This week I was able to make good progress and finalize on a couple of PRs on my GSoC project repository on GitHub.
In particular, this weeks work was focused on visualization of the results of the linear regression analysis for neural time series data that I've been working on during the last few weeks, with special concentration on inferential measures, such as p-values, t-values, and indices of goodness of fit for the model, such as R-squared.
In addition I started to build up the documentation for my GSoC project. The idea is to use the documentation site as a gallery of examples and practical guides or "walkthroughs" that focus on typical analysis scenarios and research questions. This way MNE-users can easily adapt the code to their needs and make use of the linear regression framework more flexibly.
Next week, I will continue to build up the site and documentation for my GSoC project repository on GitHub and extend the examples to perform second-level analyses.