Cargando…

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

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-specif...

Descripción completa

Detalles Bibliográficos
Autores principales: Syrov, Nikolay, Mustafina, Alfiia, Berkmush-Antipova, Artemiy, Yakovlev, Lev, Demchinsky, Andrey, Petrova, Daria, Kaplan, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244693/
https://www.ncbi.nlm.nih.gov/pubmed/37292240
http://dx.doi.org/10.1016/j.mex.2023.102213
_version_ 1785054698262233088
author Syrov, Nikolay
Mustafina, Alfiia
Berkmush-Antipova, Artemiy
Yakovlev, Lev
Demchinsky, Andrey
Petrova, Daria
Kaplan, Alexander
author_facet Syrov, Nikolay
Mustafina, Alfiia
Berkmush-Antipova, Artemiy
Yakovlev, Lev
Demchinsky, Andrey
Petrova, Daria
Kaplan, Alexander
author_sort Syrov, Nikolay
collection PubMed
description 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.
format Online
Article
Text
id pubmed-10244693
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-102446932023-06-08 Single-Subject TMS Pulse Visualization on MRI-Based Brain Model: A precise method for mapping TMS pulses on cortical surface Syrov, Nikolay Mustafina, Alfiia Berkmush-Antipova, Artemiy Yakovlev, Lev Demchinsky, Andrey Petrova, Daria Kaplan, Alexander MethodsX Neuroscience 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. Elsevier 2023-05-18 /pmc/articles/PMC10244693/ /pubmed/37292240 http://dx.doi.org/10.1016/j.mex.2023.102213 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Neuroscience
Syrov, Nikolay
Mustafina, Alfiia
Berkmush-Antipova, Artemiy
Yakovlev, Lev
Demchinsky, Andrey
Petrova, Daria
Kaplan, Alexander
Single-Subject TMS Pulse Visualization on MRI-Based Brain Model: A precise method for mapping TMS pulses on cortical surface
title Single-Subject TMS Pulse Visualization on MRI-Based Brain Model: A precise method for mapping TMS pulses on cortical surface
title_full Single-Subject TMS Pulse Visualization on MRI-Based Brain Model: A precise method for mapping TMS pulses on cortical surface
title_fullStr Single-Subject TMS Pulse Visualization on MRI-Based Brain Model: A precise method for mapping TMS pulses on cortical surface
title_full_unstemmed Single-Subject TMS Pulse Visualization on MRI-Based Brain Model: A precise method for mapping TMS pulses on cortical surface
title_short Single-Subject TMS Pulse Visualization on MRI-Based Brain Model: A precise method for mapping TMS pulses on cortical surface
title_sort single-subject tms pulse visualization on mri-based brain model: a precise method for mapping tms pulses on cortical surface
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244693/
https://www.ncbi.nlm.nih.gov/pubmed/37292240
http://dx.doi.org/10.1016/j.mex.2023.102213
work_keys_str_mv AT syrovnikolay singlesubjecttmspulsevisualizationonmribasedbrainmodelaprecisemethodformappingtmspulsesoncorticalsurface
AT mustafinaalfiia singlesubjecttmspulsevisualizationonmribasedbrainmodelaprecisemethodformappingtmspulsesoncorticalsurface
AT berkmushantipovaartemiy singlesubjecttmspulsevisualizationonmribasedbrainmodelaprecisemethodformappingtmspulsesoncorticalsurface
AT yakovlevlev singlesubjecttmspulsevisualizationonmribasedbrainmodelaprecisemethodformappingtmspulsesoncorticalsurface
AT demchinskyandrey singlesubjecttmspulsevisualizationonmribasedbrainmodelaprecisemethodformappingtmspulsesoncorticalsurface
AT petrovadaria singlesubjecttmspulsevisualizationonmribasedbrainmodelaprecisemethodformappingtmspulsesoncorticalsurface
AT kaplanalexander singlesubjecttmspulsevisualizationonmribasedbrainmodelaprecisemethodformappingtmspulsesoncorticalsurface