app-make-watershed-bem

Brainlife App to make watershed BEMs based on Freesurfer output MNE/Python mne.bem.make_watershed_bem function

1. Input file is:

   • T1 T1.mgz or NIFTI file

2. Ouput files are:

   • 3 .surf files

Authors

• [Kami Salibayeva] (ksalibay@iu.edu)

Contributors

• [Kami Salibayeva] (ksalibay@iu.edu)
• [Maximilien Chaumon] (maximilien.chaumon@icm-institute.org)
• [Guiomar Niso]

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your code and publications. Copy and past the following lines into your repository when using this code.

Citations

1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y
2. Taulu S. and Kajola M. Presentation of electromagnetic multichannel data: The signal space separation method. Journal of Applied Physics, 97 (2005). https://doi.org/10.1063/1.1935742
3. Taulu S. and Simola J. Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements. Physics in Medicine and Biology, 51 (2006). https://doi.org/10.1088/0031-9155/51/7/008