Deep brain temporally interfering magnetic stimulation via parametric characterized spatial array

Bibliographic Details
Title: Deep brain temporally interfering magnetic stimulation via parametric characterized spatial array
Authors: Xiao Fang, Shaolong Wang, Yaoyao Luo, Yu Lin, Wenlong Yang, Tao Zhang
Source: AIP Advances, Vol 14, Iss 8, Pp 085201-085201-14 (2024)
Publisher Information: AIP Publishing LLC, 2024.
Publication Year: 2024
Collection: LCC:Physics
Subject Terms: Physics, QC1-999
More Details: Transcranial magnetic stimulation (TMS) shows great research potential in human neuroscience. However, when it comes to stimulating deeper brain regions, traditional TMS is restricted by the balance between stimulation focalization and stimulation depth. Temporal interference (TI) stimulation offers a new thought to solve the problem. In this paper, we first discussed the principles of TI-TMS and then established the theoretical model of TI-TMS using the head-surrounded spatial array. Next, we specially designed the parametric characterized spatial array (PCS array) suitable for TI-TMS. The proposed PCS array contains eight special-shaped coils that constitute four sets of difference frequency stimulation pairs and are placed around the human head. Distribution characteristics of the temporally interfering electric fields (E-fields) including stimulation intensity, stimulation focalizations on 1D, 2D, and 3D levels, and attenuation ratios in X, Y, and Z directions were obtained using the finite element analysis method. Our results indicate that the proposed PCS array could form an obvious focusing area with strong stimulation at a stimulation depth of 5 cm below the human scalp while the superficial region is under weak stimulation, which effectively combines the advantages of TMS and TI stimulation. Compared to the traditional TMS systems, the TI-TMS with PCS array can realize selective and focalized stimulation in the deep brain and increase the average attenuation ratio of the induced temporally interfering E-fields by more than 1.93 times. A real human head model containing gray matter was also employed in this paper to verify our results.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2158-3226
08554005
Relation: https://doaj.org/toc/2158-3226
DOI: 10.1063/5.0219428
Access URL: https://doaj.org/article/e178d08a08554005b3a75f410f6efd41
Accession Number: edsdoj.178d08a08554005b3a75f410f6efd41
Database: Directory of Open Access Journals
More Details
ISSN:21583226
08554005
DOI:10.1063/5.0219428
Published in:AIP Advances
Language:English