DocumentCode :
27715
Title :
Use of electric field orientation as an index for estimating the contribution of model complexity in transcranial direct current stimulation forward head model development
Author :
Shahid, Syed Salman ; Bo Song ; Salman, Humaira ; de Oliveira, Marilia Menezes ; Peng Wen
Author_Institution :
Nat. Univ. of Sci. & Technol., Islamabad, Pakistan
Volume :
9
Issue :
5
fYear :
2015
fDate :
8 2015
Firstpage :
596
Lastpage :
605
Abstract :
The study evaluates the role of human skull composition and brain anisotropy in the context of transcranial direct current stimulation (tDCS) based predictive modeling. Four head models were developed and each proposed attribute (cancellous bone and brain anisotropy) was compared with the isotropic model. By employing a single high-definition montage, the efficacy of each attribute in shaping induced electric field was analyzed by its magnitude and orientation information. Relative error (RE) was used to estimate the variation in field magnitude. It was observed that for a given high-definition montage, the brain anisotropy contributed to 5% change (RE) in the strength of the gray matter (GM) electric field and 10% for the white matter (WM). Inclusion of diploe in the model resulted in 45% variation in the magnitude of the brain electric field. On average, brain anisotropy contributed to field deviations of up to 20 degrees in major WM fiber tracts. Skull heterogeneity caused field deviations of up to 35 degrees in diploe, 15 degrees in subcutaneous fat and marginal variations in brain regions. These simulation results demonstrated the importance of considering refinement in forward models of tDCS, especially; the role of diploe should be considered for more accurate field assessments.
Keywords :
bioelectric phenomena; biomedical MRI; brain; medical image processing; statistical analysis; HD montage; brain anisotropy evaluation; brain electric field orientation analysis; brain region; field magnitude variation estimation; grey matter; high definition montage; human skull composition evaluation; model complexity estimation; motor cortex; predictive modelling; statistical index; tDCS forward head model development; transcranial direct current stimulation; white matter;
fLanguage :
English
Journal_Title :
Science, Measurement & Technology, IET
Publisher :
iet
ISSN :
1751-8822
Type :
jour
DOI :
10.1049/iet-smt.2014.0220
Filename :
7172629
Link To Document :
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