A computational investigation of preconditioning strategies and iterative methods for finite element based neurostimulation simulations

DOI10.1016/j.camwa.2020.02.021OpenAlexW3011124388MaRDI QIDQ2192527

E. T. Dougherty, Frank Vogel, J. C. jun. Turner

Publication date: 17 August 2020

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2020.02.021

zbMATH Keywords

preconditioningmultigridmathematical modelingnumerical simulationneurostimulationtDCS

Mathematics Subject Classification ID

Neural biology (92C20) Medical applications (general) (92C50) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) Computational methods for problems pertaining to biology (92-08)

Uses Software

• Diffpack
• Gmsh
• gnuplot
• ParaView

Cites Work

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• Accuracy and run-time comparison for different potential approaches and iterative solvers in finite element method based EEG source analysis
• Advanced topics in computational partial differential equations. Numerical methods and Diffpack programming
• Iteration number for the conjugate gradient method
• Multiscale coupling of transcranial direct current stimulation to neuron electrodynamics: modeling the influence of the transcranial electric field on neuronal depolarization
• Numerical model of vagus nerve electrical stimulation
• Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities
• A Multigrid Tutorial, Second Edition
• Iterative Krylov Methods for Large Linear Systems
• Computing the Electrical Activity in the Heart

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