Single-Subject TMS Pulse Visualization on MRI-Based Brain Model: A precise method for mapping TMS pulses on cortical surface

• Published in: MethodsX Vol. 10; p. 102213
• Main Authors: Syrov, Nikolay, Mustafina, Alfiia, Berkmush-Antipova, Artemiy, Yakovlev, Lev, Demchinsky, Andrey, Petrova, Daria, Kaplan, Alexander
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.01.2023; Elsevier
• Subjects: Blender; brain; computer software; Motor-evoked potentials; Navigated transcranial magnetic stimulation; Neuronavigation; Neuroscience; Neurovisualization; Phosphenes; TMS; TMS-affected Cortical points Visualization on MRI-based Brain Model. The software tool is implemented using the Python language and runs on the Blender software platform. It uses a subject-specific 3D model of the brain's cortical surface reconstructed from MRI data. The software marks the points of TMS application on the cortical surface; transcranial magnetic stimulation; Neurovisualization; Neuronavigation; Blender; TMS-affected Cortical points Visualization on MRI-based Brain Model. The software tool is implemented using the Python language and runs on the Blender software platform. It uses a subject-specific 3D model of the brain's cortical surface reconstructed from MRI data. The software marks the points of TMS application on the cortical surface; Navigated transcranial magnetic stimulation; TMS; Phosphenes; Motor-evoked potentials
• ISSN: 2215-0161; 2215-0161
• DOI: 10.1016/j.mex.2023.102213

Highly accurate visualization of the points of transcranial magnetic stimulation (TMS) application on the brain cortical surface could provide anatomy-specific analysis of TMS effects. TMS is widely used to activate cortical areas with high spatial resolution, and neuronavigation enables site-specific TMS of particular gyrus sites. Precise control of TMS application points is crucial in determining the stimulation effects. Here, we propose a method that gives an opportunity to visualize and analyze the stimulated cortical sites by processing multi-parameter data.•This method uses MRI data to create a participant's brain model for visualization. The MRI data is segmented to obtain a raw 3D model, which is further optimized in 3D modeling software.•A Python script running in Blender uses the TMS coil's orientation data and participant's brain 3D model to define and mark the cortical sites affected by the particular TMS pulse.•The Python script can be easily customized to visualize TMS points task-specifically. [Display omitted]