TMS-EEG Indices to Define Local Cortical Excitability Thresholds
Rissanen, I. J.; Granö, I.; Souza, V. H.; Sathyan, S.; Thirugnanasambandam, N.; Ilmoniemi, R. J.; Lioumis, P.
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IntroductionTranscranial magnetic stimulation (TMS) is widely employed to treat various psychiatric and neurological disorders. However, TMS protocols typically rely on generalizations, particularly in selecting stimulation intensities, leading to suboptimal and variable outcomes. Combining TMS with electroencephalography (EEG) offers a potential solution by allowing direct monitoring of stimulation effects. In this study, we investigate how features of the TMS-EEG signal change with intensity to identify thresholds implying qualitative shifts in the brain response. MethodsWe stimulated eight subjects at both the primary motor cortex (M1) and the pre-supplementary motor area (pre-SMA) with navigated TMS at 15 closely spaced intensities and measured TMS-evoked EEG responses (TMS-evoked potential, TEP) with 60 trials per intensity. TEP thresholds were identified with three methods: by selecting the intensity where the TEP peak-to-peak exceeds 6 V, or by fitting either piecewise-linear or sigmoid curves into the power spectral density (PSD) frequency components to identify nonlinear intensity behavior. ResultsThe identified TEP thresholds varied depending on subject, target, and identification method. In M1, the thresholds attained with the fixed-amplitude and piecewise PSD fit methods averaged around the motor threshold, and in pre-SMA around 120% of the motor threshold. The TEP thresholds yielded by the sigmoid fit method were higher in intensity, and least consistent between subjects. ConclusionsOur findings support the hypothesis that detectable changes in EEG patterns occur at specific TMS intensities. These results provide a basis for individualized stimulation dosing, potentially enhancing therapeutic efficacy and reliability. Future research should focus on refining these methods and validating their clinical applicability across diverse conditions and patient populations.
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