Documentation

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Contents

SimBio documentation films

A film about the SimBio documentation can be found here.

A film that should help compiling SimBio can be found here.

Furthermore, we have produced some films that document how to work with the SimBio testdata:

The film EEG forward modeling using FEM documents how to perform full subtraction FEM forward modeling as presented by (Drechsler et al., NeuroImage, 2009).

The film EEG inverse modeling with FEM documents how to use the ddd debugger to step through and understand the code and to perform dipole fits for a set of dipoles with different eccentricities.

The film tES forward modeling with FEM documents how to perform transcranial electric stimulation (tES) FEM forward modeling as presented by (Wagner et al., J. Neur. Eng., 2014).

Simbio Releasenotes

References

A list of papers that were produced using the SimBio code is available: here.

Furthermore, here are all references that cite the Fieldtrip-SimBio work (Vorwerk et al., Biomed Eng Online, 2018).

Compiling SimBio

Here are further instructions on how to compile SimBio on different Linux platforms.

A film that helps getting SimBio compiled and linked can be found here.

Directory Structure

Here is an overview of the directory structure of the SimBio source code: here.

Coding Standard

Here is the coding standard for developers of the SimBio source code including naming conventions: here.

File Formats

Here is a list and description of file formats that SimBio currently supports for input and/or output: here.

FE mesh generation

There are multiple possibilities for finite element mesh generation:

Hexahedra meshing

VGRID can be used to generate regular or geometry-adapted hexahedral (cubic) FE meshes. It has been shown that geometry-adapted FE meshes perform better than regular FE meshes in most tested source analysis situations Wolters et al, IEEE Trans Biomed Eng, 2017. Cubic meshes are especially interesting for applications because of the simplicity of generating them (the problem of segmentation and meshing mainly reduces to the problem of segmentation, see, e.g., Wagner et al., NeuroImage, 2016 or Rullmann et al., NeuroImage, 2009

Tetrahedra meshing

With Tetgen, constrained Delaunay tetrahedral meshes of high accuracy for source analysis applications can be constructed, see, e.g., Drechsler et al., NeuroImage, 2009 or Lew et al., Applied Numerical Mathematics, 2009. CURRY8 allows the generation of ordinary Delaunay tetrahedral meshes as used, e.g., in Wolters et al., NeuroImage, 2006.

CAUCHY

  1. Nomenclature
  2. Principles of Finite Element Modeling
  3. General Program Functionality
  4. Program proceeding
  5. Program Control
  6. Programmer’s information
  7. Validation
  8. Installation
  9. Examples
  10. Appendix A
  11. Appendix B -EIPP-
  12. Appendix C
  13. Appendix D
  14. References
  15. CAUCHY Papers


download CAUCHY documentation: part 1 part2

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