BrainSpace is a lightweight cross-platform toolbox primarily intended for macroscale gradient mapping and analysis of neuroimaging and connectome level data. The current version of BrainSpace is available in Python and MATLAB, programming languages widely used by the neuroimaging and network neuroscience communities. The toolbox also contains several maps that allow for exploratory analysis of gradient correspondence with other brain-derived features, together with tools to generate spatial null models.
For installation instructions, examples and documentation of BrainSpace see our documentation.
Happy gradient analysis!
The BrainSpace source code is available under the BSD (3-Clause) license.
If you have problems installing the software or questions about usage and documentation, or something else related to BrainSpace, you can post to the Issues section of our repository.
If you consider using BrainSpace, please cite our manuscript: Vos de Wael R, Benkarim O, Paquola C, Lariviere S, Royer J, Tavakol S, Xu T, Hong S, Langs G, Valk S, Misic B, Milham M, Margulies D, Smallwood J, Bernhardt B (2020). BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets. Commun Biol 3, 103.
- Reinder Vos de Wael, MICA Lab - Montreal Neurological Institute
- Oualid Benkarim, MICA Lab - Montreal Neurological Institute
- Boris Bernhardt, MICA Lab - Montreal Neurological Institute
Vos de Wael, R., Benkarim, O., Paquola, C., Lariviere, S., Royer, J., Tavakol, S., ... & Bernhardt, B. C. (2020). BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets. Communications biology, 3(1), 1-10.
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