Important links

• SUIT website: http://diedrichsenlab.org/imaging/suit.htm

• Official source code repository: https://github.com/SUITPy/

• HTML documentation (latest release): https://suitpy.readthedocs.io/

Dependencies

The required dependencies to use the software are:

• python >= 3.10,

• setuptools

• numpy >= 1.22.0

• nibabel >= 3.2.1

• pandas >= 2.0.0

• matplotlib >= 3.5.0

• plotly >= 5.10.0

• scipy >= 1.9.0

• neuroimagingtools >= 1.1.1

• antspyx >= 0.6.1

Install

First make sure you have installed all the dependencies listed above. Then you can install SUITPy by running the following command in a command prompt:

pip install -U --user SUITPy

More detailed instructions are available at https://suitpy.readthedocs.io/en/latest/install.html

Licence and Acknowledgements

The Python version of the SUIT toolbox has been developed by the Diedrichsenlab including J. Diedrichsen, C. Hernandez-Castillo, M. King, Y. Wang, Y. Li, D. Zhi and others. It is distributed under MIT License, meaning that it can be freely used and re-used, as long as proper attribution in form of acknowledgments and links (for online use) or citations (in publications) are given. The relevant references are:

SUITPy toolbox:

• Wang, Y., Li, Y., Arafat, B., Ashkanichenarlogh, V., Nettekoven, C., Pinho, A. L., Hernandez-Castillo, C. R., Marquand, A. F., & Diedrichsen, J. (2026). SUITPy: A Python-based toolbox for the analysis of cerebellar functional and anatomical imaging data across the human lifespan. Imaging Neuroscience, 4, IMAG.a.1323. doi: 10.1162/IMAG.a.1323

SUIT normalisation and template:

• Diedrichsen, J. (2006). A spatially unbiased atlas template of the human cerebellum. Neuroimage. 33(1), 127-138. doi: 10.1016/j.neuroimage.2006.05.056

Surface-based representation and flatmap

• Diedrichsen, J. & Zotow, E. (2015). Surface-based display of volume-averaged cerebellar data. PLOSOne. doi: 10.1371/journal.pone.0133402