A fast hand motor hotspot determination method based on neuroimaging in transcranial magnetic stimulation

Xinle Cheng; Mingzhu Li; Xuefeng Lu; Shidong Jia; Tianzi Jiang; Hao Yan; Zhengyi Yang

doi:10.1117/12.3034093

13 June 2024 A fast hand motor hotspot determination method based on neuroimaging in transcranial magnetic stimulation

Xinle Cheng, Mingzhu Li, Xuefeng Lu, Shidong Jia, Tianzi Jiang, Hao Yan, Zhengyi Yang

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 1318068 (2024) https://doi.org/10.1117/12.3034093
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

Transcranial magnetic stimulation (TMS) stands as a widely employed neuromodulation technique for addressing various brain disorders. The hand motor hotspot (hMHS) holds particular significance in TMS applications, serving to ascertain personalized treatment targets and stimulation intensity. However, the conventional determination of hMHS remains timeconsuming. Our objective was to expedite the identification of hMHS solely based on neuroimaging data. In this investigation, we pinpointed the hMHS on the cortical surface in depressed patients utilizing TMS-derived data and magnetic resonance imaging (MRI) data. Employing the kernel density estimation method, we developed a probability map for hMHS, subsequently utilizing a machine learning (ML) model to discern subjects suitable for the probability map application. The hMHS probability map was established, and the vertex with the highest probability was designated as the group hMHS. For subjects closely aligning with the group hMHS, direct application of the hMHS probability map was feasible. Conversely, for other subjects, our ML model, trained on cortical structure data of the sulci, could identify them. Our method achieved an 88% accuracy in hMHS determination and, when compared to traditional methods, exhibited an average time-saving of approximately 50%. In conclusion, our proposed method offers an efficient and rapid solution for hMHS identification during TMS treatment.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinle Cheng, Mingzhu Li, Xuefeng Lu, Shidong Jia, Tianzi Jiang, Hao Yan, and Zhengyi Yang "A fast hand motor hotspot determination method based on neuroimaging in transcranial magnetic stimulation", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 1318068 (13 June 2024); https://doi.org/10.1117/12.3034093

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Magnetic resonance imaging

Electric fields

Magnetism

Data modeling

Education and training

Matrices

Neuroimaging

Show All Keywords

Keywords/Phrases

Search In:

Publication Years