Auditory Fine-Tuned Suppressor of TMS-Clicks (TMS-Click AFTS): A Novel, Perceptually Driven/Tuned Approach for the Reduction in AEP Artifacts in TMS-EEG Studies
Source abstract
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.
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Research context
OpenAlex topics: Neural dynamics and brain function · Neuroscience and Music Perception · EEG and Brain-Computer Interfaces
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Fine Arts, Aristotle University of Thessaloniki, 57001 Thessaloniki, Greece
Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
1st Department of Neurology, Medical School, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
Brainsway Ltd., Jerusalem 9777518, Israel
Funding
GSRT and IIA
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