scholarly journals A Computational Parcellated Brain Model for Electric Field Analysis in Transcranial Direct Current Stimulation

2020 ◽  
pp. 81-99
Author(s):  
M. A. Callejón-Leblic ◽  
Pedro C. Miranda
Keyword(s):  
Finite Element Method ◽  
Electric Field ◽  
Direct Current ◽  
Transcranial Direct Current Stimulation ◽  
Clinical Applications ◽  
Field Analysis ◽  
Direct Current Stimulation ◽  
Electrode Positioning ◽  
Electric Field Analysis ◽  
Cortical Regions

AbstractRecent years have seen the use of increasingly realistic electric field (EF) models to further our knowledge of the bioelectric basis of noninvasive brain techniques such as transcranial direct current stimulation (tDCS). Such models predict a poor spatial resolution of tDCS, showing a non-focal EF distribution with similar or even higher magnitude values far from the presumed targeted regions, thus bringing into doubt the classical criteria for electrode positioning. In addition to magnitude, the orientation of the EF over selected neural targets is thought to play a key role in the neuromodulation response. This chapter offers a summary of recent works which have studied the effect of simulated EF magnitude and orientation in tDCS, as well as providing new results derived from an anatomically representative parcellated brain model based on finite element method (FEM). The results include estimates of mean and peak tangential and normal EF values over different cortical regions and for various electrode montages typically used in clinical applications.

scholarly journals Multiscale Coupling of Transcranial Direct Current Stimulation to Neuron Electrodynamics: Modeling the Influence of the Transcranial Electric Field on Neuronal Depolarization

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Edward T. Dougherty ◽  
James C. Turner ◽  
Frank Vogel
Keyword(s):  
Electric Field ◽  
Direct Current ◽  
Transcranial Direct Current Stimulation ◽  
Three Dimensional ◽  
Human Head ◽  
Multiscale Model ◽  
Medical Intervention ◽  
Medical Community ◽  
Computational Grids ◽  
Direct Current Stimulation

Transcranial direct current stimulation (tDCS) continues to demonstrate success as a medical intervention for neurodegenerative diseases, psychological conditions, and traumatic brain injury recovery. One aspect of tDCS still not fully comprehended is the influence of the tDCS electric field on neural functionality. To address this issue, we present a mathematical, multiscale model that couples tDCS administration to neuron electrodynamics. We demonstrate the model’s validity and medical applicability with computational simulations using an idealized two-dimensional domain and then an MRI-derived, three-dimensional human head geometry possessing inhomogeneous and anisotropic tissue conductivities. We exemplify the capabilities of these simulations with real-world tDCS electrode configurations and treatment parameters and compare the model’s predictions to those attained from medical research studies. The model is implemented using efficient numerical strategies and solution techniques to allow the use of fine computational grids needed by the medical community.

Determinants of the electric field during transcranial direct current stimulation

NeuroImage ◽  
2015 ◽  
Vol 109 ◽  
pp. 140-150 ◽  
Author(s):  
Alexander Opitz ◽  
Walter Paulus ◽  
Susanne Will ◽  
Andre Antunes ◽  
Axel Thielscher
Keyword(s):  
Electric Field ◽  
Direct Current ◽  
Transcranial Direct Current Stimulation ◽  
Direct Current Stimulation

High-Definition Transcranial Direct Current Stimulation Improves Delayed Memory in Alzheimer’s Disease Patients: A Pilot Study Using Computational Modeling to Optimize Electrode Position

2021 ◽  
pp. 1-17
Author(s):  
Ingrid Daae Rasmussen ◽  
Nya Mehnwolo Boayue ◽  
Matthias Mittner ◽  
Martin Bystad ◽  
Ole K. Grnli ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Electric Field ◽  
Computational Modeling ◽  
Direct Current ◽  
Transcranial Direct Current Stimulation ◽  
Cortical Atrophy ◽  
Brain Anatomy ◽  
High Definition ◽  
Direct Current Stimulation

