Abstract
TMS contaminates concurrent EEG recordings with Auditory Evoked Potentials (AEPs), which are caused by the perceived impulsive acoustic noise of the TMS coils. We hereby introduce a novel and perceptually motivated/tuned method for the suppression of auditory evoked EEG artifacts of rTMS under the name of “Auditory Fine-Tuned Suppressor of TMS-Clicks” (TMS-click AFTS). The proposed method is based on the deployment of a psychophysically-matched wide-band noise (WBN) masking stimulus, whose parametric synthesis and presentation are based upon adaptive psychophysical optimization. The masking stimulus is constructed individually for each patient/subject, thus facilitating aspects of precision medicine. A specially designed automation software is used for the realization of an adaptive procedure for optimal parameterization of masking noise level, optimizing both the subject’s comfort and the degree of AEP reduction. The proposed adaptive procedure also takes into account the combined effect of TMS intensity level and can as well account for any possibly available subject’s hearing acuity data. To assess the efficacy of the proposed method in reducing the acoustic effects of TMS, we performed TMS-EEG recordings with a 60 channel TMS-compatible EEG system in a cohort of healthy subjects (n = 10) and patients with epilepsy (n = 10) under four conditions (i.e., resting EEG with and without acoustic mask and sham TMS-EEG with and without acoustic mask at various stimulus intensity levels). The proposed approach shows promising results in terms of efficiency of AEP suppression and subject’s comfort and warrants further investigation in research and clinical settings.
Original language | English |
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Article number | 1047 |
Journal | Applied Sciences (Switzerland) |
Volume | 13 |
Issue number | 2 |
DOIs | |
State | Published - 1 Jan 2023 |
Keywords
- AEP suppression
- TMS-EEG
- acoustic artifact
ASJC Scopus subject areas
- General Materials Science
- Instrumentation
- General Engineering
- Process Chemistry and Technology
- Computer Science Applications
- Fluid Flow and Transfer Processes