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In: Brain and Human Body Modeling 2020: Computational Human Models Presented at EMBC 2019 and the BRAIN Initiative® 2019 Meeting [Internet]. Cham (CH): Springer; 2021.
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Affiliations
Affiliations
1 Department of Mechanical Engineering, Technical University of Munich, Garching, Germany
2 Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany
3 Munich School of BioEngineering, Technical University of Munich, Garching, Germany
4 Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW, Australia
Book Affiliations
1 Electrical and Computer Engineering Department, Worcester Polytechnic Institute, Worcester, MA, USA
2 Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital, Charlestown, MA, USA
Computational Models of Brain Stimulation with Tractography Analysis
Stefanie Riel et al.
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In: Brain and Human Body Modeling 2020: Computational Human Models Presented at EMBC 2019 and the BRAIN Initiative® 2019 Meeting [Internet]. Cham (CH): Springer; 2021.
Computational human head models have been used in studies of brain stimulation. These models have been able to provide useful information that can’t be acquired or difficult to acquire from experimental or imaging studies. However, most of these models are purely volume conductor models that overlooked the electric excitability of axons in the white matter of the brain. We hereby combined a finite element (FE) model of electroconvulsive therapy (ECT) with a whole-brain tractography analysis as well as the cable theory of neuronal excitation. We have reconstructed a whole-brain tractogram with 2000 neural fibres from diffusion-weighted magnetic resonance scans and extracted the information on electrical potential from the FE ECT model of the same head. Two different electrode placements and three different white matter conductivity settings were simulated and compared. We calculated the electric field and second spatial derivatives of the electrical potential along the fibre direction, which describes the activating function for homogenous axons, and investigated sensitive regions of white matter activation. Models with anisotropic white matter conductivity yielded the most distinctive electric field and activating function distribution. Activation was most likely to appear in regions between the electrodes where the electric potential gradient is most pronounced.
Bai, S., Loo, C., & Dokos, S. (2013). A review of computational models of transcranial electrical stimulation. Critical Reviews in Biomedical Engineering, 41(1), 21–35.
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Bai, S., Loo, C., Al Abed, A., & Dokos, S. (2012). A computational model of direct brain excitation induced by electroconvulsive therapy: Comparison among three conventional electrode placements. Brain Stimulation, 5(3), 408–421.
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Butson, C. R., & McIntyre, C. C. (2006). Role of electrode design on the volume of tissue activated during deep brain stimulation. Journal of Neural Engineering, 3, 1–8.
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Gunalan, K., et al. (2017). Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example. PLoS One, 7, e0176132.
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Fan, Q., et al. (2016). MGH-USC Human Connectome Project datasets with ultra-high b-value diffusion MRI. NeuroImage, 124, 1108–1114.
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