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  A principled approach to conductivity uncertainty analysis in electric field calculations

Saturnino, G. B., Thielscher, A., Madsen, K. H., Knösche, T. R., & Weise, K. (2019). A principled approach to conductivity uncertainty analysis in electric field calculations. NeuroImage, 188, 821-834. doi:10.1016/j.neuroimage.2018.12.053.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0002-D5FE-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-756D-0
Genre: Journal Article

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 Creators:
Saturnino, Guilherme B.1, 2, Author
Thielscher, Axel1, 2, Author
Madsen, Kristoffer H.1, 3, Author
Knösche, Thomas R.4, 5, Author              
Weise, Konstantin6, 7, Author              
Affiliations:
1Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Denmark, ou_persistent22              
2Department of Electrical Engineering, Technical University of Denmark, Lyngby, Denmark, ou_persistent22              
3Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark, ou_persistent22              
4Methods and Development Unit MEG and EEG: Signal Analysis and Modelling, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634559              
5Institute for Biomedical Engineering and Informatics, TU Ilmenau, Germany, ou_persistent22              
6Methods and Development Unit - MEG and Cortical Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205650              
7Department of Advanced Electromagnetics, TU Ilmenau, Germany, ou_persistent22              

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Free keywords: Non-invasive brain stimulation, Numerical methods, Sensitivity analysis, Transcranial magnetic stimulation, Transcranial direct current, stimulation, Uncertainty analysis
 Abstract: Uncertainty surrounding ohmic tissue conductivity impedes accurate calculation of the electric fields generated by non-invasive brain stimulation. We present an efficient and generic technique for uncertainty and sensitivity analyses, which quantifies the reliability of field estimates and identifies the most influential parameters. For this purpose, we employ a non-intrusive generalized polynomial chaos expansion to compactly approximate the multidimensional dependency of the field on the conductivities. We demonstrate that the proposed pipeline yields detailed insight into the uncertainty of field estimates for transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), identifies the most relevant tissue conductivities, and highlights characteristic differences between stimulation methods. Specifically, we test the influence of conductivity variations on (i) the magnitude of the electric field generated at each gray matter location, (ii) its normal component relative to the cortical sheet, (iii) its overall magnitude (indexed by the 98th percentile), and (iv) its overall spatial distribution. We show that TMS fields are generally less affected by conductivity variations than tDCS fields. For both TMS and tDCS, conductivity uncertainty causes much higher uncertainty in the magnitude as compared to the direction and overall spatial distribution of the electric field. Whereas the TMS fields were predominantly influenced by gray and white matter conductivity, the tDCS fields were additionally dependent on skull and scalp conductivities. Comprehensive uncertainty analyses of complex systems achieved by the proposed technique are not possible with classical methods, such as Monte Carlo sampling, without extreme computational effort. In addition, our method has the advantages of directly yielding interpretable and intuitive output metrics and of being easily adaptable to new problems.

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Language(s): eng - English
 Dates: 2018-12-052018-10-242018-12-262018-12-272019-03
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2018.12.053
PMID: 30594684
PII: S1053-8119(18)32203-1
Other: Epub ahead of print
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Project name : -
Grant ID : WE 59851/1
Funding program : -
Funding organization : German Science Foundation (DFG)
Project name : -
Grant ID : R118-A11308
Funding program : -
Funding organization : Lundbeckfonden
Project name : -
Grant ID : NNF14OC0011413
Funding program : -
Funding organization : Novo Nordisk fonden

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 188 Sequence Number: - Start / End Page: 821 - 834 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166