Numerical investigation of the electric field distribution induced in the brain by transcranial magnetic stimulation (TMS)
Numerical investigation of the electric field distribution induced in the brain by transcranial magnetic stimulation (TMS)
Introduction.
There has been considerable interest over the years in the treatment of serious physiological and clinical conditions, such as depression and pain relief, by
utilising electromagnetic fields through Transcranial Magnetic Stimulation (TMS) of the human brain [1].
Most of the effort has recently focused on the attempt to stimulate neurons deep inside the brain mass and to limit any hazards posed by this treatment. As a result, there is a need for new TMS coil configurations to generate sufficient and localized electric fields to achieve deep stimulation.
The advent of more powerful computers and the emergence of more accurate models for the electric properties and shape of the human brain have enabled
numerical modelling to become a significant and reliable tool for the design and optimisation of such new TMS devices in order to achieve the above requirements. The experimental prediction of the electric field distribution is still a formidable task so simulation of the fields induced inside the brain, is crucial in the optimisation and design of the stimulus coils.
This paper presents results on the simulation ofTMS by using the Finite Element Method (FEM) in three dimensions and looks at the effects of the stimulation coils and geometrical model of the head on the distribution and penetration of the electric field induced in the brain during TMS. It is revealed that the incorporation of an accurate brain model in terms of shape as well as conductivity values is crucial for an improved estimation of field distribution and threshold fields inside the brain.
153-154
Kim, Dong-Hun
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Loukaides, N.
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Sykulski, J.K.
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Georghiou, G.E.
9cfa57e6-8aea-433f-8be2-449839fc6b1d
April 2004
Kim, Dong-Hun
a320b5a0-1b03-45df-8564-2b7b61a776b0
Loukaides, N.
86800203-2cce-411a-84cf-a5db8f38c931
Sykulski, J.K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
Georghiou, G.E.
9cfa57e6-8aea-433f-8be2-449839fc6b1d
Kim, Dong-Hun, Loukaides, N., Sykulski, J.K. and Georghiou, G.E.
(2004)
Numerical investigation of the electric field distribution induced in the brain by transcranial magnetic stimulation (TMS).
Fifth IEE International Conference on Computation in Electromagnetics, .
Abstract
Introduction.
There has been considerable interest over the years in the treatment of serious physiological and clinical conditions, such as depression and pain relief, by
utilising electromagnetic fields through Transcranial Magnetic Stimulation (TMS) of the human brain [1].
Most of the effort has recently focused on the attempt to stimulate neurons deep inside the brain mass and to limit any hazards posed by this treatment. As a result, there is a need for new TMS coil configurations to generate sufficient and localized electric fields to achieve deep stimulation.
The advent of more powerful computers and the emergence of more accurate models for the electric properties and shape of the human brain have enabled
numerical modelling to become a significant and reliable tool for the design and optimisation of such new TMS devices in order to achieve the above requirements. The experimental prediction of the electric field distribution is still a formidable task so simulation of the fields induced inside the brain, is crucial in the optimisation and design of the stimulus coils.
This paper presents results on the simulation ofTMS by using the Finite Element Method (FEM) in three dimensions and looks at the effects of the stimulation coils and geometrical model of the head on the distribution and penetration of the electric field induced in the brain during TMS. It is revealed that the incorporation of an accurate brain model in terms of shape as well as conductivity values is crucial for an improved estimation of field distribution and threshold fields inside the brain.
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IEE-CEM2004April2004page153.pdf
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Published date: April 2004
Organisations:
EEE
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Local EPrints ID: 259290
URI: http://eprints.soton.ac.uk/id/eprint/259290
ISSN: 0537-9989
PURE UUID: 773d5cf7-d8e1-4a43-8b03-d4dd33e7ba4a
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Date deposited: 23 Apr 2004
Last modified: 15 Mar 2024 02:34
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Author:
Dong-Hun Kim
Author:
N. Loukaides
Author:
J.K. Sykulski
Author:
G.E. Georghiou
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