Validating computationally predicted TMS stimulation areas using direct electrical stimulation in patients with brain tumors near precentral regions

The spatial extent of transcranial magnetic stimulation (TMS) is of paramount interest for all studies employing this method. It is generally assumed that the induced electric field is the crucial parameter to determine which cortical regions are excited. While it is difficult to directly measure th...

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Main Authors: Alexander Opitz, Noman Zafar, Volker Bockermann, Veit Rohde, Walter Paulus
Format: Article
Language:English
Published: Elsevier 2014-01-01
Series:NeuroImage: Clinical
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2213158214000345
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spelling doaj-5b5b69dceb5e419a8adfb912a89502732020-11-24T23:56:18ZengElsevierNeuroImage: Clinical2213-15822014-01-014C50050710.1016/j.nicl.2014.03.004Validating computationally predicted TMS stimulation areas using direct electrical stimulation in patients with brain tumors near precentral regionsAlexander Opitz0Noman Zafar1Volker Bockermann2Veit Rohde3Walter Paulus4Department of Clinical Neurophysiology, Georg-August-University, Göttingen, GermanyDepartment of Neurosurgery, Georg-August-University, Göttingen, GermanyDepartment of Neurosurgery, Georg-August-University, Göttingen, GermanyDepartment of Neurosurgery, Georg-August-University, Göttingen, GermanyDepartment of Clinical Neurophysiology, Georg-August-University, Göttingen, GermanyThe spatial extent of transcranial magnetic stimulation (TMS) is of paramount interest for all studies employing this method. It is generally assumed that the induced electric field is the crucial parameter to determine which cortical regions are excited. While it is difficult to directly measure the electric field, one usually relies on computational models to estimate the electric field distribution. Direct electrical stimulation (DES) is a local brain stimulation method generally considered the gold standard to map structure–function relationships in the brain. Its application is typically limited to patients undergoing brain surgery. In this study we compare the computationally predicted stimulation area in TMS with the DES area in six patients with tumors near precentral regions. We combine a motor evoked potential (MEP) mapping experiment for both TMS and DES with realistic individual finite element method (FEM) simulations of the electric field distribution during TMS and DES. On average, stimulation areas in TMS and DES show an overlap of up to 80%, thus validating our computational physiology approach to estimate TMS excitation volumes. Our results can help in understanding the spatial spread of TMS effects and in optimizing stimulation protocols to more specifically target certain cortical regions based on computational modeling.http://www.sciencedirect.com/science/article/pii/S2213158214000345Transcranial magnetic stimulationMotor cortexDirect electrical stimulationFinite element method
collection DOAJ
language English
format Article
sources DOAJ
author Alexander Opitz
Noman Zafar
Volker Bockermann
Veit Rohde
Walter Paulus
spellingShingle Alexander Opitz
Noman Zafar
Volker Bockermann
Veit Rohde
Walter Paulus
Validating computationally predicted TMS stimulation areas using direct electrical stimulation in patients with brain tumors near precentral regions
NeuroImage: Clinical
Transcranial magnetic stimulation
Motor cortex
Direct electrical stimulation
Finite element method
author_facet Alexander Opitz
Noman Zafar
Volker Bockermann
Veit Rohde
Walter Paulus
author_sort Alexander Opitz
title Validating computationally predicted TMS stimulation areas using direct electrical stimulation in patients with brain tumors near precentral regions
title_short Validating computationally predicted TMS stimulation areas using direct electrical stimulation in patients with brain tumors near precentral regions
title_full Validating computationally predicted TMS stimulation areas using direct electrical stimulation in patients with brain tumors near precentral regions
title_fullStr Validating computationally predicted TMS stimulation areas using direct electrical stimulation in patients with brain tumors near precentral regions
title_full_unstemmed Validating computationally predicted TMS stimulation areas using direct electrical stimulation in patients with brain tumors near precentral regions
title_sort validating computationally predicted tms stimulation areas using direct electrical stimulation in patients with brain tumors near precentral regions
publisher Elsevier
series NeuroImage: Clinical
issn 2213-1582
publishDate 2014-01-01
description The spatial extent of transcranial magnetic stimulation (TMS) is of paramount interest for all studies employing this method. It is generally assumed that the induced electric field is the crucial parameter to determine which cortical regions are excited. While it is difficult to directly measure the electric field, one usually relies on computational models to estimate the electric field distribution. Direct electrical stimulation (DES) is a local brain stimulation method generally considered the gold standard to map structure–function relationships in the brain. Its application is typically limited to patients undergoing brain surgery. In this study we compare the computationally predicted stimulation area in TMS with the DES area in six patients with tumors near precentral regions. We combine a motor evoked potential (MEP) mapping experiment for both TMS and DES with realistic individual finite element method (FEM) simulations of the electric field distribution during TMS and DES. On average, stimulation areas in TMS and DES show an overlap of up to 80%, thus validating our computational physiology approach to estimate TMS excitation volumes. Our results can help in understanding the spatial spread of TMS effects and in optimizing stimulation protocols to more specifically target certain cortical regions based on computational modeling.
topic Transcranial magnetic stimulation
Motor cortex
Direct electrical stimulation
Finite element method
url http://www.sciencedirect.com/science/article/pii/S2213158214000345
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