Literature DB >> 23787706

The influence of sulcus width on simulated electric fields induced by transcranial magnetic stimulation.

A M Janssen1, S M Rampersad, F Lucka, B Lanfer, S Lew, U Aydin, C H Wolters, D F Stegeman, T F Oostendorp.   

Abstract

Volume conduction models can help in acquiring knowledge about the distribution of the electric field induced by transcranial magnetic stimulation. One aspect of a detailed model is an accurate description of the cortical surface geometry. Since its estimation is difficult, it is important to know how accurate the geometry has to be represented. Previous studies only looked at the differences caused by neglecting the complete boundary between cerebrospinal fluid (CSF) and grey matter (Thielscher et al 2011 NeuroImage 54 234-43, Bijsterbosch et al 2012 Med. Biol. Eng. Comput. 50 671-81), or by resizing the whole brain (Wagner et al 2008 Exp. Brain Res. 186 539-50). However, due to the high conductive properties of the CSF, it can be expected that alterations in sulcus width can already have a significant effect on the distribution of the electric field. To answer this question, the sulcus width of a highly realistic head model, based on T1-, T2- and diffusion-weighted magnetic resonance images, was altered systematically. This study shows that alterations in the sulcus width do not cause large differences in the majority of the electric field values. However, considerable overestimation of sulcus width produces an overestimation of the calculated field strength, also at locations distant from the target location.

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Year:  2013        PMID: 23787706      PMCID: PMC3759999          DOI: 10.1088/0031-9155/58/14/4881

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  27 in total

1.  The electric resistivity of human tissues (100 Hz-10 MHz): a meta-analysis of review studies.

Authors:  T J Faes; H A van der Meij; J C de Munck; R M Heethaar
Journal:  Physiol Meas       Date:  1999-11       Impact factor: 2.833

2.  A DTI-based model for TMS using the independent impedance method with frequency-dependent tissue parameters.

Authors:  N De Geeter; G Crevecoeur; L Dupré; W Van Hecke; A Leemans
Journal:  Phys Med Biol       Date:  2012-03-28       Impact factor: 3.609

3.  Impact of the gyral geometry on the electric field induced by transcranial magnetic stimulation.

Authors:  Axel Thielscher; Alexander Opitz; Mirko Windhoff
Journal:  Neuroimage       Date:  2010-08-01       Impact factor: 6.556

4.  Determining which mechanisms lead to activation in the motor cortex: a modeling study of transcranial magnetic stimulation using realistic stimulus waveforms and sulcal geometry.

Authors:  R Salvador; S Silva; P J Basser; P C Miranda
Journal:  Clin Neurophysiol       Date:  2010-10-28       Impact factor: 3.708

5.  A reconstruction of the conductive phenomena elicited by transcranial magnetic stimulation in heterogeneous brain tissue.

Authors:  Nicola Toschi; Tobias Welt; Maria Guerrisi; Martin E Keck
Journal:  Phys Med       Date:  2008-02-25       Impact factor: 2.685

6.  A structurally detailed finite element human head model for simulation of transcranial magnetic stimulation.

Authors:  Ming Chen; David Jeffery Mogul
Journal:  J Neurosci Methods       Date:  2009-01-20       Impact factor: 2.390

7.  Evaluation of automated brain MR image segmentation and volumetry methods.

Authors:  Frederick Klauschen; Aaron Goldman; Vincent Barra; Andreas Meyer-Lindenberg; Arvid Lundervold
Journal:  Hum Brain Mapp       Date:  2009-04       Impact factor: 5.038

8.  How the brain tissue shapes the electric field induced by transcranial magnetic stimulation.

Authors:  Alexander Opitz; Mirko Windhoff; Robin M Heidemann; Robert Turner; Axel Thielscher
Journal:  Neuroimage       Date:  2011-07-01       Impact factor: 6.556

9.  Elucidating the mechanisms and loci of neuronal excitation by transcranial magnetic stimulation using a finite element model of a cortical sulcus.

Authors:  S Silva; P J Basser; P C Miranda
Journal:  Clin Neurophysiol       Date:  2008-09-09       Impact factor: 3.708

10.  Transcranial magnetic stimulation and brain atrophy: a computer-based human brain model study.

Authors:  Tim Wagner; Uri Eden; Felipe Fregni; Antoni Valero-Cabre; Ciro Ramos-Estebanez; Valerie Pronio-Stelluto; Alan Grodzinsky; Markus Zahn; Alvaro Pascual-Leone
Journal:  Exp Brain Res       Date:  2008-01-10       Impact factor: 1.972

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  11 in total

Review 1.  The development and modelling of devices and paradigms for transcranial magnetic stimulation.

Authors:  Stefan M Goetz; Zhi-De Deng
Journal:  Int Rev Psychiatry       Date:  2017-04-26

2.  The effect of local anatomy on the electric field induced by TMS: evaluation at 14 different target sites.

Authors:  Arno M Janssen; Thom F Oostendorp; Dick F Stegeman
Journal:  Med Biol Eng Comput       Date:  2014-08-28       Impact factor: 2.602

3.  Computationally optimized ECoG stimulation with local safety constraints.

Authors:  Seyhmus Guler; Moritz Dannhauer; Biel Roig-Solvas; Alexis Gkogkidis; Rob Macleod; Tonio Ball; Jeffrey G Ojemann; Dana H Brooks
Journal:  Neuroimage       Date:  2018-02-07       Impact factor: 6.556

4.  Conditions for numerically accurate TMS electric field simulation.

Authors:  Luis J Gomez; Moritz Dannhauer; Lari M Koponen; Angel V Peterchev
Journal:  Brain Stimul       Date:  2019-10-03       Impact factor: 8.955

5.  Uncertainty quantification of TMS simulations considering MRI segmentation errors.

Authors:  Hao Zhang; Luis Gomez; Johann Guilleminot
Journal:  J Neural Eng       Date:  2022-02-08       Impact factor: 5.043

6.  Impact of non-brain anatomy and coil orientation on inter- and intra-subject variability in TMS at midline.

Authors:  Erik G Lee; Priyam Rastogi; Ravi L Hadimani; David C Jiles; Joan A Camprodon
Journal:  Clin Neurophysiol       Date:  2018-07-06       Impact factor: 3.708

7.  The coil orientation dependency of the electric field induced by TMS for M1 and other brain areas.

Authors:  Arno M Janssen; Thom F Oostendorp; Dick F Stegeman
Journal:  J Neuroeng Rehabil       Date:  2015-05-17       Impact factor: 4.262

8.  Incorporating and Compensating Cerebrospinal Fluid in Surface-Based Forward Models of Magneto- and Electroencephalography.

Authors:  Matti Stenroos; Aapo Nummenmaa
Journal:  PLoS One       Date:  2016-07-29       Impact factor: 3.240

9.  Modulation of Resting Connectivity Between the Mesial Frontal Cortex and Basal Ganglia.

Authors:  Traian Popa; Laurel S Morris; Rachel Hunt; Zhi-De Deng; Silvina Horovitz; Karin Mente; Hitoshi Shitara; Kwangyeol Baek; Mark Hallett; Valerie Voon
Journal:  Front Neurol       Date:  2019-06-05       Impact factor: 4.003

Review 10.  Hypothesis-driven methods to augment human cognition by optimizing cortical oscillations.

Authors:  Jörn M Horschig; Johanna M Zumer; Ali Bahramisharif
Journal:  Front Syst Neurosci       Date:  2014-06-26
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