nipy/dipy — pull request #258 by swederik (2013-10-13 22:06:27+00:00)
Title: Estimating electrical conductivity from DTI

Hello!

I've added a function for estimating electrical conductivity tensors from DTI. It's based on the SimNIBS (http://simnibs.org/) MATLAB code and supports direct mapping and volume-normalized mapping.

This is one step in a project to make it easier to generate accurate forward models for M/EEG. A nipype wrapper will follow for saving the conductivity in Nifti tensor format, along with interfaces to get the data into Gmsh (http://geuz.org/gmsh/) for visualization and GetDP (http://www.geuz.org/getdp/) for FEM calculations.

Here's a screenshot (of the first volume from the lower triangular portion of the conductivity tensor):
![screenshot 2013-10-13 23 52 22](https://f.cloud.github.com/assets/607793/1322862/dcba3a82-3451-11e3-84ee-8c794306026b.png)

See these papers for more information:

* [1] Tuch, D. S., Wedeen, V. J., Dale, A. M., George, J. S., and Belliveau, J. W., "Conductivity tensor mapping of the human brain using diffusion tensor MRI" in Proceedings of the National Academy of Sciences 98, 11697–11701, 2001

* [2] Güllmar, D., Haueisen, J., and Reichenbach, J. R., "Influence of anisotropic electrical conductivity in white matter tissue on the EEG/MEG forward and inverse solution. A high-resolution whole head simulation study", NeuroImage 51, 145–163, 2010.

* [3] Windhoff, M., Opitz, A., and Thielscher A., "Electric field calculations in brain stimulation based on finite elements: An optimized processing pipeline for the generation and usage of accurate individual head models", Human Brain Mapping, 2011.