The rt-TEP tool: real-time visualization of TMS-Evoked Potential to maximize cortical activation and minimize artifacts

Abstract

Background The impact of transcranial magnetic stimulation (TMS) on cortical neurons is currently hard to predict based on a priori biophysical and anatomical knowledge alone. This problem can hamper the reliability and reproducibility of protocols aimed at measuring electroencephalographic (EEG) responses to TMS. New Method We introduce and release a novel software tool to facilitate and standardize the acquisition of TMS-evoked potentials (TEPs). The tool, rt-TEP (real-time TEP), interfaces with different EEG amplifiers and offers a series of informative visualization modes to assess in real time the immediate impact of TMS on the underlying neuronal circuits. Results We show that rt-TEP can be used to abolish or minimize magnetic and muscle artifacts contaminating the post-stimulus period thus affording a clear visualization and quantification of the amplitude of the early (<50 ms) EEG response after averaging a limited number of trials. This real-time readout can then be used to adjust TMS parameters (e.g. site, orientation, intensity) and experimental settings (e.g. loudness and/or spectral features of the noise masking) to ultimately maximize direct cortical effects over the undesired sensory effects of the coil's discharge. Comparison with Existing Methods The ensemble of real-time visualization modes of rt-TEP are not implemented in any current commercial software and provide a key readout to titrate TMS parameters beyond the a priori information provided by anatomical models. Conclusions Real-time optimization of stimulation parameters with rt-TEP can facilitate the acquisition of reliable TEPs with a high signal-to-noise ratio and improve the standardization and reproducibility of data collection across laboratories.

TAAC - TMS Adaptable Auditory Control: a universal tool to mask TMS click

“…In case of patients unable to report their perception (e.g., disorders of consciousness, infants, newborns), TAAC can be associated with tools for the real-time visualization of evoked potentials (Casarotto et al, 2021) as in our electrophysiological proof-ofconcept. This way, the experimenter can document in real time whether the AEP is present (typically characterized by the N100 and P200 components -Fig.…”

“…As a proof of concept for the efficacy of the proposed masking noise in abolishing the AEP during TMS-EEG experiments, we performed a sham TMS-EEG recording session in subject 4. This experiment also serves as an example of how TAAC can be associated with a real-time interface for TMS-EEG (Casarotto et al, 2021) to ensure the lack of auditory confounds. Specifically, we acquired one EEG session while delivering sham TMS without noise masking (as null control) and one EEG session during the supply of customized noise generated with TAAC (CN1 administered at the minimum SPL at which the subject did not report any TMS click).…”

“…Step 3: Noise parameterization Fine masking of the TMS click can be achieved by tuning the features of the noise on the perception of the TMS click of each subject by adjusting the noise parameters (See supplementary methods) based on the real-time subject's feedback and/or on the presence of the AEP (Casarotto et al, 2021). In this manner, TAAC can be useful to mask TMS clicks also in non-compliant subjects.…”

“…The TMS evoked EEG potential (TEP) reflects the activation of cortical neurons underneath the TMS coil to the extent that confounding factors are effectively controlled for (Belardinelli et al, 2019;Conde et al, 2019). Specifically, while electromagnetic artifacts can be controlled by optimizing the experimental setup, TEPs can be still contaminated by undesired biological activationssome of which can be identified and minimized in real-time such as muscle artifacts (Casarotto et al, 2021). In addition to these more easy-to-control confounds, TMS pulses vibrate the coil, thus generating a tapping sensation on the scalp and a loud noise denoted as TMS click that may result in sensory-related activations (Conde et al, 2019;Miniussi and Thut, 2010;Nikouline et al, 1999;Rogasch et al, 2014).…”

Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback

“…Procedures for selecting initial stimulation parameters in TMS-EEG measurements by visually inspecting averaged EEG responses and manually adjusting the TMS settings have been applied, e.g., in Refs. [27][28][29] to acquire highquality, artifact-free TEPs. There are, however, also other situations, such as selecting stimulus parameters for TMS treatments, that could benefit from EEG-based targeting.…”