Using a TMS Navigation System for High-Precision Digitization of Sensor Locations to Improve Source Localization

Source localization is a technique used to estimate the sources of brain activity based on signals recorded from the scalp. Accurate source localization critically depends on the precise spatial digitization of sensor locations. In this protocol, we present a practical and reliable method for digitizing sensor locations using the Navigated Brain Stimulation (NBS) system. NBS is a component of Transcranial Magnetic Stimulation (TMS) equipment commonly available in TMS laboratories, but rarely utilized for sensor digitization of electroencephalography (EEG) or functional near-infrared spectroscopy (fNIRS) systems. This approach allows researchers to leverage existing infrastructure to significantly improve the spatial accuracy of source modeling, without investing in dedicated digitization equipment. We guide viewers through the full workflow: (1) digitizing EEG electrode locations using default tools of the Nexstim NBS system; (2) exporting coordinate data in compatible formats; (3) integrating this data into EEG preprocessing and source localization pipelines using the MNE-Python package. The protocol also includes tips for aligning digitized data with MRI images and optimizing coregistration accuracy. To illustrate the method's practical utility, we apply it to analyze data from a tactile stimulation experiment. Custom Python scripts for coordinate processing and coregistration are provided to ensure reproducibility and ease of adoption. The results show that incorporating digitized electrode positions remarkably improves the anatomical accuracy and interpretability of cortical source estimates compared to default electrode montages.