Background: The optimal stimulation parameters when using transcranial direct current stimulation (tDCS) to improve memory performance in patients with Alzheimer’s disease (AD) are lacking. In healthy individuals, inter-individual differences in brain anatomy significantly influence current distribution during tDCS, an effect that might be aggravated by variations in cortical atrophy in AD patients. Objective: To measure the effect of individualized HD-tDCS in AD patients. Methods: Nineteen AD patients were randomly assigned to receive active or sham high-definition tDCS (HD-tDCS). Computational modeling of the HD-tDCS-induced electric field in each patient’s brain was analyzed based on magnetic resonance imaging (MRI) scans. The chosen montage provided the highest net anodal electric field in the left dorsolateral prefrontal cortex (DLPFC). An accelerated HD-tDCS design was conducted (2 mA for 3×20 min) on two separate days. Pre- and post-intervention cognitive tests and T1 and T2-weighted MRI and diffusion tensor imaging data at baseline were analyzed. Results: Different montages were optimal for individual patients. The active HD-tDCS group improved significantly in delayed memory and MMSE performance compared to the sham group. Five participants in the active group had higher scores on delayed memory post HD-tDCS, four remained stable and one declined. The active HD-tDCS group had a significant positive correlation between fractional anisotropy in the anterior thalamic radiation and delayed memory score. Conclusion: HD-tDCS significantly improved delayed memory in AD. Our study can be regarded as a proof-of-concept attempt to increase tDCS efficacy. The present findings should be confirmed in larger samples.

scholarly journals Computational Finite Element Method (FEM) forward modeling workflow for transcranial Direct Current Stimulation (tDCS) current flow on MRI-derived head: Simpleware and COMSOL Multiphysics tutorial

2019 ◽  
Author(s):  
Ole Seibt ◽  
Dennis Truong ◽  
Niranjan Khadka ◽  
Yu Huang ◽  
Marom Bikson
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Direct Current ◽  
Transcranial Direct Current Stimulation ◽  
Computational Models ◽  
Current Flow ◽  
Forward Modeling ◽  
Fem Model ◽  
Direct Current Stimulation ◽  
Element Method

AbstractTranscranial Direct Current Stimulation (tDCS) dose designs are often based on computational Finite Element Method (FEM) forward modeling studies. These FEM models educate researchers about the resulting current flow (intensity and pattern) and so the resulting neurophysiological and behavioral changes based on tDCS dose (mA), resistivity of head tissues (e.g. skin, skull, CSF, brain), and head anatomy. Moreover, model support optimization of montage to target specific brain regions. Computational models are thus an ancillary tool used to inform the design, set-up and programming of tDCS devices, and investigate the role of parameters such as electrode assembly, current directionality, and polarity of tDCS in optimizing therapeutic interventions. Computational FEM modeling pipeline of tDCS initiates with segmentation of an exemplary magnetic resonance imaging (MRI) scan of a template head into multiple tissue compartments to develop a higher resolution (< 1 mm) MRI derived FEM model using Simpleware ScanIP. Next, electrode assembly (anode and cathode of variant dimension) is positioned over the brain target and meshed at different mesh densities. Finally, a volumetric mesh of the head with electrodes is imported in COMSOL and a quasistatic approximation (stead-state solution method) is implemented with boundary conditions such as inward normal current density (anode), ground (cathode), and electrically insulating remaining boundaries. A successfully solved FEM model is used to visualize the model prediction via different plots (streamlines, volume plot, arrow plot).

Electric Field Analysis Based on FEM and Corona Test of 330 kV Dampers

2014 ◽  
Vol 672-674 ◽  
pp. 773-777
Author(s):  
Tian Xi Xie ◽  
Zong Ren Peng ◽  
Zhi Cheng Zhou ◽  
Yong Ma
Keyword(s):  
Finite Element Method ◽  
Electric Field ◽  
Electric Field Intensity ◽  
Computational Models ◽  
Three Dimensional ◽  
Field Analysis ◽  
Test Results ◽  
Field Distributions ◽  
Maximum Electric Field ◽  
Electric Field Analysis

At high altitudes, 330 kV dampers usually have corona discharges on their weights, which affects the lives of the surrounding residents. To suppress the corona, optimizing the structures of the dampers is a recommended measure to reduce the electric field intensities on their weights. In this paper, three-dimensional computational models of 330 kV FDN dampers were constructed to calculate the electric field distributions on their weights, based on finite element method (FEM). The structure of the small end was optimized to reduce the electric field strength on its surface. When the radius was increased from 25 to 35 mm, the maximum electric field intensity could be decreased from 2987 V/mm to 2390V/mm. According to the results, new dampers were manufactured to test their corona characteristics. The test results show that the new dampers can prevent corona discharge at altitudes below 3500 m.

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