# DemosΒΆ

- Getting started exercise for RSA3.0
- Dataset objects in rsatoolbox
- Estimating dissimilarities
- Calculating our first RDM
- accessing RDM contents
- To access the parts of the rdms object a few functions are available:
- diagonal covariance from measurements = univariate noise normalization
- shrinkage estimate from measurements = multivariate noise normalization
- estimates based on residuals
- Computing Mahalanobis distances

- Visualising RDMs with the 92 images dataset
- Annotated RDM plots
- Demo on unbalanced designs
- Temporal RSA
- RSA on MEG data with MNE python
- EEG Demo
- Searchlight for RSA
- How to get an average RDM from a stack of partial RDMs