TY - JOUR

T1 - Electric Field Modeling in Personalizing Transcranial Magnetic Stimulation Interventions

AU - Dannhauer, Moritz

AU - Gomez, Luis J.

AU - Robins, Pei L.

AU - Wang, Dezhi

AU - Hasan, Nahian I.

AU - Thielscher, Axel

AU - Siebner, Hartwig R.

AU - Fan, Yong

AU - Deng, Zhi De

N1 - Publisher Copyright: © 2023

PY - 2024

Y1 - 2024

N2 - The modeling of transcranial magnetic stimulation (TMS)–induced electric fields (E-fields) is a versatile technique for evaluating and refining brain targeting and dosing strategies, while also providing insights into dose–response relationships in the brain. This review outlines the methodologies employed to derive E-field estimations, covering TMS physics, modeling assumptions, and aspects of subject-specific head tissue and coil modeling. We also summarize various numerical methods for solving the E-field and their suitability for various applications. Modeling methodologies have been optimized to efficiently execute numerous TMS simulations across diverse scalp coil configurations, facilitating the identification of optimal setups or rapid cortical E-field visualization for specific brain targets. These brain targets are extrapolated from neurophysiological measurements and neuroimaging, enabling precise and individualized E-field dosing in experimental and clinical applications. This necessitates the quantification of E-field estimates using metrics that enable the comparison of brain target engagement, functional localization, and TMS intensity adjustments across subjects. The integration of E-field modeling with empirical data has the potential to uncover pivotal insights into the aspects of E-fields responsible for stimulating and modulating brain function and states, enhancing behavioral task performance, and impacting the clinical outcomes of personalized TMS interventions.

AB - The modeling of transcranial magnetic stimulation (TMS)–induced electric fields (E-fields) is a versatile technique for evaluating and refining brain targeting and dosing strategies, while also providing insights into dose–response relationships in the brain. This review outlines the methodologies employed to derive E-field estimations, covering TMS physics, modeling assumptions, and aspects of subject-specific head tissue and coil modeling. We also summarize various numerical methods for solving the E-field and their suitability for various applications. Modeling methodologies have been optimized to efficiently execute numerous TMS simulations across diverse scalp coil configurations, facilitating the identification of optimal setups or rapid cortical E-field visualization for specific brain targets. These brain targets are extrapolated from neurophysiological measurements and neuroimaging, enabling precise and individualized E-field dosing in experimental and clinical applications. This necessitates the quantification of E-field estimates using metrics that enable the comparison of brain target engagement, functional localization, and TMS intensity adjustments across subjects. The integration of E-field modeling with empirical data has the potential to uncover pivotal insights into the aspects of E-fields responsible for stimulating and modulating brain function and states, enhancing behavioral task performance, and impacting the clinical outcomes of personalized TMS interventions.

KW - Brain stimulation

KW - Electric field

KW - Individualization

KW - Modeling

KW - Optimal placement

KW - Transcranial magnetic stimulation

U2 - 10.1016/j.biopsych.2023.11.022

DO - 10.1016/j.biopsych.2023.11.022

M3 - Review

C2 - 38061463

AN - SCOPUS:85183538252

VL - 95

SP - 494

EP - 501

JO - Biological Psychiatry

JF - Biological Psychiatry

SN - 0006-3223

IS - 6

ER -