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Electroencephalography (EEG) measures the brain's electrical activity at the scalp, but the raw recordings mix signals from many brain and non-brain sources. Source localization refers to computationally estimating where in the brain the measured EEG signals originate, effectively "mapping" scalp voltages back to cortical regions1. These methods let researchers link EEG oscillatory activity or event-related responses to specific brain areas, greatly enhancing EEG's interpretability. Achieving accurate source localization critically depends on knowing exactly where each electrode sits on the head relative to the anatomy. We must digitize the electrode positions to record their exact 3D locations on the head. These coordinates are then coregistered, or aligned, with the subject's MRI-derived head model for solving the EEG forward (predicting scalp voltages) and inverse (estimating brain sources) problems. Precise electrode placement is essential: even small digitization errors can shift the estimated source by up to a few centimeters or more in the brain.
Modern EEG source imaging is a multi-step process that integrates anatomical and functional information. It begins with electrode digitization, where the precise 3D coordinates of each EEG sensor are recorded on the scalp. Next, anatomical imaging is performed, typically through acquisition of the subject's structural MRI; if unavailable, a standard head model may be used2. The digitized electrode positions are then coregistered with the MRI head geometry, aligning them to the individual's anatomy. From this step, a transformation matrix is derived that maps electrode locations from head space to MRI space. The structural MRI is then segmented into tissues (scalp, skull, brain) with an MRI segmentation tool such as Freesurfer3 to build a realistic volume conductor model. With this model, the forward model is computed, combining electrode positions, head geometry, and tissue conductivities to predict scalp potentials for any hypothetical cortical source4. Finally, the inverse solution is estimated using methods such as distributed source imaging or dipole fitting to estimate the cortical current distribution that best explains the measured EEG data5. Each step is critical: the head model ensures anatomically plausible conductivities, the forward solution links sources to scalp potentials, and the inverse solution maps the recorded signals back onto the cortex. Conversely, errors in electrode digitization, coregistration, or MRI segmentation can propagate through the pipeline, leading to inaccurate source estimates.
Several digitizing methods are currently available, including ultrasound, electromagnetic system6, structured-light or infrared 3D scanning7, photogrammetry8, and motion capture with or without a probe9. While the technologies differ in hardware and procedure, their accuracy in locating electrodes is broadly comparable. Recent studies comparing these methods show that all of the approaches achieve electrode localization precision sufficient for reliable source estimation. For example, all methods tested achieved average Brodmann area identification accuracy above 80%, whereas relying solely on template electrode positions reduced accuracy to approximately 50%10. This demonstrates that, despite differences in implementation, modern digitizing techniques provide comparable reliability, significantly reducing the uncertainty of source localization relative to using generic templates, and enabling confident mapping of cortical activity.
An attractive alternative for labs equipped with transcranial magnetic stimulation (TMS) systems is to repurpose navigated brain stimulation (NBS)11 hardware for electrode digitization. NBS, also known as neuronavigation, typically combines an optical tracker and TMS coil to register the subject's head with their MRI and to stimulate a specific cortical target. Optical trackers (e.g., Polaris Vicra) consist of an infrared tracking camera and infrared reflective markers placed on the head tracker, navigation pointer, and TMS coil. For the digitization, the experimenter first places a head tracker on the participant's head, next touches each EEG electrode with the navigation pointer, and the system logs its 3D position, which may be later exported and used for source localization, e.g., with MNE-Python12. This workflow is analogous to other digitizers but leverages existing equipment: if a lab already owns a navigated TMS system (e.g., Nexstim eXimia NBS, or similar), no separate digitizer purchase is needed.
The advantages of this approach include integration and precision. The same coordinate space can be used for both TMS targeting and EEG source modeling. For labs performing simultaneous or sequential TMS-EEG, this method streamlines the setup: electrode digitization is just part of the TMS neuronavigation process. For labs that do not primarily use EEG source localization methods but already have access to TMS neuronavigation, this method offers a straightforward way to enhance the precision of source estimates.
Finally, note that this navigated digitization concept applies to other scalp sensor arrays as well. For instance, a similar procedure could localize fNIRS optodes13 or other sensors by touching each optode with the tracked pointer. In all cases, the benefit is a unified coordinate frame between the scalp sensors and the subject's MRI, improving the anatomical accuracy of any subsequent source modeling (whether EEG or fNIRS).
Several publications explicitly report the use of the NBS system for electrode digitization14,15,16,17,18. In contrast, a number of studies that employed both TMS (NBS) and EEG or fNIRS did not describe any digitization procedure19,20,21,22,23. This omission suggests that the available functionality of the NBS for electrode or optode digitization may have been underutilized, potentially affecting the accuracy of sensor localization and, consequently, the reliability of the reported findings. We assume that many researchers may be unaware that the NBS system can also serve as a coregistration tool, as this feature is not consistently emphasized by the manufacturer. Finally, we note that NBS can be applied for sensor digitization in any study involving head-mounted electrodes or optodes, regardless of whether TMS is used.