J Neurosci Methods. 2022 Jan 28:109491. doi: 10.1016/j.jneumeth.2022.109491. Online ahead of print.
ABSTRACT
BACKGROUND: Coupling transcranial magnetic stimulation with electroencephalography (TMS-EEG) allows recording the EEG response to a direct, non-invasive cortical perturbation. However, obtaining a genuine TMS-evoked EEG potential requires controlling for several confounds, among which a main source is represented by the auditory evoked potentials (AEPs) associated to the TMS discharge noise (TMS click). This contaminating factor can be in principle prevented by playing a masking noise through earphones.
NEW METHOD: Here we release TMS Adaptable Auditory Control (TAAC), a highly flexible, open-source, Matlab®-based interface that generates in real-time customized masking noises. TAAC creates noises starting from the stimulator-specific TMS click and tailors them to fit the individual, subject-specific click perception by mixing a nd manipulating the standard noises in both time and frequency domains.
RESULTS: We showed that TAAC allows us to provide standard as well as customized noises able to effectively and safely mask the TMS click.
COMPARISON WITH EXISTING METHODS: Here, we showcased two customized noises by comparing them to two standard noises previously used in the TMS literature (i.e., a white noise and a noise generated from the stimulator-specific TMS click only). For each, we quantified the Sound Pressure Level (SPL; measured by a Head and Torso Simulator - HATS) required to mask the TMS click in a population of 20 healthy subjects. Both customized noises were effective at safe (according to OSHA and NIOSH safety guidelines), lower SPLs with respect to standard noises.
CONCLUSIONS: At odds with previous methods, TAAC allows creating effective and safe masking noises specifically tailored on each TMS device and subject. The combination of TAAC with tools for the real-time visuali zation of TEPs can help control the influence of auditory confounds also in non-compliant patients. Finally, TAAC is a highly flexible and open-source tool, so it can be further extended to meet different experimental requirements.
PMID:35101524 | DOI:10.1016/j.jneumeth.2022.109491
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