## 6 Discussion and Future Work  
In this work, we introduced a novel perceptually motivated method for the suppression of auditory evoked EEG artifacts of rTMS under the name _\"Auditory Fine-Tuned Suppressor of TMS-Clicks\"_ (_TMS-click AFTS_). Herein, our hybrid approach features (a) psychophysically driven continuous wide-band noise (WBN) masking stimulus, matched to the TMS clicks' characteristics, (b) acoustic isolation of airborne/bone sound using insert earphones with highly effective insertion loss, (c) a complete adaptive procedure for optimal masking level determination and AEP reduction, together with a custom software for the automation and standardization of the procedure. All three features operate in tandem in order to provide a maximally efficient solution for AEP artifacts by reducing the subject's exposure both to the TMS click and the masking noise. The efficiency of the method to suppress the EEG's auditory artifact of the TMS clicks is remarkable across a wide range of stimulation intensities. In contrast to other related approaches [4], our suppressor contains only continuous acoustic signals (namely, we do not mix transients that mimic TMS-clicks) and follows a perceptual optimization-based parameter determination instead of free variation of several GUI variables, which can be of significant convenience for the clinical personnel and may offer the advantages of highly accurate subject individualization and efficiency. The current study reports on results for H-coils. Our preliminary data and results of application with 8-figure coils are also in line with the present findings. Regarding the relative contribution of bone-conducted vibration due to coil stimulation to the induced auditory excitation, our approach offers the possibility of also including vibratory data in the determination of the optimal acoustic suppressor. Under real TMS stimulation conditions, we observed a reduction in the vibratory component (especially with the air-bubble wrapping material) compared to the typical condition without any intermediate vibration isolation layer. The equivalent auditory excitation of this component was nevertheless shown to be much lower (\(<\)\(-\)30 dB) than that ofnits acoustic counterpart. However, this finding must be verified by further testing in a bigger sample of subjects and/or measurement setups. Figure 6: AEPs for the case of no mask (**first row**), use of auditory mask (**middle row**) and both (**bottom row**) for the different stimulation intensities (columns). The gray shaded patch corresponds to the time period of statistically significant difference between the AEPs for the comparison of stimulation vs. rest condition (**first and second row**), and stimulation with vs. without mask (**third row**). Regarding hearing safety, our computational procedure also takes into account the widely accepted standardized maximum permissible exposure levels (according to OSHA and NIOSH) in the generation and presentation of suppressor stimuli, thus ensuring minimal hearing burden. The overall subjects' judgement regarding comfort was very high. Currently, we are extending the presented framework of optimized analysis and individualization by implementing additional functionality (Figure 7), which further improves the efficiency of the computational approach beyond the ca. 20-40% reduction in CEA amplitudes (at stimulation intensities 30-70%) (Figure 5c) compared to the absence of the suppressor. We are also including measures of the subject's hearing acuity (such as PTA, etc.) ensuring the subject's hearing safety/comfort, completing the Automation Software and TMS machinery Interfacing, and employing ML for more precise control of pattern specification. These additional features are the subject of ongoing investigations.