4.6 Article

Predicted current densities in the brain during transcranial electrical stimulation

期刊

CLINICAL NEUROPHYSIOLOGY
卷 117, 期 6, 页码 1388-1397

出版社

ELSEVIER IRELAND LTD
DOI: 10.1016/j.clinph.2006.02.020

关键词

tcMEP; motor evoked potentials; finite element method; Gardner-Wells tongs; intraoperative monitoring; tissue anisotropy

资金

  1. NIBIB NIH HHS [R01 EB002389-01, R01 EB002389-04, R01 EB002389-02, R01 EB002389, R01 EB002389-03] Funding Source: Medline

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Objective: We sought an electrical modeling approach to evaluate the potential application of finite element method (FEM) modeling to predict current pathways and intensities in the brain after transcranial electrical stimulation. Methods: A single coronal MRI section through the head, including motor cortex, was modeled using FEM. White matter compartments with both anatomically realistic anisotropies in resistivity and with a homogeneous resistivity were modeled. Current densities in the brain were predicted for electrode sites on the scalp and after theoretical application of a conductive head restraint device. Results: Localized current densities were predicted for the model with white matter anisotropies. Differences in predicted peak current densities were related to location of stimulation sites relative to deep sulci in the brain and scalp shunting that was predicted to increase with inter-Plectrode proximity. A conductive head restraint device was predicted to shunt current away from the brain when a constant current source was used. Conclusions: The complex geometry of different tissue compartments in the head and their contrasting resistivities may jointly determine the strength and location of current densities in the brain after transcranial stimulation. This might be predictable with FEM incorporating white matter anisotropies. Conductive head restraint devices during surgery may be contraindicated with constant current stimulation. Significance: Individually optimized tcMEP monitoring and localized transcranial activation in the brain might be possible through FEM modeling. (c) 2006 Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

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