MNE-RSA: Representational similarity analysis using MNE-Python datastructures

This is a Python package for performing representational similarity analysis (RSA) using MNE-Python data structures. The RSA is computed using a “searchlight” approach.
This is what the package can do for you:
- Compute DSMs on arbitrary data
- Compute DSMs in a searchlight across:
   - vertices and samples (source level)
   - sensors and samples (sensor level)
   - vertices only (source level)
   - sensors only (sensor level)
   - samples only (source and sensor level)
- Use cross-validated distance metrics when computing DSMs
- And of course: compute RSA between DSMs

This is what it cannot do (yet) for you:
- Compute DSMs in a searchlight across voxels (volume level)

Supported metrics for comparing DSMs:- Spearman correlation (the default)
- Pearson correlation
- Kendall’s Tau-A
- Linear regression (when comparing multiple DSMs at once)
- Partial correlation (when comparing multiple DSMs at once)