pyNIBS 0.2022.9

A python toolbox to conduct non-invasive brain stimulation experiments (NIBS).

pyNIBS

Preprocessing, postprocessing, and analyses routines for non-invasive brain stimulation experiments.

pyNIBS provides the functions to allow cortical mappings with transcranial magnetic stimulation (TMS) via functional analysis. pyNIBS is developed to work with SimNIBS, i.e. SimNIBS' meshes and FEM results can directly be used. Currently, SimNIBS 3.2.5 is supported. Have a look at our gitlab repository for SimNIBS 4 (beta) support.

See the documentation for package details and our protocol publication for an extensive example of the usage.

Installation

Via pip:

pip install pynibs

Or clone the source repository and install via setup.py:

git clone https://gitlab.gwdg.de/tms-localization/pynibs
cd pynibs
python setup.py develop

To import CED Signal EMG data use the export to .mat feature of Signal. To read .cfs files exported with CED Signal you might need to manually compile the libbiosig package.

Bugs

For sure. Please open an issue or feel free to file a PR.

Citation

Please cite Numssen, O., Zier, A. L., Thielscher, A., Hartwigsen, G., Knösche, T. R., & Weise, K. (2021). Efficient high-resolution TMS mapping of the human motor cortex by nonlinear regression. NeuroImage, 245, 118654. doi:10.1016/j.neuroimage.2021.118654 when using this toolbox in your research.

References

• Weise, K., Numssen, O., Thielscher, A., Hartwigsen, G., & Knösche, T. R. (2020). A novel approach to localize cortical TMS effects. Neuroimage, 209, 116486. doi: 10.1016/j.neuroimage.2019.116486
• Numssen, O., Zier, A. L., Thielscher, A., Hartwigsen, G., Knösche, T. R., & Weise, K. (2021). Efficient high-resolution TMS mapping of the human motor cortex by nonlinear regression. NeuroImage, 245, 118654. doi:10.1016/j.neuroimage.2021.118654
• Weise, K., Numssen, O., Kalloch, B., Zier, A. L., Thielscher, A., Hartwigsen, G., Knösche, T. R. (2022). Precise transcranial magnetic stimulation motor-mapping. Nature Protocols. (accepted)