Study Design for Navigated Repetitive Transcranial Magnetic Stimulation for Speech Cortical Mapping

Pantelis Lioumis, Salla Autti, Juha Wilenius, Selja Vaalto, Henri Lehtinen, Aki Laakso, Erika Kirveskari, Jyrki P. Mäkelä, Mia Liljeström, Hanna Renvall

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The cortical areas involved in human speech should be characterized reliably prior to surgery for brain tumors or drug-resistant epilepsy. The functional mapping of language areas for surgical decision-making is usually done invasively by electrical direct cortical stimulation (DCS), which is used to identify the organization of the crucial cortical and subcortical structures within each patient. Accurate preoperative non-invasive mapping aids surgical planning, reduces time, costs, and risks in the operating room, and provides an alternative for patients not suitable for awake craniotomy. Non-invasive imaging methods like MRI, fMRI, MEG, and PET are currently applied in presurgical design and planning. Although anatomical and functional imaging can identify the brain regions involved in speech, they cannot determine whether these regions are critical for speech. Transcranial magnetic stimulation (TMS) non-invasively excites the cortical neuronal populations by means of electric field induction in the brain. When applied in its repetitive mode (rTMS) to stimulate a speech-related cortical site, it can produce speech-related errors analogous to those induced by intraoperative DCS. rTMS combined with neuronavigation (nrTMS) enables neurosurgeons to preoperatively assess where these errors occur and to plan the DCS and the operation to preserve the language function. A detailed protocol is provided here for non-invasive speech cortical mapping (SCM) using nrTMS. The proposed protocol can be modified to best fit the patient- and site-specific demands. It can also be applied to language cortical network studies in healthy subjects or in patients with diseases that are not amenable to surgery.

Original languageEnglish
Article numbere64492
Pages (from-to)1-14
Number of pages14
JournalJournal of visualized experiments : JoVE
Issue number193
Publication statusPublished - 24 Mar 2023
MoE publication typeA1 Journal article-refereed


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