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Burnham, E. H.

Publications and source records attributed to Burnham, E. H..

3 recordsLinked to original sources

Software Toolkit for Fast High-Resolution TMS Modeling

Computational modeling of Transcranial Magnetic Stimulation (TMS) is a tradeoff between computational speed vs. spatial precision. In this study, we introduce a software toolkit for high-resolution TMS modeling, which may offer the best of both. The toolkit employs the recently developed boundary element fast multipole method (BEM-FMM) with accurate solution computations close to tissue interfaces. It operates within the MATLAB platform and is designed for a broad, medically-oriented computational research community. To enable easy, subject-specific operation, the package is compatible with human head models generated with automated tools such as SimNIBS and FreeSurfer.\n\nBoth coil design in free space as well as efficacy and focality of TMS for a specific subject could be modeled by the package, including optional user-defined parametric loops. Detailed and widely used coil models, generated in both CAD and wire formats, may include several hundred thousand elementary current elements and observation spaces with approximately 1 M field points; the corresponding computational times are on the order of 1 sec. Detailed head models with approximately 1 M triangular facets and a mesh resolution of 0.6 points per mm2 are simulated in approximately 1.5 min which is arguably the fastest time to date. Further reduction of computational times is foreseen. The toolkit is augmented with a population of 16 ready-to-use head models for performing simulations for computational studies that do not involve MRI data collection. The toolkit is also augmented with a coil geometry generator capable of creating accurate coil models.

neuroscience↗

Collection of Sixteen High-Quality Human Head CAD Models Generated with SimNIBS 2.1 Using Connectome Subject Data within MATLAB(R) Platform

The goal of this study is to introduce a collection of sixteen high-resolution, 2-manifold CAD compatible head models within the MATLAB platform available to all interested parties for electromagnetic and acoustic simulations. Each model contains skin, skull, CSF, GM, cerebellum, WM, and ventricles head compartments and possesses an \"onion\" topology: the grey matter shell is a container for white matter, ventricles, and cerebellum objects, the CSF shell contains the grey matter shell, the skull shell contains the CSF shell, and finally the skin or scalp shell contains the skull shell. The models are fully compatible with ANSYS ED FEM software, CST Studio Suite, Sim4Life/SEMCAD software, and other electromagnetic software packages.\n\nThe collection is based on MRI data from the Human Connectome Project (HCP) segmented using the SimNIBS 2.1/2.1.1 processing pipeline. The average number of triangular surface facets in a model is 866,000, the average triangle quality is 0.25, the average edge length is 1.48 mm, and the average surface mesh density or resolution is 0.57 points per mm2. If necessary, a finer model mesh can be created for every head using available MATLAB tools.

bioengineering↗

Comparative Performance of the Finite Element Method and the Boundary Element Fast Multipole Method for a Test Problem Mimicking Transcranial Magnetic Stimulation (TMS)

A study pertinent to the numerical modeling of cortical neurostimulation is conducted in an effort to compare the performance of the finite element method (FEM) and an original formulation of the boundary element fast multipole method (BEM-FMM) at matched computational performance metrics. We consider two problems: (i) a canonic multi-sphere geometry and an external magnetic-dipole excitation where the analytical solution is available and; (ii) a problem with realistic head models excited by a realistic coil geometry. In the first case, the FEM algorithm tested is a fast open-source getDP solver running within the SimNIBS 2.1.1 environment. In the second case, a high-end commercial FEM software package ANSYS Maxwell 3D is used. The BEM-FMM method runs in the MATLAB(R) 2018a environment.\n\nIn the first case, we observe that the BEM-FMM algorithm gives a smaller solution error for all mesh resolutions and runs significantly faster for high-resolution meshes when the number of triangular facets exceeds approximately 0.25 M. We present other relevant simulation results such as volumetric mesh generation times for the FEM, time necessary to compute the potential integrals for the BEM-FMM, and solution performance metrics for different hardware/operating system combinations. In the second case, we observe an excellent agreement for electric field distribution across different cranium compartments and, at the same time, a speed improvement of three orders of magnitude when the BEM-FMM algorithm used.\n\nThis study may provide a justification for anticipated use of the BEM-FMM algorithm for high-resolution realistic transcranial magnetic stimulation scenarios.

bioengineering↗