical electric field thresholds. MEPs for different coil positions and orientations are combined with electric field modeling, exploiting the causal nature of neuronal activation to pinpoint the cortical origin of the MEPs. This involves constructing an individual head model using magnetic resonance imaging, recording MEPs via electromyography during TMS and computing the induced electric fields with numerical modeling. The cortical muscle representations are determined by relating the TMS-induced electric fields to the MEP amplitudes. Subsequently, the coil position to optimally stimulate the origin of the identified cortical MEP can be determined by numerical modeling. The protocol requires 2 h of manual preparation, 10 h for the automated head model construction, one TMS session lasting 2 h, 12 h of computational postprocessing and an optional second TMS session lasting 30 min. A basic level of computer science expertise and standard TMS neuronavigation equipment suffices to perform the protocol.

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Fig. 1: Overview of experimental design and general workflow.
Fig. 2: Example MRI data for subject_0 used for head model construction and field modeling.
Fig. 3: Initial subject data folder structure.
Fig. 4: MRI section of create_subject_0.py script.
Fig. 5: Mesh information in the create_subject_0.py script.
Fig. 6: ROI section in the create_subject_0.py script.
Fig. 7: Personalized 3D head model.
Fig. 8: Information of the refined mesh in the create_subject_0.py script.
Fig. 9: ROI information of the refined mesh in the create_subject_0.py script.
Fig. 10: Head models.
Fig. 11: Electrode placement for EMG recordings.
Fig. 12: Arbitrary coil positions/orientations over the motor cortex from the experiment.
Fig. 13: Experiment information in the create_subject_0.py script.
Fig. 14: Postprocessing of recorded EMG data.
Fig. 15: The goodness-of-fit distribution identifies the cortical MEP origin.
Fig. 16: The optimal coil position for rMT determination is identified.

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Data availability

We provide a full example dataset51 for one subject to follow along all steps in this protocol. These data are real experimental data and have been part of a previous study2. The dataset includes raw MRI data to construct a head model, EMG and TMS data, and also includes intermediate steps of the analysis pipeline and the final results. Figures 2, 10, 12 and 14–16 were generated using the example dataset51.

Code availability

All code51 needed to complete the localization procedure is presented at https://gitlab.gwdg.de/tms-localization/papers/tmsloc_proto.

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Acknowledgements

This work was partially supported by the German Science Foundation (DFG) (grant number WE 59851/2 to K.W.; HA 6314/9-1 to G.H.; KN 588/10-1 to T.K.; HA 2899/31-1 to J.H.), Lundbeckfonden (grant no. R244-2017-196 and R313-2019-622) and the NVIDIA Corporation (donation of two Titan Xp graphics cards to G.H. and K.W.).

Author information

Author notes

  1. Ole Numssen

    Present address: Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

  2. These authors contributed equally: Konstantin Weise, Ole Numssen, Gesa Hartwigsen and Thomas R. Knösche.

Authors and Affiliations

  1. Methods and Development Group ‘Brain Networks’, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

    Konstantin Weise, Benjamin Kalloch & Thomas R. Knösche

  2. Technische Universität Ilmenau, Advanced Electromagnetics Group, Ilmenau, Germany

    Konstantin Weise

  3. Technische Universität Ilmenau, Institute of Biomedical Engineering and Informatics, Ilmenau, Germany

    Benjamin Kalloch, Jens Haueisen & Thomas R. Knösche

  4. Institute of Medical Psychology, Medical Faculty, Goethe-University, Frankfurt/Main, Germany

    Anna Leah Zier

  5. Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark

    Axel Thielscher

  6. Technical University of Denmark, Center for Magnetic Resonance, Department of Health Technology, Kongens Lyngby, Denmark

    Axel Thielscher

  7. Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

    Gesa Hartwigsen

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Contributions

K.W. and O.N. developed the theory, wrote the code and carried out the simulations. B.K. contributed to the postprocessing and refinement of the head models. K.W. and O.N. conceived and planned the experiments. K.W., O.N., A.L.Z. and B.K. carried out the experiments. K.W., O.N., J.H. and A.T. contributed to the interpretation of the results. G.H, T.R.K, A.T. and J.H. supervised. A.T. and O.N. contributed to the developments of SimNIBS. K.W. and O.N. took the lead in writing the manuscript. K.W., O.N., T.R.K. and G.H. supervised the project. G.H., T.R.K., J.H., K.W. and A.T. obtained funding for this project. All authors provided critical feedback and helped to shape the research, analysis and manuscript.

Corresponding authors

Correspondence to Konstantin Weise or Ole Numssen.

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Nature Protocols thanks Petro Julkunen and Nicholas L. Balderston for their contribution to the peer review of this work.

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Key references using this protocol

Weise, K. et al. NeuroImage 209, 116486 (2020): https://doi.org/10.1016/j.neuroimage.2019.116486

Numssen, O. et al. NeuroImage 245, 118654 (2021): https://doi.org/10.1016/j.neuroimage.2021.118654

Key data used in this protocol

Numssen, O. et al. OSF (2022): https://doi.org/10.17605/OSF.IO/MYRQN

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Weise, K., Numssen, O., Kalloch, B. et al. Precise motor mapping with transcranial magnetic stimulation. Nat Protoc 18, 293–318 (2023). https://doi.org/10.1038/s41596-022-00776-6

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